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Editor: Prof.dr.sc. Marinko Škare Conference Proceedings of the Third International Scientiﬁc Conference for Doctoral Students and Young Researchers

Editorial board: Prof. Dr. Dr. h.c. Csaba Székely (Hungary) Dr.h.c. Prof. Ing. Ludmila Lipková, CSc. (Slovakia) Dr. Mgr. Boris Mattoš,PhD (Slovakia) Prof. Dr. Sc. Valter Boljuncic (Croatia) Prof.Dr.Sc.Marinko Škare (Croatia) Dr. habil Csilla Obádovics, PhD (Hungary) Prof. Dr. László Kulcsár, PhD. (Hungary) Assoc. Prof. Ing. Martin Grešš, PhD. (Slovakia) Univ.-Prof. Dr. Sc. Dr.h.c. Irena Zavrl, PhD. (Austria)

Reviewers Board: Univerza na Primorskem, Slovenia | University of Economics in Katowice, Poland | University of Castilla-La Mancha, Spain | Juraj Dobrila University of Pula, Croatia | University of Cantabria, Spain | Koszalin University of Technology, Poland | Manchester Metropolitan Univrersity, UK | Biyalstock University of Technology, Poland | University of Novi Sad, Serbia | Ondrej Cástek, Masaryk University, Czech Republic | University of Teramo, Italy | University of Maribor, Slovenia | Wrocław University of Economics, Poland | Institute of Business Management, Pakistan Organisational board: Klaudija Hašaj Marijana Tadić ISBN: 978-3-9519937-0-6 Online: https://*burgenland.contentdm.oclc.org/digital/collection/p16083coll2 CONTENTS

RELATIONS BETWEEN ACADEMIC EDUCATION AND SELECTED BEHAVIORAL FINANCE EFFECTS ! AUSTRIAN PERSPECTIVE 5 Reinhard Furtner

DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW 25 Vesna Sesar* and Anica Hunjet

HOW DIGITALIZATION CHANGES CONTROLLING 45 Brigitta Kovacs

INNOVATIONS FOR MANAGING OVERHEAD COSTS 57 Wolfram Irsa

MAKING AMERICA ATTRACTIVE AGAIN FOR INVESTORS ! DONALD J. TRUMP’S REFORMS AND THE POSSIBLE OUTCOME OF INCREASED PRODUCTION!OUTPUT IN TRADE 75 Hoﬀer, Thomas

OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES 103 Philipp Klein MA

QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM!SYSTEMS IN THE PACKAGING INDUSTRY 117 Ing. Martin A. Moser, MA MSc

TRANSFORMATION OF VET IN LESS DEVELOPED REGIONS ! CHALLENGES AND OPPORTUNITIES 145 Anton Aufner MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS PERFORMANCE 167 Manuel Benazić Ines Karagianni Ladašić

AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS: A MIXED METHODS STUDY 199 Victoria Petsch

DATA PREPARATION AND HARMONIZATION FOR CONSISTENT AND COMPREHENSIVE ESTIMATE OF ICT SECTORS CONTRIBUTION TO NATIONAL ECONOMY 217 Damira Keček Valter Boljunčić

HRM AND CULTURAL CAPITAL " INNOVATIVE APPROACH FOR THE DEVELOPMENT OF CULTURAL TOURISM ON THE EXAMPLE OF THE REGION OF ISTRIA 227 Doris Cerin Otočan

BLOCKCHAIN IN A NUTSHELL " AN INTRODUCTION TO COMMUNITY BASED DECENTRALIZED OPEN LEDGER TECHNOLOGIES 247 Markus Schindler

BACK!RESHORING & INDUSTRY 4.0 " A RELATIONSHIP FOR THE FUTURE? 269 Gerald Seidler 5

Reinhard Furtner RELATIONS BETWEEN ACADEMIC EDUCATION AND SELECTED BEHAVIORAL FINANCE... (5 - 24)

ARTICLE INFO Received: 21.9.2018. Accepted: 28.4.2019. JEL classiﬁcation: D14, D91, G41

Keywords: framing; investment decision; loss aversion; mental accounting; sunk cost eﬀect

RELATIONS BETWEEN ACADEMIC EDUCATION AND SELECTED BEHAVIORAL FINANCE EFFECTS ! AUSTRIAN PERSPECTIVE

Reinhard Furtner 1719001129@!-burgenland.at

5 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

Behavioral finance literature and research results indicate that investment decisions, among other factors, are influenced by cognitive (behavioral) factors. So far little attention has been paid to the relationship of academical background and behavioral effects in the investment decision-making process.

$e current quantitative study examines relations between academic education and four selected behavioral finance effects (behavioral finance knowledge) in the context of investment decisions (mental accounting, loss aversion, sunk costs, framing) in a sample of Austrian (prospective) academics (n = 134). Further-more, one sub-sample consists of (prospective) academics of economic related studies and the other of (prospective) academics with non-economic related study-background. Data were tested using descriptive and inductive methods (frequency distributions, contingency tables, Chi-square test, Cramer V).

Results show that the behavioral effects appear in both subsamples. In addition, results differ among the subsamples of (prospective) academics with economic related study back-ground and those with non-economic related study background. Addi- tional research would be necessary to explore the underlying psycho-logical process in investment decision-making - particularly in the context of different educational or academical background.

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I. INTRODUCTION

Regularly, individuals have to choose among different investment alternatives. In that context, personal investment decisions with huge financial impacts have to be made every now and then. %ese decisions are, for example, the purchase of a new home or the suitable investment selection for one’s pension provision. Against this backdrop, the relevance of the investment process, its understanding and optimization is evident. Previous research has identified various relevant factors (e.g. demographic factors or cognitive factors) which influence investment decisions. Research results indicate that financial behavior (particular in context with financial literacy and income) has a significant effect on investment decisions. Especially, knowledge regarding behavioral finance should improve financial behavior and lead to better investment decisions. %us, it is important that persons understand the psychological, sociological and financial aspects in that context.1 %erefore, it is recommended to implement financial education (including behavioral finance knowledge) as an educational part in college and university curricula.2 %e current situation is that tertiary educational institutes especially fail to include behavioral elements in their educational programs.3 %is also seems to be true for the situation of Austrian (economical) tertiary educational institutes. For example, the curricula of the Vienna University of Eco- nomics and Business do not explicitly show elements of behavioral finance.4 However, it can be assumed that those elements are taught - as least rudimentary - in economical courses at Austrian economical universities. Hence, the main aim of the paper is to show whether or not an (behavioral) economical academical background changes investment decision results of students in Austria. Indications should be gained, if (behavioral) education leads to better (or at least different) investment decisions.5

1 Baiq F. Arianti, “%e influence of financial literacy, financial behavior and income on investment decision,” Economics and Accounting Journal 1, no. 1 (2018): 4–8. 2 Brenda Cude et al., “College students and financial literacy: What they know and what we need to learn,” Proceedings of the Eastern Family Economics and Resource Management Association 102, no. 9 (2006): 107–8. 3 Randall Peteros and John Maleyeff, “Application of behavioural finance concepts to investment decision-making: Suggestions for improving investment education courses,” International Journal of Management 30, no. 1 (2013): 249. 4 Vienna University of Economics and Business, “Curricula for the study programs,” Vienna University of Economics and Business, accessed April 19, 2019, https://www.wu.ac.at/en/students/my-program/ bachelors-programs/business-economics-and-social-sciences/curricula. 5 Maria Silgoner, Bettina Greimel-Fuhrmann, and Rosa Weber, “Financial literacy gaps of the Austrian population,” Monetary Policy & the Economy Q 2 (2015): 45.

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%erefore, in this paper results of an empirical study which investigated behavioral effects in a sample group of Austrian (prospective) academics (n=134)6. In that context, it has to be mentioned that one sub-sample consists of (prospective) academics with economic related study-background and the other of (prospective) academics with a non-economic related study-background. %us, the sample was divided in two sub-samples and four behavioral effects (mental accounting, loss aversion, sunk costs, framing) were tested in both sub-samples by using an online-survey. Moreover, it is important to note that the focus was on forming a summarizing group variable which measures the behavioral finance knowledge in both subgroups. Especially, potential differences or parallels between the two sub-samples should be identified. %e basic assumption is that an individual’s economical or non-economical academical background might influence the level of behavioral finance knowledge and, therefore, investment decision making in the context of the selected and investigated behavioral effects. %e quantitative study was realized as a part of the author’s master study.7 %erefore, the main hypothesis of the research is defined as follows: • H1: Behavioral finance knowledge differs in both subgroups.

II. LITERATURE REVIEW

1. The ﬁction of the homo oeconomicus

It is important to point out that classical and neoclassical economic theories have been built on the premise of the home oeconomicus. In fact, the underlying (too simple) model assumptions do not meet economic reality. Based on the homo oeconomicus model, humans are considered to act self- interested and rationally in the context of economic decisions. %erefore, main goal regarding those decisions is to maximize the own beneﬁts. Furthermore, humans are in knowledge of full (market) information and they clearly deﬁne

6 %e non-representative sample (n=134) consists of 68,7 % (prospective) academics with an economical-related study background (e.g. business administration or management) and 31,3 % with a non economical-related study background (e.g. languages, technical study subjects). 52,2 % of the test persons were female and 47,8 % were male. Moreover, 76,1 % of the test persons showed an age below 30 years. %e sample included active undergraduate and graduate students as well as graduates. 7 Reinhard Furtner, “Behavioral Finance - Eine empirische Studie über diesbezügliche Verhaltensweisen (angehender) österreichischer Akademikerinnen und Akademiker” (Masterarbeit, Department of Management and Entrepreneurship, University of Applied Sciences for Management and Communication, 2014), 1–10.

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preferences. In this regard, humans can be defined as permanent-calculators or benefit-maximizers.89 Research, especially in the context of capital market theory, which is based on the homo oeconomicus axiom, has already identified weaknesses of the concept (e.g. limited information, no striving for profit-maximization).10 Weaknesses of the homo oeconomicus axiom can be observed in real-life examples of capital market decision making: For example, people may purchase a stock of their employer without any analysis of the underlying financial key figures. %ey might be fully driven by a long-lasting personal relationship to their employer-company. Moreover, investing in stocks of soccer clubs (e.g. Borussia Dortmund, DE0005493092 or Juventus Football, IT0000336518) probably o'en is triggered by (irrational) passion for a specific soccer team. 11 Furthermore, it is understandable that people use different sources and amounts of capital market information which they evaluate differently. Moreover, cognitive limitations do not enable humans to evaluate all information available fully on a rational basis like a microprocessor.

8 Norbert Rost, “Der Homo oeconomicus: Eine Fiktion der Standardökonomie,” Zeitschri& für Sozialökonomie 45, 158/159 (2008): 50. 9 Hans-Jürgen Schlösser, “Menschenbilder in der Ökonomie,” Orientierungen zur Wirtscha's- und Gesellscha'spolitik 41, no. 112 (2007): 69–70. 10 Norbert Betz and Ulrich Kirstein, Börsenpsychologie, 2. Auﬂage 2015, Simpliﬁed (München: FBV, 2015), 58–59. 11 Furtner, “Behavioral Finance - Eine empirische Studie über diesbezügliche Verhaltensweisen (angehender) österreichischer Akademikerinnen und Akademiker,” 12.

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Based on literature analysis, the relevant factors which inﬂuence a person’s investment decision can be visualized as follows: Figure 1.: Factors inﬂuencing investment decisions

Source: Author’s figure based on literature12 13 14 15 16 $e cognitive factor finance-related knowledge for the research is defined in the context of financial literacy: It is an individual’s ability to “understand and use personal finance-related information”.17

2. The explanatory approach of behavioral ﬁnance

%e field of behavioral finance thematically is situated between the poles of economics and psychology.18 Historically, Amos Tversky, Daniel Kahneman and Richard %aler can be considered as the scientific founding fathers of the field.

12 Peter Adelt and Bert Feldmann, “Spar- und Anlageentscheidungen älterer Menschen,” in Finanzpsychologie, ed. Lorenz Fischer, %omas Kutsch and Ekkehard Stephan (München, Wien: Oldenbourg, 1999), https://doi.org/10.1515/9783486801149-011, 250–72. 13 Horst Müller, “Zur Risikobereitscha' privater Geldanleger,” Kredit und Kapital 11, no. 1 (1995): 134– 60. 14 %omas Günther and Martin Detzner, “Risikoverhalten von Managern: Ergebnisse empirischer Controllingorschung,” CFO aktuell 3, no. 3 (2009): 127. 15 Tina S. Harrison, “Mapping Customer Segments for Personal Financial Services,” International Journal of Bank Marketing 12, no. 8 (1994): 19, https://doi.org/10.1108/02652329410069010. 16 Karl Erik Wärneryd, Stock-market psychology: How people value and trade stocks (Cheltenham: Elgar, 2001), 202. 17 Sandra J. Huston, “Measuring ﬁnancial literacy,” Journal of Consumer Aﬀairs 44, no. 2 (2010): 306. 18 Hersh Shefrin, Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing (Financial Management Association Survey and Synthesis), Revised Edition (Oxford: Oxford University Press, 2007), 4.

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Already in the 1970s, in their experiments, and also in experiments by other researchers, significantly different human behavior was identified in the context of specific tasks. Especially, human behavior in certain situations differs from the expected behavior of the (theoretical) homo oeconomicus. %erefore, the main research focus was placed in investment decisions in the field of behavioral finance. To conclude, the full investment process is covered by the field of behavioral finance, e.g. processing of information, handling of risks, effects of specific behavioral patterns or the subjective valuation of gains and losses.19 Apparently, behavioral finance approaches strive to close the gap between (theoretical) behavior of the homo oeconomicus and effective human behavior which can be observed, e.g. in experiments. Basically, the field of behavioral finance can be divided into three basic directions:20 • Heuristics and cognitive biases • Prospect theory (a model for acting under uncertainty and risk)21 • Framing effects However, the large body of literature on behavioral finance shows a relatively unstructured systemization of various behavioral finance effects. Similar effects regularly are named differently. Furthermore, the boundaries between the different effects are not always clearly defined. At this point it is important to consider that, of course, items sometimes measure a mixture of two or more effects. %erefore, it is of huge importance to exactly state the effects which should be investigated for the research project in advance. Consequently, clearly definable and well-known behavioral effects were selected for the current empirical research project. In particular, the specific research focus was put on “mental accounting”, “loss aversion”, “sunk costs” and “framing effects”. To provide a brief overview, these four selected effects are outlined in the following sections.

3. Mental accounting

Imagine a couple which is saving funds on a deposit account for a future purchase of a new home. Currently, already an amount of $ 15.000,00 has been

19 Heinz-Kurt Wahren, Anlegerpsychologie, 1. Auﬂ. (Wiesbaden: VS Verlag für Sozialwissenscha'en / GWV Fachverlage GmbH Wiesbaden, 2009). https://doi.org/10.1007/978-3-531-91374-2, http:// dx.doi.org/10.1007/978-3-531-91374-2, 45–46. 20 Daniel Kahneman, “Maps of Bounded Rationality: Psychology for Behavioral Economics,” American Economic Review 93, no. 5 (2003): 1449, https://doi.org/10.1257/000282803322655392. 21 Daniel Kahneman and Amos Tversky, “Prospect %eory: An Analysis of Decision under Risk,” Econometrica 47, no. 2 (1979): 263–92, https://doi.org/10.2307/1914185.

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saved up. Furthermore, the annual interest rate of the savings account is stable at 10 % and funds, also in the future, should be continued to be saved at this rate. Additionally, recently the couple purchased a new car for $ 11.000,00. Moreover, this new car is financed through a three year-period credit at an interest rate of 15 %.22 %is example was created by Richard %aler, who was investigating this and other behavioral effects for decades. %e underlying idea of this example is the concept of mental accounting: Dedicated funds for the future house purchase are saved at an annual interest rate of 10 % on the one hand, on the other hand credit financed resources for the car purchase are borrowed at an annual interest rate of 15 %. In this respect, the question arises what the rationally-acting homo oeconomicus would do? Of course, a rational agent, in this simplified example, would use the saved house funds for financing the car purchase due to the interest rate advantage (10 % vs. 15 % annual interest rate). However, humans might act as described in this example; they mentally build separate accounts for different investment purposes and they do not consider their overall (financial) situation. %erefore, mental accounting can be defined as the result of various cognitive operations that are used by individuals and households in order to organize, evaluate and comprehend their financial activities.23 In other words, humans strive for optimization of the separated accounts. Instead, they should focus on the optimization of the whole position to improve their financial overall situation.24

4. Loss aversion

Loss aversion effects repeatedly have been investigated in different markets: For example, an empirical US real estate market analysis proved the effect for real estate sellers in Boston. Real estate sellers that found themselves in a situation where they had to sell their properties less than their purchasing prices (market value below purchase value) quoted their prices 25 to 35 % above the market price. However, house sellers in a more financially comfortable situation (market value above purchase value) offered their properties much more closer to the market value. Furthermore, those sellers who overpriced their houses were able to generate

22 “%aler mental accounting and consumer choice,” 199. 23 Richard H. %aler, “Mental accounting matters,” Journal of Behavioral Decision Making 12, no. 3 (1999): 183, https://doi.org/10.1002/(SICI)1099-0771(199909)12:3<183::AID-BDM318>3.0.CO;2-F. 24 Andreas Oehler, “Anomalien, Irrationalitäten oder Biases der Erwartungsnutzentheorie und ihre Relevanz für die Finanzmärkte,” Zeitschri& für Bankrecht und Bankwirtscha& 4, no. 2 (1992): 106.

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a comparatively higher selling price of about 3 to 18 % of the diﬀerence between market value and purchase value.25 %erefore, loss aversion can be deﬁned as an individual’s tendency to overval- ue a decrease in wealth in comparison to an increase of the same.26In other words, humans experience losses more intensive than gains similar in amount. Empirical basis of loss aversion is visualized in the value function which is one of the anchor points of prospect theory: Figure 2.: Value Function

Source: Ghent University Association Department27 As shown in ﬁgure 2, value function visualizes the human orientation towards a speciﬁc reference point. Gains (upper right quadrant) show a concave shape which is related to risk-averse behavior. Furthermore, in loss situations (lower le& quadrant) a convex shape and, therefore, high risk tolerance exists. Moreover, the function is steeper in loss situations compared to gain situations.28

25 David Genesove and Christopher Mayer, “Loss Aversion and Seller Behavior: Evidence from the Housing Market,” $e Quarterly Journal of Economics 116, no. 4 (2001): 1235-1236, 1255-1256, https:// doi.org/10.3386/w8143. 26 Shlomo Benartzi and Richard %aler, “Myopic Loss Aversion and the Equity Premium Puzzle,” $e Quarterly Journal of Economics 110, no. 1 (1995): 73, https://doi.org/10.3386/w4369. 27 Jan Devos, “Small and Medium-sized Enterprises (SMEs) and IT: A Market for Lemons?,” Slide No. 11. 28 Kahneman and Tversky, “Prospect %eory: An Analysis of Decision under Risk,” 279.

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To conclude, the loss aversion effect in investment decisions (orientation towards a reference point, relatively stronger perception of losses etc.) influences human investment decisions which, due to that effect, potentially diverge from the hypothetical decision the purely rationally acting homo oeconomicus would have made. 5. Sunk cost e!ect

%e sunk cost effect can be discovered in various real-life decisions. In a well- known experiment, individuals showed different behavior regarding the use of a theater season ticket. People who bought the season ticket for the regular price visited significantly more theater performances than people who bought the same ticket at a discounted price.29 Psychological background of the effect is the intrinsic human rule not to waste (monetary) resources. Research proved that simple animals and very young humans do not follow this rule. Instead, they orientate themselves on the incremental cost or incremental benefit.30 Basic starting point of this effect is a past decision. Furthermore, further information is received at a later point in time. Now, this new information, from a rational point of view, indicates, subsequently, a change of the chosen strategy. However, individuals tend to stick to the decision they have made, even though new information indicates that the chosen strategy should be changed.31 As a result of the effect, individuals tend to remain at a decision as far as already resources like financial funds, time resources or personal efforts have been invested. Nevertheless, past invested resources should not influence the actual decision making against the background of new information available.32 Furthermore, the process of decision-making is based on the interaction between the issue of already invested resources and the social pressure to complete a project started.33

29 Hal R. Arkes and Catherine Blumer, “%e psychology of sunk cost,” Organizational Behavior and Human Decision Processes 35, no. 1 (1985): 128, https://doi.org/10.1016/0749-5978(85)90049-4. 30 Hal R. Arkes and Peter Ayton, “%e sunk cost and Concorde effects: Are humans less rational than lower animals?,” Psychological Bulletin 125, no. 5 (1999): 598, https://doi.org/10.1037//0033- 2909.125.5.591. 31 Chandra Kanodia, Robert Bushman, and John Dickhaut, “Escalation Errors and the Sunk Cost Effect: An Explanation Based on Reputation and Information Asymmetries,” Journal of Accounting Research 27, no. 1 (1989): 59, https://doi.org/10.2307/2491207. 32 Arkes and Blumer, “%e psychology of sunk cost,” 124. 33 Henry Moon, “Looking forward and looking back: Integrating completion and sunk-cost effects within an escalation-of-commitment progress decision,” Journal of Applied Psychology 86, no. 1 (2001): 106, 110-111, https://doi.org/10.1037/0021-9010.86.1.104.

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6. Framing e!ect

A perfect example of framing effects can be found in the opt-in and opt-out legal frameworks regarding the willingness for organ donation. Empirical research showed significant differences between two frameworks: Opt-in frameworks require people to actively note their willingness of organ donation in case of lethal accidents on their driving license. On the contrary, opt-out systems require people to actively state that they do not allow the donation of their organs. Austria and Germany which certainly have a comparable cultural background show large differences regarding the willingness for organ donation which is caused by the different legal framework (opt-in vs. opt-out systems). Expressed as percentages, in Austria willingness for organ donation is close to 100 % (opt-out system), whereas in Germany the willingness is about 12 % (opt-in system).34 %erefore, the frame, which is the opt-in or the opt-out legal framework, significantly influences the peoples’ willingness for organ donations. Also, practical implication for everyday business were derived from these findings: For example, discounts for high-priced goods are perceived higher if they are presented in absolute figures (not percentages); for low-priced goods, the opposite is the case. Time restrictions regarding a certain offer, for instance, increase the purchase intentions of potential buyers.35

III. METHODOLOGY

%e hypothesis was tested by applying an ex post facto research design. Fur- thermore, the survey was conducted at one speciﬁc point in time (cross-sectional quantitative study design). In 2014, a sample of 134 (prospective) Austrian academics entirely answered the pre-tested online survey (n = 134). Results regarding partially completed surveys were not included in data analysis; this because discontinuation mostly appeared already on the ﬁrst page of the online survey. Furthermore, the sample was divided into two subsamples of (prospective) Austrian academics with economic related study background respectively with non-economic related study background. %e study was based on a convenience sample. For example, a major part of the sample consisted of students and graduates from the University of Applied

34 Daniel Kahneman, $inking, fast and slow (London: Penguin Books, 2012), 373. 35 Elke Schuster, “Framing von Preisen und seine Auswirkungen auf den Erfolg von Coupons und Sammelaktionen: Eine empirische Analyse möglicher Framingeﬀekte.” (Diploma %esis, Johannes Gutenberg University Mainz, 2007), 11.

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Sciences for Management & Communication in Vienna. Furthermore, persons in the author’s circle of friends and acquaintances participated in the empirical study. Also, online networks were used for acquiring additional participants. Moreover, most of the participants were Viennese residents. Due to the sampling technique (convenience sampling), representativeness of the study must not be assumed. In other words, the sample does not reflect the underlying population. However, basic implications and inspiration for further research can be gained from the results. In the first section, the online questionnaire focused on behavioral finance effects which were based on 9 different example problems derived from literature (double choice answering options). Furthermore, these example problems were translated from English to German language. Also, demographic respectively socio-demographic factors were collected in the second section of the online survey (multiple choice answering options). For measuring the behavioral effects, it was necessary to develop two version of the survey (partially different answering options in each version). %erefore, either version A or version B of the survey was assigned to each participant using a so'ware-driven trigger. However, items (sample problems) that refer to the relevant hypothesis in this paper were the same in both versions. Based on the described framework, the study design can be visualized as follows:36 Figure 3.:Quantitative study design

Source: Author’s ﬁgure

36 Furtner, “Behavioral Finance - Eine empirische Studie über diesbezügliche Verhaltensweisen (angehender) österreichischer Akademikerinnen und Akademiker,” 9.

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Statistical analysis of the nominal data focused on differences between the two subsamples (descriptive methods: frequency distributions, contingency tables) and on possible correlations regarding behavioral finance knowledge and demographic/ socio-demographic variables (inductive methods: Chi-square test, Cramer V). In total, with reference only to the surveys completed, 68,7 % of the participants were (prospective) academics with an economic related study background and 31,3 % of them showed a non-economic related study background. Further- more, 52,2 % of the participants were females respectively 47,8 % of them were of male gender. Predominantly, participants showed younger age (76,1 % were 29 years or younger). Moreover, 32,1 % of the participants were active students before their first academical degree. 47,0 % already completed their Bachelor’s degree, whereas 16,4 % already finished at least one Master’s degree. Besides, 4,5 % held a PhD or other doctoral degree. %e sample structure is summarized in table 1: Table 1.: SAMPLE STRUCTURE (n= 134) Gender: Female Male 52,2 % (70*) 47,8 % (64)

Age: Up to 29 years 30-49 years 50-69 years 76,1 % (102) 19,4 % (26) 4,5 % (6)

Academic study Non-economic related study- Economic related study-background background: background 68,7 % (92) 31,3 % (42)

Undergraduate Doctoral Undergraduate Master degree(e.g. degree(e.g. Dr., Academic status: degree (e.g. B.A., M.A., M.Sc.) student B.Sc., Bakk.) Ph.D.) 32,1 % (43) 47,0 % (63) 16,4 % (22) 4,5 % (6)

*Frequencies (absolute numbers) are shown in brackets

Source: Research results (derived from SPSS-output)

IV. FINDINGS

For testing the main hypothesis, which focuses on potential differences regarding behavioral finance knowledge between the two subgroups, a summarizing group variable was formed. %erefore, the results of the separate behavioral finance

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problems in the questionnaire have been united. It is important to point out, that not all problems in the questionnaire were used for this group variable (behavioral finance knowledge), because other hypotheses also were tested in the underlying study. Indeed, only three selected behavioral finance problems that offer a clear right or wrong behavior in the context of behavioral finance knowledge were considered in data analysis regarding the relevant group variable. %e problems37 refer to investment decisions regarding a private home investment38, an aircra' development investment39 and an investment decision in a printing company40. With reference to both subgroups, the percentage distribution (low/medium/ excellent behavioral finance knowledge group) is presented in figure 4. In the low behavioral finance knowledge group, the percentage of (prospective) academics with non-economic related study background is three times higher than the percentage of (prospective) academics with an economic related study background. Moreover, percentages in the medium and the excellent behavioral finance knowledge group show higher values for (prospective) academics with an economic study background: Figure 4.: BEHAVIORAL FINANCE KNOWLEDGE IN BOTH SUBGROUPS

Source: Research results (SPSS-output)

37 Furtner, “Behavioral Finance - Eine empirische Studie über diesbezügliche Verhaltensweisen (angehender) österreichischer Akademikerinnen und Akademiker,” 45, 53-54, 56. 38 Richard H. %aler, “Mental Accounting and Consumer Choice,” Marketing Science 27, no. 1 (2008): 15, https://doi.org/10.1287/mksc.1070.0330. 39 Arkes and Blumer, “%e psychology of sunk cost,” 129. 40 Arkes and Blumer, “%e psychology of sunk cost,” 133-34.

18 Reinhard Furtner RELATIONS BETWEEN ACADEMIC EDUCATION AND SELECTED BEHAVIORAL FINANCE... (5 - 24)

Regarding inductive analysis results indicate that behavioral finance knowledge is different in the two subgroups examined. First, as shown in table 2, Chi- square test (Chi-Square = 10.056, p = 0.007) indicates at a significant level (p < 0.05) that differences exist between (prospective) academics with economic related and non-economic related study-background: Table 2.: CHI Square test

Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 10,056a 2 ,007 Likelihood Ratio 9,427 2 ,009

Linear-by-Linear 7,108 1 ,008 Association N of Valid Cases 134 a. 0 cells (,0%) have expected count less than 5. %e minimum expected count is 7,52.

Source: Research results (SPSS-output)

Furthermore, as shown in table 3, Cramer’s V as a measure of association (Cramer’s V = 0.274, p = 0.007) suggests a weak relation between academical background and behavioral ﬁnance knowledge on a statistical signiﬁcant level (p < 0.05): Table 3.: CRamer’s V test

Symmetric Measures Value Approx. Sig.

Nominal by Phi ,274 ,007 Nominal Cramer’s V ,274 ,007 Contingency Coeﬃcient ,264 ,007 N of Valid Cases 134

Source: Research results (SPSS-output) V. DISCUSSION

Descriptive statistics findings (relative frequencies) show a lower level of behavioral finance knowledge for the subgroup of (prospective) academics with a non-economic related study background. In particular, the amount of test subjects with low behavioral finance knowledge is approximately three times higher

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for test persons with non-economic study background. Moreover, percentages of test subjects with medium or excellent behavioral finance knowledge is higher for (prospective) academics with an economic related study background. Already, these findings indicate the importance of the study background for the level of behavioral finance knowledge. Furthermore, also inferential statistics (Chi-square, Cramer’s V) indicate a significant relation between academical background and the level of behavioral finance knowledge. As shown in the introduction section, cognitive factors like study background seem to influence behavioral finance knowledge and therefore acts as an influencing factor for investment decisions. Especially, behavioral finance biases like loss aversion or framing effects occur in both subgroups. %us, results illustrate that humans tend not to act like the hypothetical homo oeconomicus Although study background is considered to act as an independent factor, a causal structure is not proven by this study design. Moreover, since the sample is not representative and because of the small sample size, the study is not a basis for comprehensive analysis of the underlying research question. Also, the problem of spurious causalities cannot be excluded. However, implications for a possible relation could be identified. Furthermore, a longitudinal research design could provide further insights in the question how the academical background influences the level of behavioral finance knowledge. It also should be pointed out that the queried sample problems can not strictly be linked to one single behavioral finance effect. In fact, different behavioral finance effects are included in the sample problems to different degrees. Based on the findings of the study, a broad involvement of behavioral aspects in the academical curricula could act as a profound basis for improving investment decisions in private and professional situations with huge financial impact.

VI. CONCLUSION

%e aim of this study is to investigate the relation between economic or non- economic academical background and behavioral finance knowledge. In that context, it is important to note that behavioral finance knowledge acts as a cognitive (behavioral) factor that influences the quality of our investment decisions. Since investment decisions in a personal or professional situation could have a strong impact on overall wealth of individuals or profit-oriented organizations, underlying factors which could improve the quality of such decisions are of high practical relevance.

20 Reinhard Furtner RELATIONS BETWEEN ACADEMIC EDUCATION AND SELECTED BEHAVIORAL FINANCE... (5 - 24)

Study results show, that (prospective) academics with an economic related study-background show better results regarding behavioral finance knowledge. Moreover, a weak relation between study-background and behavioral knowledge is identified. Although, a causal structure is not proved through this study, basic implications can be derived. Another limitation of the study is the fact that data about past investment experience was not collected. Due to the small sample size and the sampling procedure the subsamples are not a base for scientifically-verified further conclusions. Practical contribution of the study results is the evidence that the study background (economical related or non-economical related) influences investment decisions. %erefore, the area of behavioral effects should be integrated in (academical) education. Moreover, it can be assumed that behavioral elements are already taught in Austrian academical education, although those elements are frequently not outlined explicitly in the curricula. Further research regarding the research question could be realized through a larger-scaled quantitative study or through causal analysis which investigates the underlying heuristics and considerations on solving investment problems.

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REFERENCES

Adelt, Peter, and Bert Feldmann. “Spar- und Anlageentscheidungen älterer Menschen.” In Finanzpsychologie. Edited by Lorenz Fischer, %omas Kutsch and Ekkehard Stephan, 250-72. München, Wien: Oldenbourg, 1999. https://doi.org/10.1515/9783486801149-011. Arianti, Baiq Fitri. “%e influence of financial literacy, financial behavior and income on investment decision.” Economics and Accounting Journal 1, no. 1 (2018): 1-10. Arkes, Hal R., and Peter Ayton. “%e sunk cost and Concorde effects: Are humans less rational than lower animals?” Psychological Bulletin 125, no. 5 (1999): 591-600. https://doi.org/10.1037//0033- 2909.125.5.591. Arkes, Hal R., and Catherine Blumer. “%e psychology of sunk cost.” Organizational Behavior and Human Decision Processes 35, no. 1 (1985): 124-40. https://doi.org/10.1016/0749-5978(85)90049-4. Benartzi, Shlomo, and Richard %aler. “Myopic Loss Aversion and the Equity Premium Puzzle.” $e Quarterly Journal of Economics 110, no. 1 (1995): 73-92. https://doi.org/10.3386/w4369. Betz, Norbert, and Ulrich Kirstein. Börsenpsychologie. 2. Auflage 2015. Simplified. München: FBV, 2015. Cude, Brenda, Frances Lawrence, Angela Lyons, Kaci Metzger, Emily LeJeune, Loren Marks, and Krisanna Machtmes. “College students and financial literacy: What they know and what we need to learn.” Proceedings of the Eastern Family Economics and Resource Management Association 102, no. 9 (2006): 106-9. Devos, Jan. “Small and Medium-sized Enterprises (SMEs) and IT: A Market for Lemons?” Furtner, Reinhard. “Behavioral Finance - Eine empirische Studie über diesbezügliche Verhaltensweisen (angehender) österreichischer Akademikerinnen und Akademiker.” Masterarbeit, Department of Management and Entrepreneurship, University of Applied Sciences for Management and Communication, 2014. Genesove, David, and Christopher Mayer. “Loss Aversion and Seller Behavior: Evidence from the Housing Market.” $e Quarterly Journal of Economics 116, no. 4 (2001): 1233-60. https://doi. org/10.3386/w8143. Günther, %omas, and Martin Detzner. “Risikoverhalten von Managern: Ergebnisse empirischer Controllingorschung.” CFO aktuell 3, no. 3 (2009): 124-28. Harrison, Tina S. “Mapping Customer Segments for Personal Financial Services.” International Journal of Bank Marketing 12, no. 8 (1994): 17-25. https://doi.org/10.1108/02652329410069010. Huston, Sandra J. “Measuring financial literacy.” Journal of Consumer Affairs 44, no. 2 (2010): 296-316. Kahneman, Daniel. “Maps of Bounded Rationality: Psychology for Behavioral Economics.” American Economic Review 93, no. 5 (2003): 1449-75. https://doi.org/10.1257/000282803322655392. Kahneman, Daniel. $inking, fast and slow. London: Penguin Books, 2012. Kahneman, Daniel, and Amos Tversky. “Prospect %eory: An Analysis of Decision under Risk.” Econometrica 47, no. 2 (1979): 263. https://doi.org/10.2307/1914185. Kanodia, Chandra, Robert Bushman, and John Dickhaut. “Escalation Errors and the Sunk Cost Effect: An Explanation Based on Reputation and Information Asymmetries.” Journal of Accounting Research 27, no. 1 (1989): 59. https://doi.org/10.2307/2491207.

22 Reinhard Furtner RELATIONS BETWEEN ACADEMIC EDUCATION AND SELECTED BEHAVIORAL FINANCE... (5 - 24)

Moon, Henry. “Looking forward and looking back: Integrating completion and sunk-cost effects within an escalation-of-commitment progress decision.” Journal of Applied Psychology 86, no. 1 (2001): 104-13. https://doi.org/10.1037/0021-9010.86.1.104. Müller, Horst. “Zur Risikobereitscha' privater Geldanleger.” Kredit und Kapital 11, no. 1 (1995): 134- 60. Oehler, Andreas. “Anomalien, Irrationalitäten oder Biases der Erwartungsnutzentheorie und ihre Relevanz für die Finanzmärkte.” Zeitschri& für Bankrecht und Bankwirtscha& 4, no. 2 (1992): 97-124. Peteros, Randall, and John Maleyeff. “Application of behavioural finance concepts to investment decision-making: Suggestions for improving investment education courses.” International Journal of Management 30, no. 1 (2013): 249. Rost, Norbert. “Der Homo oeconomicus: Eine Fiktion der Standardökonomie.” Zeitschri& für Sozialökonomie 45, 158/159 (2008): 50-58. Schlösser, Hans-Jürgen. “Menschenbilder in der Ökonomie.” Orientierungen zur Wirtscha&s- und Gesellscha&spolitik 41, no. 112 (2007): 68-71. Schuster, Elke. “Framing von Preisen und seine Auswirkungen auf den Erfolg von Coupons und Sammelaktionen: Eine empirische Analyse möglicher Framingeffekte.” Diploma %esis, Johannes Gutenberg University Mainz, 2007. Shefrin, Hersh. Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing (Financial Management Association Survey and Synthesis). Revised Edition. Oxford: Oxford University Press, 2007. Silgoner, Maria, Bettina Greimel-Fuhrmann, and Rosa Weber. “Financial literacy gaps of the Austrian population.” Monetary Policy & the Economy Q 2 (2015): 35-51. %aler, Richard H. “Mental accounting matters.” Journal of Behavioral Decision Making 12, no. 3 (1999): 183-206. https://doi.org/10.1002/(SICI)1099-0771(199909)12:3<183::AID- BDM318>3.0.CO;2-F. %aler, Richard H. “Mental Accounting and Consumer Choice.” Marketing Science 27, no. 1 (2008): 15-25. https://doi.org/10.1287/mksc.1070.0330. “%aler mental accounting and consumer choice.” Vienna University of Economics and Business. “Curricula for the study programs.” Accessed April 19, 2019. https://www.wu.ac.at/en/students/my-program/bachelors-programs/business-economics-and- social-sciences/curricula. Wahren, Heinz-Kurt. Anlegerpsychologie. 1. Aufl. Wiesbaden: VS Verlag für Sozialwissenscha'en / GWV Fachverlage GmbH Wiesbaden, 2009. https://doi.org/10.1007/978-3-531-91374-2. http:// dx.doi.org/10.1007/978-3-531-91374-2. Wärneryd, Karl Erik. Stock-market psychology: How people value and trade stocks. Cheltenham: Elgar, 2001.

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Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

ARTICLE INFO Received: 20.9.2018. Accepted: 28.2.2019. JEL classiﬁcation: M20, M21, M29

Keywords: Kaizen; Continuous Improvement; Business Performance

DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW

Vesna Sesar* and Anica Hunjet *[email protected]

25 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

When analysing the literature on continuous improvement (CI) as a concept of continuously moving forward it seems there are still gaps in the literature about the relation between continuous improvement and its link to business performance. Many authors state that continuous improvement brings many benefits to organizations however it seems that the benefits of this concept are more expressed in literature than in practice, since studies show its stagnation in organizations over a certain time a&er its been implemented. Here an overview of possible barriers will be presented. Few studies aimed to analyse organizations who had more mature continuous improvement programs implemented which brought to higher performance of an organization, which seems to be an opportunity in a fast hanging environment. $e aim of the research is to address this gap between the continuous improvement and business performance and show a systematic literature review about the topic. Databases Web of Science and Ebscohost were addressed with terms continuous improvement, kaizen and performance. Concentration was on contemporary studies, published articles from 2007 till the end of 2018 were taken into analysis. Research results show that most of analysed articles found a positive relation between continuous improvement and one or more perspectives of business performance however the most prominent perspective in articles is internal process performance, then innovation and learning perspective, a&er that customer perspective, and then financial performance perspective. On the basis of an analysis there is still a gap considering analysing CI as a strategical process that must be included in every aspect of an organization, therefore the need to be measured and linked to all four business performance measures: financial perspective, customer, innovation and learning and internal process perspective.

26 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

". INTRODUCTION

Continuous improvement or kaizen in organizations had ascending path since Masaki Imai in 1986 wrote a book Kaizen: %e Key to Japan’s Competitive Success (Imai, 1986). However, the concept itself began to evolve with Shewhart’s cycle at the beginning of 20th century in quality control. Many authors differ continuous improvement in the West and East, where on the West managers call it continuous improvement, and in Japan is called kaizen. Actually this is the same philosophy, but implemented differently in every organization that has its specific knowledge, resources and technology. %e economy of Japan a'er the World War 2 blossomed based on the principle of continuous improvement. %e philosophy of continuous improvement is a main proposition of total quality management and lean production (Brunet and New, 2003). It can be stated that continuous improvement gains its value in raising operating performance in manufacturing industry (Cardona Mora, 2014), while in the last ten years gains a lot of attention in service industry as a key to customer satisfaction (Neacsu, 2015). Many authors tried to explain what continuous improvement is therefore many definitions appeared. Table 1. shows the review of definitions from the authors Sanchez and Blanco (2014). Table 1.: %e review of definitions of continuous improvement

No. Authors Definition of contiuous improvement Improve constantly and forever the system 1 Deming (1982) of production and service (principle 5 of transformation) Progressive improvement involving everyone 2 Imai (1989) in the company (including both workers and managers) Bessant, Caffyn, Gilbert, Harding, and A company-wide process of focused and 3 Webb (1994) in Carpinetti, Buosi, and Gerolamo (2003) continuous incremental innovation Juergensen (2000) in Bhuiyan and Baghel Improvement initiatives that increase 4 (2005) successes and reduce failures A particular bundle of routines which 5 Bessant, Caffyn, and Gallagher (2001) can help an organisation improve what it currently does

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No. Authors Deﬁnition of contiuous improvement 6 Dahlgaard, Kristensen, and Kanji (2002) Small continuous changes for the better Pervasive and continual activities, outside Brunet and New (2003) the contributor’s explicit contractual roles, 7 to identify and achieve outcomes he believes contribute to the organisational goals %e planned, organised and systematic Boer and Gertsen (2003) in Middel, op de process of ongoing, incremental and 8 Weegh, and Gieskes (2007) company-wide change of existing practices aimed at improving company performance %e continuous improvement cycle consists of establishing customer requirements, Chang (2005) meeting the requirements, measuring 9 success, and continuing to check customers’ requirements to ﬁnd areas in which improvements can be made Culture of sustained improvement aimed Bhuiyan et al. (2006) a eliminating waste in all organisational 10 systems and processes, and involving all organisational participants

Manos (2007) Subtle and gradual improvements that are 11 made over time

Source: Sanchez and Blanco, 2014, p. 988 Shumpei (2017) in his case study states that continuous improvement is a batch of innovations and to support those activities organization has to be designed in a proper manner to be able to deliver its results. According to Imai (1986) continuous improvement can happen on the individual level, team level, it can be a special event or a day to day activity and happens on a process-level or sub process level. Continuous improvement can be explained through PDCA cycle, famously known as the Deming cycle, where steps PLAN, DO, CHECK and ACT must happen continuously in order to generate improvements. Sokovic et al. (2010, p. 478) states the key for improvements „are „in the “act” stage a'er the completion of a project when the cycle starts again for the further improvement “. And that is how the level of quality is raised in an organization.

#. THE PROBLEM OF CONTINUOUS IMPROVEMENT SUSTAINABILITY

Brunet and New (2003, p. 1428) state that continuous improvement is simple use which represents “both its weakness and its strength “. Many companies are trying to ﬁnd a magic wand for successful CI application, however it seems that CI activities disappear over a time.

28 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

Analysing scientific articles regarding barriers to successful implementation or sustainability of CI process seems to be a forest of different barriers, what is not surprising since continuous improvement develops specifically for every organization. However, recent research done by McLean et al. (2017) analyses barriers on the basis of 73 matching articles which were chosen from 782 papers. %e findings are in short represented in table 2 under 8 topic names. Table 2.: %e review of definitions of continuous improvement

$e review of CI barriers

No. of Topic name Explanation topics

Motives and expectations Implementing CI for the wrong reason 1 causes his end Unrealistic beliefs, resistance, culture Organisational culture and environment not well suited, or structure of the 2 organization, the level of support from other business areas

$e Management leadership mng support and commitment, demand 3 for high level of involvment %e level the initiative is implemented to, 4 Implementation Approach the deployment speed and the way how is it implemented inﬂuences outcomes. %e manner of delivery and training 5 Training content is important, putting knowledge into practice also important

Project Management poor selection, managing and resources 6 are barriers of success Except management team, other Employee involvement levels employees must be involved during 7 implementation process, considering: time allocation, role conﬂict, participation levels Lack of mechanisms to review projects, false impression of results, poor Feedback and results communication, inaccuracies, poor review. 8 In short-run: negative impact, in the long run: if not able to deliver ﬁnancial returns and measurable results its likely to fale

Source: Author according to McLean et al. (2017, p. 5-13)

Macpherson et al. (2015, p. 8) state that organizations have to assure “informal and formal education and training“ to sustain their continuous improvement activities. Bateman (2005) states that process improvement programs are the key to sustaining continuous improvement activities where use of PDCA cycle is needed, enabling process for CI activities and managers support. Iwao and Marinov (2018)

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analysed on the example of two companies why continuous improvement activities in one do and in the other do not generate changes in organizations. %ey’ve analysed it from the aspect of theory of routine dynamics and concluded that CI improvements have eﬀect on performance if three routines; material, ostensive, and performative are in line with each other. Further they conclude that Stand- ard Operating Procedures must be created in combination with company’s reward system. Many barriers to CI success are mentioned and they should be tested to see their mediatory or moderating role in sustaining the CI system organizations. Continuous improvement can be seen as a resource by which organization can improve their position on the market (Choo et al. 2007). %erefore, its implementation should be planned on a strategic organizational level to yield the best of it. As Wu and Chen (2006, p. 706) note the CI can achieve its sustainability only if organization builds “integrated super system where regenerative input is injected on a timely basis”. Further, a link between CI and business performance will be analysed.

$. METHODOLOGY

%e aim of this study is 3 fold: (1) to represent basic characteristics and a short review of the most common barriers addressing continuous improvement sustainability, (2) to see which business performance indicators were taken into account and are most commonly analysed regarding the connection with continuous improvement and (3) identify gaps, contribution and limitations of the research. For doing this systematic literature review the methodology of Sfreddo et al. (2018) was used. %ree steps where followed. First step was searching articles with defined key words in databases Web of Science and Ebscohost. We used key term „kaizen“, „continuous improvement“ and „performance“, where kaizen and CI where used to identify narrow field in quality management. Performance was used to identify business performance indicators related to continuous improvement from the literature. %e screening of selected key words in abstracts was done and three inclusion criteria were followed: (1) up to date articles from period 2007 till the end of 2018 (2) articles that indicated relation between continuous improvement and business performance; and (3) articles written in English language. %e second step of the search included exclusion criteria’s. For doing quality analysis authors used three exclusion criteria: (1) articles not published in English language (2) articles that where stating relation between continuous improvement and business performance in their abstract but in further reading they did not reach that aim. (3) the same articles that multiplied in database’s. And in final step the authors prepared a final article list that was further analysed (Figure 1).

30 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

Figure 1.: Steps taken for ﬁnalizing the list of the articles to be analysed.

Source: Author’s work

%. RESULTS

A'er ﬁnalizing the list of articles and analysing papers some general information’s will be presented. Figure 2 presents the number of articles published per year about the link between continuous improvement and business performance. It can be seen that in the last two analysed years CI has gained much attention among scholars and practice. Figure 2.: Number of published articles from year 2007-2018

Source: Author’s work

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Figure 3 represents data about the origin of the paper. It can be seen that Unit- ed States are leading the way about the topic with 8 published papers. While under other countries there are 26 diﬀerent countries with only one published paper about the topic, from which for example Slovenia had one published paper and Croatia has no published paper about the topic. Figure 3.: %e number of published articles by country

Source: Author’s work

Figure 4 represents scientific area of analysed articles where 26 papers (50%) are in the field of business economics. 18 papers (35%) belong to technical field engineering. %is is an interesting fact since CI originated from quality process improvement and is usually implemented on operational level where improvements that’s why so many papers about CI have been published primarily in technical field which changed over a time. %is is changing due to fact that CI represents a strategy for the companies and more o'en is being applied on strategic level. Figure 4.: Articles by research area

Source: Author’s work

32 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

Figure 5 represents an analysis which shows paper type. 75% (39 out of 52 papers) of articles are published in scientiﬁc journals, while 17% are conference papers and 8% are review’s. Figure 5.: Papers by document type

Source: Author’s work A'er presenting general information’s a detailed reading of articles about the relation between continuous improvement and business performance will be stated. Performance indicators have to be picked and used in the company so it can enable easy control a'er organization sets its plans and achieves set goals. Also data gathered from performance measures have to be clear and easy to use for management. Performance measures can be divided into traditional or financial measures which may “lead investors and other relevant stakeholders to make inap- propriate decisions when allocating scarce resources” (Firer and Williams, 2003, p 351) or non-financial measures which are perceived as “sufficient but subjective” (Sitkı and Aslan, 2012, p.758). Mahmood et al. (2014, p. 664) divides those indicators to judgmental and objective dimension where first could be subjective and indicates measures such as quality of the service, customer satisfaction and retention, while objective dimension is concentrated on sales growth, profit, market share and efficiency. Overall, it all comes to the same point, in today’s environment both measures (objective and subjective) are required. Organizations have to satisfy the law in country of origin by admitting financial reports to responsible bodies. Also, they have to create their own comprehensive reports in order to gain benefits from it. In most cases big organizations are establishing controllership department to be able to maximize their resources. Based on that view the author used the Balanced scorecard approach for measuring business performance. Figure 6 represents in short some performance measures that where then systematized under four BSC perspectives; financial, customer, innovation and learning and internal process

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perspective. Figure 6.: Performance indicators taken from the literature and sorted on the basis of BSC framework

Source: Author’s work

Figure 7.: %e relation between CI and business performance

INNO- INTERNAL FINANCIAL CUSTOMER LEARNING PROCESS NO. AUTHOR PERSPEC- PERSPEC- PERSPEC- PERSPEC- TIVE TIVE TIVE TIVE 1 Abdulmouti, H (2015) NA NA NA V 2 Antunes et al. (2017) NA NA V NA 3 Aouag et al. (2015) NA NA NA V 4 Azizi (2015) NA NA VV 5 Azizi (2015) NA NA NA V 6 Backlundet al. (2015) VV NA NA 7 Baker III et al. (2012) NA NA VV

Belekoukias et al. NA NA NA V 8 (2014)

Bratu and Radutu NA NA NA V 9 (2017) 10 Bratu et al (2016) NA NA NA V 11 Butler et al (2018) NA NA NA V

34 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

INNO- INTERNAL FINANCIAL CUSTOMER LEARNING PROCESS NO. AUTHOR PERSPEC- PERSPEC- PERSPEC- PERSPEC- TIVE TIVE TIVE TIVE 12 Cardoso et al. (2018) NA NA NA V 13 Chan and Tay (2018) NA NA NA V 14 de Souza et al. (2018) NA NA NA V 15 Delgado et al. (2014) NA V NA V

Dhiravidamani et al. NA NA NA V 16 (2017) 17 Doolen et al (2008) NA NA NA V

Ebrahimi and Sadeghi V NA NA V 18 (2013) 19 Erez, A (2016) VVVV 20 Garcia et al. (2014) NA V NA V 21 Glover et al. (2015) NA NA NA V 22 Gupta et al. (2013) VVV NA 23 Habidin et al. (2018) NA NA VV 24 Hambach et al. (2017) NA NA NA V 25 Heavey et al. (2014) VV NA NA

Iwao and Marinov NA NA NA V 26 (2018) 27 Kattman (2014) NA V NA NA 28 Kohlbacher (2013) NA NA VV

Kovach and NA NA V NA 29 Fredendall (2013) 30 Koval et al. (2018) NA V NA NA 31 Kumar et al. (2018) NA V NA V 32 Lam et al. (2015) NA NA NA V 33 Maletič et al. 2012 NA NA NA V 34 Mallick et al. (2013) VVVV

Marin-Garcia et al. NA NA NA V 35 (2009)

Marin-Garcia et al. NA V NA V 36 (2008)

Mehmood et al. VVVV 37 (2014)

Muras and Hovell V NA VV 38 (2014)

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INNO- INTERNAL FINANCIAL CUSTOMER LEARNING PROCESS NO. AUTHOR PERSPEC- PERSPEC- PERSPEC- PERSPEC- TIVE TIVE TIVE TIVE

Pantouvakis and VV NA NA 39 Karakasnaki (2016)

Phoewhawm, R. NA NA VV 40 (2017) 41 Popescu (2015) NA NA NA V 42 Saleem et al. (2012) NA NA NA V 43 Gao and Low (2014) NA NA NA V

Singh and Singh VVVV 44 (2009)

Singh and Singh NA V NA V 45 (2017)

Singh and Singh VV V V 46 (2018)

Suárez-Barraza et al. NA NA VV 47 (2012) 48 Sugiyama et al. (2011) NA V NA V Todorovic and Čupić 49 V NA NA V (2017)

Oropesa Vento et al V NA V NA 50 (2016)

Verdinejad et al. NA NA VV 51 (2010)

Wiengarten et al. NA NA VV 52 (2013) * NA - not analysed relation * V- validated relation

Source: Author’s work

Erez (2016) found that company in service sector increased its revenue a'er kaizen adaptation, also this program affected customer satisfaction by 11% as well as employee satisfaction. Also, the research of Koval et al (2018) confirmed strong impact of continuous improvement on customer satisfaction in service sector by researching mediator variables such as reward system, quality culture, management commitment, training and goal setting. Further, Bratu and Răduţu (2017) represented three case studies in Romania that introduced kaizen on operational and strategic level. All three cases represent as authors call it “the next generation companies” since they have all reached higher levels of efficiency and effectiveness

36 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

(Bratu and Răduţu, 2017, p. 1066). %erefore, they’ve become internationally competent a'er adopting the kaizen approach. Antunes et al. (2017) analysed innovation and found connection between continuous improvement and innovation which then led to better ﬁnancial results of the company.

&. DISCUSSION, RESULTS AND FUTURE IMPLICATIONS

%e results in short are presented in Table 3 which represents number of articles that validated CI relation with one or more business perspectives. In systematic literature review which included 52 articles, it can be concluded that most authors analysed and validated the relation between CI and internal processes (43 articles). A'er that the most analysed relation was between CI and innovation and learning perspective where 18 articles validated that effect. 17 articles validated the influence of CI on customer perspective. Finally, 13 articles out of 52 validated the relation between CI and financial perspective. Table 3.: %e number of articles that analysed relation between CI and one or more business performance perspectives

Relation beetween Inno- Internal- Financial Customer CI and learning process perspec- % perspec- % % % business perspec- perspec- tive tive perfor- tive tive mance Not analysed relation 39 75 35 67 34 65 9 17 (NA)

Validated 13 25 17 33 18 35 43 83 relation (V) SUM 52 100 52 100 52 100 52 100

Source: Author’s work

%is systematic literature review also shows in Figure 8 the number of papers that concentrated on analysing one or more business performance perspective in relation to continuous improvement. %e results show that 48% of articles analysed and validated connection between CI and at least one business perspective, while analysing the inﬂuence of CI on all four business perspectives was found in 5 articles (10%).

37 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

Figure 8.: %e number of articles analysing one or more business performance perspectives

Source: Author’s work

'. CONCLUSION

%is aim of the paper was to present the main findings about the connection between continuous improvement concept and business performance where financial perspective, customer perspective, innovation and learning and internal process perspective where taken into account based on the BSC approach. Ana- lysed papers showed that studied relation between continuous improvement in most cases have a positive relation on internal processes since 43 articles out of 52 show its connection while customer perspective is linked to CI in 17 articles, innovation and learning in 18 articles and financial benefits where validated in 13 articles. However continuous improvement performance indicators where mostly concentrated on operational benefits of the company while in today’s competitive environment they should be closely connected with overall company strategy and from operational level raised to strategic level of the organization. To do so every company has to select its own performance indicators to be able to track the continuous improvement impact on the strategic level. %en it could be easier to demonstrate the CI benefits for the company in all perspectives rather than concentrate mostly on internal processes. On the other hand, continuous improvement programs once implemented are the core essence of internal processes so

38 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

this is not surprising that most papers show positive relation to this perspective. However, in today’s business environment the effects of continuous improvement should be broadly analysed. So the authors recognized a certain gap in the systematic review where most articles are concentrated on analysing one or two aspects of business performance while there is a necessity to analyse a broader picture of continuous improvement effect on overall business performance and its influence on all four business performance perspectives, so this finding shows an area to be researched in the future. %is could also bring to a better sustainability of continuous improvement concept in organizations. Some limitations must be stated. While researching the article base, the authors concentrated on three terms: continuous improvement, kaizen and performance. Maybe this research can be expanded in the future with new key words since the concept itself originated from the quality or concentrate on the other aspect of continuous improvement benefits for the company. Also the period of the articles included more up to date articles from 2007 till 2018, so also the period should be taken into consideration. On the basis of an analysis there is still a gap considering analysing CI as a strategical process that must be included in every aspect of an organization, therefore the need to be measured and linked to all four business performance measures: financial perspective, customer, innovation and learning and internal process perspective.

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REFERENCES

Abdulmouti, H. (2015, March). %e role of Kaizen (continuous improvement) in improving companies’ performance: A case study. In Industrial Engineering and Operations Management (IEOM), 2015 International Conference on (pp. 1-6). IEEE. Alič, M. “Impact of ISO 9001 certification cancellation on business performance: a case study in Slovenian organizations.” Total Quality Management & Business Excellence 25, no. 7 (2014): 790-811. Antunes, M. G., Quirós, J. T., & Justino, M. D. R. F. (2017). %e relationship between innovation and total quality management and the innovation effects on organizational performance. International Journal of Quality & Reliability Management, 34(9), 1474-1492. Aouag, H., Kobi, A., & Mechenene, A. (2015). Analysis of competitiveness level in an industrial company using a continuous improvement-based approach. International Journal of Six Sigma and Competitive Advantage, 9(2-4), 87-108. Azizi, A. (2015). Designing a future value stream mapping to reduce lead time using SMED-A case study. Procedia Manufacturing, 2, 153-158. Azizi, A. (2015). Evaluation improvement of production productivity performance using statistical process control, overall equipment efficiency, and autonomous maintenance. Procedia Manufacturing, 2, 186-190. Backlund, F., Chronéer, D., & Sundqvist, E. (2015). Maturity assessment: towards continuous improvements for project-based organisations?. International Journal of Managing Projects in Business, 8(2), 256-278. Baker III, F. W., Chow, A., Woodford, K., & Maes, J. D. (2012). Applying Continuous Improvement Techniques to Instructional Design Technology (IDT) for Greater Organizational Effectiveness. Organization Development Journal, 30(1). Belekoukias, I., Garza-Reyes, J. A., & Kumar, V. (2014). %e impact of lean methods and tools on the operational performance of manufacturing organisations. International Journal of Production Research, 52(18), 5346-5366. Bratu, J., & Răduţu, A. (2017, July). Kaizen Award in Romania: the KAIZEN™ way in obtaining the continuous improvement success. In Proceedings of the International Conference on Business Excellence (Vol. 11, No. 1, pp. 1058-1067). De Gruyter Open. BRATU, J., RĂDUŢU, A., & PETRESCU, C. A. (2016). KAIZEN™ Management System (KMS): the driving engine of companies’ sustainability. ENERGY, CLIMATE CHANGE AND SUSTAINABILITY, 175. Butler, M., Szwejczewski, M., & Sweeney, M. (2018). A model of continuous improvement programme management. Production Planning & Control, 29(5), 386-402. Cardoso, W., Bassi, E., Bertosse, J. F., Saes, R. M., & Achcar, J. A. (2018). %e implementation and use of the” 5s” and Kaizen program for the management of sewing offices of a middle family company. Independent Journal of Management & Production, 9(3), 767-784. Chan, C. O., & Tay, H. L. (2018). Combining lean tools application in kaizen: a field study on the printing industry. International Journal of Productivity and Performance Management, 67(1), 45-65. Choo, Adrian S., Kevin W. Linderman, and Roger G. Schroeder. “Method and context perspectives on learning and knowledge creation in quality management.” Journal of operations management 25.4 (2007): 918-931.

40 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

de Souza, I. G., Lacerda, D. P., Camargo, L. F. R., Dresch, A., & Piran, F. S. (2018). Do the improvement programs really matter? An analysis using data envelopment analysis. BRQ Business Research Quarterly, 21(4), 225-237. Delgado, A., Weber, B., Ruiz, F., De Guzmán, I. G. R., & Piattini, M. (2014). An integrated approach based on execution measures for the continuous improvement of business processes realized by services. Information and So'ware Technology, 56(2), 134-162. Deshmukh, G., Patil, C. R., & Deshmukh, M. G. (2017, January). Manufacturing industry performance based on lean production principles. In Nascent Technologies in Engineering (ICNTE), 2017 International Conference on (pp. 1-6). IEEE. Dhiravidamani, P., Ramkumar, A. S., Ponnambalam, S. G., & Subramanian, N. (2018). Implementation of lean manufacturing and lean audit system in an auto parts manufacturing industry-an industrial case study. International Journal of Computer Integrated Manufacturing, 31(6), 579-594. Doolen, T. L., Van Aken, E. M., Farris, J. A., Worley, J. M., & Huwe, J. (2008). Kaizen events and organizational performance: a field study. International Journal of Productivity and Performance Management, 57(8), 637-658. Ebrahimi, M., & Sadeghi, M. (2013). Quality management and performance: An annotated review. International Journal of Production Research, 51(18), 5625-5643. Erdogan, S., Quesada-Pineda, H., & Bond, B. (2017). An empirical tool to measure the effectiveness of kaizen events: A case study in the wood products industries. Forest Products Journal, 67(3), 164-178. Erez, A. (2016). %e role of kaizen in creating radical performance results in a logistics service provider. LogForum, 12. Firer, S., & Mitchell Williams, S. (2003). Intellectual capital and traditional measures of corporate performance. Journal of intellectual capital, 4(3), 348-360. Gao, S., & Low, S. P. (2013). Impact of Toyota Way implementation on performance of large Chinese construction firms. Journal of Professional Issues in Engineering Education and Practice, 140(3), 04013022. García, J. L., Maldonado, A. A., Alvarado, A., & Rivera, D. G. (2014). Human critical success factors for kaizen and its impacts in industrial performance. %e International Journal of Advanced Manufacturing Technology, 70(9-12), 2187-2198. Gupta, M. C., Sahi, G. K., & Chahal, H. (2013). Improving market orientation: the theory of constraints-based framework. Journal of Strategic Marketing, 21(4), 305-322. H. James Harrington,”Continuous versus breakthrough improvement”, Business Process Re- engineering & Management Journal, Vol. 1 Iss 3 (1995): 31-49. Habidin, N. F., Hashim, S., Fuzi, N. M., & Salleh, M. I. (2018). Total productive maintenance, kaizen event, and performance. International Journal of Quality & Reliability Management, 35(9), 1853-1867. Hambach, J., Kümmel, K., & Metternich, J. (2017). Development of a digital continuous improvement system for production. Procedia CIRP, 63, 330-335. Heavey, C., Ledwith, A., & Murphy, E. (2014). Introducing a new continuous improvement framework for increased organisational return on investment. %e TQM Journal, 26(6), 594-609. Iwao, S., & Marinov, M. (2018). Linking continuous improvement to manufacturing performance. Benchmarking: An International Journal, 25(5), 1319-1332.

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Iwao, Shumpei, “Revisiting the existing notion of continuous improvement (Kaizen): literature review and field research of Toyota from a perspective of innovation.” Evolutionary and Institutional Economics Review, no 14.1 (2017): 29-59. Kaye, M., & Anderson, R., “Continuous improvement: the ten essential criteria”, International journal of quality & reliability management, No. 16(5), (1999): 485-509. Kohlbacher, M. (2013). %e impact of dynamic capabilities through continuous improvement on innovation: the role of business process orientation. Knowledge and Process Management, 20(2), 71- 76. Kovach, J. V., & Fredendall, L. D. (2013). %e influence of continuous improvement practices on learning: An empirical study. Quality Management Journal, 20(4), 6-20. Koval, O., Nabareseh, S., Chromjaková, F., & Marciniak, R. (2018). Can continuous improvement lead to satisfied customers? Evidence from the services industry. %e TQM Journal, 30(6), 679-700. Kumar, S., Dhingra, A. K., & Singh, B. (2018). Kaizen Selection for Continuous Improvement through VSM-Fuzzy-TOPSIS in Small-Scale Enterprises: An Indian Case Study. Advances in Fuzzy Systems, 2018. Lam, M., O’Donnell, M., & Robertson, D. (2015). Achieving employee commitment for continuous improvement initiatives. International Journal of Operations & Production Management, 35(2), 201-215. Larsson, C., Syberfeldt, A., & Säfsten, K. (2017). How to visualize performance measures in a manufacturing SME. Measuring Business Excellence, 21(4), 337-350. Lidia Sanchez and Beatriz Blanco, “%ree decades of continuous improvement.” Total Quality Management & Business Excellence 25.9-10 (2014): 986-1001. Macpherson, Wayne G., et al. “Kaizen: a Japanese philosophy and system for business excellence.” Journal of Business Strategy 36.5 (2015): 3-9. Mahmood, S., & Ahmed, A. (2014). Relationship between TQM dimensions and organizational performance. Pakistan Journal of Commerce and Social Sciences, 8(3), 662-679. Maletič, D., Maletič, M., & Gomišček, B. (2012). %e relationship between continuous improvement and maintenance performance. Journal of Quality in Maintenance Engineering, 18(1), 30-41. Mallick, D. N., Ritzman, L. P., & Sinha, K. K. (2013). Evaluating Product‐Centric Continuous Improvements: Impact on Competitive Capabilities and Business Performance. Journal of Product Innovation Management, 30, 188-202. Marin-Garcia, J. A., Garcia-Sabater, J. J., & Bonavia, T. (2009). %e impact of Kaizen Events on improving the performance of automotive components’ first-tier suppliers. International Journal of Automotive Technology and Management, 9(4), 362-376. Marín-García, J. A., García-Sabater, J., & Miralles, C. (2008). Manufacturing perfomance: Impact of Kaizen-Blitz implementation in several automotive components first tier suppliers. Dirección y Organización, (35), 37-44. Masaaki Imai, Kaizen: %e Key to Japan’s Competitive Success, New York: MacGraw-Hill, 1986. McLean, Richard S., Jiju Antony, and Jens J. Dahlgaard. “Failure of Continuous Improvement initiatives in manufacturing environments: a systematic review of the evidence.” Total Quality Management & Business Excellence 28.3-4 (2017): 219-237.

42 Vesna Sesar* and Anica Hunjet DOES CONTINUOUS IMPROVEMENT REALLY MATTER FOR THE BUSINESS: A REVIEW (25 - 44)

Muras, A., & Hovell, J. (2014). Continuous improvement through collaboration, social learning, and knowledge management. Journal of Corporate Accounting & Finance, 25(3), 51-59. Neacsu, Nicoleta Andreea, “Implementation of ISO 22000-a tool to increase business efficiency and customer satisfaction. A Case Study: SC Prodlacta Brasov.” Bulletin of the Transilvania University of Brasov. Economic Sciences. Series V, no. 8.2 (2015): 105. Oropesa Vento, M., Garcia Alcaraz, J. L., Maldonado Macias, A. A., & Martinez Loya, V. (2016). %e impact of managerial commitment and Kaizen benefits on companies. Journal of Manufacturing Technology Management, 27(5), 692-712. Oyadomari, J. C. T., Afonso, P. S. L. P., Dultra-de-Lima, R. G., Mendonça Neto, O. R. R., & Righetti, M. C. G. (2018). Flexible budgeting influence on organizational inertia and flexibility. International Journal of Productivity and Performance Management, 67(9), 1640-1656. Phoewhawm, R. Aspects of Learning Performance as a Cross-Functional Team in a Kaizen-Led Working Environment. Popescu, D. (2015). Kaizen-driven approach while managing industrial projects. A Scandinavian company succeeds in Eastern Europe. Management and Production Engineering Review, 6(1), 26-35. R. Kattman, B. (2014). In today’s global environment organizational culture dominates national culture!. Benchmarking: An International Journal, 21(4), 651-664. Saleem, M., Khan, N., Hameed, S., & Abbas, M. (2012). An analysis of relationship between total quality management and kaizen. Life Science Journal, 9(3), 31-40.C Sesar, V., Hunjet, A. (2018). Continuous improvement as a company strategy. 4th International Scientific Conference for Doctoral Students and Young Researchers, 4 May 2018, University of Applied Sciences Burgenland, Eisenstadt, Austria. Sfreddo, L. S., Vieira, G. B. B., Vidor, G., & Santos, C. H. S. (2018). ISO 9001 based quality management systems and organisational performance: a systematic literature review. Total Quality Management & Business Excellence, 1-21. Shang, Huaxing. “A Literature Review on Kaizen: What Have We Learned over the Past 30 Years?.” Yokohama International Social Science Research, no. 22.4 (2018): 127-139. Singh, J., & Singh, H. (2018). Enigma of KAIZEN approach in manufacturing industry of Northern India-a case study. International Journal of Quality & Reliability Management, 35(1), 187-207. Sıtkı İlkay, M., & Aslan, E. (2012). %e effect of the ISO 9001 quality management system on the performance of SMEs. International Journal of Quality & Reliability Management, 29(7), 753-778. Sokovic, M., D. Pavletic, and K. Kern Pipan. “Quality improvement methodologies-PDCA cycle, RADAR matrix, DMAIC and DFSS.” Journal of achievements in materials and manufacturing engineering 43.1 (2010): 476-483. Suárez-Barraza, M. F., Ramis-Pujol, J., & Estrada-Robles, M. (2012). Applying Gemba-Kaizen in a multinational food company: a process innovation framework. International Journal of Quality and Service Sciences, 4(1), 27-50. Todorovic, M., & Čupić, M. (2017). How Does 5s Implementation Affect Company Performance? A Case Study Applied to a Subsidiary of a Rubber Goods Manufacturer from Serbia. van Assen, M. F. (2018). Exploring the impact of higher management’s leadership styles on lean management. Total Quality Management & Business Excellence, 29(11-12), 1312-1341.

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Verdinejad, F., Mokhtari Mughari, A., & Ghasemi, M. (2010). Organizational suggestion system in the era of holding by developing an innovative model: the case of bonyade ta avon holding in Iran (an applied model). Iranian Journal of Management Studies, 3(3), 5-22. Vilarinho, S., Lopes, I., & Sousa, S. (2018). Developing dashboards for SMEs to improve performance of productive equipment and processes. Journal of Industrial Information Integration. Wiengarten, F., Fynes, B., Cheng, E. T., & Chavez, R. (2013). Taking an innovative approach to quality practices: exploring the importance of a company’s innovativeness on the success of TQM practices. International Journal of Production Research, 51(10), 3055-3074. Zangwill, Willard I., and Paul B. Kantor. “Toward a theory of continuous improvement and the learning curve.” Management Science 44.7 (1998): 910-920.

44 45

Brigitta Kovacs (45 - 56)

ARTICLE INFO Received: 21.9.2018. Accepted: 14.1.2019. JEL classiﬁcation: M11, M49, O11, O20

Keywords: Controlling; Industry 4.0; Digitalization; Role of controller

HOW DIGITALIZATION CHANGES CONTROLLING

Brigitta Kovacs [email protected]

45 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

Industry 4.0 is a very important topic, as it transform not only production, but the whole business model of the companies. Information and communication technologies will merge with production. Products, machines and people will communicate with each other. $is leads to much tighter vertical and horizontal integration in production.

Controlling has to be adopt to this new challenge. On the one hand, controlling methods have to be rethink and digitalized. New approaches are necessary, for example in product controlling, investment analyses and planning.

On the other hand, also the role of controller will be further developed from business partner. In the near future, the task of controlling will be to operate the strategic early warning system of the company. Controlling becomes part of value creation network. $is require new skills from the controllers like much deeper IT skills and better understanding of digitalized business and Industry 4.0 production model. Also new roles, like Data Scientist will turn up.

46 Brigitta Kovacs (45 - 56)

I. INTRODUCTION

Economy face with such a new challenge like digitalization. %e technological transformation in course of Industry 4.0 has a very high speed. Also changes of market environment getting more and more faster and volatile. If companies want to exploit the competitive edge, they have to develop in a new and more innovative way and elaborate a new digital business model. (Bauer 2017) %e digitalization changes not only the primary production processes of a company but also the support processes like administration and ﬁnance and so transform controlling. In my secondary research I collected and analysed scientiﬁc views and publications about digitalization. I collected which controlling methods have to be changed or newly developed and how it transform the role of controlling.

II. WHAT IS INDUSTRY (.)?

Digitalization and internet of things1 completely changed our way of leaving and working. Also production is getting digitalized. Industry 4.0 is a conjunction of information and communication technologies with production systems which enables a more efficient, more flexible and more individually customized production. (Meissner, Ilsen, Aurich, 2017) Let´s take a look, how production has changed during industrial revolutions: %e first industrial revolution took place at the end of the 18th century. It started with the development of steam engine, which allowed the heat energy contained in steam to be converted into mechanical work. %e steam engine also revo- lutionized the transportation thanks to steam ships and steam locomotives. %e second industrial revolution at the beginning of the 20th century was led by development of electrical energy. Henry Ford developed his assembly line and opened the door for mass production. %e third industrial revolution started at the beginning of 1970s. %e main drivers were growing use of electronics and information and communication technologies which enabled an increasing automation of production processes. %is lead to further rationalization and very diversified serial production. (Gänßlen, Losbichler, Horváth , Michel, 2014) Industry 4.0 means digitalization and networking of products, value chain systems and business models. Its tree drivers are:

1 %e interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.

47 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

1. Increasing productivity by better control of vertical and horizontal value chain. 2. Increasing revenue and competitiveness by digitalization and networking of own products and services. 3. Digitalization of business models, what ﬁts much more to the needs of customers and serves additional beneﬁts. It is close connected with cooperation of value chain systems and analyses of Data, what serves better understanding and satisfaction of customer needs. Figure 1.: %e fourth industrial revolution

Source: Kagermann, Wahlster, Helbig, 2013

Industry 4.0 has a very big importance, as it changes not only the vertical and horizontal value chain system but also revolutionize the whole product- and service portfolio of the company. It shall be on the Chief Executive Officer (CEO) Agenda, as it transform the whole company and strongly influence it´s long term future. %e implementation of Industry 4.0 indicates also huge investments. Basis study of PWC (Koch, Kuge, Geissbauer, Schrauf, 2014) industrial companies in Germany will invest 3,3% of their average yearly revenue, what makes out 40 billion Euro until 2020. With such investments more than 80% of companies will digitalize their value chain system. Industry 4.0 is heavily driven by technology. Within the auspices of a joint study, the Federal Association for Information Technology, Telecommunications and New Media (BITKOM) and the Fraunhofer Institute for Industrial Engineer- ing (IAO) identified five technology fields which are shaping Industry 4.0 (Bauer, Schlund, Marrenbach, Ganschar, 2014):

48 Brigitta Kovacs (45 - 56)

• Embedded Systems and Cyber-Physical Systems (CPS): %e initial basis for intelligent networking is embedded systems which is the linking of autonomous, powerful minicomputers with diﬀerent objects (e.g. machines or devices). Increasingly, these embedded systems are being networked with each other and with the internet, resulting in a merging of the physical world with the virtual one into cyber-physical systems. • Smart factory: Within a smart factory, machines and production employees are networked with one another. %e machines and people of a smart factory can communicate with one another and exchange data. • Robust Networks: intelligent networking in a smart factory is only than possible, when big volume of data can be rapidly and secure transferred inside and outside of the production environment. • Cloud computing: makes possible storage and sharing of much larger data as conventional servers. %is opens new possibilities to analyze and optimize the factory. • IT-Security: refers to securing data of employees and business partners and security of industrial network. Sensitive data shall be protected. %ere is no exact way how digitalization shall be implemented at a company, but the whole value chain system shall be changed completely. %is is a transformation process of several years. Every company has to ﬁnd its own strategy of Industry 4.0 based on current level of customer satisfaction, market competition and capability of investments. Basis the applied strategy companies can be: • Formative: speedy and risk taking companies, who take the early chance of digitalization, uses untried solutions and co-working on the standards of Industry 4.0 combined with higher risks. • Fast adaptive: such companies learn from the experiences of formatives. %ey adopt and implement successful concepts to their needs. • Dilatory: waiting with digitalization until tested concepts and standards are available, taking into consideration that they can be overlapped in global competition by faster ones.

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III. HOW DIGITALIZATION CHANGES CONTROLLING?

Digitalization is already started in production area. In course of industry 4.0 producing companies already use the most modern information- and communication technologies to connect machines, processes and products. %anks of such technologies, they can produce more flexible, individualized to customer’s needs and cost effective. Digitalization can serve also automated processes in financial area. %is gives the chance to Chief Financial Officers (CFO´s) to improve productivity, quality and compliance in financial area. So Industry 4.0 creates new challenges for both controllers and their instruments and methods. A distinguish shall be taken between controlling in digitalization and digital controlling. Controlling in digitalization focuses on the new challenges of controlling and how these change the role of controllers in the organization. Digitaliza- tion of controlling mean new technological development, how controlling can be automatized and analyzing and planning methods can be more effective. In my research I am dealing with controlling in digitalization and focus on the controlling areas, what have to be change and on the changing role of controllers. Figure 2.: differentiation between digital controlling and controlling in digitalization.

Source: Sieler, Waßmer, 2017 Digitalization changes also such core tasks of controllers like product controlling, planning, investment controlling and reporting and indicates new tasks like evaluation of digital business models. Let´s take some examples, what tasks of controllers change because of digitalization:

50 Brigitta Kovacs (45 - 56)

Product controlling: Industry 4.0 lead to modular networking of production processes. A module provides largely autonomous output and can therefore be used flexibly. Because of such change of production processes also the method of production controlling have to be changed. With Industry 4.0, operative production controlling and thus ongoing cost control become even more relevant and complex. %e Industry 4.0 controller has clear requirements to define the IT systems and therefore must have basic knowledge in the fields of business information systems and process management. Table 1.: Development of product controlling approach in Industry 4.0

Production Classical production Extended production controlling of controlling controlling Industry 4.0 Costs and production Added value for the Orientation Costs and units process customer Decentralized in Decentralized, ad hoc Organizational Central approach deﬁned processes for module Cost center and cost Via processes and Via customer oriented Attribution of costs units interfaces production process Partly more Prior more Decision procedure One dimensional dimensional dimensional

Source: Reischauer, Schober 2015

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Evaluation of digital business models: Industry 4.0 gives new economical potentials to the companies. Such potentials are different company to company. %e task of the controllers to identify and evaluate the economic benefits of that and help the management to take right decisions how implement digitalization. Controllers shall analyze practicability and future profits of the potentials. (Rusch, Treusch, David, Seiter, 2016)

Planning: Implementation of Big Data2 solutions dramatically increases the ability to take decisions on the very latest up to the moment information. Due to digitalization and better and faster processing of data, the decision making will be based on real-time data and not on analyses of past ﬁgures and trends. %e technical developments and robotic so'ware enables that more time is spent in controlling to qualitative and predictive analyses and reduce the invested time in quantitative and retrospective once.

How digitalization changes financial department and role of controllers: Digitalization will transform also the financial department. Jobs will require more and more flexibility, IT competency and analytical skills. In the future new processes, roles and skills are required. Such a new role is the “Data Scientist”, who extract necessary information from the huge data volume. Also such experts are needed, how can transform the business needs into data models and can develop algorithms of evaluation. Due to automation of processes, controllers will have free resources and can much more concentrate on their role as business partner of the management. %ey have to work in a very strong cooperation with Data Scientists, understand the method of data warehouses and business models and be able to develop implementation-oriented measures and optimize performance. (Grönke, 2017) %e controlling maturity model shows the development of controlling in the term of digitalization. %e model identify five evaluation stages: 1. Data Management: controlling focuses on operative tasks and legal requirements. %e analyses are quantitative and describes what happened in the past. 2. Data Analysis: controllers are responsible for data management and supports other departments with informations. Besides quantitative analyses already prepare qualitative ones of available information. 3. Business Partner: the role of controller turns into business partner of manage-

2 Big data represents the information assets characterized by such a high volume, velocity and variety to require speciﬁc technology and analytical methods for its transformation into value.

52 Brigitta Kovacs (45 - 56)

ment. %e controller is supporter and advisor of management and involved in decision-making process. Process oriented and more forward looking. 4. Strategic early warning system: focuses on detection of threats and opportunities at an early stage. Identify measures for correction or for realization of opportunities. 5. Value creation network: the value contribution of controlling is very high. Ac- tivities are standardized and automated. Controlling focuses on forward-looking steering of the company. %is orientation of controlling allows rapid actions to fast market environment. %e role of controlling already become a business partner from data administration and analysis. %is role will in the next years further develop. %e task of controlling will be to operate a strategic early warning system and as part of the value creation network. (Sieler, Waßmer, 2017) Figure 3.: Development of roles in controlling

Source: Sieler, Waßmer (2017)

IV. CONCLUSION

Development of production steps into the fourth industrial revolution. %e production will be digitalized, so information and communication technologies will merge with production. Products, machines and human resources will be networked and communicate with each other. Also the way, how companies interact with their suppliers and customers will be transformed into a higher level of hori-

53 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

zontal integration. Such development requires a digital business model from companies. %e aim of my publication to highlight, what controlling methods shall be changed because of digitalization and what new skills controllers need. Controlling methods have to be adopt in order to ﬁt to Industry 4.0. Focus of product controlling shall be added value to customer and has to be decentralized. Due to Big Data and faster proceeding of information forecasting will be qualitative and retrospective. Decision taking will be based on more recent informations. Industry 4.0 indicates huge investment volume. It will be the task of controllers to evaluate such investment plans, appraise future potentials and identify relevant Supply-Chain risks. Scientiﬁc researchers can help to companies in the development of new controlling methods and reshaping the old ones. Controllers require new skills in Industry 4.0. %ey need deeper IT knowledge regarding Big Data and Business Intelligent Systems and better understanding of new business and production models. Apart from controllers a new role will be developed for Data Scientists. %e role of controllers will be further developed. %eir task will be to operate the strategic early warning system of the company and controlling will be part of value creation network.

54 Brigitta Kovacs (45 - 56)

REFERENCES

Bauer, J., Schlund, S., Marrenbach, D.,Ganschar, O., (2014) Industrie 4.0 - Volkswirtscha'liches Potenzial für Deutschland, Berlin Gänßlen S., Losbichler H., Horváth P., Michel U., Industrie 4.0, in International Controller Association Dream Factory 2014 September, www.controllerverein.com/iw, Downloaded: 02.03.2018 Grönke, K. (2017), Au4ruch eine neue Ära, https://www.horvath-partners.com/hu/ magazin/2017-02/cfo-organisation-40/, Downloaded: 07.02.2018 Kagermann, H., Wahlster, W., Helbig, J., (2013) Recommendations for implementing the strategic initiative „Industrie 4.0”, Main, Frankfurt Koch V., Kuge S., Geissbauer R., Schrauf S. (2014), Industrie 4.0 - die vierte industrielle Revolution, https://www.strategyand.pwc.com/media/ﬁle/Industrie-4-0.pdf, Downloaded: 07.02.2018 Meissner H., Ilsen R., Aurich J. (2017), Analysis of control architectures in the context of Industry 4.0, 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME ‘16, https://www.sciencedirect.com/science/article/pii/S2212827117300641, Downloaded: 22.02.2018 Reischauer G., Schober L. (2015), Controlling von Industrie 4.0-Prozessen, https://www. researchgate.net/publication/305455775_Controlling_von_Industrie_40-Prozessen?enrichId=rgreq- d7ee4de227751e7855a05b03994c0d79-XXX&enrichSource=Y292ZXJQYWdlOzMwNTQ1NTc 3NTtBUzo0NzMzNTA1NzAwMjQ5NjBAMTQ4OTg2Njk3ODA1OQ%3D%3D&el=1_x_2&_ esc=publicationCoverPdf, Downloaded: 21.02.2018 Rusch M., Treusch O., David U., Seiter M (2016) Industrie 4.0 - Controllers Aufgaben, Ansatz zur Umstellung von Industrie 4.0 in der betrieblichen Praxis, in Controllermagazin 2016 Mai/Juni Sieler, S., Waßmer, K. (2017), Digitalization as the driving force of the controlling transformation, https://www.camelot-mc.com/us/study/digitalization-as-the-driving-force-of-the-controlling- transformation/, Downloaded: 01.02.2018

Wolfram Irsa INNOVATIONS FOR MANAGING OVERHEAD COSTS (57 - 74)

ARTICLE INFO Received: 20.9.2018. Accepted: 30.12.2018. JEL Classiﬁcation: D23, O14, O33

Keywords: cost management; Grounded %eory; innovation; value creation; qualitative research; VUCA (volatile; uncertain; complex; ambiguous)

INNOVATIONS FOR MANAGING OVERHEAD COSTS

Wolfram Irsa 1719001125@!-burgenland.at

57 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

$e digitalization of business processes becomes a matter of fact as the society evolves towards a conglomerate of digital natives. $e arising problem with this development is the exponential yearly increase of data. $is results in an overflow of information which hinders business leader to make sound and well-thought decisions under time pressure. $e research at hand follows recent innovative developments to get a grip on the data, which - hopefully - becomes information and finally a decision model. $e creation of values for customers - but also in a broader sense to the society - requests a sustainable business model, which is determined by transparent and pre- dictable costs. First insights indicate that volatile, uncertain, complex and ambiguous (VUCA) environments solicit dynamic and flexible costing systems. $is enables the decision makers to keep the long-term impact in mind on the one side, and to leverage attractive spot business on the other side. $ree major findings have been discovered. (1) Sophisticated digitalized processes create an abundance of data which needs transformation to reasonable information and finally the conversion to a scalable model, (2) advanced overhead cost management models complement existing accounting systems, especially for well-established businesses, and (3) the digitalization of business processes helps traditional businesses to expand their visibility around the world, which attracts further commerce. Overall, the results indicate that the management of overhead cost is crucial for sustaining high technology businesses in the region of Kapfenberg. $e nouveau value of the research is in the original collection of qualitative empirical data, the processing of the information, and finally the display of the findings by using a qualitative research approach as recommended by the Grounded $eory methodology. $e results are feasible to explore further the subject matter and to benchmark it to other regions in the world.

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". INTRODUCTION

%e aim of this research is a scientific inquiry about the impact of innovations for managing overhead costs in the field of high-technology companies, in particular in the area of Kapfenberg. Kapfenberg is the third largest town in Styria, Austria with 23.000 inhabitants on 82 km², mainly fields, mountains and forests but also an industrial and trading area of approximately 1.8 km². It has a long tradition in industrial entrepreneurship reaching from the Böhler brothers in the 19 century to world-market leaders nowadays (e.g. Pankl Racing, Boehler Welding). Tables 1.: State of economy in Kapfenberg

Key attribute (on a yearly basis) Quantity Value creation [Euro] 1.500.000.000 Purchase power [Euro] 600.000.000 Industrial area [m²] 1.660.000 Trading area [m²] 100.000 Employees [#] 14.000 Companies [#] 1.250 World-market leader [#] 12 Technical study programs [#] 4 Applied university [#] 1

Source: WKO (2018)

%e table above holds the key attributes of the economy in Kapfenberg. %e city plays an essential role for the country. %e area of Kapfenberg accounts for a value creation of €1.5 billion per year. An industry area of 1.7 km² provides space for 1.250 companies, which includes a high-technology park of 230.000m². World- famous customers like Airbus, Boeing, Ferrari, Rolls Royce, or Siemens trust the products and services from the region. %e range of products reaches from special steel to carbide cutting tools, further to components for aerospace, automotive, racing and medical engineering. Almost all commercial aircra's are equipped with high-strength components from Kapfenberg. %e education system plays a pivotal role for the success of the region. Primary, secondary as well as middle schools - already in the ﬁeld of economics and engineering - provide suﬃcient supply of talents for the economy. An university of applied sciences with four technical study programs provides teaching and research capabilities for the region and country. In total, 4000 young citizens are in the educational system. Additional

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3000 places for on-the-job trainings concludes the oﬀer of the educational program (WKO, 2018). %e high-technology economy stages o'en a high entry-barriers with propri- etary technology and complex costing systems. On the other side, disruptors have launched new business ideas - o'en referred as startups - within the ﬁeld of high- technology by applying new costing tools. Notably, the research looks for an explanation how innovations in overhead cost management acts as a game changer by using sophisticated approaches.

#. COST AND INNOVATION

%e definition of overhead costs is “the total cost of indirect materials, indirect labor and indirect expenses” (CIMA, 2011). It is the cost of material, labor, and expenses that cannot be assigned easily to a specific saleable cost object. %erefore, it needs models and tools to assign reasonably and as precise as possible the overhead costs to the cost object. In the past o'en this took place based on direct labor. Notwithstanding that such a model has been always questionable, it becomes obsolete in the wake of new technologies with lots of automation that hardly needs any direct labor. %e question arises what type of innovations in cost management are needed to address this change of business practices? %e BusinessDictionary (2018) states as the definition of digitalization as “the integration of digital technologies into everyday life by the digitization of everything that can be digitized.” %e digitalization impacts everybody and all businesses on a daily basis. %e so called 4th industrial revolution integrates autonomously machines with business processes. What may look for an outsider as a mysterious miracle requires indeed proper preparation and sound standardization. Certainly such complex systems are expensive. An enormous amount of engineering power and maintenance effort is needed to sustain the digitalized processes. %e question emerges how to make use of the digitalization for creating transparency into the associated overhead costs? As an example may serve the semiconductor industry:

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Figure 1.: Overhead allocation in the semiconductor industry (Inﬁneon Dresden, 2017)

%e figure above illustrates the difficulty to allocate huge overhead costs (i.e. 85% of the costs of goods sold are overhead) to many inexpensive cost objects (i.e. one RFID chip has an average selling price of €0.2). Any miss-calculation in the cost model has a severe impact on the financial health of the cooperation. %erefore, innovations in overhead costs management are urgently needed in order to understand the costs of the enterprise right. %is is not only true for cutting-edge industries like the semiconductor industry but also for the businesses in Kapfenberg.

$. LITERATURE REVIEW AND METHODOLOGY

%is section exchanges views on roots and utilization of Grounded %eory (Glaser and Strauss, 1967; Martin and Turner, 1986; Turner, 1983; Glaser, 1978; Strauss, 1987; Strauss and Corbin, 1990, 1998; Dey, 1999; Charmaz, 2003, 2006, 2008). Grounded %eory materialized in the ground-breaking work of Glaser and Strauss (1967). It is a well-tested methodology with extensive usage across many different fields of social science disciplines including business administration themes. %e nature of a grounded theory encompasses the discovery, development, and tentative verification of systematically collected data relevant to particular phenomena (Strauss and Corbin, 1990). It is of great value for conducting an empirical research. For the novel researchers in the field of qualitative research it is an attractive choice for administering the qualitative research project as it provides sound procedures and plenty of recommendations. %e methodology helps to discover the conceptual properties and categories from a set of qualitative data by using the specific procedures and guidelines.

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%e goal of Grounded %eory is the seeking of a mid-level theory which is closely tied with the evidence. As a result, the theory is supposed to be consistent with the empirical data (Orlikowski 1993; Eisenhardt 1989). %e data collection, the rationale of the coding, the integration of categories, the abstraction from the original data and finally the construction of the theory is led by the theory as it emerges. Hughes and Wood-Harper (1999) indicate that the main application areas of the Grounded %eory methodology are most notably in Glaser and Strauss’ own field of research, which is social science in health care systems. Next to them, performed by many others, o'en in the field of medical or nursing related areas (e.g. experiences with chronic illness) (Charmaz, 1980), homecoming (Hall, 1992), and the management of a hazardous pregnancy (Corbin, 1992). Addition- ally, a lot of work has been done concerning the guidance on the application of the Grounded %eory methodology. Most notable amongst them include Turner (1983); Martin and Turner (1986); Strauss (1987); Strauss and Corbin (1990); Dey (1999); Charmaz (2003, 2006, 2008); Jones and Alony (2011). %e result, the detected theory grounded by the evidence to the specific phenomenon, iterates by permanently challenging the concept of the theory with the data and vice versa. %e comparative nature of this approach happens constantly by scrutinizing the evidence. %is develops the conceptual structure next to the overall scope of emerging a mid-level theory to explain the phenomena. %e usage of the Grounded %eory methodology has become popular in other disciplines next to social sciences; notably, research in information systems (Torasker, 1991; Pidgeon et al, 1991; Oliphant and Blockley, 1991; Pries-Heje, 1992; Orlikowski, 1993; Pettigrew, 1990; Calloway and Ariav, 199l; Baskerville and Pries-Heje, 1995, 1998) and business management (Goulding, 2002; O’Reilly et al, 2012). %e most remarkable use of Grounded %eory in business management research is that by Goulding (2002) in which she presents an in-depth case study in the fields of organizational and business studies, marketing and management. Further, Adolph, Kruchten, & Hall (2012) investigated the appropriate social co- hesion and structures that impact the so'ware development in an organization. Additionally, Wolfwinkel, Furtmueller, E., and Wilderom (2013) published how the Grounded %eory approach advanced by Strauss and Corbin (1990, 1998) is useful as a method for rigorously reviewing literature. %ey concluded that “applying grounded theory aims to point to well-rooted and fruitful new links between variables”. Utulu, Sewchurran, and Dwolatzky (2013) shared that systematic literature reviews used Grounded %eory for explaining the process improvement of so'ware (i.e. knowledge economy, corporate ideology, organizational design, quality management, and performance management as intertwined variables).

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%e Grounded %eory methodology suits well with an interpretivist rather than post-positivist research approach. %e grounded theory studies in the interpretivist tradition have become increasingly attractive in the field of research literature for social science. %is is mainly because the methodology fits perfectly in developing a process-oriented description, is context-based and provides explanations of a phenomenon (Myers, 1997; Urquhart, 2001). Hughes and Howcro' (2000) emphasize the matter of fact that the individual researcher as well as a research team plays an essential role in an interpretive study. %ey point out that the rigid application of the Grounded %eory procedures provides guidance to the researcher in order to deal with the anxiety when confronted with data collection and analysis in interpretive studies. Additionally, the methodology connects the novice researchers with the community of experienced researchers. It provides a useful template, which serves as a stabilizing force in the nerve-racking and ambiguous nature of performing qualitative research (Hughes and Jones, 2003). It is considered as a major advantage of the Grounded %eory methodology that the general style of doing the analysis is free from any particular disciplinary perspectives (Strauss 1987). Subsequently, it suits well for business management research which can be characterized as a holistic discipline reaching from strategy, marketing, research and development, engineering, operations, logistics, distribution, accounting, controlling, legal, human resources to customer services. %e major attribute of the Grounded %eory methodology, that distinguishes it from other qualitative research methods, is its focus on theory development (Strauss and Corbin, 1998). According to the founders of Grounded %eory, a theory is grounded if it emerges from the observed data and produces explanations of events and dependencies which come from real-life phenomena. %e researcher tries to understand the situation, the processes and the involved people. Further, despite other traditional qualitative approaches that gather first the data and start then the analysis back home away from the research site, the Grounded %eory methodology works differently by already analyzing while still in the field. %e interaction of the emerging theoretical categories with the fieldwork of data collection takes place simultaneously. %e real-time analysis of data happens concurrent to the hands-on observations of the researcher with the research participants. %is enables the researcher from the beginning to compose their view of the observed view of the world, respectively the specific phenomenon. %e application of Grounded %eory is built on the assumption that it is fundamental for a profound understanding of phenomena that the emerging of a theory happens at various levels (Glaser and Strauss 1967; Glaser 1978). It requires

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that the researcher manifests theoretical sensitivity (Glaser and Strauss 1967; Gla- ser 1978) by being well educated in technical literature as well as from professional and personal experiences in collection/analysis of the data (Strauss and Corbin 1990). %is encourages researchers to allow their thinking process outside the box of the technical literature. It avoids too well established ways of reflecting the data and it triggers new approaches. %e give-and-take between the emerging theory and the technical literature avails when new aspects become visible in the study. %is is either achieved by integrating supplementary as well as conflicting analysis into the theory or criticizing them as it emerges. Technically these are included as categories or conditions (Strauss 1987). %e methodology of Grounded %eory suits particularly well for a case study aimed at the exploration of the influencing factors concerning the innovation of the management of overhead costs. It is useful for understanding the contextual elements (Orlikowski 1993) that constituted the main focus of a case study. One very practical issue with the grounded theory methodology is the sub- stantial time effort it takes to conduct the study. It is highly labor intensive and requires considerable cognitive resources of disciplined effort by the researcher. However, the author is convinced that the Grounded %eory methodology is a very suitable approach for scientific research of business management issues. %is is valid especially when the research works needs an analyses of large quantities of semi-structured or even unstructured qualitative data that describes complex systems like the innovations of overhead costs accounting. %is section has presented and discussed the background of Grounded %eory as a hands-on tool for collecting, analyzing, and interpreting qualitative data in order to form an explanatory model of complex systems. %e limitations of Grounded %eory as a method for business research are numerous. %e most widely stated criticism of the Grounded %eory methodology refers to its epistemological origin. %is means that the logical discourse deals with the theory of knowledge to address the questions “What makes justified beliefs justified?”, and “How do we know what we know?” (Wenning, 2009). It has been falsely argued that Grounded %eory advocates a positivist epistemology. %is avoids questions of reflexivity. Actually, the opposite is true. Grounded %e- ory heavily encourages reflexivity. For researchers in business research, another shortcoming of Grounded %eory might be its - once - preoccupation with uncovering mainly social processes. %is might limit its applicability to more phenom- enological research questions (Dey, 1999).

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%. APPROACH

%e qualitative study has been performed by using the Computer Assisted/ Aided Qualitative Data Analysis So'ware (CAQDAS) tool ATLAS.ti. CAQDAS provides great functionalities that support the qualitative research. Figure 2.: %e Hermeneutic Unit in a CAQDAS system (Muhr; 2001)

Hermeneutic Unit

Code familyuses uses Super Codes uses Families causes Networks

isa causes isa Codes

indicated-by indicated-by indicated-by

Quotations supports contained-in contained-in

Primary documents

Figure 2 shows the structure and the elements on a so called Hermeneutic Unit in a CAQDAS system. On the bottom, several Primary documents (e.g. pictures, original text, videos, audio recording, observations) are the basis for the qualitative research. %ey are augmented with Quotations (i.e. citations, comments/notes of the researcher) on the next higher level. %ere, interactions between the quotations might be already discovered. %ey can be captured in memos. %e level of Codes uses the concept of Grounded %eory with the three step approach: open, axial and selective coding of all detected quotations. Super Codes Families Networks condense further the ﬁndings to build a model with interactions, dependencies, and causes (in the picture above ISA stands for a ‘is a’ relation). %e entire construction with all elements is called a Hermeneutic Unit, which follows the idea of hermeneutics, a methodology of interpretation, o'en in the context of biblical texts, wisdom literature, and philosophical texts. %e inductive developed model in the CAQDAS system is the source of the explanation for the mid-level theory, which ﬁndings will be described later. CAQDAS is very helpful for transcribing the text, describing the data (e.g. videos, pictures, situations), assigning the codes to the text, managing the comments including memos, and building the interaction of the information. Con-

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sequently, this leads to a model described as a mid-level theory for the specific phenomenon. ATLAS.ti is headquartered in Berlin, Germany and is the leading so'ware package for scientific qualitative research. Given the introductory information about the businesses in Kapfenberg, the needed innovations for overhead cost management, and the nature of Grounded %eory this leads to the following research question: • Which challenges concerning the management of overhead costs have emerged due to the ramifications caused by Industry 4.0? As a subsequent question the research addresses further: • How will the future affect innovations in overhead management because of the digitalization of business processes? In total 16 semi-structured interviews took place in the second quarter of 2018. %e target group had been factory managers in the region of Kapfenberg. %e guideline for the interviews held the following questions: • How do you feel about the current challenges concerning overhead cost? • What has Industry 4.0 to do with these challenges? • Which innovations do you foresee in the future with regards to cost transparency? • What plans to you have to tackle the digitalization of business processes? • Is there anything else you wish to add in this context? %e author applied the same guideline for all interviews. It took 40 and 60 minutes for each interview. %e setup of the interview allowed room for complementary information if the interviewee felt an urge to share it. %e author transcribed the interviews in ATLAS.ti. All interviews together form a heuristic unit in the so'ware tool. A'erwards the author assigned codes (open coding) to significant text passage that describe the subject matter. In the course of coding the interviews the author saw already re-occurring patterns and used these discoveries to fine tune the codes (axial coding). Finally, the entire heuristic unit was reviewed again, code families were formed und missing links between the developed codes added (selective coding). %e summary of codes (the code book) plus the network view, which displays the different types of objects and relations, is the cornerstone for describing the findings, which follow in the next section.

&. FINDINGS

%e research unfolds three major ﬁndings. %ey follow the logical order of (1) setting the context right, (2) co-existence of multiple models, and (3) ﬁnally expanding the digital capabilities to new horizons.

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Firstly, sophisticated digitalized processes create an abundance of data which needs transformation to information and eventually conversion to a scalable model. %ere is consensus throughout all interviewees that the main challenge comprises the huge amount of data. Two interviewees - both from companies with more than 500 employees - pointed out, that the amount of the gathered data is so huge that they need a very expensive data analytics department to make sense out of the data. %ey said the continued over the last 20 years to collect data without challenging the overhead cost model. %e model is now so complex, inflexible, and slow that the managers in charge ignore the calculations and act on gut feeling. %ey are aware that such an approach is risky. In their opinion it needs a hard reset and to set up a new cost model from scratch by considering all lessons learned from the previous years, especially since the journey of digitalization has begun. One of the two companies is planning such an initiative in 2019, the other is still reluctant and hopes for cloud-computing solutions. Contrarily, one interview partner - representing a small company with 40 employees - said, that they keep the cost model as simple as possible. From the very beginning, which is five years ago, they have collected only data from their business operations that is relevant to any outside expenditure. %ey use this information to make transparent in real-time the added value as the business operation progresses. %is is of great use for the decision makers. %e applied method is called Value Stream Analyses and delivers so far very viable results. %ey asked for benchmark information for how long such a pragmatic approach can be performed. %ey believe if the company continues to grow that they will face limits and need to switch to a more complex model. Secondly, advanced overhead cost management models complement existing accounting systems, especially for well-established businesses. Interestingly, all 16 interviewed corporations shared that they monitor the academic research in this matter closely. %e models discovered are: absorption costing, activity-based costing, full cost accounting, marginal costing, and standard costing. Traditionally, the marginal costing - more precisely the marginal planned cost accounting (German: Grenzplankostenrechung) - plays the most important role. Interestingly, eight out of the 16 interview partners mentioned that the pay close attention to activity- based costing (ABC). ABC is a method to allocate overhead based on cost drivers. %e cost drivers represent the significant metrics of a business process to the cost object. %is creates useful transparency to the causality what triggers overhead costs and how the cost object - in a broader sense the product sold to the customer - is charged with these costs. ABC has been made public by %omas H. Johnson and Robert S. Kaplan (1987) and enjoyed for several years great popularity. %ere is a strong push to use the abundance of available data for cost accounting pur-

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poses. Eight of the interviewees said, that they look again - a'er more than 20 years - into the applicability of ABC. %e difference nowadays is that we have now computer power and sufficient data available to make ABC work. One participant even said: “Activity-based costing had never a chance against marginal planned cost accounting. But now we have the data that we can intelligently turn into information which fits perfectly our ABC model.” %ey believe that further innovation is needed to bridge concept with actual process data. %irdly, the digitalization of business processes helps traditional businesses to expand their visibility around the world, which attracts further business. Eleven interviewees elaborated that their companies use digitalization as a marketing instrument. It increases their visibility and the perceptibility of the industry in general around the world. It is pointless to fight digitalization. It is a matter of fact, without any way around it. Digitalization allows to better focus on the own strengths (e.g. service, professionalism, loyalty programs). Further, it is opportune to use the benefits of digital capabilities to attract - o'en young - employees and customers. %ey are intrigued with digitalized products. %ey like to use apps via smart phones or tablets. Two companies disclosed that they have apps as virtual solution guide (VSG) for use-cases applied for their products. It is download-able in the Apple App Store and in the Google Play Store. %e VSG tracks the search behavior of the users anonymously. %is allows an algorithm to prioritize the interests of the customers and the potential leads. As word of mouth spreads, co-workers, friends and neighbors hear about the capability of the company. A customer who uses first the VSG might choose to visit the website of the company. Additionally, they like to show their co-workers the fancy functionalities. %is additional awareness would not take place if the customer would not like to play with the app. %e digitalization serves as a low-barrier entrance to attract talent and customers. Although, this has only indirectly to do with overhead costs it is a mind-altering observation that exposes the nature of innovation in the sense of useful by-products. Overall, the results indicate that the management of overhead cost is crucial for sustaining high technology businesses in the region of Kapfenberg. %e businesses in Kapfenberg have been ahead of the game by using innovations in digital costing tools due to the very dynamic environment of the region. %ey show an increase in capabilities and knowledge. All in all, the digitalization of business processes is considered as an opportunity to set apart the own strengths ahead of the competition. It does not have a negative effect on the employee’s moral.

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Figure 3.: Summary of the ﬁndings

For future research it is recommended to look into the detailed specification for ABC tools, which use the capabilities of digitalized processes. %e findings indicate a need for innovation to align Big Data (i.e. cloud computing in the context of Industry 4.0) with easy comprehendible cost models. %e research of this study shows that many transparency efforts have failed because of too complex models. On the other side it is essential to avoid information overflow for the involved employees. Ideally, only the currently needed information is provided for making the decision.

'. DISCUSSION

It seems, based on finding #1, that the age and the size of a company has a severe impact of the applied overhead cost model. Younger and smaller companies appear to have an advantage as they do not need to deal with outdated processes; they are open to solution-oriented innovations. Consequently, finding #2 implies the co-existence of several overhead costing tools. Traditional businesses need to follow high and expensive safety standards which are hardly met by start-ups. New businesses allow lower costs and innovate new approaches by focusing on outside expenditure only. Well established businesses have the opportunity to focus on their well-developed unique selling proposition (e.g. service, fringe benefits, cer- tifications, loyalty programs) that a start-up cannot offer but need to become lean in its cost management processes. Finally, finding #3 indicates that the digitalization in general helps businesses in the rather remote area of Kapfenberg to make their products visible to the world. At the end of the day, digitalization is another

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category of competition that needs to be dealt with. As the course of history has shown that competition is the source of all innovation.

*. CONCLUSION

It is fair to say that digital cost management has an impact on the region of Ka- pfenberg. Overall, the impact seems to be positive. All businesses benefit indirectly from the dynamics that the digitalization creates in the country. %is is also true for companies that - at the first glance - are less active in this field. It is interesting to see that traditional businesses think about setting up new product segments using their capabilities by leveraging the functionality of digital platforms. Volatility, uncertainty, complexity and ambiguity (VUCA) in the industry requires agile approaches. %e interviewed factory managers are all eager to use digital processes to their advantage in order to understand the true costs of a products. %e reasonable assignment of overhead costs is an essential element. Innovations are needed to do it quickly and transparent. It is a bundle of measures that attracts and maintains the customer base for continuous success. %e co-existence of digital platforms with other traditional means seems to be the key success factor. %e paper opens the door for further qualitative research in the field of cost management. It is recommended to repeat the study in a different region of Eu- rope as well as internationally. %e benchmark results might unveil an underlying theme of innovations that is not visible at this point in time.

+. ACKNOWLEDGMENTS

%e author would like to thank Professor Csaba Székely, Professor Irena Zavrl and Ms Gabriele König for their help. %eir inspiration has been the driving force to finish the paper. Further, the authors would like to thank the 16 interview partners for their time, effort and interest in this research. %eir provided data has been the source of all findings in the paper. I also thank Gudrun Irsa-Klingspiegl for proof-reading this manuscript and for her valuable advice on points of grammar. %is work was supported by the Family Irsa Foundation under grant no. 2020.

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REFERENCES

Adolph, S., Kruchten, P., & Hall W. (2012). Reconciling perspectives: a grounded theory of how people manage the process of so'ware development. %e Journal of Systems and So'ware, 85, 1269-1286. Baskerville, R., and Pries-Heje, J. (1995), Grounding the %eory in Action Research, Proceedings of the 3rd European Conference on Information Systems, G. Goukidis, B. Galliers, T. Jelassi, H. Krcmar, and F. Land, eds., Athens University of Economics and Business, Athens Greece, 837-349. Baskerville, R., and Pries-Heje, J. (1998). Information Technology Diffusion: Building Positive Barriers, European Journal of Information Systems, 7, 17-28. BusinessDictionary (2018). What is digitalization? Definition and meaning. Retrieved from http:// www.businessdictionary.com/definition/digitalization.html on July-15, 2018. Calloway, L. J. and Ariav, G. (1991). Developing and Using a Qualitative Methodology to Study Relationships among Designers and Tools, in Nissen, H.E., Klein, H.K. and Hirschheim, R. (eds.), Information Systems Research: Contemporary Approaches and Emergent Traditions, North Holland Amsterdam, pp. 175-193. Charmaz K (2006). Constructing Grounded %eory: A Practical Guide through Qualitative Analysis, London Sage Publications. Charmaz, K. (2003). Grounded theory - Objectivist and constructivist methods, in N. K. Denzin & Y. S.Lincoln (Eds.), Strategies of qualitative inquiry, London Sage Publications, pages 249-291. Charmaz, K. (2008). Grounded theory, in J. A. Smith (Ed.), Qualitative psychology: A practical guide to research methods. Los Angeles sage Publications, pages 81-110. Charmaz, K., (1980). %e construction of self-pity in the chronically ill, Studies in Symbolic Interaction, volume 3, pp. 123- 145. CIMA (2011). Chartered Institute of Management Accountants - Management Accounting, London. Corbin, C.B., (1992). %e effects of verbal feedback on intrinsic motivation and perceived competence of cricketers, Australian Journal of Science and Medicine in Sport (AJSMS), 24(4) 94 - 99. Dey, I., (1999). Grounding grounded theory: Guidelines for qualitative inquiry, San Diego Academic Press. Eisenhardt, K.M., (1989), Building theories from Case Study Research, Academy of Management Review, volume 14, number4, pp. 532-550. Glaser, E.G., (1978). Advances in the Methodology of Grounded %eory: %eoretical Sensitivity, Sociology press, Mill Valley, California. Glaser, E.G., and Strauss, A.L., (1967), %e Discovery of Grounded %eory: Strategies for Qualitative Research, Weidenfeld and Nicplson, London, England. Goulding, C. (2002). Grounded %eory: A Practical Guide for Management, Business and Market Researchers Hall, S., (1992), New Ethnicities’ - In Race, Culture and Difference, Edited by A. Rattansi and J. Donald, Sage Publications. Hughes, J., and Howcro', D., (2000). Grounded %eory: I mentioned it once but I think I got away with it, UKAIS Conference, York.

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Hughes, J., and Jones, S., (2003). Reflections on the use of Grounded %eory in Interpretive Information Systems Research, Electronic Journal of Information System Evaluation, issue 1. Hughes, J., and Wood-Harper, T., (1999). Systems development as a research act, Journal of information technology, 14, 83- 94. Infineon Dresden (2017). Company key figures. Retrieved from http://www.infineon.com Johnson, H. and Kaplan, R., (1987). Relevance lost - the rise and fall of management accounting. Boston, MA: Harvard Business School Press. Jones, M., and Alony, I., (2011). Guiding the Use of Grounded %eory in Doctoral Studies - An Example from the Australian Film Industry, International Journal of Doctoral Studies, Volume 6. Kelley, J., (2012). Organizational Research Methods, 15, pp. 247-262, DOI: 10.1177/1094428111434559 Martin, P.Y., and Turner, B.A., (1986). Grounded theory and organisational research, Journal of Applied behavioural science, vol.22 (2), pp. 141-157. Muhr, %. (2001). ATLAS.ti - %e Knowledge Workbench, Berlin. Myers, M. D. (1997). Qualitative Research in Information Systems, Management Information Systems Quarterly, vol. 21, no. 2, pp. 221-242. Oliphant, J. and Blockley, D. I. (1991). Knowledge-Based System: Advisor on the Earth Retaining Structures, Computers and Structures, vol. 40, no. 1, pp.173-183. O’Reilly, K and Paper, D. and Marx, S. (2012). “Demystifying Grounded %eory for Business Research Orlikowski, W.J., (1993). CASE tools as organisational change: Investigating incremental and radical changes in systems development, MIS Quarterly, vol. 17, pp. 309-340. Pettigrew, A., (1990). Longitudinal field research on change: theory and practice, Organisational science, 1:3, pp. 267-292. Pidgeon, N.F., Turner, B.A., and Blockley, D.I., (1991). %e use of grounded theory for conceptual analysis in knowledge elicitation, International journal of Man-machine studies, vol.35 (2), pp. 151- 173. Pries-Heje, J., (1992). %ree barriers for continuing use of computer-based tools in information systems development: a grounded theory approach, Scandinavian journal of information systems, vol. 4, pp. 119-136. Strauss, A.L, (1987). Qualitative Analysis for Social Scientists, Cambridge University Press, Cambridge. Strauss, A.L, and Corbin, J., (1990, 1998), Basics of Qualitative Research: Techniques and Procedures for developing Grounded %eory, Sage Publications Ltd, London. Torasker, K., (1991). How managerial users evaluate their decision support: a grounded theory approach, In Nissen, H.E., Klein, H., Hirschheim, R., (eds.), Information systems research: Contemporary approaches and emergent traditions, Proceedings of the IFIP WG 8.2 Working Conference, Copenhagen, 14-16 December, North-Holland, Amsterdam. Turner, B.A., (1983). %e use of grounded theory for the qualitative analysis of organisational behaviour, Journal of management studies, vol. 20, no.3, pp. 333-348.

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Utula, S., Sewchurran, K., Dwolatzky, B. (2013). Systematic and Grounded %eory Literature Reviews of So'ware Process Improvement Phenomena: Implications for IS Research. Proceedings of Informing Science & IT Education Conference (InSITE) 2013. Urquhart, C. (2001). An Encounter with Grounded %eory: Tackling the Practical and Philosophical Issues. In Trauth, E. (Ed.) Qualitative Research in Information Systems: Issues and Trends, Idea Group Publishing, London. Wenning, C. (2009). Wenning, C. J. (2009). Scientiﬁc epistemology: How scientists know what they know. Journal of Physics Teacher Education Online, 5(2), 3-15. WKO (2018). Kapfenberg: Stadtgemeinde Kapfenberg - Standortmanagement, Graz. Wolfswinkel, J., Furtmueller, E., & Wilderom, C. (2013). Using grounded theory as a method for rigorously reviewing literature. European Journal of Information Systems, 22, 45-55

Hoﬀer, Thomas MAKING AMERICA ATTRACTIVE AGAIN FOR INVESTORS - DONALD J. TRUMP’S REFORMS... (75 - 102)

ARTICLE INFO Received: 25.9.2018. Accepted: 9.3.2019. JEL Classiﬁcation: B27,F13,F14, F62

Keywords: Trump; Trade; Productivity; Import; Export

MAKING AMERICA ATTRACTIVE AGAIN FOR INVESTORS ! DONALD J. TRUMP’S REFORMS AND THE POSSIBLE OUTCOME OF INCREASED PRODUCTION!OUTPUT IN TRADE

Hoﬀer, Thomas 1719001135@!-burgenland.at

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ABSTRACT

$is research project was designed to find connections between the production of goods and trade in the USA, and in order to predict the outcome of President Donald J. Trump’s reforms. It has been implied that such a connection might point to an efficient and effective application of micro- and macro-management and to related policies which contribute significantly to the local attractiveness of the place of production. If its local conditions are not favorable over those abroad, and if its economy is dependent on production as was observed in the USA before Donald J. Trump became President of the USA, such a country cannot grow and develop. $e key results of this study are twofold. Firstly, in a now globalized economic environment, a country’s economic development is, to an immense extent driven by the creation of innovative capabilities. Secondly, Foreign Direct Investments and related decisions about a company’s manufacturing location are mostly impacted by the attractiveness of the location and by local conditions which point out the importance of implementing the proper micro- and macro-policies.

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I. INTRODUCTION AND OBJECTIVES OF THIS STUDY

%e President of the United States of America (U.S.), Donald J. Trump and his administration who were subject to more than 80% negative reporting by the media (York, 2017) faced a weak U.S. economy, particularly considering the U.S. trade deficit in goods and services of more than 566Bn USD in 2017 (Schlesinger and Torrey, 2018). Trade, and subsequently productivity and performance in a global context, are relevant parts of academic research. Taking issues such as Brexit, Cli- mate Change, immigration- and financial-crises into account (Shaw and Huatuco, 2018), such global challenges and the addressing of them, led by U.S.-institutions, one may find a shi' of paradigm in US politics since Donald J. Trump became President of the USA in 2017, from a usage of so'- to hard power strategies (Na- kamura and Eilperin, 2016). Furthermore, it must be pointed out that ‘America First’ clearly focuses on the U.S. itself instead of pursuing a ‘policy of globalization’ (O’Brien, 2017), in which ‘jobs, wealth and factories moved to Mexico and overseas’ as Trump (2016) said. Considering such shi' of paradigm, one may draw the conclusion that the ‘Age of Globalization’ might get superseded by an ‘Age of Competition’ or an ‘Age of Trump’, if the U.S. plays a leading and subsequently very influencing role in the world (Kagan, 2016). As part of his agenda, Trump rene- gotiates trade deals and changes local conditions in the U.S. (e.g. tax reform) with the goal to attract Foreign Direct Investments (FDI) and bring back U.S. companies (and consequently jobs) to their homeland. Trump’s politics already showed results: Apple announced a $350 billion investment plan in the U.S. (Apple, 2018), or Exxon presented a $50 billion investment plan for the next five years (CNBC, 2018). LG will build the most modern production facility for washing machines in the world in the U.S. and create 600 new jobs (LG, 2018). Ford (2017) announced to create (or remain) more than 800 jobs in the U.S. However, there are also strike backs for Trump: %e most recent example is Harley Davidson: %e company will shi' production from the U.S. to Europe as a direct result of Trump’s tariffs on European products, which were answered by the EU with implementing tariffs on U.S.-products (Harley Davidson, 2018). %e main objective of this paper is the addressing and discussion of such shi' of paradigm, the production of goods in a direct context with trade (imports and exports) and investment flows. It is questioned, whether the U.S. lost attractiveness as a place for production of goods and investment in production facilities, and if Trump’s ‘Make America Great Again’-agenda is based on any factual reasons. %is is not only contemporary relevant but rather helps comprehending Trump’s politics and provide important implications for macro-policy makers

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and micro-managers (e.g. marketing managers of small- and medium sized enterprises). %e literature review of this paper includes a theoretical explanation for the structure and emergence of foreign trade by taking Product-Life-Cycle theory into consideration, respectively the directions of investments (FDI inwards and outwards), both from a micro (company) and macro (government) perspective. To give the theoretical explanations a further meaning, the development of trade and the production of goods in the U.S., the integration of the U.S. in World Trade, and the investments-flows to and from the U.S. need to be analyzed by contextualizing its developments with theoretical foundations. Such approach seems to be most promising, since there is only insufficient data available for the time since Trump was sworn in as 45th President of the U.S. In this paper it is not claimed that Trump’s policies are necessarily all ‘good’ for the U.S., but rather the situation, when he took office is presented and possible future developments and outcomes are subject to discussion.

II. LITERATURE REVIEW AND THEORETICAL FRAMEWORK

%e Literature review is consistent of two parts. First, the Product Life Cycle %eory is reviewed and explaining the structure and emergence of foreign trade. Second, the International Market Selection is reviewed by considering one general model, aiming to explain how a ﬁrm might decide, based on the consideration of diﬀerent indicators, abroad.

A. Product Life Cycle Theory (PLC)

In this paper the PLC theory is used as a theoretical framework explaining the structure and developments of foreign trade. Developed by Raymond Vernon (1966) it was noticed that a'er World War Second (WWII) there were only inadequate tools available for understanding shi's in international trade and investment (p.190). Scholars were focusing on more efficient tools since concepts such as comparative cost analysis and other basic tools were not from greater help in understanding problems in international trade and capital movements. However, Vernon put less emphasis upon comparative cost doctrine, but rather focused on ‘the timing of innovation, the effects of scale economies, and the roles of ignorance and uncertainty in influencing trade patterns’. Vernon’s first assumption, which seems to be worth a scientific study itself, stated that companies in advanced countries have similar access to scientific

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knowledge and the capacity to comprehend scientific principles (Vernon, 1966, p.191). Moreover, he pointed out that such assumption of equal access shall not mean that these companies are able to apply these principles in the generation of new products (p.191), but rather need to accept risks involved in testing, whether such gap can be bridged (p.192). %e second assumption stated that companies, which have easy access to knowledge are more likely aware of the possibility to in- troduce new products (p.192). In 1966, U.S.-based markets were subject to “certain unique kinds” of opportunities, which, if being aware of them, enabled companies to take advantage of those (p.192). Moreover, Vernon (1966, p.192ff.) pointed out that consumers’ needs relate to higher incomes. At this point, Vernon (1966, p.196) summarized that a producer probably chooses the U.S. as the location for production of a new product by focusing on “national locational considerations which extend well beyond simple factor-cost analysis plus transport considerations.” However, such assumptions apply for new products in the first place. Vernon (1966, p.196ff.) further pursued the question, what may happen, if a newly introduced product in the U.S. further matures, and how this may affect the location of production at some later point. It must be pointed out that his research is not limited to the location of production, but rather considering the question, how demand and trade of the respective product develops over time. Once the production of a new product starts in the U.S., production surpluses are utilizing in exports to other countries (Fig.1). Figure 1.: Production-Maturity and Trade Patterns in the USA

Source: Vernon, 1966, p.199 Author’s own representation

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Following the timeline of product maturity (Fig.1), production in the U.S. decreases at some point. While there was an export surplus till that point, the demand of such product remains high in the U.S. To close such gap between production and demand, imports from other locations than the U.S. are the most likely result when the product in question is highly standardized (Fig.1). Vernon (1966, pp.196-198) explained and connected such developments with other locations of production than the U.S. due to a growth of demand and competition (p.196), less need for flexibility (p.196), considerations in marginal production- and transport-costs (p.197). Subsequently, investments in other advanced countries than the U.S. (p.198) with new forces coming into play. A'er a decade, Vernon’s request for further research regarding his hypotheses is subject to critical discussion and analyses within this paper. He himself did not draw conclusions in his paper, but rather clearly stated, that his models are speculative in nature (p.207). Vernon reconsidered his original PLC hypothesis from 1966 in 1979 by contextualizing it with current developments (then in 1979) regarding World trade and changes of conditions within this particular time-frame (Vernon, 1979, p.255). However, as in 1966 any clear definition of the term ‘innovation’ is absent even if he pursued research questions regarding innovations. %erefore, it is considered a stringent necessity to give the term a clear meaning. Vernon’s basic assumptions and reconsideration from 1979 regarding the PLC are as following: When a new product is developed and introduced, the more mature such product becomes, it more likely may affect trade patterns, location of production and other market-related factors. %erefore, a newly introduced product only can become an innovation, if there is any kind of maturity following the introduction through successful diffusion of the product. It is very difficult to define innovations accurately and make the term understandable in general terms for different disciplines or areas other than economics, since the term is ‘notoriously ambiguous’, ‘lacks either a single definition or measure’ (Adams et al., 2006, p.22) and there does not exist any authoritative definition (Baregheh et al., 2009). %e proposition in this paper that there is a connection between something becoming an innovation over a certain period (when the product is diffused) including certain steps, is supported by Müller-Prothmann and Dörr (2014, p.7) by defining innovations as ‘innovation = idea + invention + diffusion’. One clearly finds indications in literature that innovation, if seen as a process, consists of an efficient- and effective (Baregheh et al., 2009; Antunes et al., 2017) combination of technological capabilities and skills in marketing and organizational skills (Kay, 1994; Mothe and %i, 2010).

80 Hoﬀer, Thomas MAKING AMERICA ATTRACTIVE AGAIN FOR INVESTORS - DONALD J. TRUMP’S REFORMS... (75 - 102)

Vernon (1979, p.265) then found that his PLC hypothesis had strong ‘predictive power’ in the first twenty years a'er WWII explaining the composition of U.S.-trade and projecting likely patterns of FDI by U.S.-based companies. However, Vernon (1979) noticed a change of circumstances, particularly conditions in terms of market- size and factor costs, which were no longer uniquely existing in the U.S. at the end of the 1970s (p.265). One may notice that terms such as ‘Multi-National-Companies’ (MNCs) were used in his reconsideration of the original paper from 1966 in 1979. However, the term ‘MNCs’ became popular among scholars, and eventually qualified as an innovative term in economic theory at some later point in time (Piekkari and Westney, 2017). %e term originally appeared in the early 1960s (Pagell and Halperin, 1999) described as ‘companies, which have their home in one country, but which operate and live under the laws of other countries as well’ (Lilienthal, 1960, p.119). No doubt, the emergence of MNCs lead to a very strong growth of trade not only in the U.S., but rather radical changes and developments of - and in World trade could be observed. Nonetheless, a standard definition for the term ‘MNC’ does not exist (Pagell and Halperin, 1999). Nevertheless, Vernon (1979, p.265) pointed out that ‘leading MNCs’ had developed ‘global networks of subsidiaries’ within the years. However, for instance, the terms ‘global’ and ‘MNCs’ might be very problematic themselves since there does not even exist a mutual understanding of them. ‘Global’ is o'en not differentiated enough from ‘International’ (Kunczik, 1992; Wilcox et al. 1992; Banks, 1995; Culbertson and Chen, 1996; Pagell and Hal- perin, 1999; Lane et al., 2009) and a clear set of criteria for identifying MNCs does not exist due to the absence of any formal definition (Ajami and Goddard, 2014).

B. International Market Selection (IMS)

Vernon (1979, p.265) pointed out, ‘leading MNCs’ had developed ‘global networks of subsidiaries’. %erefore, the question is necessary to be asked what is relevant for making decisions to invest abroad or to engage in international trade. %is process of finding possibilities for direct investments abroad is (or should at least be) subject to International Market Selection (IMS). %e International Market Segmentation and Integral Market Segmentation are parts of IMS. Whilst the International Market Segmentation has the objective to select the most attractive market for a company by considering different criteria e.g. economical-, political-, industry-specific data (Kutschker and Schmidt, 2002; Zentes et al., 2004), the Integral Approach is considered with customers (buyers), which are classified on a cross-country level (Hassan and Katsanis, 1991) by demo-, psychographic and

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behavioral issues including country- and cultural indifferent life style typologies (Keegan, 2002). %is form of clustering has an important meaning in B2B markets (Backhaus et al., 2003). Another typological differentiation includes descriptive approaches, in which only widely the firm’s behavioral approaches are described (Andersen and Buvik, 2002) and normative approaches, where a systematized decision-structure is postulated (Zentes et al., 2004). %e process of the market selection must be formalizable and structured. %e decision is based upon the definition of problems and selection-criteria, prioritiz- ing those and determining the optimal decision (Andersen and Buvik, 2002). Older literature refers to Single-Stage Models where mostly Secondary Data is evaluated (Papadopoulos and Denis, 1988; Papadopoulos et al., 2002) while the current literature refers to Multi-Stages-Models, which seek for a strategic result by evaluating countries in a differentiated analysis (Zentes et al., 2004) by considering several factors. One typical Multi-Stage-Model was developed by Rahman (2003). %e model (Fig.2) includes two stages. First, the market size attractiveness is determined by considering macroeconomic and other indicators, micro indicators and the firm’s international business capabilities. %ere are variables included such as ‘gross national product, population size, rate of inflation, country’s foreign currency reserve position, stability of exchange rate, and some product significant demographics’ (Rahman, 2003, p.127). Figure 2.: TWO-STAGE IMS MODEL

Source: Rahman, 2003, p. 129 Author’s own representation

82 Hoﬀer, Thomas MAKING AMERICA ATTRACTIVE AGAIN FOR INVESTORS - DONALD J. TRUMP’S REFORMS... (75 - 102)

Variables contributing to the firm’s international business capabilities include ‘synergy with existing markets and marketing skills, international marketing capabilities and orientations, firm’s competitive advantage, and management’s overall feel about the target market’ (Rahmann, 2003, p. 127). However, Rahman (2003) simplified the illustration (Fig.2) to make it quickly understandable also for researchers who are not fully into IMS research. $e real, or one may say, the more complete picture is presented in Tab.1, in which the different factors are being operationalized by naming the variables which must be considered in the different steps. $erefore, we can understand the attractiveness of a country for a firm to invest in as a real big basket of different (business-)environmental realities.

Table 1.: RAHMAN’s (2003, p. 130) EXTERNAL VARIABLES EXPLAINING MODEL CONSTRUCTS

Factor Variables Gross national product (GNP) GNP growth rate Rate of inflation Currency reserve Macro-economic indicators Stability of exchange rate Population size Size of middle class Literacy rate Product significant demographics Cultural practices Religious practices Other macro-level indicators Traditional links Attitude towards foreign products Local production statistics Import statistics Micro level indicators Projected demand Competitive offerings Intensity of competition Tariff barriers Cost indicators Non-tariff barriers Marketing costs Availability of local business partners Potential to develop strategic alliances Business structure compatibility Distribution system compatibility Structural compatibility indicators Legal system compatibility Business structure compatibility Level of corruption Level of own government support International property right law Level of government control on business Policy indicators Pricing restrictions Profit repatriation restrictions Political stability in the country

Source: Rahman, 2003, p.130 (Table does not include all Factors; external factors only) Author’s own representation

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Of course, the variables in this model (Fig.2; Tab.1) are only examples for an approach. It does not necessarily mean that there is any completeness and generalization present. But understanding Rahman’s approach (2003) helps ultimately to better understand, how ﬁrms decide to invest, and it provides a theoretical framework for broadly explaining investment ﬂows inwards or outwards a country.

III. METHODOLOGY

%e aim of this research project is the addressing and discussion of a shi' of paradigm, namely the approach of Trump to minimize U.S. trade deficits. Trump’s approach is based upon a strategy: On the one hand, implementing tariffs, and, on the other hand, to make the U.S. more attractive for investors (e.g. recent tax cuts). Of course, this leads to the analyses of production of goods in a direct context with trade (imports and exports) and investment flows (inwards and outwards). But did the U.S. loose attractiveness as a place for production of goods and investment in production facilities in the first place? Is Trump’s ‘Make America Great Again’- agenda based on any factual reasons with regard to the historical development of indicators linking the topics together? Such indicators include Employment numbers (All Employees, Unemployment), Corporate Profits A'er Taxation and Pro- ductivity (and Output) in the U.S. itself. %en, there needs to be a contextualization with Foreign Direct Investments (both inwards and outwards) and trade patterns (U.S. Imports and Exports, World trade) with the domestic indicators. Such approach, in terms of contextualizing the different areas, is most appropriate when assuming that attractiveness of a place (in this research project the U.S. entirely) leads to or is transformed in respective outputs which are then utilized in outcomes by stakeholders (e.g. Slack et al. 2010, Zwikael and Smirk, 2011). %is approach is based upon two different parts. %e first part to be conducted is consistent of simple correlation analyses. Correlation analysis, in general, is used by many scientist (also in the area of economics) for determining a quantified numerical relationship between two variables (Koop, 2005). %is relationship, more a statistical association, implies the strength or the degree of a linear association between these two variables (Gujarati, 2003, p.23; Gujarati and Porter, 2009, p.20). %e strength is implied in a range between -1 and +1, whilst a result of 0 implies no statistical association. It cannot be stressed out enough that a statistical association is not automatically implying any cause (Hoover, 2013, p.38; Gujarati and Porter, 2009, p.20). Such approach must be conducted in a way that different time periods are under investigation to find out how respective developments of indicators possibly changed.

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In a second part, obtained data needs to be subject to review and interpretation to ﬁnd out how the indicators developed in absolute terms. %e results are then subject to discussion and are connected with theoretical foundations, particularly the Product Life Cycle %eory and the IMS (or in other terms the topics and areas which make a country attractive for investment).

IV. DATA AND FINDINGS

For the first part, the correlation analyses, data was used from different sources. %e indicators Foreign Direct Investment, both inwards and outwards to/of the U.S., and World Trade were taken from the World Bank (2017, 2018, 2018a). Both U.S. exports and imports data were used from Census.gov (2018). Produc- tion Output (meaning Nonfarm Business Sector, Real Output Per Hour of All Per- sons), Corporate Tax indicator (in particular Corporate Profits A'er Tax without IVA and CCAdj, CP), Productivity, which is ‘Total Factor Productivity at Constant National Prices’, and finally numbers of all employees are based upon data from Federal Reserve Economic Data in St. Louis (FRED, 2018, 2018a, 2018b, 2018c). Unemployment numbers for the U.S. were used from bls.gov (2018). For the second part, additionally, data was used from the U.S. Census Bureau (USCB, 2018, 2018a), firstly for presenting trade balances of different sectors, and secondly, for outlining trade balances with different regions and nations.

A. Correlation analysis of indicators

For processing of data, SPSS and Microso' Excel were used by the author. Af- ter converting the data, the question was, whether the data is distributed normally. %e determination of normality is important for the choice of using a parametric or non-parametric test for the computation of the correlation coefficients. Two different tests were applied (Kolmogorov-Smirnov and Shapiro-Wilk) to determine normal distribution of data. Both tests clearly implied that data is not distributed normally. Hinton et al. (2014, p.301) pointed out that non-parametric testing is applied if ‘data when it is ordinal (one or both variables are not measured on an interval scale), when data is not normally distributed, or when other assumptions of the Pearson correlation are violated’, non-parametric tests for correlation analyses are most appropriate. One option available in SPSS is the Kendall’s Tau-b Test, in which it is assessed ‘how well the rank ordering on the second variable matches the rank ordering on the first variable’ (p.304). %e results of the conducted testing are presented in Tab.2.

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Table 2.: RESULTS OF CORRELATION ANALYSES (KENDALLS TAU-B COEFFICIENTS) a d b h b a e f c Output Worldtrade Productivity Corporate Tax Corporate FDI (WB/IN) FDI Export Goods Export Import Goods All Employees All Unemployment FDI (WB/OUT) FDI

1960-2017 .904** .766** .798** .933** .943** .932** .030 .934** .933** 1960-1969 .911** -- .867** .911** .867** -.822** .956** .867** 1970-1990 .838** .733** .543** .800** .810** .771** -.028 .695** .790** 1991-2017 .692** .544** .647** .846** .886** .858** .031 .906** .852** All Employeesb FDI (WB/IN)a FDI (WB/OUT)a Export Goodsb Import Goodsb Outputc Unemploymentd ProductivityeWorldtradef 1960-2017 .849** .778** .932** .947** .941** -.018 .919** .925** 1960-1969 -- .956** 1.000** .956** -.822** .867** .956** 1970-1990 .876** .533** .905** .971** .914** -.000 .800** .914** 1991-2017 .715** .578** .755** .772** .789** -.230 .761** .715** FDI (WB/IN)a FDI (WB/OUT)a Export Goodsb Import Goodsb Outputc Unemploymentd Productivitye Worldtradef 1960-2017 .730** .816** .814** .807** -.266** .760** .801** 1960-1969 ------1970-1990 .505** .876** .867** .810** .028 .676** .886** 1991-2017 .556** .618** .613** .630** -.276* .551** .567** FDI (WB/OUT)a Export Goodsb Import Goodsb Outputc Unemploymentd Productivitye Worldtradef 1960-2017 .816** .814** .796** -.191 .820** .826** 1960-1969 ------1970-1990 .533** .505** .505** -.161 .543** .562** 1991-2017 .709** .715** .664** .031 .725** .726** Export Goodsb Import Goodsb Outputc Unemploymentd Productivitye Worldtradef 1960-2017 .971** .955** 0.039 .937** .985** 1960-1969 .956** 1.000** -.778** .911** 1.000** 1970-1990 .895** .857** .057 .724** .971** 1991-2017 .937** .875** -.008 .906** .949** Imports Goodsb Outputc Unemploymentd Productivitye Worldtradef 1960-2017 .967** .032 .956** .971** 1960-1969 .956** -.822** .867** .956** 1970-1990 .943** .028 .810** .905** 1991-2017 .892** -.014 .942** .932** Outputc Unemploymentd Productivitye Worldtradef 1960-2017 .033 .961** .958** 1960-1969 -.778** .911** 1.000** 1970-1990 .028 .848** .867** 1991-2017 -.019 .942** .880** Unemploymentd Productivitye Worldtradef 1960-2017 .069 .046 1960-1969 -.778** -.778** 1970-1990 -.104 .028 1991-2017 .072 .042 Productivitye Worldtradef 1960-2017 .943** 1960-1969 .911** 1970-1990 .733** 1991-2017 .935**

Sources and Notes: (a) Worldbank 2018; Worldbank, 2018a (b) Census.gov, 2018; (c) FRED, 2018; (d) bls.gov, 2018; (e) FRED, 2018a; (f) World Bank, 2017; (g) FRED, 2018b; (h) FRED,

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2018c. Notes: (a) Net inflows and outflows, BoP, current USD; (b) BoP basis; (c) Nonfarm Business Sector, Real Output Per Hour of All Persons; (d) In %, seasonally adjusted, annual averages calculated; (e) Total Factor Productivity at Constant National Prices; (f) USD at current prices; (g) Corporate Profits A&er Tax without IVA and CCAdj, CP. / ** = significant at the 1% level; * = significant at the 5% level. Corporate Profits a'er Taxation correlating with the other indicators implied that the correlation coefficient remained mostly very strong in the different periods of observation but decreased in general. One might expect that if Profits increase, also an expansion of the firm taking place and therefore new employees are hired. Such claim can be generally confirmed, not only considering All Employees and Unemployment Rate (significant at the 1% level in 1960-1969, but not significant at all in other periods), but the decrease in strength might be explained with an ongoing automation in production. %e results for All Employees implied that the greater are Investments from Abroad, the greater is the number of All Em- ployees. Interestingly, the correlation coefficient is (what sounds logical) greater for flows inwards than outwards. Furthermore, we can find nearly perfect, very strong positive correlations for trade patterns (U.S. Exports and Imports of goods, and World trade; Imports in the observation period 1960-1969 even correlated perfectly, calculated 1.000, which is a number of .99999 and was rounded up by SPSS). It must be pointed out that Unemployment correlated very strong negatively and significantly in 1960-1969, but for other observation periods no significant correlation was found. Due to limitations in data available, the investment flows inwards and outwards the U.S. cover the period from 1970-2017. %e results imply that inward investments are very strong and positively in-line with other indicators, except Unemployment. However, most correlations with inward investments lost strength considering the period from 1970-1990 and 1991-2017. %e opposite trend is noticeable for outward investments. Such development implies that for a fact inward investment were more decoupled from other indicators, vice versa for outward investments. When it comes to trade patterns, one can clearly find that U.S. trade is highly and significantly correlating with World trade. Such high correlation was expected, since it is commonly known that the U.S. plays a very, if not the most important role in the global trade system. Furthermore, trade very strong and significantly correlates with Productivity and Output. Higher productivity, as already mentioned, utilizing in lower Unemployment is also noticeable when it comes to trade (the more positively trade develops, the more negatively unemployment develops; significant only in 1960-1969).

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B. Analyses of the development of trade and investment ﬂows

In the second part of the analyses, trade and FDI were subject to isolated investigations because these two indicators are contextualized with theoretical foundations. %e presentation of the development of U.S. Trade in absolute terms from 1948-2017 (Fig.4) implies an exponential growth, particularly from the 1980s. Such development is, of course, the result of a commonly known intensified corporation among nations/regions. However, in 1971, it was the first time a trade deficit in the trade of manufactured goods appeared in the U.S. (USD 48,342,000,000 Imports vs. USD 43,549,000,000 Exports) which continued to grow till today. Figure 4.: DEVELOPMENT OF TRADE IN THE U.S (in current usd)

Source: Census.gov, 2018 Author’s own representation

%is is the first interesting fact, since many people (including researchers) believe that the situation of U.S. trade deficits is a phenomenon starting in the current/last decade. Such belief might be linked to the fact that the deficit intensified under Bush in the 2000’s and continued to grow under Obama, but the roots for such development can be found much earlier. %erefore, the developments of the indicators (Fig.5) are subject to discussion. %e basis for analyses (Fig.5) is the year 2002. U.S. Imports exceeded 1,200,230.0 Mn USD and U.S. Exports exceeded 693,103.0 Mn USD. World trade (avg. of Exports and Imports in the same year) exceeded 6,619,505.0 Mn USD.

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Figure 5.: DEVELOPMENT OF TRADE IN THE U.S. AND THE WORLD

Source: World Bank, 2017; Census.gov, 2018 Author’s own representation

%e determined very high correlation coefficients are visually talking for themselves, since we can see parallel developments of the indicators (Fig.5). To give U.S. trade deficits a further meaning, the respective avg. balances of trade in goods and merchandise were differentiated by sectors (Fig.6).

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Figure 6.: SELECTED PRODUCTS AND CATEGORIES SUBJECT TO TRADE IN THE U.S.

Source: USCB, 2018, 2018a Author’s own representation

%e results clearly imply a dominance of deficits in most sectors under investigation. As one can find (Fig.6), the U.S. have a strong position in Transport Equipment and some agricultural areas such as Oil seeds and Oleaginous fruits besides other commodities. A surplus can be also noted in Chemical Materials and Plastics in primary forms. However, these areas and the surpluses are in total amounts little, directly compared with trade results to be found in Road Vehicles and Telecommunications equipment. Other areas in the electronic segment such as Office Machines and Electrical Machinery exceed by far the surpluses noted. However, these numbers do not show the respective development of the sectors over time. %e other question was with which countries and regions the U.S. had a surplus or deficit with. In consequence one might point to existing attractiveness for firms investing in a country or region in question. %e trade-balances of the U.S. in 2016/2017 have been subject to review (Tab.3). Again, these numbers do not show a development over time but rather reflect the current situation.

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TABLE 3.: AVERAGE TRADEBALANCE OF GOODS OF THE USA WITH SELECTED COUNTRIES AND REGIONS (2016/2017; in million us-dollar)

Selected Regions Average Balance Selected Countries Average Balance APEC -597,996 China -361,286 OECD in Europe -327,383 Japan -68,840 European Union -149,104 Mexico -67,413 NATO -107,477 Germany -64,177 MERCOSUR 3,077 Belgium 15,006 CAFTA-DR 6,154 United Arab Emirates 17,384 Asia -- Near East 6,482 Netherlands 23,613 South/Central America 31,156 Hong Kong 30,025

Source: USCB, 2018, 2018a Author’s own calculations and ranking

%e data obtained (Tab.3) clearly points to ‘unfair trade’, as Trump would say, in the Asian Region (APEC, Asia Near East), particularly for Chinese and Japanese trade agreements. Furthermore, such trade deficits are observable in the European region (OECD in Europe, European Union), particularly and most impacting for German trade agreements. Mexico, which is subject to Trump’s review of trade agreements (Trump, 2016) generated a trade deficit as Germany did. Already identified the general trends in trade and the integration of the USA in World Trade (Fig.5), the link between production of goods and trade patterns of the U.S. (Tab.2), and sectoral- (Fig.6) and regional weaknesses (Tab.3), it must be found out, if and how investment flows developed in a context with trade patterns for further understanding Trump’s trade politics and to predict respective outcomes.

C. Investments inwards/outwards the U.S. and the development of world trade

It is necessary contextualizing previous interpretations and indicators with investment ﬂows. Following Vernon (1966; 1979), foreign investments are the result of ‘good’ local foreign conditions somewhere preferable over those domestically (1966, p.194; 1979, p.265). To gain competitive advantage, a company selects that location for production in which it faces the most needed and wanted environment (e.g. Rahman, 2003; Koch, 2001), both from an inside-outside and outside- inside perspective.

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%e data processed clearly indicates that companies from the U.S. are investing more, in absolute terms, abroad than foreign companies invest in the U.S. (Fig.7). %e growing intensity of such development can be observed starting in the 2000s whilst before it seemed to be so that investment flows were more or less balanced. Furthermore, and surprisingly, it seems to be so that the global financial crises had no significant impact in foreign direct investment activities at all (in the years of the crisis starting), both from and by domestic and foreign companies. %erefore, it is legitimate to implicate that local conditions for investments in production facilities in the U.S. were not favorable over those abroad. %is implication is not limited to new products but rather includes mature products. Figure 7.: Investement flows in/out the u.s. (IN CURRENT USD)

Source: World Bank (2018), (2018a) Author’s own representation

Additionally, it must be noted that the investment ﬂows were heavily not following a smooth development starting in the late 1990s but rather outlying with tops and downs (Fig.7, Fig.8)

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Figure 8.: DEVELOPMENT OF Investement ﬂows in/out the u.s.

Source: World Bank (2017), (2018), (2018a) Author’s own representation

Nevertheless, such implication is subject to discussion and further research particularly to be able making predictions for future developments in the U.S. in the ‘Age of Trump’.

V. DISCUSSION

Nevertheless, the theory is most general. %e most critical factor for making predictions about the favorable location of production is time. Vernon (1966; 1979) did not describe a time span and did not distinguish between industries. An- other issue, which needs our attention is the ‘acceleration of time’, meaning globalization as a phenomenon itself causing policy makers to act and react very quickly in a connected world. Of course, there are diﬀerences between industrial sectors and products, but to be able to use the theory in managerial practice, e.g. being able to plan locations of production at a certain point in time due to competitive advantages in one country, there needs to be a more accurate and precise application of the theory to diﬀerent industrial sectors and products. %e same need applies for politicians making macro-policies for controlling certain (intended) developments of respective industrial sectors or product categories to gain competitive advantage. Furthermore, Vernon (1966, 1979) very well understood and observed the

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emergence of MNCs which do not operate in one nation solely, but rather operate internationally or even globally. It was pointed out that the location of production for new products does not necessarily has to be in the firm’s homeland but can be abroad. %ere are plenty of examples how supply chains are organized today. It is commonly known that many firms, particularly in recent years, fully use the possibilities, which globalization brings with it and have several locations for pro- ductions in different countries. Empirical evidence is present, particularly for the U.S. in this paper: On the one hand, exports are growing, on the other hand and at the same time, imports are growing. Furthermore, investment activities abroad (meaning FDI outwards the U.S.) have clearly become an issue compared with investments made in the U.S. by foreigners (meaning FDI inwards from abroad in the U.S.). Nevertheless, the question is, if these outflows of capital are harmful for Americans at all or if it even benefits the American people as many in support of globalization say. Consequently, the question is whether an MNC does necessarily have a homeland at all considering the globalization of financial markets and different shareholders, from different countries, are owners of the firm. Significant very strong correlations between trade patterns and productivity in the U.S. point to a situation of interconnection. Such interconnection is the outcome of effective policy making. On the one hand it has been clearly implied that the U.S. are very well integrated into World trade. On the other hand, U.S. imports and exports correlate between themselves significantly very strong and both indicators correlate again respectively very strong and significantly with productivity indicators. However, one thing, Trump always underlines, is the decoupling of these indicators from Unemployment. And in this paper, there is statistical evidence present which supports his claim. Nevertheless, the decoupling of the unemployment indicator from other indicators is subject to further research because there is no theoretical explanation given and related areas of interest are missing, e.g. development of migration and automatization, for instance. Back to the phenomenon of correlating trade patterns: What could such observation mean in practice? One shall assume that a new factory is build. New jobs are created, products are manufactured and sold, possibly abroad (leading to increased exports). %e firm pays its employees. Now, considering basic principles of consumer-needs, we can assume that employees are buying electronic equipment such as smart phones or a new TV. Where do such products come from? Possibly and most likely from abroad (leading to increased imports). On the one hand, the newly build factory sells goods abroad (added to the balance of exported goods), and, on the other hand, e.g. employees are buying consumer goods from

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abroad (added to the balance of imported goods). Investigating selected products and industrial sectors, one can clearly find a dominance of imports of highly tech- nologized items what makes the chosen example quite a useful reflection of reality. %e problem begins if the trade balance is not balanced at all in one or the other side. For U.S.-trade one can clearly identify the beginning of the 1970s as the point in time where a change from a balanced trade balance to a trade deficit shaped balance took place. %ese trade deficits, which became clearly larger over decades, point to a situation in which there seems to be no advantage for producers of those items to manufacture them in the U.S. (in most general terms). Such low attractivity is mostly given when comparing the U.S. directly with China, Japan, Mexico and Germany. As Rahman (2003) identified different factors and respective variables, it is not possible to imply which of those is, in direct comparison of the U.S. with another country the reason for less attractivity because there does not exist a common understanding of attractivity: For one sector and even a particular firm one factor/variable is from great importance, for another sector/firm, another factor/variable is important. Nevertheless, the fact that there is such deficit allows the statement that conditions elsewhere, where you find a negative trade balance, are favorable over those domestically. Vice versa, a trade surplus of the U.S. with South/Central America, the Netherlands and Hong Kong points to the U.S. as a favorable location for manufacturing. Such determination seems to be supported by data for U.S. investment flows in- and outwards. It has been observed that in- and outward investment activity developed relatively balanced from the beginning of the 1980s to the middle of the 1990s. However, in the late 1990s such balance was superseded with more investments, in absolute terms, taking place abroad by U.S.-firms than foreign direct investments took place by foreign firms.

VI. CONCLUSION AND IMPLICATIONS FOR FURTHER RESEARCH

Different shi's of paradigm were identified in this research project. First, the U.S. was an exporting nation and became a deficit trade economy in the early 1970s. Second, not only a trade surplus was present but with increased trade and production, unemployment was positively (meaning a reduction of it) influenced. Such parallel development was not present anymore in the future and for a fact, the unemployment indicator was somehow decoupled from textbook-assumptions (no significant or strong correlations found). However, naming reasons for this

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decoupling were not possible in this research project but must be addressed in future research. %erefore, one must ask if an increase of production consequently leads to less unemployment without considering many more factors and variables in the long term. %ird, investment flows, both inwards and outwards the U.S. were not developing stable but rather outlying (in both directions) from what was considered to be normal in the late 1990s compared with the decades before. Furthermore, outward investments dominated the economic and financial reality that the U.S. was less attractive for a place of production of manufactured goods, as the results clearly implied. In this paper, Product Life Cycle theory from the late 1960s was revisited, and it was empirically shown that production of goods is highly connected with trade patterns. If there exists such a high correlation one must assume that micro- and macro-policies are both efficiently and effectively applied. Nonetheless, these policies must be questioned at all: On the one hand, there exists a large trade deficit of goods in the U.S.-trade balance starting to grow expo- nentially from the middle of the 1970s. On the other hand, investment flows are more intensive outwards than inwards starting in the late 1990s. In conclusion and in most general terms, one can find that the U.S. is no longer an attractive location for production since the local conditions are not favorable over those existing abroad in many industrial sectors. Such conclusion is based upon two pillars: In the International Market Selection Model reviewed different factors and variables were identified. %ese are the decision criteria for a firm to invest in a country. If needs, or one may say the basic assumptions made by a firm individually defining attractiveness, are not met, the firm will invest somewhere else. Namely there, where the U.S. faces trade deficits. One can say that the outcome of the firm’s decision to invest is not only reflected in FDI indicators but rather in trade balances. As the literature review implied, it was already clear in the 1960s that there is a continuous need for innovations taking place to ensure the survival of the firm and, from the macro-perspective to ensure growth and further development. If local conditions are not favorable in the U.S. over those abroad at a large scale, what might be indicated by considering the large trade deficit and respectively the outwards investment flows in recent years, no growth and development can take place, but rather the opposite: Social peace is at stake and democracy itself is in great danger. When it comes to Donald J. Trump, there is, undoubtedly and commonly known, a large bias in place. However, breaking it down to economic-, trade- and foreign policy one cannot solely condemn the president’s intensions and actions taken: Big firms announced large investments or

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the remain of production facilities in the U.S. as a direct results of Trump’s tax reduction plans and other policies to be implemented in the future. Of course, there are also companies, which will relocate production from the U.S. to another country due to tariffs implemented as a reaction of Trump’s trade barriers implemented. But such decisions of firms are, considering Vernon’s basic principles from 1966, comprehensible: Even if the Trump administration lowered taxes and installed different mechanisms to stabilize the manufacturing sector in the U.S., the local conditions are not favorable over those in e.g. Europe, particularly a'er the EU answered U.S.-tariffs with tariffs itself for U.S.-products. As for the beginning of Trump’s presidency, general conditions (e.g. lowering taxes) were improved. How- ever, now, in the middle of his first term, such improvements need to take place not only in directly concerned areas of decision makers (those, who decide about the location for production) but rather in areas such as e.g. science and education, what then leads to attractiveness and innovation capabilities of the U.S. in the long term. It is not enough to fix trade agreements and neglect other areas, which are linked with innovation. Trump is on the right path, but this path will take long, particularly considering the doings of his predecessors. For further research it is implied that the high correlation coefficients determined for productivity, import and export need to be further statistically analyzed and compared in cross-country-analyses. Furthermore, trade balances need to be further monitored to measure the effectiveness of Trump’s policies. Last, the Prod- uct Life Cycle and all its implications need to be applied to every industrial sector for a better and deeper understanding of production and the outcome in trade patterns.

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REFERENCES

Adams R., Bessant J. and Phelps R. (2006) Innovation management measurement - A review. International Journal of Management Reviews. Vol. 8. 21-47. Adjami R. and Goddard J. (2014) International Business- %eory and Practice .3rd revised edition. London: Routledge. Andersen O. and Buvik A. (2002) Firms’ Internationalization and Alternative Approaches to the International Customer Market Selection. International Business Review. 11(3). 347-363. Antunes M., Texeira Quiros J. and Do Rossrio Fernandes Justino, M. (2017) %e relationship between innovation and total quality management and the innovation effects on organizational performance. International Journal of Quality & Reliability Management. 34(9). 1474-1492. APPLE (2018) Apple accelerates US investment and job creation. [ONLINE]. Retrieved from: https:// www.apple.com/newsroom/2018/01/apple-accelerates-us-investment-and-job-creation/ [Accessed 12 April 2018]. Backhaus K., Buschken J. and Voeth M. (2003) Internationales Marketing. 5th edition. Stuttgart: Schäffer Poeschl. Banks S. (1995) Multicultural Public Relations - a social-interpretative approach. London et al.: Sage. Baregheh A., Rowley J. and Sambrook S. (2009) Towards a multidisciplinary definition of innovation. Management Decision. 47(8). 1323-1339. Bls.gov (2018) Economy at a Glance / Unemployment. [ONLINE] Retrieved from: https://www.bls. gov/eag/eag.us.htm [Accessed 22 December 2018]. Census.gov (2018) Foreign Trade. [ONLINE]. Retrieved from: https://www.census.gov/foreign-trade/ statistics/historical/index.html [Accessed 22 December 2018]. CNBC (2018) Exxon Mobil announces $35 billion in new US investments over 5 years, citing tax reform. [ONLINE]. Retrieved from: https://www.cnbc.com/2018/01/29/exxon-mobil-to-invest-50- billion-in-us-over-5-years-citing-tax-reform.html [Accessed 11 February 2018]. Culbertson H. and Chen N. (1996) International Public Relations - a comparative analysis. Mahwah: Lawrence Erlbaum. FORD (2017) Ford invests in Michigan. [ONLINE]. Retrieved from: https://media.ford.com/content/ fordmedia/fna/us/en/news/2017/05/19/ford-invests-350-million-creates-or-protects-800-jobs.html [Accessed 12 April 2018]. FRED (2018) Nonfarm Business Sector: Real Output Per Hour of All Persons (PRS85006092). [ONLINE]. Retrieved from: https://fred.stlouisfed.org/series/PRS85006092#0 [Accessed 19 December 2018]. FRED (2018a) Total Factor Productivity at Constant National Prices for United States (RTFPNAUSA632NRUG). [ONLINE]. Retrieved from: https://fred.stlouisfed.org/series/ RTFPNAUSA632NRUG#0 [Accessed 26 December 2018]. FRED (2018b) Corporate Profits A'er Tax (without IVA and CCAdj) (CP). [ONLINE]. Retrieved from: https://fred.stlouisfed.org/series/CP#0 [Accessed 23 December 2018]. FRED (2018c) All Employees: Total Nonfarm Payrolls (PAYEMS). [ONLINE]. Retrieved from: https://fred.stlouisfed.org/series/PAYEMS [Accessed 19 December 2018].

98 Hoﬀer, Thomas MAKING AMERICA ATTRACTIVE AGAIN FOR INVESTORS - DONALD J. TRUMP’S REFORMS... (75 - 102)

Gujarati, D. N. (2003) Basic Econometrics. 4th edition. New York et al.: McGraw-Hill Higher Education. Gujarati, D. N. and Porter, D. C. (2009) Basic Econometrics. 5th edition. New York et al.: McGraw-Hill Irwin. Harley-Davidson (2018) Form 8-K. [ONLINE]. Retrieved from: http://investor.harley-davidson.com/ node/17401/html [Accessed 30 June 2018]. Hassan S. and Katsanis L. (1991) Identification of Global Consumer Segments - A Behavioral Framework. Journal of International Consumer Marketing. 3(2). 11-28. Hinton P.R., McMurray I. and Brownlow C. (2014) SPSS explained. 2nd edition. New York: Routledge. Hoover, K. D. (2013) Indentity, Structure, and Causal Representation in Scientific Models. In: Hsiang-Ke C., Szu-Ting C. and Millstein R. L. (eds.) (2013) Mechanism and Causality in Biology and Economics. Heidelberg et al.: Springer. Kagan R. (2016) Why America Must Lead. %e Catalyst - A Journal of Ideas from the Bush Institute. Winter 2016 Issue 1. [ONLINE]. Retrieved from: http://www.bushcenter.org/cata lyst/leadership/why- america-must-lead.html [Accessed 5 January 2018]. Kay J. (1994) Fundamentos del exito empresarial. El valor anadido de la estrategia. Barcelona, Spain: Ariel Sociedad Economica. Keegan W. (2002) Global Marketing Management. 7th edition. Upper Saddle River: Prentice Hall. Koch A.J. (2001) Factors influencing market and entry mode selection - developing the MEMS model. Marketing Intelligence & Planning. 2001. 19(5). 351-361. Koop, G. (2005) Analysis of Economic Data. 2nd edition. Hoboken et al.: John Wiley & Sons. Kunczik M. (1992) Images of nations and international public relations. In: Avenarius H. and Armbrecht W. (eds.) (1992) Ist Public Relations eine Wissenscha'?. Opladen: Westdeutscher Verlag. Kutschker M. and Schmid S. (2004) Intemationales Management. 3rd edition. Munich: Oldenbourg. Lane H., Maznevski M., Deetz J. and Di Stephano J. (2009) International Management Behavior - Leading with a Global Mindset. 6th edition. Hoboken: John Wiley & Sons. LG (2018) LG Electronics To Build U.S. Factory For Home Appliances In Tennessee. [ONLINE]. Retrieved from: http://www.lg.com/us/press-release/lg-electronics-tobuild-us-factory-for-home- appliances-in-tennessee [Accessed 20 April 2018]. Lilienthal D. E. (1960) %e multinational corporation. A review of some problems and oppor tunities for business management in a period of world-wide economic change. Adapted from a paper prepared for the symposium “Management and corporations, 1985”, April 21-22, 1960, at the Graduate School of industrial administration of the Carnegie Institute of Techno logy. New York: Development and Resources Corporation. Mothe C. and %i, T.U.N. (2010) %e link between non technological innovations and techno ‐ logical innovation. European Journal of Innovation Management. 13(3). 313-332. Müller-Prothmann T. and Dörr N. (2014) Innovationsmanagement - Strategien, Methoden und Werkzeuge für systematische Innovationsprozesse. 3rd edition. Munich: Hanser Verlag. Nakamura D. and Eilperin J. (2016) Trump to focus on ‘peace through strength’ over Obama’s ‘so' power’ approach. [ONLINE]. Retrieved from: https://www.washingtonpost. -com/politics/trump- to-focus-on-peace-through-strength-over-obamas-so'-powerapproach/2016/12/28/286770c8-c6ce- 11e6-8bee-54e800ef2a63_story.html [Accessed 4 January 2018].

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O‘Brien M. (2017) Donald Trump’s plan to bring jobs back to America comes with one giant asterisk. [ONLINE]. Retrieved from: https://www.washingtonpost.com/news/wonk/wp/2017/01/30/donald- trumps-big-plan-tobring-jobs-back-to-america-has-one-giant-astericks/ [Accessed 4 January 2018]. Pagell R. and Halperin M. (1999) International Business Information - How to Find It, How To Use It. 2nd edition. Chicago et al.: Glenlake Publishing. Papadopoulos N. and Denis J. (1988) Inventory, Taxonomy and Assessment of Methods for International Market Selection. International Marketing Review. 5(3). 38-51. Papadopoulos N., Chen H. and %omas D. (2002) Toward a tradeoff model for International Market Selection. International Business Review . 11(2). 165-192. Piekkari R. and E. Westney (2017) Language as meeting ground for research on the MNC and organization theory. In: Dörrenbächer C. and Geppert M. (eds) (2017) Multinational Corporations and Organization %eory - Post Millennium Perspectives. Volume 49. 193-232. Bradford: Emerald Publishing. Rahman S. (2003) Modelling of International Market Selection process - a qualitative study of Australian International businesses. Qualitative Market Research: An International Journal. 6(2). 119- 132. Schlesinger J. M. and Torry H. (2018) U.S. Trade Deficit Grew to $566 Billion in 2017, Its Widest Mark in Nine Years. [ONLINE]. Retrieved from: https://www.wsj.com/articles/u-s-trade-gap-highest-in- nine-years-in-december-1517923918 [Accessed 12 April 2018]. Shaw N., Huatuco L. (2018) Editorial. International Journal of Productivity and Performance Management. 67(1). 2-3. Slack N., Chambers S. and Johnston R. (2010) Operations Management. 6th edition. Harlow et al.: Pearson. Trump D. (2016) Speech on Trade and Economics in Monessen, Pennsylvania. In: Time (2016) Read Donald Trump’s Speech on Trade. [ONLINE]. Retrieved from: http://time.com/4386335/donald- trump-trade-speech-transcript/ [Accessed 04 January 2018]. USCB (2018) U.S. INTERNATIONAL TRADE IN GOODS AND SERVICES December 2017. CB 18-15 | BEA 18-06 | FT-900 (17-12). Washington: U.S. Department of Commerce. USCB (2018a) U.S. INTERNATIONAL TRADE IN GOODS AND SERVICES ANNUAL UPDATE. CB 18-82 | BEA 18-27. Washington: U.S. Department of Commerce. Vernon R. (1966) International Investment and International Trade in the Product Cycle. Quarterly Journal of Economics. 1966(2). 190-207. Vernon R. (1979) %e product cycle hypothesis in the new international environment. Oxford Bulletin of Economics and Statistics. 41(4). 255-267. Wilcox D., Cameron G., Ault P. and Agee W. (1992) Public Relations Strategies and Tactics. New York: HarperCollins. World Bank (2017) Trade. [ONLINE]. Retrieved from: https://data.worldbank.org/topic/trade [Accessed 3 January 2018]. World Bank (2018) Foreign direct investment, net inflows. [ONLINE]. Retrieved from: https://data. worldbank.org/indicator/BX.KLT.DINV.CD.WD?locations=AF-US [Accessed 08 January 2019].

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World Bank (2018a) Foreign direct investment, net outﬂows. [ONLINE]. Retrieved from: https://data. worldbank.org/indicator/BM.KLT.DINV.CD.WD [Accessed 08 January 2019]. York B. (2017) Harvard study: CNN, NBC Trump coverage 93 percent negative. [ONLINE]. Retrieved from: http://www.washingtonexaminer.com/byron-york-harvard-study-cnn-nbctrump-coverage-93- percent-negative/article/2623641 [Accessed 6 January 2018]. Zentes J., Morschett D. and Schramm Klein, H. (eds.) (2004) Außenhandel - Marketingstrategien und Managementkonzepte. 1st edition. Wiesbaden: Betriebswirtscha'licher Verlag Dr %omas Gabler. Zwikael O. and Smyrk J. (2011) Project Management for the Creation of Organisational Value. 1st edition. London: Springer-Verlag London Ltd.

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103

Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

ARTICLE INFO Received: 1.11.2018. Accepted: 21.1.2019. JEL Classiﬁcation: A23, M00, M19

Keywords: controlling; opportunity management; risk management; small enterprises

OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES

Philipp Klein MA 1519001011@!-burgenland.at

103 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

$e global economic crisis showed that for a successful company not only customer-oriented management is required but also opportunities and risks need to be managed eﬀectively. A detailed literature analysis indicates that small businesses are especially aﬀected by this challenge.

A conducted research examined seven leader statements within small companies regarding their perceptions of different internal and external risks and their current usage of tools. $e interviewed managers were selected from different Austrian companies in various industries and hold a managerial position in their organization. $e findings showed that leaders o&en not measure risks and opportunities because it is too costly and time intensive and because of the missing knowledge.

$e focus of this paper was to develop a concept for small companies to show management that there are simple and inexpensive instruments for the implementation of opportunity and risk controlling.

104 Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

I. INTRODUCTION

%e controlling of opportunities and risks is also called ORC and is part of strategic management. Managers have to make decisions within levels of uncertainty and insecurity. In controlling risks, it is essential to identify potential crises in time and to adjust and prepare for it. At the same time opportunity controlling should be used to identify and exploit chances. Once risks begin to affect business, it is time to identify them, evaluate and then to control them. In some cases, threats cannot be avoided, but it is essential to learn, to reduce or to accept them. Oppor- tunity management combines the strengths of the company with the needs of the market through market analysis. A detailed literature analysis at the beginning of the research showed that different internal and external risks could harm a company. %erefore a qualitative study was conducted to analyze the current usage of OCR in small enterprises in Austria. %e interviews with the experts from various industries took place between the 15. March and the 24. August 2013. %ey were in the position of the managing directors or at least in a management position. All interviewed businesses measure risks by key figures and compare monthly and annual results of the previous year to derive risk tendencies. According to experts, there is no own controlling position in small businesses regarding ORC. %is activity runs in six of the seven small enterprises by the manager or key account manager. However, merely an expert knew the concept of opportunity and risk control. Only two interview experts know instruments of risk identification, due to their education. All respondents would assign OR controlling responsibilities hierarchically directly to the Managing Director. However, this position cannot directly be performed by them because of the lack of time because. In small business they have to perform so many different roles. Further the implementation of new tools is o'en too costly and time intensive. According to their long experience, the asked managers see no reason to change anything in their leadership style and their current toolset. %is work focuses on the development of a concept for small companies to provide simple and inexpensive instruments for opportunity and risk controlling. %e results of the expert interviews are not content of this paper.

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II. LITERATURE REVIEW

A. Risk Controlling

%e word risk comes from the Italian and derives from “risicare,” which means to dare. (Wolke 2008, 1) A risk is defined as an event with the chance of a negative as well as a positive outcome. It is a product of deviation from the company’s stated objectives and of the likelihood of an occurrence and its consequences. (Krause/Borens 2009: 4) %e responsibility of controlling is to support the leadership by providing information that will help to achieve the companies’ objectives. Another function is the preparation of data for decision-makers to make individual decisions and furthermore the monitoring of events within the company and the establishment of an early warning system for the identification of opportunities and risks. (Siller/ Grausam 2013: 44) Risk controlling supports the process of risk management and extend management functions. (Burger/Buchart 2002, 9) %e main task of controlling is the provision of company-relevant information about impending or future risks. (Damaschke 2005: 5) %e data is used by management for planning, coordinating and controlling risks. An important part of risk controlling is the risk reporting, which obtains sufficient information and represents a significant part. It supports Management in risk monitoring and risk management by providing suggestions for dealing with risks. Risks are split into internal eg. degree of liquidity or the capital structure and external threats eg. the competition, the political situation of the country or the market situation. Risk controlling offers considerable opportunity for the reaction, adaptation, and coordination within the company. %e interaction between controlling and management reveals a parallel concerning content. (Diederichs 2010: 27)

B. Opportunity Controlling

An opportunity is a facility for success or the prospect of achieving success. Furthermore, it means that there is a likelihood that a positive event will occur. Rarely do opportunities arise without risks and vice versa. (Diederichs 2010: 193) %e responsibility of opportunity management (OM) is, like at risk management, at the management. %e main task of opportunity controlling is the recognition of opportunities, achieved by linking instruments of strategic management. OM is referred to as a dynamic form. A market analysis tries to combine the strengths of the company with the needs of the market, thereby deriving formative

106 Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

and initiative measures to help realize opportunities. %e challenge is the regular mapping and documentation of market developments and the restructuring of the company. %e interface between risk and opportunity management occurs at the point where managing directors’ and owners’ scope of action may be restricted. %erefore an early-warning system instead of a hazard-focused system should be implemented. It deduces new opportunities as part of the risk management process. %e early warning system does not take into account the positive or negative eﬀects of future developments and events. %e task of opportunity controlling is to prepare possible active or reactive actions before developments and events take place. (Dickmann 2002: 344) %erefore, it is part of successful management strategies. (Form 2004: 87)

III. RESEARCH METHODOLOGY

Before the elaboration of a theoretical concept of opportunity and risk controlling for small enterprises, a qualitative market research was used to evaluate the current situation of ORD in Austrian companies. %e guided interview which uses experts opinions for data collection was used. (Hug/Poscheschnik 2010: 124 ) %ereby versatile insights on a subject area can be gained. An expert is a person who has many years of professional experience in a specialist field or extensive specialist knowledge. (Fischer 2006: 17) %e interviews with the experts had the same procedure and took place between the 15. March and the 24. August 2013. First, the framework of the discussions was explained, followed by a short introduction with warm-up questions with the aim to know more about the background and the work experience. With the agreement of the experts, the interviews were recorded on tape and took between 20-36 minutes. %e experts came from the gastronomy, home appliance, hotel, transport, and automobile industry and are responsible for between 10 and up to 49 employees. For the topic of this research group, it was important that all of the experts have had many years of experience in their field to be able to respond to changes in requirements. %e results have shown that there is hardly any opportunity and risk controlling in small companies. At the moment controlling departments o'en use some key figures to steer companies. For most small businesses, the outlay is too significant regarding the high costs and time needed for the implementation of opportunity and risk controlling tools. %erefore, based on these findings, a concept for

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ORC for small businesses has been developed, as well as a collection of simple tool toolkit for implementation.

IV. RESULTS

A. The concept of opportunity and risk controlling for small businesses

For companies and their entire environment, it is not only essential to explain and describe opportunities and risks, but also to conclude future developments from the accumulated insights. (Gutenberg 1962, 5) Controlling is as important in small businesses as it is in large companies. For small businesses, a standardized controlling concept cannot be created because the opportunities and risks vary from industry to industry. However, a simple and effective controlling system in organizations would be useful. (Siller/Grausam 2013: 119) Targeted action is necessary to make analyses, assessments and the optimization of opportunities and risks possible. (Picot/Schuller 2001: 237) In opportunity and risk controlling, as in general controlling, a structure is developed in which the goals, the tasks and the concept are gradually given a concrete form. Depending on the specific application, the defined controlling structure forms the framework for detailed and varied instrumental design.

B. The conﬁguration of opportunity and risk controlling

%e decision-maker does not carry out the opportunity and risk controlling in every small business; the information gathered must, therefore, be summarized and used to support the CEO (Chief Executive Oﬃcer) or owner of a company. Based on the individual situation, a company can use a variety of instruments. %e instruments relate to basic information on the opportunity and risk proﬁle, analyzing potential opportunities and risks for the company, and using the toolkit for further management, evaluation, monitoring and analysis. %e information collected is reprocessed into reports and sent to the decision-makers. %e information communicated in this way helps to improve the quality of decision-making.

108 Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

Figure 1.: CONFIGURATION OF OPPORTUNITY AND RISK CONTROLLING

Source: Form (2004): 377

When setting up opportunity and risk controlling, three main elements must be considered and presented. (see figure 2) First, the critical opportunity and risk types or fields have to be determined. A'erward, a suitable toolkit for identification is selected which analyze, evaluate, monitor and control them. %e collected information are used for the third and final step for the development of reports. %is process visualizes, compiles and presents the data and transmits it as part of a reporting system. (Form 2004: 377) Senior executives receive only filtered information on facts and circumstances that illustrate the impacts on profit or equity, or amounts of profit or loss. Informa- tion that is irrelevant at executive level remains at the reporting level below. Reporting cycles may be longer, for example, quarterly, biannual or annual, and may differ from short-term or monthly reporting by other reporting systems. However, certain situations require short and prompt action from decision-makers, for which there is the alarm system. By using this system, necessary informa-

109 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

tion or, for example, image-damaging occurrences are communicated directly and immediately to management level. Depending on the content and type of information, there are various possibilities for information system-based or formalized reporting. (Form 2004: 391)

C. Instruments for small businesses

Each toolkit for opportunity and risk controlling supports a different phase in the management process, using and providing information to support the decision making. In the beginning, structured research is performed and an initial identification takes place. Based on the findings a toolkit is created which can be constantly expanded in the future. (Reichmann/Form 2003: 167) %e following chapter introduces simple tools of opportunity and risk controlling for small companies which are inexpensive and not time intensive. %ey help to react to potential opportunities and risks promptly. Written documentation of the instruments is recommended to ensure a certain level of quality and further to control the results and progress. (Siller/Grausam 2013: 120) %e following tools have been selected because they can be applied without any special knowledge about ORC management.

i. Risk Checklist A risk checklist helps to detect potential risks. Potential sources of uncertainty must first be identified to initiate measures to avert dangers. An essential factor in the risk checklist is the likelihood of occurrence and possible associated damage to the company. %is instrument aims to describe the risks and define countermeasures qualitatively. Some risks, such as the foreign exchange risk, can also be covered by insurance. However, it is not possible to exclude all risks in this way. Figure 3 shows an extract of a checklist. %is should help to identify sources of uncertainty within the organization.

110 Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

Figure 2.: Risk checklist

Source: Adopted Haunerdinger/Probst (2006): 116 %e advantage of the risk checklist is that it gives an overview of the processes in the company and tries to assess them according to the probability of occurrence and to deﬁne possible countermeasures at an early stage. %e disadvantage is that not all risks are excluded with the method. (Haunerdinger/Probst 2006: 115)

ii. Strengths and weaknesses analysis %e strengths and weaknesses analysis evaluates potential factors but also outside inside the company to their strongest competitor. In the first step the company’s significant success factors are written down and rank-ordered. %ese key factors are set in contrast with the strongest competitor and assessed. It is essential to improve on the success factors that are rated lower than those of the competition because these offer potential for improvement. Fig- ure 4 shows an example of a strengths and weaknesses analysis. (Plümer 2003: 11)

111 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

Figure 3.: STRENGTHS / WEAKNESS PROFILE

Source: Adopted from: Plümer (2003): 11

%e advantage of the strengths and weaknesses analysis is that the management gets an overview and its approximate position. However, only individual parts of the company are examined, and there is no overall picture. Another disadvantage is that the assessment of resources is subjective, and does not correspond 100% with reality. (Von Holdt “Externe Controlling in Kleinen- und Mittelständi- schen Unternehmen (KMU).“

iii. Opportunity-risk identification sheet An opportunity-risk identification sheet is useful for identifying and disclos- ing company’s opportunities and risks because it records all aspects. It should contain the following points: (Siller/Grausam 2003: 155) • naming the opportunity or the risk, • type of risk, • area in which the opportunity or the risk belongs, • responsible employee, • description, • early detection indicator(s), • likelihood of occurrence, • potential level of success or risk, • possible measures or measures taken, • interactions with other risks, - overall score between 1 and five according to urgency (1 = urgent/acute, 5 = continue to monitor).

112 Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

Figure 4.: RISK MATRIX

Source: Adopted from: Siller/Grausam (2013): 156 Figure 5 shows the risk matrix (traﬃc light colors). Here, the likelihood of occurrence and the potential amount of damage is displayed in a graph. In addition to the actual risk matrix, a plan risk matrix is recommended, so that a plan-actual comparison can be carried out on a regular basis. %e tool can be used to show the impact of a company’s risks and thus provides an overview. A disadvantage is that the entrepreneur can interpret these risks wrong, and therefore it makes sense to develop the risk matrix in collaboration with a responsible employee. (Siller/Grausam 2013: 156)

iv. Scoring model %e scoring model support decision makers and is used to provide a comprehensive summary and description of opportunities and risks, therefore these are not precise and objective. Measurements can be used to make comparisons and assessments of identiﬁed opportunities and risks. %e scoring method is useful for assessing new strategic business lines or for evaluating alternative investment projects. Figure 6 shows an example of a possible scoring model. Figure 5.: COLLECTION AND PRESENTATION OF ORDINAL CHARACTERISTICS IN PROFILES

Source: Adopted from: Form (2004): 393

113 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

Features in the assessment of, for example, suppliers, might be flexibility, delivery reliability, transport costs, etc. Assessing risks using scoring models includes value benefit analysis, such as a supplier analysis, and thus takes a step in the direction of accuracy and objectivity of consideration. %e model is based on the availability of information on events and developments and links these with subjective evaluations. (Form 2004: 393) %e data collected is sorted according to the identification and classification of significant opportunities and risks for the company, weighted by individual or group and subjected to an accurate evaluation based on experience. %e risks are assessed on the highest level of the scale. An assessment of the dangers takes place according to the information and availability of the data, so there may be an immediate need for action if there is a high expectation of loss or likelihood of occurrence. An advantage of the small business tool is that goals are formulated in operational and concrete terms. %e wording exposes the company’s preference structure and, with a focus on the crucial aspects, helps to accept and enforce decisions. %e problem with the scoring model is that the rating is carried out subjectively. (Harting 1992: 52)

V. CONCLUSION

Opportunity and risk controlling supports strategic management decisions and gives leadership the chance to react quickly to detected opportunities and risks. Different internal and external risks can harm a company and need therefore be monitored and can thereby result in opportunities. OCR tools are already being adopted in large companies but it is also essential for small businesses to derive market share and remain competitive therefore an implementation of a toolkit make sense. For small businesses, a standardized controlling concept cannot be created because the opportunities and risks vary from industry to industry. A survey has shown that these controlling tools are o'en known in theory but not used practically in small firms. %e central aspect not to implement these instruments is the time and cost factor. Further managers do not want to change their management style and toolset. However, a simple and effective controlling system in organizations would be useful. %is paper shows different tools for risk and opportunity controlling which can easily be used. However, each manager of small enterprises has to decide for himself which method fits best for ORC.

114 Philipp Klein MA OPPORTUNITIES AND RISK CONTROLLING IN SMALL ENTERPRISES (103 - 116)

REFERENCES

A. Books Burger, Anton, and Buchart, Anton. Risiko-Controlling. Oldenburg: Wirtscha'sverlag GmbH, 2002. Damaschke, Dominik. Instrumente des Risikocontrollings zur Bewertung von Risiken. Norderstedt: GRIN Verlag, 2005. Diederichs, Marc. Risikomanagement und Risikocontrolling: Risikocontrolling - ein integrierter Bestandteil einer modernen Risikomanagement-Konzeption. München: Vahlen, 2010. Fischer, Tim. Unternehmenskommunikation und neue Medien: das neue Medium Weblogs und seine Bedeutung für die Public-Relations-Arbeit. Wiesbaden: Springer, 2006. Form, Stefan. Chancen- und Risiko-Controlling. Wien: Peter Lang Verlag, 2004. Gutenberg, Erich. Unternehmensführung - Organisation und Entscheidungen. Wiesbaden: Springer, 1962. Haunerdinger, Monika, and Probst, Hans-Jürgen. Finanz- und Liquiditätsplanung in kleinen und mittleren Unternehmen. München: Haufe-Lexware, 2006. Hug, %eo, and Poscheschnik, Gerald. Empirisch Forschen: Über die Planung und Umsetzung von Projekten im Studium. Studieren, aber richtig. Stuttgart: UTB, 2010. Krause, Lars, and Borens, David. Das strategische Risikomanagement der ISO 31000. Berlin: Erich Schmidt Verlag GmbH & Co. KG, 2009. Picot, Arnold, and Schuller, Susanne. Vertragstheoretische Interpretation des Risk-Management, in: Lange, K; Wall, F. Risikomanagement nach dem KonTraG. Aufgaben und Chancen aus betriebswirtscha&licher und juristischer Sicht. München: Vahlen, 2001. Plümer, %omas. Logistik und Produktion: Managementwissen für Studium und Praxis. Oldenbourg: De Gruyter Oldenbourg, 2003. Reichmann, %omas, and Form, Stefan. Instrumente des Risikomanagement und - Controlling in Reichmann, T. Controlling 2003 jetzt aktiv steuern - nicht nur Kontrollieren. Dortmund: Vahlen, 2003 Siller, Helmut, and & Grausam, August. Selbstcontrolling für Selbständige und kleine Unternehmen. Wiesbaden: Springer, 2013. Wolke, %omas. Risikomangagement. Oldenburg: De Gruyter Oldenbourg, 2008.

B. Jounals Dieckmann, C. Au(au eines integrierten Chancen- und Risikomanagementsystems am Beispiel der Energieversorgung. (2002) Controller Magazin, Nr. 4, Seite 344-347. Form, Stefan, and Hüllmann, Ulrich. Chance and Risk Scorecarding. Umsetzungsaspekte eines IT- gestützten strategischen Reportings. (Dezember 2002) Controlling Magazine Harting, Detlef. Lieferantenauswahl mittels Nutzwertanalyse erleichtert Selektion. Maischenmarkt, 1992. Nr. 39, 52-55

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C. Internet sources Von Holdt, Ingo. “Externe Controlling in Kleinen- und Mittelständischen Unternehmen (KMU).“ Accessed May 1, 2013. http://www.controllingportal.de/Fachinfo/Konzepte/Externes-Controlling-in- Kleinen-und-Mittelstaendischen-Unternehmen-KMU.html

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Ing. Martin A. Moser, MA MSc QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM... (117 - 144)

ARTICLE INFO Received: 20.9.2018. Accepted: 14.6.2019. JEL Classiﬁcation: M10, M15, M31, O30

Keywords: Acceptance criteria; Customer Relationship Management (CRM); Customer satisfaction

QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM! SYSTEMS IN THE PACKAGING INDUSTRY

Ing. Martin A. Moser, MA MSc [email protected].

117 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

Customer Relationship Management (CRM) is the process of achieving a continuing dialogue with customers across all available touch points to maximize their contribution to the overall profitability and evolution of companies as well as to achieve satisfaction and loyalty. CRM-systems as the IT-component of this process support a business strategy to establish long-term and profitable relationships with customers and are constant companions in sales and marketing. $ey help organizations to increase the value of every customer interaction and drive superior corporate performance. $e success of a CRM-system is dependent on the acceptance of the respective users. $is paper identifies, due to a qualitative research approach through problem- centered interviews in the global sales organization of a leading company in the flexible packaging industry, necessary criteria for the acceptance and furthermore the success of CRM-systems by its users to contribute to the overall goal of an increased profitability and evolution of companies.

118 Ing. Martin A. Moser, MA MSc QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM... (117 - 144)

I. INTRODUCTION

Nowadays organizations are almost unable to diversify from their competitors only by their products while customer requirements are rising continuously. Only very few companies command an effective technological leadership. For the majority of organizations it is therefore important to differentiate from competitors through appropriate investments in a customer-orientation and service-orientation (Helmke, Uebel, & Dangelmaier, 2013, p. 5). Another challenge lies within a decreasing customer loyalty and the dispro- portionately expensive customer acquisition compared to the maintenance and preservation of regular customers. %at is why companies need to fulfil strategically important activities more effective than its competitors in order to gain competitive advantages. A possibility to differentiate from competitors is a use of Cus- tomer Relationship Management (Stokburger & Pufahl, 2002, pp. 16-17). CRM is an enterprise approach to understand and influence customer behavior through meaningful communications via all possible touch points to improve customer acquisition, customer retention, and customer profitability (Swi', 2001). Customer Relationship Management is not a temporally limited project or single IT-solution, but a holistic approach and customer oriented strategy, which needs to be implemented within a continuous and organizational learning process (Hippner & Wilde, 2004, p. 15). An important prerequisite is the comprehensive and intensive IT-support via CRM-systems to enable the implementation of the overall CRM-strategy. CRM- systems provide employees with the information and tools needed to deliver customer and supplier experience and allow the optimization of time spent on developing and maintaining successful relationships as well as maximizing opportunities. CRM-systems help to catalog information from initial marketing cam- paigns and sales contacts through quoting, customer orders, production, shipping, invoicing, and payment and return goods authorization cycles. %ey enable users to capture, manage and track every interaction with customers and suppliers in one place (TechBiz, 2018).

A. Problem statement

In markets with high competitive pressure, companies can only secure their existence by building and assuring long-term competitive advantages via the effective and comprehensive implementation and usage of CRM-systems (Meﬀert, Pohlkamp, & Boeckermann, 2010, pp. 7-8).

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One indispensable success factor for the implementation of CRM in an organization is the acceptance by its users or the employees of the company respectively. Without this necessity, a CRM-system is hard to implement and the corresponding added value cannot be achieved to the desired and needed extent. In most cases a potential resistance against a CRM-approach by the employees can be explained by uncertainties, which result in being afraid of excessive demand due to new tools and systems, the uncovering of weak points and even by the fear for a loss of the workplace. If employees are not convinced by the advantages and beneﬁts of a CRM-system, they will hardly and inaccurately use this tool, resulting in a decreased data quality (Helmke, Uebel, & Dangelmaier, 2013, pp. 280-281). %e current literature and data is mentioning many technical requirements and prerequisites for CRM-systems and their respective functionalities and processes as well as general information about the acceptance of IT-systems. Com- mon requirements for the successful implementation of a CRM-system and the acceptance by the employees and users, especially in the packaging industry, can hardly be found.

B. Objectives

%is paper is dealing with the qualitative identification of requirements of a CRM-system that contribute to an increase in the acceptance of the users or employees of organizations in the packaging industry respectively. %e identified acceptance criteria can be used for further implementations of CRM-systems to ensure a proper usage and approval of the employees and furthermore the achieve- ment and assurance of the intended purpose of a holistic CRM-approach. %e core topic of this work is therefore the acceptance of IT-systems, in particular of CRM-systems. %rough qualitative research, the factors influencing the acceptance of CRM-systems by its users will be identified. %e goal is to derive a requirement profile for a CRM-system in the packaging industry, so that the system is accepted by the employees and also applied accordingly. Likewise, their motivation to use the system should increase.

C. Research question

%e following research question can be concluded: “Which are the necessary criteria for the acceptance and furthermore the success of CRM-systems by its users to contribute to the overall goal of an increased proﬁtability and evolution of companies in the packaging industry?”

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With the help of the methodological approach presented in this paper, the research question will be answered and the results critically questioned, discussed and put into a common context with existing literature.

II. THEORETICAL BACKGROUND

In order to address the objectives of this paper, the theoretical background, starting with the basics of CRM and CRM-systems, as well as general information about acceptance theory, will be outlined in more detail. %e aim is to provide the necessary basic knowledge and the theoretical prerequisites for the subsequent methodological part.

A. Customer Relationship Management

Customer Relationship Management describes the integrated processing of the relationship between a company and its customers. Communication policies, distribution policies and supply policies should be aligned and oriented on the customer needs and requirements. %e central measure of CRM success is the customer satisfaction, which is an indicator for the customer loyalty and ultimately for the long-term corporate success (Helmke, Uebel, & Dangelmaier, 2013, p. 7). Customer Relationship Management has been evolving over time and several definitions attempted to incorporate the meaning discovered till then as stated and summarized below. “CRM is the strategic process of selecting customers that a firm can most profitably serve as well as of shaping interactions between a company and these customers. $e ultimate goal is to optimize the current and future value of customers for the company.” (Kumar & Reinartz, 2012, p. 5) “CRM is a comprehensive strategy and process of acquiring, retaining and part- nering with selective customers to create superior value for the company and for the customers.” (Parvatiyar & Sheth, 2001) “CRM is considered as strategic, process oriented, cross-functional and value creating for buyers and sellers and a way of achieving superior financial performance.” (Lambert, 2004) “$e practice of CRM is described as the process for achieving a continuing dialogue with customers across all available touch points to offer them customized treat- ment, based on their expected response to available marketing initiatives, such that the contribution from each customer to overall profitability is maximized.” (Bohling et al, 2006)

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“A Customer Relationship Management (CRM) system is a combination of people, processes, and technology that seeks to provide understanding of a company’s customers and to support a business strategy to build long-term, profitable relationships with them.” (Shang & Ko, 2006) “Customer Relationship Management is defined as an effective tool to achieve the objectives such as satisfied and loyal customers and increased market share.” (Shafia et al, 2011) “CRM is a continuously updated process of identifying relative value of customers and designing customized company interaction to delight them so that they do not just remain with the company profitably, but also be the company’s ambassador. Full involvement and empowerment of employees and appropriate technology are two essentials for successful CRM.” (Rai, 2013, p. 30) %e previously stated definitions of CRM imply the following: • CRM is a process • CRM needs continuous revision and updates • CRM needs customer value identification • Company interaction requires customization suiting to the exclusive profile of the customers • CRM strives for customer delight • %e CRM process aims at a profitable relation with customers • CRM aims to convert customers to act as a company’s brand ambassador • Involvement and empowerment of employees is a must for a successful implementation of CRM • Adequate technological support is essential for successful CRM CRM is an integrated approach to identify, acquire, and retain customers. By enabling to manage and coordinate customer interactions across multiple channels, departments, lines of business, and geographies, CRM helps organizations to maximize the value of every customer interaction and drive superior corporate performance (Rai, 2013, p. 30). Customer interactions must be managed across multiple communication channels, like for example web applications, call centers, field sales, and dealers. Many organizations also have multiple lines of business with many overlapping customers. %e challenge is to make it easy for customers to do business the way they like or prefer to do it at any time, through any channel, and in any language or currency. Furthermore it should be achieved to make them feel that they are dealing with a single organization that recognizes them at every touch point accordingly (Rai, 2013, p. 30).

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FIGURE 1.: Customer Relationship Management (CRM)

Source: www.siebel.com/whatiscrm CRM implies building long-term relationships with the customers, understanding their needs, and responding through multiple products and services via multiple channels as shown in figure 1. CRM should finally enable a targeted mu- tually beneficial profitable relationship with individuals and groups (Rai, 2013, p. 31).

B. CRM-systems

Information and communication technologies are playing an essential role with regards to the implementation and realization of CRM. An important prerequisite of CRM is the technological aspect. %is includes IT-requirements and system-requirements as well as the usage of new technologies. CRM-systems are a possibility for the specific management of customer relationships (Meffert, Pohlkamp, & Boeckermann, 2010, pp. 23-24). CRM-systems are information and communication systems that assist a CRM-strategy significantly. %ey are o'en seen as sheer application systems to collect information about customers and analyze this data collection accordingly. %e aim of CRM-systems is the automatization of customer-oriented processes. %is IT-orientation implies the risk to forget the necessary framework conditions of companies nowadays, which are relevant and important for a comprehensive information system (Leusser, Hippner, & Wilde 2011, pp. 17-18). %e following figure shows the correlation between information and application system.

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FIGURE 2.: Correlation between information & application system

Source: Laudon, Laudon, & Schoder, 2010, p. 18

CRM-systems are used for tracking and analyzing the correlations of the respective company with its customers with the goal to optimize turnover, profitability, customer satisfaction and customer loyalty. %erefore a CRM-system simplifies and assists the implementation and realization of a holistic CRM-approach (Lau- don, Laudon, & Schoder, 2010, pp. 533-534). A CRM-system collects company-wide customer-related data in a standardized way, saves, maintains and makes this information available for all relevant parties any time. Incompatible objectives can also be identified, analyzed, and aligned with the use of a CRM-tool. %rough the automatization of manual work steps, company-internal processes are simplified and reduced, consequently leading to savings and cutbacks. Main tasks of a CRM-system are therefore the coordination and integration of the individual communication channels between customers and companies, the support and synchronization of the essential customer touch- points, as well as the uniform integration and evaluation of all customer data and information (Neumann, 2014, pp. 115-116).

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C. CRM in B2B-environments

CRM is usually designed as an instrument and collection of tools for guiding sales people and to support engineers in developing sales projects, creating appropriate business proposals, dealing with customer objections, and providing post-sales customer support (Agrawal, 2003). CRM applications are therefore seen as closed-loop systems focused at the customer level on a set of priorities and time- critical functions (Ku, 2010). Typical CRM databases are designed to provide sales people with assistance and support for prospecting, customer qualification, proposal development, ob- jection-handling, as well as closure and follow-up. Everything is tracked on the basis of contacts, outcomes, and deliverables with the intent of pushing forward the project to a positive completion (Stein, Smith, & Lancioni, 2013). %e variety of CRM data, especially in B2B-environments like the packaging industry, makes it difficult to aggregate the collected information and data in a way that facilitates generalization across groups of customers. Customer-specific requirements and processes make it challenging to classify customers in a meaningful way. %ese classifications are therefore o'en not correct and logical or strategic (Narayandas & Rangen, 2004). Customers are perceived to be unique, whereas generalization across them is o'en seen as prohibitive (Laiderman, 2005). CRM- systems are o'en seen as libraries or archives with little more purpose than providing sales teams with historical information for future offer development or giving managers the necessary information in the event of contract disputes, whereas CRM data and information needs to be structured accordingly to support meaningful cross-sectional or longitudinal analysis (Zahay, 2012). %e true value of CRM data lies within the availability of the basis for understanding the nature of the relationship between customers and the respective organization. In addition to helping determine the basis for value proposition development, the CRM-record can provide a living picture of the interactions of the organization and individual customers or customer segments (market segments) and across the entire customer base. CRM is increasingly utilized as a common database for the organization and its customers. Key customers and buying groups can be granted limited access to CRM data concerning contract volumes, ship- ment dates, and committed volume, acceptance/rejection rates, and pricing trends. Many suppliers are finding that an openness that fosters collaboration also aids in customer retention (Abdi & Kotler, 1999). CRM and CRM-systems help to gather relevant and important information about customers to assist in improving trust and commitment in dealing with

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clients, for improving the organization’s responsiveness to customer’s service and support needs, for reducing customer defections and for lowering marketing and other related costs. %e consistent application of CRM data for managerial decision-making can transform the organization’s value creation process from initial customer prospecting right through contract renewal negotiations (Stein, Smith, & Lancioni, 2013). All information in a CRM-system and related to CRM in general, as well as other sources of market intelligence must be accessible to a wide range of decision- makers in the organization (Rigby & Ledingham, 2004). It can be stated that only a few managers in most companies know of the availability of CRM transactional information and that they do not understand how it can be utilized. Once managers become familiar with the value and application of CRM-information, it can become an invaluable resource for the company’s decision-making processes. %e ﬁrst step therefore needs to be the education of those who will be generating the data and information (sales and sales support people) and those who will be applying the resulting information for their decision-making purposes (executive level managers). Consistency of data collection and ﬂexibility in decision-making are critical for the overall success of CRM (Stein, Smith, & Lancioni, 2013).

D. Acceptance theory

%e implementation of a CRM-system is usually a complex procedure, involving all processes of an organization in a technical and organizational way. It is essential to integrate the CRM-system in the structure of the respective company to ensure its efficiency and effectivity accordingly. A CRM implementation must be considered as a strategical project, which forms and develops the prospective design of customer processing. In the scope of an extensive CRM-audit, the selection of the so'ware itself, the alignment of CRM on the strategic company goals, the identification of needs for necessary process reorganizations, as well as the needed change management must be discussed and defined. Human beings are playing the leading role during the implementation of CRM, as this process requires change in the daily work life. %e system and the CRM approach itself should not be considered as additional expenditures or a monitoring instrument of their work performance. It should be understood and function as an essential assistance and support tool for customer processing and administrative tasks. %e added value of CRM as well as the individual benefit and usefulness must be visible for every single user to ensure acceptance (Helmke, Uebel, & Dangelmaier, 2013, pp. 267-270).

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Acceptance is a key term used in social and sociological discussions for the description of positive and negative decisions. Several different and varying definitions of this term exist and the search for a universal and generally valid definition is relatively low (Kollmann, 1998, p. 37). Acceptance refers to the degree of willingness of a user to deal with a specific situation or system, to identify with it and to retrieve the provided utilization potential in a task-based manner (Manz, 1983, p. 177). Colloquially, acceptance is understood to mean a generally affirmative attitude of an individual or a social group towards the matter in question. %e term is o'en used as a synonym for recognition, endorsement, approval, and affirmation. Due to its partly inflationary use, a precise definition of the term is increasingly difficult (Betz, 2003, p. 97). In this paper, the acceptance of CRM-systems is referred to the recognition and readiness for an efficient usage. Economical acceptance research differentiates between attitude acceptance and behavioral acceptance. Attitude-oriented research is characterized by equat- ing acceptance with attitudes. Attitudes are latent variables that are not directly measurable and must be derived from verbal and non-verbal responses. Attitudes are unconsciously learned through experience, stored and recalled in a particular situation (Trommsdorff, 2004, p. 159). With regards to the equality of acceptance and attitude, attitude acceptance refers to a long-term, learned cognitive and af- fective posture, combined with an active willingness and corresponding intention to behave towards an object. %e difficulty is the neglect of open behavior. %e willingness to act merely describes the behavioral tendency, but this does not necessarily result in an actual action (Rengelshausen, 2000, p. 72). %e definition of behavioral acceptance goes beyond the action-oriented component of attitude acceptance, but at the same time limits itself to open behavior. %is leads to the fact that the internal structure of the acceptance education is ig- nored and no conclusions on appropriate influence factors are possible. For this reason, the adjustment level is always taken into account (Rengelshausen, 2000, p. 72). Acceptance for technological innovations only exists if attitude acceptance and behavioral acceptance exist at the same time. Acceptance occurs when the user is positively disposed towards the technology or the system and a basic readiness for usage exists. Furthermore, a task-related behavior must be observable. One speaks in this connection of an overall acceptance, which is a combination of the inner rational appraisal and expectation formation with the assumption of the innovation usage and voluntary task-appropriate use (Kollmann, 1998, pp. 68-69). %e concept of acceptance from the point of view of business informatics usually refers to the acceptance of application systems. In this context also the term “technology acceptance” is o'en used. Due to its interdisciplinary task, modern

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information and communication technologies focus on human activities with regards to the development and use of technical innovations. In addition to the technical framework, determinants from society, economics and sociology are taken into account (Kornmeier, 2009, p. 108). Basically, in the use of the concept of acceptance in connection with information systems, a positive assumption of a fact or product is assumed. However, the exact definition depends on the respective objective and object of investigation. In the technical environment, an acceptance concept with an evaluative and a cona- tive dimension exists. A positive readiness for usage therefore does not necessarily lead to the actual use of the technology or the system. It is therefore advisable to start from an acceptance concept, which takes both the acceptance decision and the usage into account (Rengelshausen, 2000, p. 10). As part of scientific research, specific models have been developed to explain the phenomenon of acceptance. %e aim of the investigations was to understand, which factors lead to the acceptance of information systems in order to derive recommendations for action from them. In essence, a distinction can be made between determinant models and process models (Frenzel, 2003, p. 114). Determinant models reflect the more or less dominant influencing factors on acceptance. Different input quantities are used and interconnected, creating complex networks that explain the relationships between the determinants and the formation of acceptance (Kollmann, 1998, p. 73). Process models on the other hand place the main emphasis on the process steps of acceptance formation and focus on the degree of acceptance or rejection. %e process steps are considered over time. %e basis for most process models are the findings of adoption research. %e focus lies on the analysis of the individual takeover process. In the first step, a potential buyer experiences for the first time the existence of the innovation. %en he starts to be interested in the innovation and carries out an information search. A'er completion of the research, the knowledge gained is assessed. In the fourth step, he decides to test the innovation. A'er positive testing, he decides during the last step to purchase the innovation (Rogers, 2003, p. 170). %e acceptance models of the existing literature and the definition of business information systems show that the factors “person”, “task” and “technology” play an essential role in the acceptance of information systems. In an operational context, the aspects of “organization” and “management” are added as influencing factors (Laudon, Laudon, & Schoder, 2010, p. 18).

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User-related determinants %e personal experience with business information systems is an essential factor for attitude and acceptance. Motivations, expectations and opinions have a big impact, as nobody approaches new technical tools without specific pre-settings and pre-attitudes. Familiarity with the technology is therefore a significant factor for acceptance. Furthermore, behavioral psychological factors influence the acceptance of the system (Swoboda, 1996, p. 31). Expectations are related to the likelihood that a particular behavior will result in a particular outcome. %ey represent individual yardsticks and are a central measure in the acceptance process (Kollmann, 1998, p. 123). Needs are deficiency symptoms that can be divided into primary (innate) and secondary (learned) needs. %ey act as personal stimuli that put a person in a general action readiness (Staehle, 1999, pp. 165-166).

Task-related determinants %e task-related determinants deal with the question of whether the task can even be solved with the help of an operational information system. %is is understood as the actual usability of the technology in the respective sphere of inﬂuence. %e more diﬃcult the task is, the higher the demands on the system (Reichwald, 1978, p. 33). %e individual performance of the user and the associated acceptance of the system depend on the support during the task performance. Collaboration between multiple organizational units requires an integrated information system that can ensure cross-unit information sharing (Goodhue, 1995, pp. 1828-1833).

Technological determinants %e technology-related determinants represent the primary influencing factors for the formation of acceptance. %ey determine the properties and possible uses of information systems and influence their perception. Essential factors are the relative advantage, the compatibility, the complexity, the probability and the communicability (Rogers, 2003, pp. 229-230). %e relative advantage describes the degree to which an innovation for individual need satisfaction is perceived to be better compared to the technology used hitherto. Compatibility is the degree of perceived compatibility of technology with existing values, norms, experiences and needs. %e complexity indicates how difficult it is to perceive a technological innovation and which application difficulties it presents to the user. %e probabilistic refers to the possibility to test the innovation before the introduction. Communicability describes how easily the features of the new innovation can be communicated to future users. Apart from the complexity, there is a positive correlation between all determinants and the acceptance of an information system (Kollmann, 1998, p. 120).

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Organizational determinants Organizational determinants relate to the company, the application situation, the organizational environment, and the social environment within the organization in which the business information system is used. %ey represent the organizational framework and the basis for corporate acceptance and willingness to innovate. %e higher the willingness to innovate in a company, the faster the acceptance process will go through. %e willingness to innovate depends on the organizational culture and structure (Rogers, 2003, pp. 411-413). Organizational culture reflects the individual character of an organization expressed through values, norms and collective patterns of order. %e organizational culture is responsible for the fundamental attitude of an organization toward change (Schreyögg, 2008, p. 407). %e organizational structure can be understood as a formal system that controls cooperation, communication, responsibilities, regulations and processes within the organization. Due to the different degrees of flexibility, not every organizational culture is supportive for acceptance (Jones & Bouncken, 2008, p. 42).

Management-related determinants In light of increasingly complex enterprise tasks and processes, management is given a central role in the adoption of information systems. For the employees, the efficient task fulfillment and automation of business processes is in the foreground, while the management requires structured and processed information. Although executives are also users of the information system, management sets the general framework for the use of the system (Laudon, Laudon, & Schoder, 2010, p. 27). %e planning concerns the fundamental decision regarding the goals and the conditions of the technical application. %ese decisions usually mean a change in the structure and process flow of the company. Since these are complex issues, many organizations are establishing a buying center that deals with planning and deciding on the use of technology (Kollmann, 1998, p. 127). %e management has the task to organize the use of the technology for the task execution. %e obligation to use the system specifies to what extent an information system must be mandatory in the company. A commitment to use does not necessarily mean a negative acceptance of the system (Hartwick & Barki, 1994, pp. 440-443). Management can grant restrictions and freedoms on system usage, affecting user attitudes to the system (Hilbig, 1984, p. 322). %e users of the information system must be applied according to their qualifications. %e task of the management is to continuously control the personnel decisions and otherwise to redistribute the human resources (Picot & Reichwald, 1987, p. 170). %e management task includes the effective control of the tasks within the organization and the initiation of the work execution of the daily

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work activities (Steinmann & Schreyögg, 2005, pp. 11-12). Employee motivation is the main task of the management to ensure the acceptance of information systems. Managers serve as role models through their particular interest in innovations (Pi- cot & Reichwald, 1987, p. 164). %e control relates to the collection of information and the comparison of results with planning data. Due to the high complexity of business information systems, continuous control is important to enable eﬃcient management of the business. In addition, users can also be checked whether they are doing their job eﬃciently and in the interest of the company.

III. CASE STUDY

For the empirical part and the collection of the data, the qualitative approach of the problem-centered interview is chosen. %rough the openness and flexibility of this method, the discovery of unknown facts is made possible, higher information content is generated and the viewpoint of the interviewees is centered. %e objective of the empirical study is the identification of necessary criteria for the acceptance and furthermore the success of CRM-systems by its users to contribute to the overall goal of an increased profitability and evolution of companies in the packaging industry. Previous methodological approaches show a clear tendency towards quantitative methods. Quantitative surveys can be used to determine the distribution of the individual acceptance factors. However, this research methodology runs the risk of disregarding or not recognizing CRM-specific factors. Because of this problem and taking into account the exploratory nature of the research question, a qualitative research seems more appropriate (Quiring, 2005, pp. 2-3).

A. Survey methodology

%e data collection will be conducted by guided and problem-centered interviews, which have the advantage that the problem statement can be defined by the interviewer himself. %e basis for the preparation of the interview guides and the related questions are the information and current knowledge base from the literature on this subject. %e interview guides consist of a short introduction (including an icebreaker to start the discussion) and a main part. %e introduction serves to briefly outline the meaningfulness and usefulness of the survey. When conducting the interviews, it has been tried to ask open questions where possible and appropriate in order to gain as much information as possible from the interviewees and not lead them in a specific direction (Mayring, 2016, pp. 67-68).

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%e problem-centered interview selects a linguistic approach to determine the position on the basis of subjective meanings. It’s tried to establish a situation of trust between the individual parties. Although the interview partners are di- rected by the guidelines through certain questions, they react openly and without any speciﬁc answer possibilities. %is approach has the advantages of being able to check the general understanding of the interviewees, as well as the disclosure of subjective opinions and the discussion of concrete terms of the interview situation (Mayring, 2016, pp. 68-69). %e areas of application for the problem-centered interview are mainly within theory-based research, since it integrates the aspects of the primary problem analysis into the interview. It is particularly suitable, if in principle a lot is already known about the research ﬁeld. %e standardization through the interview guide facilitates the comparability of the conducted interviews and thus also the subsequent evaluation (Mayring, 2016, pp. 70-71).

B. Evaluation method

%e evaluation method is based on the structured approach of the qualitative content analysis according to Mayring. For the structuring of the conducted interviews and the respective results, specific categories for the acceptance of CRM- systems must be identified and defined in advance, before the respective record- ings of the interviews will be transcribed. In a further step all utterances, which do not change the content, are removed, since the main interest is aimed only at the content-based information (Mayring 2016, pp. 115-116). %e categories are “person”, “task”, “technology”, “organization” and “management” (Laudon, Laudon, & Schoder, 2010, p. 18). %e aim of the structured content analysis is to reduce the material to its essential contents and to create a manageable basic form. Written statements will be structured according the previously defined categories in order to subsequently draw conclusions for answering the research question. A'erwards the results will be discussed and put into context with the relevant literature (Mayring, 2016, pp. 115-116).

C. Execution

Constantia Flexibles is the world’s fourth largest manufacturer of ﬂexible packaging solutions in the pharmaceutical and food division. Headquartered in Vienna, more than 3,000 employees are working in 40 plants in 18 countries worldwide (http://www.cﬂex.com/de/ueber-uns/, April 30th 2018).

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In order to gain access to the field and the widest possible knowledge spectrum, eight sales representatives of different sales regions as well as various sales hi- erarchy levels of Constantia Flexibles (Regional Sales Manager, Key Account Man- ager, Account Manager) and three external CRM-experts of IT-providers on the market have been interviewed in the empirical setting. %e selection criterion of the sales representatives was a direct relation to CRM-systems or CRM-approaches in their day-to-day work, as well as to determine the needs for a respective acceptance of a CRM-system. %e interviews with external experts are the objective counterpart and provide additional expert knowledge and objectivity. A total of eleven interviews have been conducted. Since qualitative research focuses less on the determination of frequencies than the formation of categories and typologies, representativeness is not a decisive selection criterion. Much more important is the choice of theoretical questions. %e aim of this case study is to obtain the broadest possible picture of the field of investigation (Lamnek, 2005, p. 193). %e general readiness for the interview and the subsequent evaluation of the obtained information was clarified via preliminary information by e-mail or telephone. A'erwards, an appointment for an online-interview was arranged at larger local distances, or an appointment for a personal discussion has been made. A readiness for the audio recording of the conversations has also been requested in advance. In the course of a test run of the interview at two selected interview partners, the general suitability of the interview guide has been checked. Since no problems and difficulties could have been observed, the prepared guides have not been further modified. In preparation for the problem-centered interviews, two interview guides (internal and external) were prepared. %e interview guides serve as a guidance and outline the framework in which the interview should be conducted. %ey serve as quality assurance and support for the interviewer during the data collection. Free- dom of choice over how and when a question is asked belongs to the interviewer. %e use of interview guides increases the comparability of individual interviews, since similar topics are queried in each conversation. %e concept of the interview guidelines is based on the theoretical understanding of the object of investigation. %e basis for the preparation of the guidelines is key questions that represent the connection between theoretical considerations and the qualitative survey method (Gläser & Laudel, 2009, p. 90).

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TABLE 1.: MAIN QUESTIONS OF THE INTERVIEW GUIDELINES

Internal To what extent does a CRM-system support you in your current area of responsibility? What experiences have you had in your previous professional career with technical aspects of CRM- systems? What experiences did you have with the organizational framework of CRM-systems? To what extent have you been able to gain experience with management decisions regarding a CRM- system? What personal opinion and attitude do you have about CRM-systems? External What experiences have you had in your previous professional career with technical aspects of CRM- systems? To what extent and how can a CRM-system support your work life? What experiences did you have with the organizational framework of CRM-systems? What experiences have you made so far with management decisions for the introduction or usage of a CRM-system? What personal opinion and attitude do you have about CRM-systems?

Source: Author’s table

D. Results

Out of the results of the qualitative evaluation, a profile of requirements and furthermore an overview of acceptance criteria for CRM-systems in the packaging industry is generated. %e starting point for the presentation of the results is an overview about previously carried out research on the qualitative identification of design features of a CRM-system, which can contribute to an increase in sales. %e sources of the statements made are the conducted interviews. Figure 3 shows the overall analysis of the five main categories from previously conducted research. For the empirical part and the collection of the data of the previously conducted research, the qualitative approach of the problem-centered interview was chosen. %e data collection was conducted by guided and problem- centered interviews. %e basis for the preparation of the interview guide and the related questions were the information and current knowledge base from the literature on this subject. %e evaluation method was based on the summary approach of the qualitative content analysis according to Mayring. A comprehensive content analysis was used for the data evaluation. As a result of the summarized content analysis, 190 exploitable statements from the interviews, which were assigned to these categories, could have been obtained. %e main category ‘requirements’ describes the prerequisites for the successful introduction of a CRM-system with the goal that this system is appropriately used and maintained. %e category ‘benefits’ refers to the expected advantages from the usage of a CRM-system. %e actual research question of this work is covered by the category ‘profit’. %e main

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category ‘problem’ contains possible or expected problems when working with CRM-systems or CRM-approaches and the category ‘efficiency’ refers to the prerequisites for efficient work. When presenting the results, it must be taken into account that sub categories can appear in several main categories. %e respective sub category is therefore always to be viewed and understood in relation to the concrete main category, since one and the same sub category can have an effect on different aspects. An example here is the time saving that can result from working with CRM-systems. According to the interviewees, this can have an impact on the profit, but is also considered as a basic prerequisite for a CRM-system, an increase in efficiency and thus a concrete benefit. %e identified main category “requirements” is highly belonging to the acceptance criteria of CRM-systems. As a further consequence it has been decided to conduct a subsequent detailed analysis of this category, which is subject of this paper. It provides additional in-depth knowledge and insights with regards to acceptance criteria for CRM-systems and furthermore its success to contribute to the overall goal of an increased profitability and evolution of companies in the packaging industry. FIGURE 3.: MAIN CATEGORIES OF PREVIOUS RESEARCH

Source: Author’s ﬁgure %e appropriate involvements of the users, as well as a simple handling of the system have been identiﬁed as the most common nominations. %e CRM-system must bring added value to all users and integrate them fully in advance in order to

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take account of their needs and desires. In this context, it is important to know who the decision-makers are in implementing a CRM-system in order to be able to incorporate all needs. It has to be communicated, why a CRM-system is introduced and what exactly the concrete beneﬁt of this system is. FIGURE 4.: ANALYSIS OF MAIN CATEGORY “REQUIREMENTS”

Source: Author’s figure %e system must be easy to use and to maintain, so the chance of an ongoing update is correspondingly large. A living system must be continuously updated. %is must not involve too many efforts, since no one will work with the system. A CRM-system must provide useful information and not just consist of entering data. It should also not only be an instrument for the management level. %e import of data into the system must be done in a reasonable framework and not every small change should be updated immediately. %e following section presents the results of the empirical study of this paper. %e results are presented both quantitatively and qualitatively according to the main influencing factors and subcategories. A total of 283 text passages have been identified in the individual interviews, which refer to the already mentioned five determinants as influencing factors of acceptance of CRM-systems in the packaging industry. Figure 5 shows the distribution of the main influencing factors for the acceptance of CRM-systems. A certain similar distribution of the determinants of “person”, “technology” and “management” can be recognized. Task-related and or-

136 Ing. Martin A. Moser, MA MSc QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM... (117 - 144)

ganizational factors account for the least amount. %is means that the acceptance of CRM-systems in the packaging industry largely depends on person-related, technology-related and management-related factors. FIGURE 5.: ANALYSIS OF MAIN DETERMINANTS

Source: Author’s ﬁgure

In a further step it has been examined into which subcategories the result of the distribution of the main determinants can be classiﬁed. %e selection of subcategories was based on the subcategories of the determinants of acceptance of CRM-systems described in the theoretical part of this paper.

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FIGURE 6.: ANALYSIS OF SUBCATEGORIES

Source: Author’s ﬁgure

Figure 6 is indicating that the system’s supportability has the biggest impact on acceptance with a level of 16%. During the interviews, the “added value” has been o'en mentioned in this relation. Only the recognition of the meaningfulness of a system and the provision of an added value for the daily work can lead to acceptance by the respective users. %e employees must be convinced that the CRM-system is important in terms of their daily work and their success as sales representatives. Since some people might be not open-minded enough with regards to changes, they must be convinced that the respective change brings added value to them. %en acceptance can take place. User-friendliness plays a decisive role. If this is not the case, the system’s utilization rate will be correspondingly low. %e analysis also showed that an organizational culture (12%) that supports and is open to innovative technologies is important. %e willingness to innovate should therefore be correspondingly high and knowledge must be shared. %e data input must be simple and accessible from anywhere. %e system must not be used as a control function and should provide an actual beneﬁt. %ere must be training during the implementation and installation of a CRM-system. Further- more, regular training on a CRM-system is important, as the system is dependent on the quality of the data and the better the employees are trained, the better the input and quality of the data. %e advantages of such a system need to be illustrated by clear and understandable examples.

138 Ing. Martin A. Moser, MA MSc QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM... (117 - 144)

%e importance of the CRM-system must be clarified throughout the organization starting from the management level (subcategories “planning” and “leadership”). %ere must be a willingness of the organization to work with the system in the future. All users should be informed about the meaningfulness and importance for the company. Starting from an expectation, the necessary decisions have to be taken. %e use of a CRM-system may not exceed a certain amount of work, since otherwise it loses its benefit. It must ensure that employees have enough time for other work. Such a system is intended to simplify work for users. CRM-approaches from the past have failed due to lack of acceptance and too high complexity. Sys- tems are regarded as control instruments, which are associated with additional work. As part of the generalization of the text passages and evaluation of the conducted interviews, the following five criteria for the acceptance of CRM-systems in the packaging industry could have been identified. • Added-value • Usability • Create awareness • Planning and implementation • Management, commitment and involvement For the acceptance of a CRM-system, the added value is crucial. %e user must realize that the system is more than just a management control tool. %ey need to feel that the use of the system gives them additional value. %e usability as a technology-related determinant of the acceptance of CRM- systems describes that CRM-systems must be easy, fast and mobile with regards to their usage. %e system must support the user in everyday life and should be logical and intuitive, as complex systems lead to rejection and demotivation. %e awareness that the CRM-system is important to the company is part of the organizational culture. %e system must therefore be transparent and not giving the user the feeling of being replaceable. CRM has to be understood as part of the corporate strategy. As part of the planning and implementing of a CRM-system, management must make fundamental decisions about goals, usage, and expectations. Employ- ees must be involved in the process right from the start. %e decision for a CRM-system is made by the top management. %e management must therefore stand behind the project and support it. Employees who are not convinced by the system must be motivated accordingly by them. In the course of the empirical investigation it could be determined that certain influencing factors are responsible for the acceptance of CRM-systems. %e quali-

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tative evaluation of the interviews led to the development of a collection of criteria to promote the acceptance of CRM-systems in the packaging industry. %ese categories must be taken into account so that the system can be accepted by the employees or users.

IV. CONCLUSION

CRM includes both a management and technology component (Laudon, Laudon, & Schoder, 2010, pp. 533-534). %e latter are CRM-systems, which can be used to support a CRM-strategy. With the help of a CRM-system, customer-specific data can be stored, maintained, evaluated, and made accessible to the entire organization at all times (Neumann 2014, pp. 115-116). %e fact that the basic introduction of a CRM-system is only to take place a'er the creation of all necessary personnel requirements and necessities, since the system is otherwise at risk of not being accepted by the employees (Georgi & Mink, 2011, p. 84) can be confirmed on the basis of the statements of the interviewed persons. %e success of a CRM-system depends on the creation of the organizational prerequisites. Georgi and Mink (2011) describe that a CRM- strategy and a CRM-system must be actively supported and demonstrated by the management board of a company in order to gain acceptance and recognition of the project by the employees. In addition, the existing customer knowledge should be shared willingly (Georgi & Mink, 2011, p. 83). %e analysis of the interviews has confirmed that the importance of using the CRM-system needs to be mentioned throughout the whole organization from the management board. %ere must be a concrete will of the organization to ensure that the system is accepted and used. Georgi and Mink (2011) also mention the prerequisites for a successful implementation of the customer relationship strategy to reduce resistances and to appropriately qualify and motivate the employees within the scope of training measures (Georgi & Mink, 2011, p. 83). %e corresponding integration of the users and a simple operation are necessary prerequisites during the introduction of a CRM- system, as well as regular training courses. Users fear a complex maintenance of CRM-systems and the association of such a system with control instruments as well as losing their knowledge. For a positive impact of CRM-systems on the profit of companies in the packaging industry, a large number of necessary requirements must be met. One of them is the acceptance of its users. As part of the qualitative evaluation of the interviews, five criteria influencing the acceptance of CRM-systems could have been

140 Ing. Martin A. Moser, MA MSc QUALITATIVE IDENTIFICATION OF ACCEPTANCE CRITERIA FOR CRM... (117 - 144)

identiﬁed (“added-value”, “usability”, “create awareness”, “planning and implementation”, and “management, commitment and involvement”). %e derived criteria were assigned in accordance with the determinants of acceptance deﬁned in the theoretical part (person, task, technology, organization, and management). %e catalog of criteria derived from the empirical study contains the items that must be met for employees to accept a CRM-system. To answer the research question, the catalog of criteria will be used.

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REFERENCES

H. Abdi & P. Kotler (1999). Marketing in the network economy. Journal of Marketing, Special Issue, 146-163. M. L. Agrawal (2003). Customer Relationship Management (CRM) & corporate renaissance. Journal of Services Research, 3, 149-171. J. Betz. Die Akzeptanz des E-Commerce in der Automobilwirtscha&: Ausmaß, Konsequenzen und Determinanten aus Sicht von Neuwagenkäufern. Wiesbaden: Deutscher Universitätsverlag, 2003. T. Bohling, D. Bowman, S. LaValle, V. Mittal, D. Narayandas, G. Ramani, & R. Varadarajan (2006). CRM Implementation Effectiveness - Issues and Insights. Journal of Service Research, 9(2), pp. 184- 194. T. Frenzel. Akzeptanz von Systemen der digitalen Distribution im E-Commerce der Musikwirtscha&. Berlin: Logos Verlag, 2003. D. Georgi & M. Mink. Konzeption von Kundenbeziehungsstrategien. Wiesbaden: Gabler, 2011. J. Gläser & G. Laudel. Experteninterviews und qualitative Inhaltsanalyse als Instrument rekonstruierender Untersuchungen (3. Auflage). Wiesbaden: VS Verlag für Sozialwissenscha'en, 2009. D. L. Goodhue (1995). Understanding User Evaluations of Information Systems. Management Science, Vol. 41, No. 12, pp. 1827-1844. J. Hartwick & H. Barki (1994). Explaining the role of user participation in information system use. Management Science, Vol. 40, No. 4, pp. 440-465. S. Helmke, M. Uebel & W. Dangelmaier. Effektives Customer Relationship Management: Instrumente, Einführungskonzepte, Organisation. Wiesbaden: Gabler, 2013. W. Hilbig (1984). Akzeptanzforschung neuer Bürotechnologien: Ergebnisse einer empirischen Fallstudie. Office Management, Nr. 4, pp. 320-323. H. Hippner & K. D. Wilde. IT-Systeme im CRM: Au(au und Potentiale. Wiesbaden: Springer, 2004. G. R. Jones & R. B. Bouncken. Organisation: $eorie, Design und Wandel (5. Auflage). München: Pearson Studium Verlag, 2008. T. Kollmann. Akzeptanz innovativer Nutzungsgüter und -Systeme. Konsequenzen für die Einführung von Telekommunikations- und Multimediasystemen. Wiesbaden: Gabler, 1998. K. Kornmeier. Determinanten der Endkundenakzeptanz mobiler kommunikations-basierter Zahlungssysteme. Duisburg/Essen: Mercator School of Management, 2009. E. C. S. Ku (2010). %e impact of customer relationship management through implementation of information systems. Total Quality Management and Business Excellence, 21(11), pp. 1085-1102. V. Ku m a r & W. R e i n a r t z . Customer Relationship Management - Concept, Strategy, and Tools (2nd edition). Heidelberg, New York: Springer Publishing, 2012. J. Laiderman (2005). A structured approach to B2B segmentation. Database Marketing and Customer Strategy Management, 13(1), pp. 64-75. D. M. Lambert (2009). Customer relationship management as a business process. Journal of Business & Industrial Marketing, Vol. 25, Issue: 1, pp. 4-17. S. Lamnek. Qualitative Sozialforschung (4. Auflage). Weinheim/Basel: Beltz Verlag, 2005.

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K. Laudon, J. Laudon, & D. Schoder. Wirtscha&sinformatik: Eine Einführung. München: Pearson Studium, 2010. W. Leusser, H. Hippner, & K. D. Wilde. Kundeninformationen als Basis des CRM. Wiesbaden: Gabler, 2011. U. Manz. Zur Einordnung der Akzeptanzforschung in das Programm der sozialwissenscha&lichen Begleitforschung. München: V. Florenz, 1983. P. May r i n g . Einführung in die qualitative Sozialforschung: Eine Anleitung zu qualitativem Denken. Weinheim: Beltz, 2016. H. Meffert, A. Pohlkamp and F. Boeckermann. Wettbewerbsperspektiven des Kundenbeziehungsmanagements im Spannungsfeld wissenscha&licher Erkenntnisse und praktischer Exzellenz. Wiesbaden: Gabler, 2010. D. Narayandas & V. K. Rangen (2004). Building and sustaining buyer-seller relationships in mature industrial markets. Journal of Marketing, 68, pp. 63-77. A. K. Neumann. CRM mit Mitarbeitern erfolgreich umsetzen: Aufgaben, Kompetenzen und Maßnahmen der Unternehmen. Wiesbaden: Springer, 2014. A. Parvatiyar & J. N. Sheth (2001). Customer Relationship Management: Emerging Practice, Process, and Discipline. Journal of Economic and Social Research, Vol. 3(2). A. Picot & R. Reichwald. Bürokommunikation: Leitsätze für den Anwender. München: CW- Publikationen Verlag, 1987. O. Quiring (30.04.2018). Methodische Aspekte der Akzeptanzforschung bei interaktiven Medientechnologien. Retrieved from https://epub.ub.uni-muenchen.de/. A. K. Rai. Customer Relationship Management - Concepts and Cases (2nd edition). Delhi: PHI Learning Private Limited, 2013. R. Reichwald. Zur Notwendigkeit der Akzeptanzforschung bei der Entwicklung neuer Systeme der Bürotechnik (Band 1). München: Arbeitsbericht der Hochschule der Bundeswehr, 1978. O. Rengelshausen. Online-Marketing in deutschen Unternehmen: Einsatz-Akzeptanz-Wirkungen. Wiesbaden: Deutscher Universitätsverlag, 2000. D. K. Rigby & D. Ledingham (2004). CRM done right. Harvard Business Review, 82, pp. 118-129. E. M. Rogers. Diffusion of Innovations (5th edition). New York: Free Press, 2003. G. Schreyögg. Organisation: Grundlagen moderner Organisationsgestaltung (5. Auflage). Wiesbaden: Gabler Verlag, 2008. M. A. Shafia, M. M. Mazdeh, M. Vahedi, & M. Pournader (2011). Applying fuzzy balanced scorecard for evaluating the CRM performance. Industrial Management & Data Systems, (111:7), pp. 1105-1135. S. C. S. Shang & Y. Ko (2006). Understanding the Technology and Organizational Elements of Customer Relationship Management Systems. Proceedings of the twel&h Americas Conference on Information Systems, Acapulco, Mexico. W. H . St a e h l e . Management: Eine verhaltenswissenscha&liche Perspektive (8. Auflage). München: Vahlen Verlag, 1999. A. D. Stein, M. F. Smith, & R. A. Lancioni (2013). %e development and diffusion of customer

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relationship management (CRM) intelligence in business-to-business environments. Industrial Marketing Management. H. Steinmann & G. Schreyögg. Management: Grundlagen der Unternehmens-führung (6. Auflage). Wiesbaden: Gabler Verlag, 2005. G. Stokburger & M. Pufahl. Kosten senken mit CRM: Strategien, Methoden und Kennzahlen. Wiesbaden: Gabler, 2002. R. Swi'. Accelerating Customer Relationship Using CRM and Relationship Technologies. New York: Prentice Hall Inc., 2001. B. Swoboda (1996). Akzeptanzmessung bei modernen Informations- und Kommunikationstechnologien. $exis, Nr. 3, St. Gallen, pp. 1-82. V. Tr o m m s d o r ff . Konsumentenverhalten (6. Auflage). Stuttgart: Kohlhammer Verlag, 2004. TechBiz (08.03.2018). Customer Relationship Management (CRM) System. Retrieved from http://www. techbiz.com.kw/index.php/so'ware-solutions/c/cus-tomer-relationship-management-crm-system. D. Zahay (2012). Building the foundation for customer data quality in CRM-systems for financial services firms. Journal of Database Marketing & Customer Strategy Management, 19(1), pp. 5-16.

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Anton Aufner TRANSFORMATIONOF V E T IN L ESS D EVELOPED R EGIONS - C HALLENGESAND O PPORTUNITIES (145 - 166)

ARTICLE INFO Received: 22.9.2018. Accepted: 15.3.2019. JEL Classiﬁcation: I21, I22, I28, J24, F15

Keywords: knowledge-transfer; training; transformation; vocational education

TRANSFORMATION OF VET IN LESS DEVELOPED REGIONS ! CHALLENGES AND OPPORTUNITIES

Anton Aufner 1719001133@!-burgenland.at

145 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

In a global world and its continued search for new markets, knowledge and know- how transfer become more and more important.

Vocational educational training is a key factor in the economic and social development of a country. Demographic change, prevention of brain-drain, technological innovation (industry 4.0), climate change, foreign investment of companies and therefore also the growth of local economies depends on the framework conditions and the supply of a skilled workforce. Companies operating globally expect the same qualiﬁca- tion standards from their foreign partners as they have at home.

$e major locus of world population growth lies in the developing countries, where more than three fourths of humankind dwell and where the unemployment rate is constantly increasing, especially amongst the younger generation. $e transfer of VET to less developed regions poses the main question of whether “the transfer of knowledge can be a win/win situation for the target region and for the exporting country and/or its enterprises?” Beside analysing the challenges and opportunities arising through know-how transfer, the author further investigates how this process of knowledge-transfer can be measured for its eﬃciency.

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I. INTRODUCTION

%e development and importance of the world economy is focused on economic growth. Economic growth is derived from innovation and technology transfer as part of the trade and competitiveness of a country. %is all is based on education, especially on vocational educational training (VET) as a key factor in the economic and social development of a country. %e growth of global and local economies depends on the framework conditions and the supply of a skilled workforce, which is or should be the backbone of every economy. %ese parameters converge around the question “can companies which are operating globally, expect the same qualification standards - worldwide - as at home?”. My work contributes a deeper and scientifically based knowledge of the VET topic - where I try to bridge between developed and less developed regions - and to the importance of implementing a successfully VET transformation program. Demographic change, technological innovation, such as industry 4.0 as well as climate change are demand-oriented challenges of globalization of markets, making them drivers of change in local and in world policies and therefore also in the world economy. %e world economy, which is part of world policy, is based on people with entrepreneurial thinking, innovation, international trade and a well-trained and equipped workforce. Stutz and Waf (2012, 75) describe people as both the producers as well as the consumers of goods and services, making human beings the most important element in the world economy. All this, especially a well-trained workforce but also entrepreneurial thinking and understanding combined with drivers to intensify innovation, is the output of a policy that provides all requirements of a global, target-oriented and effectual education. “Global trends, affecting all regions, set the context for education and training today and in the future” (International Labour Office 2010, 7). Education in this sense refers to basic school education, higher and/or further education in the field of training, skills development and vocational education. A future-oriented world economy therefore needs framework conditions, which are based on legal guidelines and rules, which focus not only on management but also on the skilled work force. So, it is necessary to match the needs of enterprises, investors and labour markets, enable the staff to adjust to changes in technology and markets and therefore to prepare human resources customized to the needs of the future.

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“%e globalization of markets is accelerating the diffusion of technology and the pace of innovation. New occupations are emerging and replacing others. With- in each occupation, required skills and competencies are evolving, while at the same time the knowledge content of production processes and services is rising” (International Labour Office 2010, 1). %e need of vocational qualification is rising even more, especially in a globalizing and knowledge-based world. It’s the basis for the development of every economy and a precondition in international markets and their competitiveness. Skills can trigger innovation and growth, move production up the value chain, stimulate a concentration on higher level skills and shape the future labour market (European Commission, 2012). Under the pressure of a rising lack of a highly qualified workforce, the search for investors in countries with low industry but also high youth unemployment rates, low GDP, but with the potential to become a future emerging region, countries start to think about implementing a dual system as part of a VET system. A VET system has a high proportion of work-based learning in professional education and is ideal in structurally weak areas or regions with the potential to become future dynamic regions. %e time, when competition came especially from countries with low skilled work has come to an end (European Commission, 2012). All this sounds very clear and simple - yet, what are the real preconditions and current situation? On one hand countries have to fulfil the requirements of possible future investors, while on the other hand they have to build up an education and training environment that should be based near the legal framework on a high part of practical and possible rapid transformation. %erefore, it is unavoidable to finance investments in training facilities, work-labs which cover the newest technology and a well-trained staff of teachers with practical private sector experience in their field. %is results in a kind of vicious circle with the question of where to start and what can be the way for a successful implementation. %e importance of knowledge export and transformation is increasing and becoming a fast-growing market. %e main focus in this sector always was and is the field of tertiary - meaning academic - education. %e great gap starts one level below - when lacking a highly qualified workforce, which is the backbone of every economy. %e field of VET therefore gains a new perspective, which makes it necessary to know what VET in the sense of this paper is and in which relation is it used and understood.

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II. LITERATURE REVIEW

1. Deﬁnition of VET

A lot of countries, even in Europe, have different approaches and definitions. From the point of scientific research, it is essential, to have the same understanding and the same meaning of the term. National and international understand- ings, translations of terms, comparisons and statistic data depend on the common understanding of the idea of VET. For example, “%e key terms used for VET in Europe, for instance, vocational (in English), professional (in many Romance languages), or “beruflich” (in German, which stands more for occupational) all have their specific connotations, which do not reliably survive in one-to-one translations. What looks like tiny shi's in meaning can have major consequences in national conceptions of VET and VET systems” (Cedefop 64 2017, 13). “For instance, Cedefop translates VET into Berufsbildung […] in German, which are also the most common terms used in Austria […] and thus the best match one can get. However, ministries of education in Austria translate Berufs- bildung on their official English websites as vocational education - accidentally or intentionally - omitting the extension ‘and training’. %is could either be dismissed as quibbling or bad translation, or it could be interpreted as an indication that the Austrian concepts of VET […] underline more clearly the educational aspects of VET.” (Cedefop 64 2017, 11). Vocational education and training takes many forms; it is the most heterogeneous of the main education and training sectors in Europe today. Unlike the typical general education, which does not aim to prepare people for a particular occupation or occupational group, VET has this task. Cedefop (European Center of Development of Vocational Training) defines VET as, ”[…] education and training which aims to equip people with knowledge, know-how, skills and/or competences required in particular occupations or more broadly in the labour market” (Cedefop 2014a, 292). If countries try to compare their models, they have to find a common definition, because of different laws of implementation, e.g. whether it is part of the educational system of a country, whether it is public or if it is the way statistical departments analyze the data etc. %erefore, to understand the role of vocational education and training it requires a clear definition of what is meant by VET. Cedefop had tried to find the definition, which is more or less a starting point (Cedefop 63 2017, 7). Many further authors as for example S. Billett or G. Moodie create definitions of VET under different views and dimensions but all come to the following conclu-

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sions that “it is the least homogeneous part of the key educational fields” (Billett 2011, 3) and “the development and application of knowledge and skills for middle level occupations needed by society from time to time” (Moodie 2008, 42). %is definition especially in the latter context - the development and application of knowledge and skills for middle level occupations - is a very realistic one. I would not only focus the definition on the needs of the society but would prefer the term ‘labour market’. From the view of enterprises, it makes no sense to offer professional or vocational education and training without established needs. %e only argument can be that institutions - private and public- have a forecast with a knowledge about future needs. In my essay, I focus the definition on the socioeconomic and labour market perspective. %is is what makes VET so important for companies. VET has to fulfil criteria as • rapid development of trainings regarding new professions, • a permanent observation of the labour market, • high flexibility in offering new professions and curricula, • close contact to the industry. A definition of VET related to the industry could be ‘to bring theory to practice’ meaning that the transfer and acquisition of knowledge and skills is based on a theoretical and practically oriented approach. Legal rules and guidelines are necessary, but not vital for the definition. Know-how transfer is carried out by the learner’s transformation from the theoretical school/work-based learning to the real work situation competency. In general, VET in this case is understood as an additional offer to adults and young people, who have finished their basic school education. It is the possibility for the individual and companies to strengthen the knowledge and know-how of their staff and to provide them with brand new technologies and working methods. %e combination learning - not only for young students - in school and at work has developed over years into the so-called dual principle, which is currently being discussed under the concept of crossing boundaries (Cedefop 63 2017, 17). Exclusively work-based formal VET programs are rare today, but for continuing vocational learning in informal contexts (such as learning in in-company training centres) work-based learning is still the dominant form. “%ese ‘educa- tionalized’ forms of traditional VET need to be distinguished from ‘vocationalized’ forms of schooling. %e latter also form part of VET but are rooted in the traditional classroom setting while also integrating work-based elements” (Cedefop 63 2017, 17).

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We can conclude that literature mostly deﬁnes VET in the classical deﬁnition (dual system and upper secondary school). %e approach in this paper also includes development training and training to upgrade skills in the sense of lifelong learning.

2. Current socio-economic situation and framework condition

In the current political discourse, politicians and company leaders very o'en refer to the lack of a qualified workforce in their discussions. Looking back at the last decades, we know that the importance of qualified staff in the non-academic sectors has decreased. It was a self-conception by the population that, anyone of the young generation who has the chance to become an academic, has the opportunity to step up into a ‘better life’. Also, the industry - with their permanent replacement of workforce, the increasing investment and search for automatization - had not observed the upcom- ing lack and gap of a qualified workforce. %e development of automatization, industry 4.0 and digitalization expects a workforce that is no more comparable with the former generation, nor their skills and their requirements on the job. What was further disregarded in the forecast in great parts of the European economy was the demographic development. Today the role of highly skilled workers has changed. %e demands in skills are increasing, additional social skills and flexibility, as well as analytical and entrepreneurial thinking are asked for. VET is not only addressed to the young generation and people with basic skills. %e demographic trends and the changing requirements in the working process demand new ways of thinking and an open mind regarding cra's professions and of the future workforce target group. %e demand for such proficient workers is verified by the fact that workers with high-level qualifications also earn higher wages. %e following graph, which compares relative earnings of 25- to 64-year- olds with their income from employment, is based on an OECD analysis and displays a country comparison of the influence qualification has on wages. It shows very clearly, that workers with high-level (tertiary) qualifications, i.e. the most attractive to employers in a dynamic world, are earning higher wages, not only in Europe but also in most developed countries.

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(upper secondary education=100)

1: Workers with high-level qualiﬁcations earn higher wages; Source: $e economics of knowledge: Why education is key for Europe’s success (Schleicher 2006, 3)

To compare skills, a national but also a European framework was developed. It is the unique chance for people with formal school, but also certified informal knowledge to compare and classify their skills in the qualification frame. Bach- elor’s degrees from universities are suddenly on the same level as ‘master of profession’ degrees. %is is a great opportunity for VET in Europe to take over the role of supplier of a qualified and high skilled workforce. More and more countries and companies all over the world see the great advantage of comparing skills and the benefits of strengthening the education of their workforce, yet it was a long way in understanding the necessity to picture and map educational levels in a framework.

3. Research Field and Research Question

%e importance of this research, as explained in the introduction, is that the growth of local economies is dependent on framework conditions and the supply of a skilled workforce, which is or should be the backbone of every economy. A German study, cited by the WIFI Institute, concluded that 40% of a company’s success depends on its workforce’s qualifications. Changing geographic hotspots and the changing fields of trade have major and permanent consequences for skills requirements. For example, the change from more labour-intensive manufactures to higher value-added manufacturing requires a completely different set of skills and understanding of working process-

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es. It can and is a permanent process and also needs the understanding and the willingness of the staff involved. %is change is not only a single occurrence, it is a permanent challenge in the globalizing of markets and is not reduced to a single country, region or enterprise. It is accompanied by the international movement of labour where figures are increasing permanently. %e below graph (Cedefop 2018, Vol 3) documents the migration of workforce within Europe to the strongly developed economies, which offer higher labour market opportunities, mostly with higher wages.

2: Percentage of population born in another country; SOURCE: (Cedefop 67 2018). $e changing nature and role of vocational education and training in Europe, based on ﬁgures by Eurostat.

%e major locus of world population growth lies in the developing countries, where more than three fourths of humankind dwell. %is calls for special policy strategies on how to integrate these people in the labour market and how to match their skills with those skills required by the industry and the economy. On the other hand, there are the questions on how the brain drain can be prevented from especially the least developed countries and how the local economy can be stabi- lized there in particular. Otherwise the given factors would lead to a negative spiral - such poorly developed countries are not a place of interest for foreign investment and innovation, and as a consequence, the rate of unemployed people increases, causing people to leave their country. In turn, this leads to local companies not being able to hire high qualiﬁed workers, which would be needed and be the basis to bring the country up to a higher standard. %e main problem is that partly local populations are increasing at a higher rate than the economy, not to mention corresponding jobs. On the one hand people have no education, no job and therefore little chance on the labour market. %is

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is paired with a lack of vision and future, which is consequently also part of today’s migration wave. It goes without saying that these issues can bring about social conflicts as a consequence (Stutz and Waf 2012, 102). In their training strategy, published by the International Labour Office in 2010, the G 20 leaders too see skills development as a pathway out of poverty and towards to more productive economies. %e topic of transferring VET to less developed regions therefore poses the main research question, “Can the transfer of knowledge be a win/win situation for the target region and for the exporting country and/or enterprises?“. Beside reviewing the challenges and opportunities of knowledge transfer, further sub-questions analysed by the author are “What impacts can the transfer of knowledge have across countries?” and, “How can the process of knowledge-transfer be measured for its effectivity and influence on a region?” %ese questions can however only be touched on in this paper and will thus be presented in a short example. What is already researched and indisputable, is that human capital is the driver of economic growth, that it is based on the four pillars of macro economy (employment, export/import, price stability, GDP) and that it has to be strengthened (Skare 2018). In this conference paper, which is work in progress for a PhD %esis and also a preliminary literature review to test the thesis, the focus and the prime goal is to first give a general overview of the importance of vocational training and an insight into the wide range of VET. It further presents a short overview of the different models of VET and the possible key elements required to measure the effectiveness of the knowledge-transfer process in terms of the labour market. A ex ante study of a sample in form of a case study was done, to check if the research has a chance to deliver necessary and realistic information.

4. Inﬂuences and framework conditions

It is important to point out that one main requirement of economic growth is employment, and this depends on the education and its level, as part of ‘human capital’. %e VET system becomes more and more influenced by several unpredictable external factors, which have different implications for the system and on the labour market. %e growing unemployment rate, migration, technical change, etc. has intensified the competition for jobs, not only in Europe, but all over the world. VET systems and institutions are challenged more than ever. %e mismatch between key sectors such as IT, CNC and construction are increasing and more and more complex. For example, people are over or underqualified for available

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jobs or the type of skills needed, or the skills levels are not suited to the jobs available. %e reasons for this could be diverse: Skills can lose their relevance, or the level of competence does not fulfil the required criteria. Most countries worldwide are facing the same set of external influences and pressures on their VET system. According to the analysis of Cedefop (research paper 67 2018, 14) the following elements may be affecting VET systems: • demographic change (ageing, migrant flows, declining youth cohorts); • globalization/offshoring; • technical change/digitization/robotics; • organizational change within workplaces and sectors (including sectoral restructuring) that affects the structure of work; • the outflow from other policy areas (such as systems of social protection that use VET as part of their efforts to combat social exclusion, macroeconomic policy) which affect the demands made of VET systems. In addition to the afore mentioned influences, the following illustration by the author (Aufner 2017) visualizes additional factors such as health/wealth, income and satisfaction in general.

3: $e frequently identified 7 fields which are influenced by VET (Aufner 2017)

To be prepared to accept, work on and adapt, as well as integrate the inﬂu- ences on VET and turn them to success has a precondition, i.e. the collaboration between the economy, the political framework, education providers and as a result, the possible access to labour markets. A main part of training in modern VET systems is based on the willingness and participation of the companies. Employers’ decision to hire apprentices or

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trainees will be determined by the framework conditions, which are based on the local law and also on benefits such as funding by the state. %ere has to be a win/ win situation for every side. Companies must be sure that their investment in VET leads to rising productivity and for example higher quality. Based on the technology progress as driver of economic growth a further aspect has to be observed: it is the structural shi' in the demand of employment and skills and in the society. Education as an exporting good and service is becoming more and more important. %e demand of services in the field of education and training is increasing, not only in the western world but also in emerging markets and in less developed regions. Beside higher education on a university level, as dominated by Anglo-Ameri- can countries, VET acquires an increasing position and a key role in strengthening the development of exporting enterprises. A lot of merchandising exports are connected to accompanied qualification services.

5. Measuring VET

Education is a critical success factor and a driver for innovation. It is the key factor for economic progress and so the regional providing of a highly skilled work-force is an important question in the site-related decision of investors. All this sounds very logical and simple. A lot of scientists have tried to analyse these arguments and demonstrated their correctness. In 1964 Becker (ibw, Forschun- gsbericht 144, 2008) developed a basic theory called ’human capital theory‘. %is documents that further occupational training can be understood as an investment in human capital, which leads to an increasing productivity of the employee. %is increasing productivity leads also to an increasing salary and the grade of salary depends on the ’transferability’ of the human capital investment to other companies. In a simple form, this means that an enterprise is not really interested to invest in skills, which can lead to an employee’s advantage when changing the employers. Seen in a wider sense, it means that employees should also invest in their human capital themselves. In the neoclassical model of R.M. Solow (Skare, Sinkovic 2018), the gross domestic product (GDP) is a function of the aggregated capital stock, the work force stock and the level of technical progress. %is means that without technical progress no economic growth can happen in a long-term view. %is model was later further developed and supplemented with human capital as an additional factor of productivity. Model of economic growth: y = f (F, H, L)

156 Anton Aufner TRANSFORMATIONOF V E T IN L ESS D EVELOPED R EGIONS - C HALLENGESAND O PPORTUNITIES (145 - 166)

* T. It also considers the technical knowledge stock as the fourth production factor. Further studies and improvements were made and especially the human capital factor became more important. Different calculations counted a human capital factor share of 22% to 49% (ibw, Forschungsbericht 144, 2008). A 2007 study by the Austrian researchers Böheim and Schneeweiss, (Schmid 2008, 89) concluded that if a company doubles their investment in training, the productivity rises by 4%. A further aspect regards the wages, which would be over 10% higher than before. %e author believes that the impact of the effectiveness of VET can only be measured through the combination of different parameters, which is to be analysed and merged in the final conclusion. Parameters could be as follows: • GDP - percentage of education • Number of exporters (registered international training institutes) • Increasing number of employees and income • Increasing fields of students • International investments and companies (high tech vs. simple production) • Rate of innovation • Decreasing rate of illiteracy • International cooperation of local institutes Table 1, which is based on the World Economic Forum Competitiveness Re- port 2017-2018, Schwab, K. (2017), gives an example of possible parameters and their dependency for measuring the effectivity of knowledge. %e table documents the influence and correlation between higher education and training as well as to innovation and the macro-economic environment, meaning GDP, gross national savings, debts and inflation. Table 1.: Global Competitiveness Index - Comparison, Source: World Economic Forum Competitiveness Report 2017-2018, Schwab, K. (2017)

Macro- Higher Labour market Spalte1 economic education & Innovation eﬃciency environment training

Germany 6.1 5.7 5.6 5.0 Austria 5.5 5.7 5.0 4.5 USA 4.5 6.1 5.8 5.6

China 6.0 4.8 4.1 4.5 Indonesia 5.7 4.5 4.0 3.9

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Macro- Higher Labour market Spalte1 economic education & Innovation eﬃciency environment training Korea 6.6 5.3 4.8 4.2

Brazil 3.4 4.2 3.2 3.7 Mexico 5.2 4.1 3.4 3.8 Argentina 3.4 5.0 3.3 3.3

%e figures, especially those on innovation, conclude a work force’s readiness for higher technology processes, which also influences labour market efficiency. %e parameters document the necessity of transferring in order to close the qualification gap and to build the basis for future economic growth. It has to be noted, that not all effects of VET will be measurable and attestable; important for companies and the economy will be the visible sustainable success of the implemented measures.

III. METHODOLOGY AND FINDINGS

%is conference paper is based on a theoretical analysis and description of VET models and strategies; followed by a case study, which investigates the research question, “Can the transfer of knowledge be a win/win situation for the target region and for the exporting country and/or its enterprises?“. %is review is seen as preliminary research to investigate the feasibility of further global scientific research. Beside this the paper serves to observe which effects the transfer can have and how this process of knowledge-transfer can be measured for its efficiency. %e question will be answered in the next paragraphs. %e first challenge was to find a reality-related definition so that the reader can agree and understand VET in practice. %e articles, scientific studies and books used and analysed, are focused more or less on higher education or VET in the sense of the dual system. %e researched studies mainly focus on a very theoretical content and are closely related to Europe. %ere is no well-known literature that discusses experiences and best practices of sustainable knowhow transfer outside the individual countries. In my opinion and research, VET, as primarily described in literature, is more than only the training of young people, especially apprentices. It covers the whole range of occupational training on offer, including training and occupational re-

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training to prepare people for their entrance to the labour market. Especially outside Europe we have to find new or mixed models, with our experience combined with local needs and adapted to and for local cultural requirements. One of the main challenges is the gap between language, culture differences and the attitude to labour work; this will be the greatest challenge of the future. %e figures in different statistics outside of Europe are not really comparable, because the investments in education, which come in the form of classic investments are not always classified as investment but are very o'en classified in “human capital”. Measurement tools are not really developed and the data basis for an international - not European - comparison in different fields of VET is therefore difficult. “Investments in the transfer of vocational education and higher qualification strengthen the competitiveness of a country and are the common driver of economic growth” is a hypothesis from my side and I have tried to figure out, what has validity for Europe, must be even more valid for developing regions. %e following illustrations (Cedefop 2018) therefore give a good example of the influence of training on employment, qualification and also the rate of overqualification in the EU 15.

7 Labour market regulation and training; Source: Eurostat (c). Participation/enrolment in education [educ_ipart_s] and OECD Employment and protection database

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8 Indication of overqualiﬁcation in the EU (1995-2015); Source: $e changing nature and role of vocational education and training in Europe. Volume 3: the responsiveness of European VET systems to external change (1995-2015). Luxembourg: Publications Oﬃce. Cedefop research paper; No 67.

%e over-qualification rate, as shown in figure 5, documents that the education system in the EU has reached a high standard and fulfils the requirements of the labour market. %e economy can choose and hire people with high qualifications, even for jobs with lower qualifications. In the example of the education policy and the investment in education programs through funding by the European Commission, the importance of these topics is obvious. %e economic growth visualizes and documents that the success is based on a highly qualified work force. It is a question of philosophy and economic policy that determines which importance the field of education in common is dedicated to. It goes without saying that a youth without a future is a lost generation. A youth without future is a generation without occupational education, with less chance on the labour market. %e same applies to situations where skills were taught that are no longer in demand on the labour market. %e author, through more than 20 years of experience, in Austria and internationally, is very familiar with VET and the transfer of VET. His personal practical experience is integrated in this paper, based on feedback got from companies who successfully engaged in know-how transformation processes to build the basis for their companies’ development by investing in skilled workers. %e next chapter reports a case study to give an example of a know-how transfer process, which was personally accompanied by the author. %is acquired knowledge forms the basis for further VET implementation processes in different countries.

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%is paper shall create awareness for a topic that more or less constitutes the basis of economic growth.

IV. CASE STUDY CHINA

In 2012 and the years before Austrian companies reported a great lack of qualified workforce in the People’s Republic of China. So, the Economic Chamber of Commerce started a survey about the needs of the estimated 250 Austrian companies which have subsidiaries in the region of Shanghai. %e outcome showed and documented the lack of qualified workers especially in terms of their practical and language skills. %e task was to find possibilities to support the companies in their search, not for ordinary helpers but for skilled workers comparable to Austrian standards. %is meant to fulfil criteria such as flexibility, problem solving techniques, language- and intercultural skills combined with professional skills. A'er intensive internal discussions between interested companies and the chamber world leading companies, one in the field of moulding and the other in the manufacturing of moulding machines, decided to implement the established Austrian dual VET system under Chinese framework conditions. %e project was seen as a way to guarantee the companies a ’long-term, sustainable basis of qualified workers’. %e aim was to train further staff under the guidelines and regulations of the Austrian dual system, embedded in the Chinese school system. %e training has now been running for more than four years and has meanwhile been extended to further classes and additional companies. %e project was not free of risk because a dual system based on Austrian standards did not exist and involved high investments and trust from every side, i.e. Chinese education authorities, the participating companies, the vocational institute. In collaboration between the companies and WIFI Institute for Economic Promotion, which is the leading VET training institution in Austria, and the commitment of the local education authorities we set up a project team. %is consisted of a maximum of 10 persons depending on the topic and the implemented field. %e preparation time, starting from the decision to the first class needed nine months. In this time, we had to adapt the occupational curriculum for it to fulfil the local requirements. %e first batch of trainees targeted future skilled CNC workers. At the outset it was necessary to choose a Chinese training institution/ college which was open for international cooperation, establish learning work labs in the companies, set up the acquisition process for qualified students and had to train the local teachers and trainers.

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%e students started with a general introduction and the obligatory subjects in school and a'erwards switched to the companies where the spent nearly 80% of their time to be trained on the job to acquire the practical skills. %e participating students’ great advantage was the opportunity to earn money during their vocational apprenticeship training and that a'er finishing their studies - documented in an examination - they hold a double degree, i.e. a Chinese and an Austrian vocational proficiency certificate. A first survey and analysis showed that nearly 90% passed the first four years of training, i.e. a drop-out rate of only 10%. 81% of the remaining high skilled workers were taken under contract. At the time of this publication, 59 students had passed or were already in training. From the alumni of the first class, 30% made their first career advancement from junior CNC Operator to CNC Operator. Each step also generates a salary step of 10%. %is project, which was have described in brief, was not an easy project, especially due to its preparation short time. Yet it is a best practice example of how to implement a know-how transfer process. It documents that the transfer of skills can generate a win - win situation for all participants, i.e. for the company, the people and the region. %e success is also measurable in minor items such as securing a job (81% of the remaining participants) for the individual, higher income compared to employees in other companies, an increasing participation of companies (at the time of this paper four companies were participating), additional professions being taught (currently three professions) and the further investment by foreign companies. %is investment can become sustainable through the guarantee of allocating a highly qualified workforce, which on the other hand increases the competitiveness of the respective company. %e process of implementing the dual system is now documented and will be adapted permanently. It can be transferred to every profession. %e reported case study fulfils all criteria which are pointed out in chapter II/1) page 4. as well as the described elements in chapter I/4) page 9, which affect VET systems. In the meantime, we have started to establish this kind of education in other countries outside of China.

V. CONCLUSION

%e aim of this conference paper was to give an insight into the research on vocational educational training and the possibilities of education and training transfer. In this context it was necessary to obtain a global view of economic processes and dependencies. Study results based on primary literature and the author’s

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own experiences show that the transformation of VET can lead to advantages for the exporting country (e.g. by building of economic relations), the importing country (innovation and impulses for its vocational education system) as well as the involved exporting country’s enterprises (availability of labour in industrial standard of origin). A'er diligently researching the huge field of VET and the impact on the economy, as well as conducting very intense literature research, which is very theoretical and not very comprehensive, paired with the author’s own personal experience in transforming and exporting VET to less developed regions, the question “Can the transfer of knowledge be a win/win situation for the target region and for the exporting country and/or its enterprises?“, can be answered with a clear “yes, it can”. Within the ever-closing net of globalisation, the topic is becoming more and more relevant and also the focus of governmental institutions and politicians. Na- tional and international policy more and more recognizes the high value of VET. An education system is not only a system that has to be adapted to changing structures, it is also the driving force in an overall change process. Education and training are the ’raw material’ to a knowledge-based society; from which the power of innovation results. %e development and production of highly advanced technology, goods and services is not possible without a high level of know-how. %e lack of qualification endangers and limits the potential of growth, but the required and offered skills are not independent from each other. As discussed in the paper, the following authors’ statements confirm the importance of vocational education as the basis for sustainable growth, as a way out of poverty but also that a lack of suitable vocational education leads to more and more difficulties, finally ending in chaos or, as aptly put by Schleicher: “Education and skills will always be the key for a growing and sustainable economy. Success will go to those individuals and countries which are swi' to adapt, slow to com- plain and open to change” (Schleicher 2006). “%e alternative to education in the long run is poverty and a not-countable increasing population without any vision and chance” (Klingholz 2016). %e greatest challenge of our century - especially for the economy - will be to close the qualification gap and to prevent not the so-called ‘war of cultures’ but rather the ‘war of knowledge’, i.e. highly developed countries versus countries that are falling back in centuries-old education models. Moreover, it is concluded that education is not a way to solve short-time problems; it is a long journey with conflicts and rebounds but which eventually leads to growing economies finally making it the key to health, wealth and peace.

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REFERENCES

American Psychological Association. (2010). Publication manual of the American Psychological Association. Washington, DC Becker, G.S. (1964): Human Capital, Chicago Billett, S (2011). Vocational education: purposes, traditions and prospects. Dordrecht: Springer Bliem, W., Petanovitsch, A., Schmid, K. (2014). Success factors for the Dual VET System, ibw research brief 2. Wien Bock-Schappelwein, J. & Janger, J. & Reinstaller, A. (2012). Bildung 2015 - Die Rolle von Bildung in der österr. Wirtscha&. Wien Böheim, R.&Scheeweiss, N. (2007). Renditen betrieblicher Weiterbildung in Österreich, Institut für Volkswirscha'slehre, Kepleruniversität Linz Camilleri, A.F. et al. (2014). Professional higher education in Europe: characteristics, practice examples and national differences. Malta: Knowledge Innovation Centre. http://files.eric.ed.gov/fulltext/ ED561268.pdf Cedefop Research paper No. 64. (2017). $e changing nature and role of vocational education and training in Europe Vol.2, Luxembourg. http://dx.doi.org/10.2801/548024 Cedefop Research paper No. 67. (2018). $e changing nature and role of vocational education and training in Europe Vol.3, Luxembourg. http://data.europa.eu/doi/10.2801/621137 Cedefop Research paper No.63. (2017). %e changing nature and role of vocational education and training in Europe Vol.1, Luxembourg. http://dx.org/10.2801/532605 Cedefop. (2011). $e economic benefits of VET for individuals. Luxembourg: Publications Office. http://www.cedefop.europa.eu/files/5511_en.pdf Dar, A. (2016). Skills Development in a Global Context: Towards a Future Ready Workforce. World Bank EU Commission. (2012). Rethinking education: Investing in skills for better socio-economic outcomes, Strassbourg Green, F. (2013). Skills and skilled work: an economic and social analysis. Oxford: Oxford University Press. International Labour Office. (2010). A skilled workforce for strong, sustainable and balanced growth. Geneva 11 International Labour Organization .(2012). Overview of Apprenticeship Systems and Issues. ILO contribution to the G20 Task Force on Employment. Geneva. Japannathan, S. & Geronimo, D. (2013). Skills for competitiveness, Jobs and Employability in Developing Asia-Pacific. ADB Briefs.Vol.11. Manila Klingholz, W. (2016). Ohne Bildung kein Überleben. Vortrag 5.7. Königstein Krugman & Obstfeld & Melitz. (2015). International Economics - %eory and Policy. Pearson Education Lutz W., Sola schola et sanitate: human capital as the root cause and priority for international development, Philosophical transactions of the royal society, Vienna 2009

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Lutz, W. & Cuaresma J. & Sanderson W. (2008). $e Demography of Educational Attainment and Economic Growth. Science, Vol. 22.2. Washington Morris, M., Murray, C., Murphy, S. (2016). Report Destination Education, Institute for public policy Research, London Moodie, G. (2008). From vocational to higher education: an international perspective. Berkshire: Open University Press OECD Science (2017). Technology and Industry Scoreboard 2017, THE DIGITAL TRANSFORMATION, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264268821-en OECD. (2012). Post-secondary vocational education and training: pathways and partnerships, higher education in regional and city development. Paris: OECD. http://www.oecdilibrary. rg/docserver/ download/8912061e.pdf?expires=1507323431&id=id&accname=guest&checksum=3C355E9F0CFF7 B655CA6E6526BACB027 http://dx.doi.org/10.1787/22183140 Onsomu, E.D. (2010). %e Impact of skills development on competitiveness. Epaa Vol. 15.3. Arizona Rojewski, J. W. (2009). A conceptual framework for technical and vocational education and training. In: Maclean, R.; Wilson, D. (eds). International handbook of education for the changing world of work. Dordrecht: Springer, Vol. 1, pp. 19-39. ttps://link.springer.com/ chapter/10.1007/978-1-4020-5281-1_2 https://dx.doi.org/10.1007/978-1-4020-5281-1 Rudestam, K.E.& Newton, R.R. (2015). Surviving your Dissertation. London Sachse, U. (2008). Exportleitfaden - Aus- und Weiterbildung, Bundesinstitut für berufliche Bildung imove, Bonn Scalia, T. et al. (2017). Study on the dual-use potential of key enabling technologies (KETs). Brussels: Executive Agency for Small and Medium-Sized Enterprises; https://publications.europa.eu/en/ publication-detail/-/publication/c092b731-f415-11e6-8a35-01aa75ed71a1 Schettkat, R. (2011). Bildung, Wirtscha&swachstum, Arbeitsmarkt; Wirtscha'sdienst 2011 DOI:10.1007/s10273-011-1176-z Schleicher, A. (2006). %e economics of knowledge: Why education is key for Europe´success. Lisbon council Brussels Schmid, K. (2008). Zum Nutzen der Weiterbildung. ibw Forschungsbericht 144. Wien Schmid, K. (2008). Zum Nutzen der Weiterbildung. ibw researchbrief 48. Wien Schmid, K. (2010). Foreign trade & human resources: Challenges from internationalisation, ibw research brief 58. Wien Schmid, K. (2011). Zukün'iger Qualifikationsbedarf in Kleinst- und Handwerksbetrieben bis 2020. ibw researchbrief 67. Wien Schwab, K. (2017):%e Global Competitiveness Report 2017-2018, World Economic Forum Seyr, B.F. (2017). Academic Research Methodology. PPT - International Joint Cross Border PhD Program Sinkovic, D. (2018). Economic philosophy and policy of Microfinance, PPT, Eisenstadt Skare, M. (2018). Macroeconomic Analysis and Policy, Joint PhD Program, Eisenstadt Streeck, W. (1991). On the institutional conditions of diversified quality production. In: Matzner, E.; Streeck W. (eds). Beyond Keynesianism: the socio-economics of production and employment.

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London: Edward Elgar Publishing Limited, pp. 21-61. Stutz, F.P. & Waf, B. (2012). $e World Economy. Pearson Education Walliman, N. (2011). Research Methods, the basics. New York Wallner, J. (2003). Aspekte der Zertifizierung beruflicher Qualifikationen. ibw researchbrief 01. Wien Winkler, B., Gruber, B., Schmid, K. (2016). Demand for skilled workers and current recruitment difficulties, ibw research brief 9. Wien Zdrahal-Urbanek, J. (2007). Internationale Literaturrecherchen zu Mikrokredit- Finanzierungsmodellen. ibw-Schri'enreihe 134. Wien Zinser, R. (2015). Analysis of VET in Ukraine since the Soviet era. Education + Training, 57 (6), 685- 700. doi:10.1108/ET-09-2014-0114 Aufner, A. (2018) own experience.

Figures & Tables 1: Workers with high-level qualifications earn higher wages; Source: %e economics of knowledge: Why education is key for Europe’s success (Schleicher 2006, 3) 6 2: Percentage of population born in another country; SOURCE: (Cedefop 67 2018). %e changing nature and role of vocational education and training in Europe, based on figures by Eurostat. 7 3: %e frequently identified 7 fields which are influenced by VET (Aufner 2017) 9 4 Labour market regulation and training; Source: Eurostat (c). Participation/enrolment in education [educ_ipart_s] and OECD Employment and protection database 13 5 Indication of overqualification in the EU (1995-2015); Source: %e changing nature and role of vocational education and training in Europe. Volume 3: the responsiveness of European VET systems to external change (1995-2015). Luxembourg: Publications Office. Cedefop research paper; No 67. 13 Table 1: Global Competitiveness Index - Comparison, Source: World Economic Forum Competitiveness Report 2017-2018, Schwab, K. (2017) 139

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Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

ARTICLE INFO Received: 20.9.2018. Accepted: 14.1.2019. JEL Classiﬁcation: C22, G1, P43, G15

Keywords: GMM model; Alternative ﬁnancial system; Islamic ﬁnance; Financial stability

MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS PERFORMANCE

Manuel Benazić Ines Karagianni Ladašić [email protected] [email protected]

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ABSTRACT

Aim of this study was to evaluate performance of conventional banks compared to Islamic banks in terms of their profitability and risk features in order to determine if Islamic banking could be an alternative to the traditional banking system and provide stability in times of crisis. A progression of bank specific and country specific indicators were joined to clarify the stability of both conventional and Islamic banking systems.

Four regressions for each banking system were prepared using dynamic panel data (DPD) econometrics generalized method of moments system (GMM). Two data series samples were used balanced and unbalanced dataset for Islamic banks and conventional banks. Dataset was collected from Fitch Connect by Fitch Solutions and Databank Orbis Bank Focus, Bureau van Dijk Electronic Publishing, Moody’s analytics company.

168 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

I. INTRODUCTION

In 2007 the Great Financial Crisis began in subprime mortgage market in the United States and has developed into full blown international banking crisis with the collapse of the investment bank Lehman Brothers on September 15, 2008, while around 123 banks in U.S. filed for bankruptcy. %e crisis was followed by global economic downturn, the Great Recession of 2008 (Trabelsi, 2011). Com- paring the performance of conventional and Islamic banks during the global financial crisis, Islamic banks were less affected during the initial phase in 2008, but in 2009 they experienced larger declines in profitability due to second round of effect on real economy, especially real estate and construction sector. Islamic banks aren’t permitted to have any direct exposure to derivatives and securities which experienced the largest impact in the crisis. %e main risk for both types of banks is credit risk. With larger capital and liquidity buffers, Islamic banks are better positioned to withstand market or credit shocks, as their average capital adequacy ratio is higher (CTA) then the one of the conventional counterparts (Masood, A., 2009). Midst of the global financial crisis as systemic bank failure started, questions begun to rise about the role of the banks in the financial system (Bourkhis, Nabi, 2013). Attention has turned to Islamic banking as form of ethical banking values system alternative, but questioning begun of its ability to prevail en mass (Hasan, Dridi 2010, Said 2012, Zarrouk 2012). Main reasons of Islamic banks attraction was soundnes so many studies claim that have there been Islamic finance introduced on mass scale instead of conventional counterparts that the crisis could have been avoided. (Beck et al., 2013, Chong et al., 2012) Ethical finance deemed Islamic banking fair due to no interest, stable outlook, with higher chances of shock absorption (Ftiti et al., 2013, Rahim, Zakaria, 2013, Zehri, Al-Harch, 2013). Other studies have questioned the shock ability of Islamic banks and that crisis prevention is limited (Ariff et al., 2008, Said, 2012). Poor risk management and deterioration of solvency by commercial banking has brought more attention to Islamic banking as an alternative solution so the study wants to compare the two counterparts at a critical time of a potential new downturn brewing on the horizon, how both compare by their performance measured by profitability, credit risk and insolvency risk. Methodology employed consists of combination of time series micro- and macroeconomic indicators. Microeconomic indicators include bank size, capitalization, assets and liquidity, while macroeconomic indicators include GDP growth, inflation rate consumer prices and official exchange rate as of the day of reporting. Dataset includes information on both kinds of banks from 32 countries including

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Europe, Africa and Asia. Time span evaluated includes period from 2008 until 2017. Estimation method used was GMM system. %e second part consists of literature review, while methodology and data description is integrated in the third part. Results are examined in the fourth part, followed by conclusion.

II. LITERATURE REVIEW

Plenty specialists have considered the benefits of Islamic banks (Choong et al., 2012, El Khamlichi et al., 2014, Fun Ho et al., 2014, Hasan, Dridi, 2010, Jawadi et. al., 2014, Rahim, Zakaria, 2013, Onakoya et al., 2013) and their hazard risk (Bourkhis, Nabi, 2013, Rajhi, Hassairi, 2013) by joining micro and full macroeconomic pointers and making a similar investigation with the traditional banking framework. Utilizing ordinary least squares (OLS) technique (Wasiuzzaman, Tarmizi, 2010) inspected the effect of inner and outer factors on the profit of 16 Islamic banks in Malaysia. %e examination reasoned that exempt liquidity variable; asset quality and capital adversely influence bank profit, which is conflicting with findings of (Kosmidau et al., 2005, Choong et al., 2012) that discovered a positive outcome of credit risk, capital concentration and liquidity in 13 Islamic banks in Malaysia. Alike Akhtar et. al. (2011) found that capital ratio proportions have a noteworthy positive effect on performance of Islamic banks in Pakistan between 2006-2009 timeframe, much unlike the size which negatively impacted bank performance. Regardless of inflation and forex rate which prompted financial insta- bility, Rajhi and Hassari (2013) outlined that bank size, liquidity and GDP growth have added to banking stability. Nevertheless, Ashraf et al. (2016) have concluded that GDP growth development has no huge impact on the stability of financial sector of 136 banks in timeframe 2000-2013. Utilizing GLS regression and CAMELS model (Rashid, Jabeen, 2016) considered performance of both banking groups in 2006-2012 timeframe and had estimates indicating that GDP and credit interest rates impact bank performance negatively for both groups and that bank size positively but insignificant influences bank performance. Zarouk (2012) examined 20 Islamic countries from the Gulf region before and a'er crisis and demonstrated that bank specific microeconomic factors negatively impact performance in 2008 and a'er the crisis continued in 2009 sharp decrease in profitability and liquidity followed, some countries have even engaged in over the top risk taking especially U.A.E.. To achieve robuster outcomes on financial stability and Islamic banking

170 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

analysts have led similar investigations with conventional counterparts. Back et al. (2013) compared 88 Islamic and 422 conventional banks in 22 countries from 1995-2009 timeframe to find that Islamic banks are better capitalized, have better asset quality and ability to take risks. Also, Rahim and Zakaria (2013) thought about financial stability in Malaysia so they conducted a study of both bank groups over period 2005-2010 applying Z-score and NPL to find out that Islamic banks are more resistant in crisis. %ese discoveries are in accordance with conclusions cra'ed by Onakoya et al. (2013) and Zehri and Al-Herch (2013) who found out that Islamic banks are more gainful and stable amid crisis due to Shariah law appliance. Performance of Islamic banks in Egypt differed from the findings of previous studies as conducted by Fayed (2013) based on performance of 3 Islamic banks and 6 conventional counterparts in Egypt with timeframe 2008-2010, which indicated prevail of conventional banks in liquidity, credit risk, solvency and profitability field. Also Miah and Sharmen (2015) demonstrated that conventional banks execute better cost management. Jawadi et al. (2016) have pointed out that there are very few differences between the two counterparts regarding financial risk. Keeping all those conclusions in mind, the following three hypotheses have been derived: H1: Bigger bank size more negatively correlates to insolvency risk in conventional banks. H2: Higher net loans to total assets ratio stronger increases credit risk for conventional banks. H3: Higher liquid assets to total assets increase profitability for Islamic banks.

III. DATA AND METHODOLOGY

%e study is trying to determine strength of conventional and Islamic banks based on their proﬁtability, credit risk and insolvency risk performance. %e data series sample used set was a balanced dataset of annual data from total 288 banks including 213 conventional banks and 75 Islamic banks from 32 countries with time span from 2008 to 2017. Dataset was collected from Fitch Connect by Fitch Solutions and Bureau Van Dijk, Moody’s analytics company.

A. DEFINITION AND SELECTION OF VARIABLES

To examine soundness of conventional and Islamic banks, following depending variables were chosen; proﬁtability as measured by return on asset (ROA) and return on equity (ROE), while risk was divided into credit risk measured by im-

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paired loans to gross loans ratio (IMLGL) and insolvency risk measured by Z- score derived as sum of return on assets and capital adequacy ratio, divided by standard deviation of return on assets. Banks are believed to be more stable if they have higher ability to assimilate market or credit shocks. Bank profitability measured by ROA and ROE was also deployed in previously conducted studies (Fayed, 2013 and Jawadi et al., 2014). Financial ratios deployed are viewed as fundamental tools to evaluate bank stability in the financial system and indicate their ability to withstand shocks. As independent variables applied were banks specific microeconomic indicators and country specific macroeconomic indicators. Banks specific microeconomic indicators include bank size ratio, capital quality ratio, asset quality ratios and liquidity ratios. Bank size ratio SIZEBQ was derived from natural logarithm of total bank assets. Capital adequacy ratio CTA (Capital/Total Assets) was determined by dividing bank total common equity with total assets. Asset quality ratios include: LLRGL (Loan Loss Reserves/Gross Loans) determined by dividng reserves for impaired loans by impaired loans, LLPNL (Loan Loss Provisions/Net Loans) calculated as reported loan impairment charge divided by net loans, NETL- TA (Net Loans/Total Assets) determined by dividing net loans by total assets, LL- RIML (Loan Loss Reserves/Impaired Loans) determined by dividing reserves for impaired loans with impaired loans and LLPNI (Loan Loss Provision/Net Loans) determined by dividing reported loan impairment charge by net loans. Liquidity ratios include LQATA (Liquid Assets/Total Assets) calculated by dividing liquid assets by total assets and LOADSTF (Loans/Deposits and short term financing rate) calculated by dividing loans by deposits including short term financing rate. Country specific indicators used in the study include GDP growth (GGDP), inflation consumer prices (INF) and foreign exchange rate (FXRATE) as of the date of banks reporting financials.

B. WHY USE OF GMM MODEL AS ESTIMATION METHOD

%e aim of the study was to prepare four regressions using dynamic panel data (DPD) econometrics generalized method of moments system (GMM) with two balanced data set samples including 213 conventional banks and 75 Islamic banks from 32 countries in order to compare their performance based on profitability (ROA and ROE), credit risk (IMLG) and insolvency risk (Z-score) management. Total of eight time dummy variables (2010-2017) was included in the model. One lag of dependent variable was used and specified as follows (roaroa(-1)size_bqc- talqataloadstfllpniillrglnetltallrimlllpnlggdpfxrateinf). Transformation was per-

172 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

formed by differentiation in order to remove cross section fixed effects, in which the time dummies weren’t differentiated. %e GMM 2step procedure was applied. %e Arellano-Bond approach and its extension to the GMM system estima- tor were designed for situations with; time periods (t) moderately small and many individual units (n), a linear functional relationship, independent variables that are dynamic, depending on its own past realizations, dependent variables that aren’t strictly exogenous as to correlated with past and possibly current realizations of the error, fixed individual effects, implying unobserved heterogeneity and heter- oskedasticity and autocorrelation within individual units errors, but not across them. Or in other words to avoid endogenity issue from causal relationship of independent and dependent variables because of lagged dependent variables in OLS or 2SLS. Two stages least squares (2SLS) regression analysis is a statistical technique used in the analysis of structural equations. %e technique is the extension of the ordinary least squares (OLS) method, linear method for estimating the unknown parameters in a linear regression model. %e 2SLS is used when the dependent variables error terms are correlated with the independent variables. Hav- ing more instruments then endogenous variables makes the system over identified with more moment restrictions than parameters to estimate, that’s why GMM was deployed in the study. A Dynamic Panel Data (DPD) approach is considered the work of Arellano and Bond (AB) (Arellano, Bond, 1991), developed by Arellano and Bover (1995) and Blundell and Bond (1998) to solve endogenity issue. Although they have market the work of Holtz-Eakin, Newey and Rosen (Holtz-Eakin et al.,1988) based on the notion that the instrumental variables approach doesn’t exploit all of the information available in the sample and by doing so in GMM model; one can construct more efficient estimates of the Dynamic Panel Data model (DPD). As DPD model estimators are instrumental variables methods. It’s important to evaluate Sargan-Hansen test results when they are applied which tests validity of over-identifying restrictions with H0 implying over-identifying restrictions are valid. Another important diagnostic in DPD estimation is the AR test for autocorrelation of the residuals with H0 implying no autocorrelation. By construction, residuals of the differenced equation should posses serial correlation, but if the assumption of serial independence in the original errors is warranted, the differenced residuals shouldn’t exhibit significant AR (2) behaviour. Additionally Wald test or Wald Chi Squared Test was deployed testing for individual significance of each coefficient.

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IV. THE RESULTS AND INTREPRETATION

A. DESCRIPTIVE STATISTICS

Number of observations in balanced conventional banks dataset is 2130 and in balanced Islamic banks dataset 750. In both balanced datasets no values are missing. Compared by SIZEBQ Islamic banks are smaller than their conventional counterparts, although Islamic banks lead in capital to total assets ratio (CTA) with higher mean and smaller standard deviation, in liquid assets to total assets (LQA- TA), loans to deposit and short term financing ratio (LOADSTF), net loans to total assets ratio (NETLTA), loan loss provision to net loans ratio( LLPNL). Conventional banks have a slightly higher mean in loan loss reserves to impaired loans (LLRIML), higher ratio of loan loss provision to net interest income ratio (LLPNII) and impaired loans to gross loans ratio (IMLGL). By loan loss reserves to gross loans ratio they are equal (LLRGL). Negative skew indicates that the tail on the le' side of the probability density function is longer than the right side, while positive skew indicates that the tail on the right side is longer than the le' side. Kurtosis is related to the tales of distribution, not the peak. Kurtosis greater than 3 means outliers and fatter tails. Jarque- Berra on normal distribution was rejected, indicating that both datasets don’t have normal distribution, rejecting H0 at 5% significance level. In investment environment variance (sum squared deviation) measures the degree of investment risk. %e higher the variance, risk and return are higher. De- pending how aggressive or risk avoidant investors are they choose their strategies of risk exposure differently. Modern Portfolio %eory includes possibility to reduce variance without suffering return lost by investment asset diversification by different allocations of stocks, bonds, real estate, investment trusts, insurance products, derivatives, cash, foreign currency and precious metals. Contrarily to conventional counterparts, Islamic banks aren’t permitted to engage in speculations. Traditional accounting data based bank insolvency risk measure z-score estimates the probability that a banking system defaults; the indicator compares buffers (return on assets and capitalization) with the risk of volatility of ROA calculated as standard deviation of ROA over period of ten years 2008-2017 from underlying banks unconsolidated data. According to Rajhi, Hassari (2013) the z-score is a measure of distance to default, so higher z-score, increases banks distance to default and the more stable it will be. Haj Yusef (2017) interprets z-score as standard deviation of how far bank’s ROA has to fall before the bank becomes insolvent or basically as distance to insolvency. %e z-score of conventional banks is higher

174 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

than in Islamic banks, which indicates that conventional banks are more stable and less likely to default, but Islamic banks do reach the required level of insolvency risk. Same formula for measuring z-score is used by the World Bank in its Global Financial Development Report 2017/2018; Bankers without borders (WB, 2018) and Federal Reserve Bank Reserve Bank of St. Louis, FRED (fred.stlouisfed, 2018). By profitability, the mean of ROA is higher in Islamic banks (0.03) than in conventional banks (0.01), while compared by ROE both have same mean (0.1). Country specific variables have average values for inflation are 5, GDP growth rate is around 3.5, while foreign exchange reached a higher level in conventional banks compared to Islamic banks. %e use of multiple regression model demands nonexistence of multicolinearity within independent variables. According to Kervin (1992) severe multicolinearity issue within two independent variables appears when 0.7 point exceeded. Both datasets were tested for appearance of multicolinearity, none of which appeared greater than the limitation point.

B. MODEL ESTIMATION AND RESULT INTREPRETATION BALANCED GMM MODEL

Two separate two step GMM models were constructed one with conventional banks and one with Islamic banks dataset. Both contain four regression models. Introduced were time dummy variables from 2010 to 2017. Wald test for joint significance of time dummies was deployed to test for individual significance of time dummies adding to the model which reviled that time dummies were significant (p=0.0000) so the Ho=0 got rejected at 5% significance level in favour of H1≠0 and in one case (p=0.0981) the Ho=0 got rejected at 10% significance level in favour of H1≠0. Time dummy variables all predict the model.

%e Arellano and Bond test implies H0 of no autocorrelation onto differenced residuals. In first differences AR (1) rejects H0; in all but one ROA in conventional banks. Furthermore, no order 2 serial correlation of Arellano and Bond test AR (2) was observed in both groups to be greater than then 5%. %is shows that the GMM series framework display is good for predictions and has decent number of instruments without autocorrelation issues.

%e Sargan test includes H0 that overidentifying restrictions are valid. %e p value is large enough and null hypothesis cannot be rejected for both groups regarding ROE, IMLGL and z-score, which means that their instruments are determined to be valid. In both groups ROA is signiﬁcant and the null hypothesis cannot be rejected.

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Bank size variable (SIZEBQ) significantly negative impacts ROA and insolvency risk, although it positively affects ROE and credit risk in conventional banks. In Islamic banks variable SIZEBQ affects significantly negative all dependent variables, which is in line with Akhtar et al. (2011) who concluded that SIZEBQ significantly negative impacts Islamic banks performance. Such finding contra- dicts previous research which came to conclusion that bigger size warrants higher profitability (Hassan, Dridi, (2010), Zeitoun (2012), Muda, Shaharuddin, Embaya (2013)). Bank capitalization (CTA) significantly positive influences profitability and insolvency risk, while it negatively impacts credit risk in conventional banks. Is- lamic bank capitalization positively impacts profitability (although not significant), while it significantly negative impacts credit risk and positively insolvency risk. In both banks capitalization positively impacts profitability and negatively impacts credit risk. According to previous research bank capitalization has positive and significant effect on profitability (Sufian, Noor, (2009), Akhtar et al., (2011), Choong et al., (2012), Onakoya, Onakoya, (2013), Beck at al., (2013), Ramlan, Ad- nan, 2016)). It suggests that Islamic bank’s view capitalization as hazard decrease and doesn’t come unexpected as in Islam charging interest is prohibited. Islamic banks aren’t permitted to obtain conventional loans from other banks or central bank. Adequate capitalization level improves insurance against distress. Capital provides safety net and soundness. Banks have to maintain adequate reserves to guard against losses and impact. %is study confirms findings of Wasiuzzaman and Tarmizi (2010) namely that capitalization negatively affects ROE, LLPNL negatively affects profitability, while LQATA positively affects profitability. Liquid assets (LQATA) and loans to deposits (LOADSTF) positively but not significant impact conventional banks profitability and impaired loans while negatively insolvency. Liquidity in Islamic banks positively and significant impacts all, while loans to deposit and short term funding negatively impact ROA, and the rest of dependent variables positively. Improved liquidity positively augments earnings for Islamic banks, which correlates with previous findings (Wassiuzzaman, Tarmizi, (2010), Zeitoun (2012), Beck et al., (2013)). Positive relationship between liquidity and insolvency in Islamic banks was also noted by Rajhi and Hassairi (2013). Regarding asset quality in Islamic banks loan loss reserves to gross loans ratio (LLRGL), loan loss reserves to impaired loans ratio (LLRIML), net loans to total assets (NETLTA), loan loss provision to net interest income ratio (LLPNII) positively impact profitability, while loan loss provision to net loans ratio (LLPNL) negatively impacts returns and insolvency, only positive impact is on credit risk, but so does LLPNII. Also LLPNI has negative impact on insolvency as does LLPNL, while the

176 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

rest has positive impact on insolvency. LLRGL have negative impact on ROE. %e LLRIML has negative impact on credit risk. Alike conclusions have been made by Kosmidou et al. (2005), Beck at al. (2013), and Ftiti (2013). %at LLRGL and NETLA have positive impact on credit risk was also concluded by Fayed (2013), the extension in this study is LLRIML, except LLPNL which was confirmed by the study of (Trad et. al., 2017) which implied that Islamic banks hold a better quality asset base that contributes to their soundness. For conventional banks when it comes to asset quality both loan loss provision including ratios negatively impact returns and insolvency risk, while positively affect credit risk. Loan loss reserves to gross loans (LLRGL) and net loans to total assets (NETLTA) negatively impact returns and positively impact credit risk and insolvency. Loan loss reserves to impaired loans ratio (LLRIML) positively impact returns and negatively credit risk and insolvency. Country specific macroeconomic variables assert same effects on both kinds of banking systems in case of GDP growth and inflation negatively impacting returns and credit risk, while positively insolvency. %e GDP growth having significant negative impact on credit risk was also confirmed by studies of Rashid and Jabeen (2016). Foreign exchange rate negatively impacts all ratios, credit and insolvency risk in conventional banks, while in Islamic banks it exempts ROE which it positively impacts. %e impact of GDP and inflation on ROA is in fact negative, but negligible as coefficients are significant but very small. Negative effects of GDP growth and inflation on ROE like in this study was noted by many different authors as well as positive effect from GDP growth on insolvency risk and inflation having negative impact on insolvency (Fajed (2013), Rajhi, Hassairi (2013), Mat Rahim, Zakaria (2013)). %e FX rate having negative impact on insolvency was confirmed by Rajhi, Hassairi (2013) and Bourkhis, Nabi (2013). Inflation having positive impact on credit risk was found by Trad et al. (2017). Rise in FX means depreciation of local currency. Depreciation has negative impact on insolvency. In previous studies it was found that GDP growth positively affects ROA and credit risk (Trad et al., (2017), Fajed (2013), Rajhi, Hassairi (2013), Mat Rahim, Zakaria (2013)), exchange rate positively impacts credit risk (Srairi (2009), Wasi- uzzaman, Tarmizi (2010), Choong et al. (2012), Zeitoun (2012), Muda et al. (2013) and inflation positively impacts ROA (Delis, Papanikolau (2009), Wassiuzzaman, Tarmizi (2010)), which this study hasn’t confirmed. %e study of the balanced GMM model found that SIZEBQ more negatively impacts ROA in IB, positively ROE and credit risk in CB, but negatively ROE and credit risk in IB and also more negatively insolvency in CB. SIZEBQ proved significant impact on all cases highlighted above.

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Capitalization stronger positively affects ROA in CB, positively ROE in CB, but negatively ROE in IB, stronger negatively credit risk for IB and less positive insolvency in IB. CTA proved significant impact in all cases highlighted above. Liquidity measured by LQATA showed stronger positive impact on profitability and credit risk of IB, while negatively impacting CB and positively impacting IB insolvency risk. LQATA proved significant impact in all cases highlighted above. Liquidity measured by LOADSTF positively impacted ROA of CB, but negatively ROA of IB, stronger positive ROE in IB, stronger positive credit risk of CB, negatively impacted CB and significantly positive IB insolvency risk. Asset quality measured by LLPNII negatively effects ROA and significantly negative ROE in CB, while positively ROA and significantly positive ROE in IB, higher significantly positive effects IB credit risk and more negative CB insolvency risk. Asset quality measured by LLRGL negatively impacts ROA in CB, while significantly positive ROA in IB, significant strongly negative impact was noted on ROE of IB, significant stronger affect on credit risk CB and significantly higher positive effect on insolvency risk of CB. Asset quality measured by NETLTA concluded negative impact on profitability of CB and positive in IB, higher positive credit risk and insolvency risk for CB. NETLTA proved significant impact in all cases highlighted above. Asset quality measured by LLRIML showed higher positive impact on profitability of IB, higher negative impact on credit risk of IB, while negative impact on CB and positive impact on IB regarding insolvency. LLRIML proved significant impact in all cases highlighted above, beside negative insolvency affect on CB. Asset quality measured by LLPNL reviled to have higher negative impact on profitability of IB, stronger positive impact on credit risk for CB and higher negative impact on insolvency risk for CB. LLPNL proved significant impact in all cases highlighted above, beside the last one. %e GDP growth more negatively impacted ROA for CB, significantly more negative impacted ROE and credit risk for IB, while significantly more positively impacted insolvency risk in IB. %e foreign exchange rate was found to impact both equally significantly negative for ROA, significantly negative ROE in CB, while significantly positive ROE for IB, affected more negative credit risk of IB and significant more negative insolvency risk of IB. Inflation rate was found to impact both equally significantly negative for ROA, significantly more negative ROE of CB, while more significantly positive impacting credit and insolvency risk in CB.

178 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

C. UNBALANCED GMM MODEL

Simultaneously generalized method of moments system (GMM) with two unbalanced data set samples was developed including a total of 440 banks, divided between 295 conventional banks and 145 Islamic banks from 32 countries over the same time period. It included 2809 observations of conventional banks and 1261 observations of Islamic banks. In commercial banks SIZEBQ was found to significantly positive affect profitability and credit risk, while significantly negative insolvency risk. In Islamic banks SIZEBQ was found to positive, but no significant affect ROE which is in line with previous conducted studies which concluded that increasing total assets leads to higher returns (Hassan, Dridi (2010), Zeitoun (2012), Muda, Shaharuddin, Em- baya (2013), Rashid, Jabeen (2016)). %e rest of dependent variables were found to be negatively affected, significant for credit risk in line with Cihak and Hesse (2008) and non significant for insolvency. Capitalization in commercial banks proved to be significantly positive affecting dependent variables, insignificant only for credit risk. In Islamic banks CTA significantly negative affected ROA, no significant for ROE, positively significant impacted insolvency and no significantly credibility. Having insolvency positive affected by capital is in line with Trad et al. (2017). Other authors have found significant positive effects on profitability and negative on credit risk (Sufian, Noor Mohamad (2009), Aktar et al. (2011), Choong et al. (2012), Onakoya and Onakoya (2013), Rajhi and Hassairi (2013). Liquidity in commercial banks proved to have negative impact on all dependent variables, while significant only for LOADSTF on ROA. Liquidity in Is- lamic banks showed positive effects on all dependant variables, beside LOADSTF negatively non significant impacting insolvency. It’s in line with previous findings (Wassiuzzaman, Tarmizi (2010), Zeitoun (2012), Beck et al. (2013) Rajhi, Hassairi (2013)). Conclusion is that higher liquidity expands earnings. In asset quality LLRGL and NETLTA have significant positive impact on dependent variables, insignificant only in case of NETLTA on returns. Both loan loss provision ratios affect significantly negative returns and insolvency, while showing significant positive impact on credit risk, but no significant only in case of LLPNII on ROA. %e LLRIML significantly positive impacts returns, significantly negative credit risk and non significant negative insolvency. Islamic bank asset quality includes LLRIML having not significant positive impact on ROA, same was found by Kosmidou et al. (2005), Beck et al. (2013) and Ftiti et al. (2013). Negative impact was found by LLPNL (significant) and LLRIML

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(not significant) on profitability, at the same time LLPNL significantly negative impact on insolvency and LLRIML significant positive impact on insolvency, all in line with Trad et al. (2017). Credit risk was determined being positive correlated to LLPNII, LLRGL and NETLTA as found by Fayed (2013). In commercial banks GDP growth and foreign exchange proved to negatively impact returns and credit risk, significant only for GDP growth on ROA, while not significant positive insolvency. Infatuation significantly negative correlated with returns and insolvency, while significantly positive credit risk. In Islamic banks GDP growth had negative effect on all dependent variables, significant for ROA and credit risk. Foreign exchange had same impact on banking systems, negatively impacting returns and credit risk, while positively insolvency risk. Not significant only for ROA. Inflation was found to significant positive affect credit risk, positive but not significant ROE and negative but not significant ROA and insolvency risk. Trad et al. (2017) findings have found the same that insolvency risk is significantly positive correlated to foreign exchange rate, inflation significantly positive impacting credit risk and GDP growth having negative, not significant effect on ROE. Like in balanced model, the unbalanced model wasn’t able to confirm what previous studies found; namely GDP growth positively affects ROA and credit risk (Trad et al., (2017), Fajed (2013), Rajhi, Hassairi (2013), Mat Rahim, Zakaria (2013)), exchange rate positively impacts credit risk (Srairi (2009), Wasiuzzaman, Tarmizi (2010), Choong et al. (2012), Zeitoun (2012), Muda et al. (2013) and inflation positively impacts ROA (Delis, Papanikolau (2009), Wassiuzzaman, Tarmizi (2010)). %e study of the unbalanced GMM model found that SIZEBQ significantly positive impacts ROA in CB, significantly negative ROA in IB, stronger positively ROE in IB, has positive effect on credit risk in CB and is significantly negative on IB credit risk, while being significantly negative for CB and negative on insolvency risk for IB. Capitalization shows significantly positive impacts on ROA CB, while significantly negative on ROA IB. It has significant positive effect on ROE CB, while negative for ROE in IB. It has more positive effect on credit risk for CB and significantly positive impact on insolvency risk for both. Liquidity measured by LQATA showed negative impact on profitability of CB, while having significant positive effect on profitability of IB, negatively impacting CB credit and insolvency risk, while positively impacting IB credit and insolvency risk. Liquidity measured by LOADSTF significantly negative impacted ROA and negative ROE for CB, while having positive effect on profitability for IB. It has

180 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

negative credit and insolvency risk for CB and significant positive effect on credit risk for IB, while negatively effecting insolvency risk of IB. Asset quality measured by LLPNII more negatively effects IB ROA and significantly more negative CB ROE, while affecting significantly more positive credit risk in IB and slightly more negative insolvency risk for IB. Asset quality measured by LLRGL impacts significantly positive profitability of CB, while significantly negative profitability of IB. Significantly more positive it affects credit risk in CB, while significantly positive insolvency of CB and negative insolvency of IB. Asset quality measured by NETLTA concluded more positive impact on profitability of IB, significantly more effect on credit risk CB, while having significantly positive effect on insolvency CB and negative effect on insolvency IB. Asset quality measured by LLRIML proved significant positive impact on CB profitability, while being higher for ROA it had a negative coefficient for ROE IB. It had significantly more negative impact on credit risk CB, showed negative insolvency risk for CB, but significantly positive insolvency for IB. Asset quality measured by LLPNL reviled significant negative impact on profitability of both, significant positive impact on credit risk for CB, being negative for credit risk IB and also being significantly more negative for insolvency risk CB. %e GDP growth had significantly more negatively impact on IB ROA, more negative ROE for CB, significantly more negative credit risk for CB and impacting positively CB and negatively IB insolvency risk. %e foreign exchange rate was found to impact more negatively IB profitability (significant for ROA), significant negative credit risk of IB, while significantly positively impacting insolvency risk for IB. Inflation rate was found to impact significantly negative profitability of CB; it was negative on ROA, but positive on ROE IB. It had significant but small impact posing a higher positive credit risk for IB. It also had significantly more negative impact on IB insolvency risk.

V. CONCLUSION

%e outcome acquired on the connection amongst proﬁtability and risk of banks and diverse bank speciﬁc variables seem to approve all hypotheses in both models. Bigger bank size does more negatively impact insolvency in conventional banks. Increase in banks assets doesn’t necessary lead to higher solvency. Higher net loans to total assets ratio means higher credit risk for conventional banks. As- set quality of the bank determines risk, thus credit risk positively correlates with

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NETLTA. Better liquidity ratio maximizes gains of Islamic banks. Higher LQATA means also lower credits risk for Islamic banks thus more resistance in liquidity crisis period. %e motivation behind this study was to determine if Islamic finance, monetary interest free cosmos could be an alternative version to customary monetary framework or a monetary supplement with few restrictions. To address this issue GMM model was deployed to determine which micro and macroeconomic determinants impact banks profitability, credit and bankruptcy chance. Mostly in line with previous findings, the study determined that micro and macroeconomic determinants fundamentally impact profitability, credit and insolvency risk at 5 and 10 percent significance levels. %e study of the balanced GMM model found that SIZEBQ more negatively impacts ROA in IB, positively ROE and credit risk in CB, but negatively ROE and credit risk in IB and also more negatively insolvency in CB. SIZEBQ proved significant impact on all cases highlighted above. Capitalization stronger positively affects ROA in CB, positively ROE in CB, but negatively ROE in IB, stronger negatively credit risk for IB and less positive insolvency in IB. CTA proved significant impact in all cases highlighted above. Liquidity measured by LQATA showed stronger positive impact on profitability and credit risk of IB, while negatively impacting CB and positively impacting IB insolvency risk. LQATA proved significant impact in all cases highlighted above. Liquidity measured by LOADSTF positively impacted ROA of CB, but negatively ROA of IB, stronger positive ROE in IB, stronger positive credit risk of CB, negatively impacted CB and significantly positive IB insolvency risk. Asset quality measured by LLPNII negatively effects ROA and significantly negative ROE in CB, while positively ROA and significantly positive ROE in IB, higher significantly positive effects IB credit risk and more negative CB insolvency risk. Asset quality measured by LLRGL negatively impacts ROA in CB, while significantly positive ROA in IB, significant strongly negative impact was noted on ROE of IB, significant stronger affect on credit risk CB and significantly higher positive effect on insolvency risk of CB. Asset quality measured by NETLTA concluded negative impact on profitability of CB and positive in IB, higher positive credit risk and insolvency risk for CB. NETLTA proved significant impact in all cases highlighted above. Asset quality measured by LLRIML showed higher positive impact on profitability of IB, higher negative impact on credit risk of IB, while negative impact on CB and positive impact on IB regarding insolvency. LLRIML proved significant impact in all cases highlighted above, beside negative insolvency affect on CB. Asset quality measured by LLPNL reviled to have higher negative impact on profitability of IB, stronger positive impact on credit risk for CB and higher negative impact on insolvency risk for CB. LLPNL proved signifi-

182 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

cant impact in all cases highlighted above, beside the last one. %e GDP growth more negatively impacted ROA fro CB, significantly more negative impacted ROE and credit risk for IB, while significantly more positively impacted insolvency risk in IB. %e foreign exchange rate was found to impact both equally significantly negative for ROA, significantly negative ROE in CB, while significantly positive ROE for IB, affected more negative credit risk of IB and significant more negative insolvency risk of IB. Inflation rate was found to impact both equally significantly negative for ROA, significantly more negative ROE of CB, while more significantly positive impacting credit and insolvency risk in CB. %e study of the unbalanced GMM model found that SIZEBQ significantly positive impacts ROA in CB, significantly negative ROA in IB, stronger positively ROE in IB, has positive effect on credit risk in CB and is significantly negative on IB credit risk, while being significantly negative for CB and negative on insolvency risk for IB. Capitalization shows significantly positive impacts on ROA CB, while significantly negative on ROA IB. It has significant positive effect on ROE CB, while negative for ROE in IB. It has more positive effect on credit risk for CB and significantly positive impact on insolvency risk for both. Liquidity measured by LQATA showed negative impact on profitability of CB, while having significant positive effect on profitability of IB, negatively impacting CB credit and insolvency risk, while positively impacting IB credit and insolvency risk. Liquidity measured by LOADSTF significantly negative impacted ROA and negative ROE for CB, while having positive effect on profitability for IB. It has negative credit and insolvency risk for CB and significant positive effect on credit risk for IB, while negatively effecting insolvency risk of IB. Asset quality measured by LLPNII more negatively effects IB ROA and significantly more negative CB ROE, while affecting significantly more positive credit risk in IB and slightly more negative insolvency risk for IB. Asset quality measured by LLRGL impacts significantly positive profitability of CB, while significantly negative profitability of IB. Significantly more positive it affects credit risk in CB, while significantly positive insolvency of CB and negative insolvency of IB. Asset quality measured by NETLTA concluded more positive impact on profitability of IB, significantly more effect on credit risk CB, while having significantly positive effect on insolvency CB and negative effect on insolvency IB. Asset quality measured by LLRIML proved significant positive impact on CB profitability, while being higher for ROA it had a negative coefficient for ROE IB. It had significantly more negative impact on credit risk CB, showed negative insolvency risk for CB, but significantly positive insolvency for IB. Asset quality measured by LLPNL reviled significant negative impact on profitability of both, significant positive impact on credit risk for CB, being negative for credit

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risk IB and also being significantly more negative for insolvency risk CB. %e GDP growth had significantly more negatively impact on IB ROA, more negative ROE for CB, significantly more negative credit risk for CB and impacting positively CB and negatively IB insolvency risk. %e foreign exchange rate was found to impact more negatively IB profitability (significant for ROA), significant negative credit risk of IB, while significantly positively impacting insolvency risk for IB. Inflation rate was found to impact significantly negative profitability of CB; it was negative on ROA, but positive on ROE IB. It had significant but small impact posing a higher positive credit risk for IB. It also had significantly more negative impact on IB insolvency risk. Conclusion on hypotheses formulated and tested, using econometric regressions:

• H1: Bigger bank size (SIZE BQ) more negatively correlates to insolvency risk (Z-score) in conventional banks. In balanced GMM model SIZE BQ significantly negative impacted insolvency risk (Z-score) in both systems. In unbalanced GMM model SIZE BQ only significantly negative impacted insolvency risk (Z-score) of conventional banks. Islamic banks are generally smaller size than conventional counterparts. Larg- er size doesn’t warrant higher profitability. Size negatively impacted Islamic banks performance is in line with previous research conducted by Akhtar et al (2011).

• H2: Higher net loans to total assets ratio (NETLTA) stronger increases credit risk (IMLGL) for conventional banks. Higher net loans to total assets ratio (NETLTA) increasing credit risk (IM- LGL) proved signiﬁcant for both systems in both models; the signiﬁcance was higher for conventional banks. %at LLRGL and NETLTA have positive impact on credit risk was concluded by Fayed (2013). Trad et al (2017) extended the study and implied that Islamic banks hold a better quality asset base that contributes to their soundness.

• H3: Higher liquid assets to total assets (LQATA) increase profitability (ROA/ ROE) for Islamic banks. In balanced GMM model higher liquid assets to total assets (LQATA) ratio impacts Islamic banks profitability (ROA/ROE) significant and positive, while for conventional banks the impact is non-significant, weaker positive. In unbalanced GMM model higher liquid assets to total assets (LQATA) ratio impacts Islamic banks profitability (ROA/ROE) significant and positive, while for conventional banks the impact is non-significant, negative. Improved liquidity positively augments earnings for Islamic banks; such conclusion is in line with previous findings by Wassiuzzaman, Tarmizi (2010), Zeitoun (2012) and Beck at al (2013).

184 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

%e outcome of the study prompts the conclusion that Islamic finance can’t be a substitute of the conventional financial system, yet rather a supplement. Main strength of Islamic finance is coming from sovereign wealth funds deposits of reserves created from oil and gas revenues that fluctuate based on oil price and in case of oil, but not LNG, can be restricted by quotas. Given the never ending conflicts in the Middle East, including diplomatic blockade of Qatar, rivalry between Kingdom of Saudi Arabia and Islamic Republic of Iran, Saudi - Yemen conflict, Syria, Turkey’s currency crisis and the concerns in the further region regarding Palestine, Lebanon, Egypt, Libya, Sudan, Afghanistan, Paki- stan and Iraq all of them being countries know for Islamic finance, where both financial systems are suffering massive withdrawals of liquidity from the banking system due to conflict, particularly Islamic banking. Due to government support and solid revenues as the oil price averaged $75 per barrel in first three quarters of 2018, budget deficits have narrowed and sovereign wealth funds have been able to deposit quite sustainable amounts in banks to foster liquidity of the banking sector in the GCC. Weaker growth, lower financing demand and lower deposit growth slightly deteriorated asset quality and financial ratios for the GCC. Government issuance improved liquidity but in lesser volume. Low bank financing growth and higher financing cost burden bank financing and revenue. Islamic banks have experienced higher levels of no fees deposits. Capital levels have remained unchanged as less financing was needed so buffers remained adequate due to prevailing single borrower sector but are at risk in a sudden on setting event.

A. EXPECTED SCIENTIFIC CONTRIBUTION OF RESEARCH

%e study was conducted with the most updated dataset available, from 2008 while finishing in 2017 and offers a unique view what has happened since the Global financial crisis with bank specific ratios. Previous studies have mostly concentrated on what has happened to the banking system shortly a'er global financial crisis limited on regions and certain countries. %is research dataset includes information on both banking systems from 32 countries including Europe, Africa and Asia and compares their performance. Quite large data sample was used in balanced GMM model consisting of total 288 banks; including 213 conventional banks and 75 Islamic banks, having 1704 observations for conventional banks and 600 observations for Islamic banks, or a total of 2304 observations. Unbalanced GMM dataset model consists of total 440 banks, divided between 295 conventional banks and 145 Islamic banks, which in-

185 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

cluded 2809 observations of conventional banks and 1261 observations of Islamic banks or a total of 4070 observations. %e a'ermath of the global financial crisis contains recent developments in the financial industry. Primary issues of current monetary framework; debt obligation, derivatives, money creation, morals and the too big to fall banks haven’t been comprehended; they have become greater thus financial system remains fragile. %e study is a unique blend of the a'ermath of the financial crisis at a moment in time when many institutions started warning of a next possible downturn; it gives a glimpse at the state of the financial system and how is predestined to face a new crisis as a credit crunch could develop and gives Islamic finance solution how to build a sound financial framework.

186 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

REFERENCES

Akhtar, M., F., Ali, K., Sadaqat, S. 2011. Factors influencing the profitability of Islamic banks of Pakistan, International Research Journal of Finance and Economics, 66, p. 125-132. Arellano, M., and S. Bond 1991. Some tests of specification for panel data; Monte Carlo evidence and an application to employment equations, Review of Economic Studies, 58, p. 277-297. Arellano, M., and O. Bover. 1995. Another look at the instrument variable estimation of error component models, Journal of Econometrics, 68, p. 29-51. Ariff, M., Bader, M., Shamsher, M., Hassan, T. 2008. Cost, revenue, and profit efficiency of Islamic versus conventional banks: International evidence using data development analysis, Islamic Economic Studies, 15, p. 23-76. Ashraf, D., Rizwan, M., L’Huillier, B. 2016. A net stable funding ratio for Islamic banks and its impact on financial stability: An international investigation, Journal of Financial stability, 24, p. 47-57. Beck, T., Demirguc-Kunt, A., Merrouche, O. 2013. Islamic vs. Conventional banking: Business model, efficiency and stability, Journal of Banking & Finance, 37, p. 433-447. Blundel, R., and S. Bond. 1998. Initial conditions and moment restrictions in dynamic panel data models, Journal of Econometrics, 87, p. 115-143. Bourkhis, K., and M. S. Nabi. 2013. Islamic and conventional banks’ soundness during the 2007-2008 financial crisis, Review of financial Economics, 22, p. 68-77. Choong, Y., V., %im, C., K., Kyzy, B., T. 2012. Performance of Islamic commercial banks in Malaysia: An empirical study, Journal of Islamic Economics Banking and Finance, 8, p. 67-79. Cihak, M., and H. Hesse. 2008. Islamic banks and financial stability: An empirical analysis, IMF, WP 08/16. Delis, M., D., and N. I. Papanikolau. 2009. Determinants of bank efficiency: Evidence from a semi- parametric methodology, Managerial Finance, 35, p. 260-275. El Khamlichi, A., Sakar, K., Arouri, M., Teulon, F. 2014. Are Islamic equity indices more efficient than their conventional counterparts? Evidence from major global index families, Journal of Applied Business Research, 30, p. 1137-1150. Fakhfeh, M., Hachicha, N., Jawadi F., Selmi, N., Idi Cheffou, A. 2016. Measuring volatility persistence for conventional and Islamic banks: An FI-EGARCH approach, Emerging markets review, 27, p. 84- 99. Fayed, M., E. 2013. Comparative performance study of conventional and Islamic banking in Egypt, Journal of applied finance & Banking, 3, p. 1-14. Fiti, Z., N'i, O., Srairi, S. 2013. Efficiency of Islamic banks during subprime crisis: Evidence of GCC countries, Journal of Applied Business Research, 29, p. 285-304. Fun Ho, C., S., AbdRahman, N., A., Muhamad Yusuf, N., H., Zamzamin, Z. 2014. Performance of global Islamic versus conventional share indices: International evidence, Pacific Basin Finance Journal, 28, p. 110-121. Hassan, M., and J. Dridi. 2010. %e effects of the global crisis on Islamic and conventional bank: A comparative study, IMF, Working paper 10/201.

187 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

Holtz-Eakin, D., Newey, W., Rosen, H., S. 1998. Estimating vector autoregression with panel data, Econometrica, 56, p. 1371-1395. Jawadi, F., Chaffou, A. I., Jawadi, N. 2016. Do Islamic and conventional banks really differ? A panel data statistical analysis, Open Economics Review, 27, p. 293-302. Jawadi, F. Chaffou, A., I., Jawadi, N. 2016. Do Islamic and conventional banks really differ? A panel data statistical analysis, Open Economics Review, 27, p. 293-302. Kevin, J., B. 1992. Methods for business research, New York, Harper Collins Kosmidou, K., Tanna, S., Pasioures, F. 2005. Determinants of profitability of domestic UK commercial bank: Panel evidence from 1995-2002, Money Macro and Finance, MMF Research Group Conference Rahim, M., S., R., and R. H. Zakaria. 2013. Comparison on stability between Islamic and conventional banks in Malaysia, Journal of Islamic economics Banking and Finance, 9, p. 131-149. Masood, A. 14/10/2009. Did Islamic banks in the Gulf do better than conventional ones in the crisis?, IMFblog Miah, M., D., and K. Sharmen. 2015. Relationship between capital, risk and efficiency: A comparative study between Islamic and conventional banks of Bangladesh, International Journal of Islamic and Middle Eastern Finance and Management, 8, p. 203-221. Muda, M., Shaharuddin, A., Embaya, A. 2013. Comparative analysis of profitability determinants of domestic and foreign Islamic banks in Malaysia, International Journal of economics and Financial Issues, 3, p. 559-569. Onakoya, A., B., and A. O. Onakoya. 2013. %e performance of conventional and Islamic banks in the United Kingdom: A comparative analysis, Journal of Research in Economics and International Finance, 2, p. 29-38. Rajhi, W., and S. A. Hassairi. 2013. Islamic banks and financial stability: A comparative empirical analysis between MENA and Southeast Asian countries, Region et Developpment, 37, p. 149.-177. Ramlan, H., and M. S. Adnan. 2016. %e profitability of Islamic and conventional bank: Case study in Malaysia, Procedia Economics and Finance, 35, p. 359-367. Rashid, A., and S. Jabeen. 2016. Analyzing performance determinants: Conventional versus Islamic banks in Pakistan, Borsa Istanbul Review, 16, p. 92-107. Rosman, R., Abd Wahab, N., Zainol, Z. 2014. Efficiency of Islamic banks during the financial crisis; An analysis of Middle Eastern and Asian countries, Pacific Basin Finance Journal, 28, p. 76-90. Said, A. 2012. Efficiency in Islamic banking during a financial crisis - an empirical analysis of forty- seven banks, Journal of Applied Finance & Banking, 2, p. 163-197. Srairi, S. 2009. A comparison of the profitability of Islamic and conventional banks: %e case of GCC countries. Bankers, Markets & Investors, 98, p. 16-27. Sufian, F., and A. Mahamad Noor. 2009. %e determinants of Islamic banks’ efficiency changes: Empirical evidence from the MENA and Asian banking sectors. International Journal of Islamic and Middle Eastern Finance and Management, 2, p. 120-138. Trabelsi, M., A. 2011. %e impact of the financial crisis on the global economy: Can the Islamic financial system help? Journal of Risk Finance, 12, p. 15-25. Trad, N., Trabelsi, M., A., Goux, J., F. 2017. Risk and profitability of Islamic banks: Areligious deception or an alternative solution? European Research on Management and Business Economics, 23, p. 40-45.

188 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

Wasiuzzaman, S., and H. A. B. A. Tarmizi. 2010. Profitability of Islamic banks in Malaysia: An empirical analysis. Journal of Islamic Economic Banking and Finance, 6, p. 53-68. World Bank 2018. Bank z-score for Qatar, retrieved from FRED, Federal Reserve Bank of St. Louis, 21/08/2018 World Bank 2018. Global Financial Development Report 2017/2018, Bankers without borders, WB Group, IBRD/WB, Washington D.C., 30/07/2018, p. 67. Zarrouk, H. 2012. Does financial crisis reduce Islamic banks’ performance? Evidence from the GCC countries. Journal of Islamic Finance and Business Research, 1, p. 1-16. Zehri, F., and N. Al-Herch. 2013. %e impact of the global financial crisis on the financial institutions: A comparison between Islamic banks and conventional banks. Journal of Islamic Economics Banking and Finance, 9, p. 69-88. Zeitoun, R. 2012. Determinants of Islamic and conventional banks performance in GCC countries using panel data analysis. Global Economy and Finance Journal, 5, p. 53-72. Islamic finance references: Alrifai, T. 2015. Islamic finance and the new financial system, Willey, Singapore Erian, M. A. 2016. %e only game in town, Random House, New York, U.S.A. Jamaldeen, F. 2012. Islamic finance for dummies, Willey, Singapore Kureshi, H., and M. Hayat 2015. Contracts and deals in Islamic Finance, Willey, Singapore Mirakhor, A., and N. Krichene. 2014. Introductory mathematics and statistics for Islamic finance, Willey, Singapore Trad, N. et al. 2017. Risk and profitability of Islamic banks: A religious deception or an alternative solution?, European Research on Management and Business Economics, 23, p. 40-45. Xiping, L. et al. 2017. An exploration of z-score, Massey University, 01, New Zealand

189 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

APPENDIX

Calculations explanation Total Assets - as reported in Balance Sheet under Total Assets - Banks Size BQ - natural logarithm of Total Assets for each bank CTA (Capita/Total Assets) - as reported in Capital Adequacy Ratios, under Equity/Total Assets. Capital Adequacy Ratio measures banks ability to withstand losses. LQATA (Liquid Assets/Total Assets) - as reported in Liquidity Ratios, under Liquid Assets/Total Assets. LOADSTF (Loans/Deposits and short term financing rate) - as reported in Liquidity Ratios, under Loans to Deposits and short term financing rate LLRGL (Loan Loss Reserves/Gross Loans) - as reported in Asset Quality Ratios, under Reserves for Impaired Loans/Gross Loans. LLRIML (Loan Loss Reserves/Impaired Loans) - as reported in Asset Quality Ratios, under Reserves for Impaired Loans/Impaired Loans. NETLTA (Net Loans/Total Assets) - calculated from reported Net Loans divided by Total Assets - Banks from Balance Sheet. LLPNL (Loan Loss Provisions/Net Loans) - calculated as reported Loan Impairment Charge from Income Statement divided by Net Loans from Balance Sheet. LLPNII (Loan Loss Provisions/Net Interest Income) - calculated as reported Loan Impairment Charge from Income Statement divided by Net Interest Income from Income Statement. Z-score (ROAA+Capital ratio)/standard deviation ROAA. Calculated from ROAA as reported in Profitability Ratios, CAR as reported in Capital Adequacy Ratios under Equity/Total Assets and calculated Standard deviation of ROAA. IMLGL (Impaired Loans/Gross Loans) - as reported in Asset Quality Ratios, under Impaired Loans (NPL)/Gross Loans. ROAA (Return on Average Assets) and ROAE (Return on Average Equity) - as reported in Profitability Ratios. FX Rate (Foreign Exchange Rate) - as converted on reporting date. GGDP (GDP real annual growth) - as per World Bank Database. INF (Inflation Consumer Prices) as per World Bank Database.

190 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

TABLE 1.:BALANCED STUDY SAMPLE

Study sample Balanced model Sequence Country Conventional banks Islamic banks 1 Germany 7 0 2 U.K. 11 4 3 Qatar 6 4 4 U.A.E. 10 7 5 Kuwait 5 3 6 K.S.A. 8 4 7 Oman 8 0 8 Jordan 12 2 9 Bahrain 11 14 10 Iran 0 1 11 Sudan 1 2 12 Brunei 0 1 13 Yemen 0 0 14 Syria 7 2 15 Malaysia 22 13 16 Bangladesh 6 5 17 Pakistan 8 6 18 Egypt 8 1 19 Indonesia 10 1 20 Tunisia 10 0 21 %ailand 10 0 22 Lebanon 9 0 23 Nigeria 5 0 24 Singapore 8 0 25 Mauritania 0 0 26 Bahamas 4 0 27 Maldives 1 1 28 Philippines 9 1 29 Palestine 2 1 30 Iraq 1 1 31 Senegal 0 0 32 B. and H. 14 1 TOTAL SEPARATE 213 75 TOTAL ALL BANKS 288

Source: Authors Research results

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TABLE 2.: UNBALANCED STUDY SAMPLE

Study sample Unbalanced model Sequence Country Conventional banks Islamic banks 1 Germany 12 1 2 U.K. 11 6 3 Qatar 6 6 4 U.A.E. 11 7 5 Kuwait 5 5 6 K.S.A. 8 6 7 Oman 10 2 8 Jordan 14 4 9 Bahrain 12 19 10 Iran 1 8 11 Sudan 6 7 12 Brunei 1 1 13 Yemen 4 3 14 Syria 10 2 15 Malaysia 28 21 16 Bangladesh 12 5 17 Pakistan 10 8 18 Egypt 10 3 19 Indonesia 10 11 20 Tunisia 11 1 21 %ailand 10 1 22 Lebanon 10 2 23 Nigeria 10 1 24 Singapore 12 1 25 Mauritania 3 1 26 Bahamas 10 1 27 Maldives 1 2 28 Philippines 10 1 29 Palestine 3 2 30 Iraq 6 5 31 Senegal 7 1 32 B. and H. 21 1 TOTAL SEPARATE 295 145 TOTAL ALL BANKS 440

Source: Authors Research results

192 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

TABLE 3.: FINANCIAL STRENGTH INDICATORS

Risk based indicators Return based indicators (proﬁtability ratios) ROAA ROAE Credit risk IMLGL Insolvency risk Z-score

Source: Authors

TABLE 4.: MICRO AND MACROECONOMIC INDICATORS

Country speciﬁc variables Bank speciﬁc variables (micro-economic) (macro- (Bourkhis, Nabi, 2013, Rosman et al, 2014) economic) (Ftiti et al, 2013)

GDP growth Capital adequacy Bank size ratio Asset quality ratios Liquidity ratios Inﬂation rate ratio Foreign exchange rate SIZEBQ CTA LLRGL LQATA LLRIML LOADSTF LLPNL LLPNII NETLTA

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Source: Authors

TABLE 5.: MODELS EXPLAINING STRENGTH IN TERMS OF PROFITABILITY AND RISK

Proﬁtability equation

Panel A PROFITABILITY j,i,t Įȕ1ɇɴj,i,tȕ2ɇDj,i,t഍j,i,t

Panel A1 ROAA j,i,t=ɲнɴ1ɇɴj,i,tȕ2ɇDj,i,t഍j,i,t

Panel A2 ROAE j,i,t=ɲнɴ1ɇɴj,i,tȕ2ɇDj,i,t഍j,i,t Risk equation

Panel B RISK j,i,t=ɲнɴ1ɇɴj,i,tȕ2ɇDj,i,t഍j,i,t Credit risk

Panel B1 IMLGL j,i,t=ɲнɴ1ɇɴj,i,tȕ2ɇDj,i,t഍j,i,t Insolvency risk

Panel B2 Z-score j,i,t=ɲнɴ1ɇɴj,i,tȕ2ɇDj,i,t഍j,i,t

Where “i”, “j” and “t” indicate successively banks (i=1,2,3,…145 and 295), countries (j=1,2,3,…32) and period (t=2008,2009,2010,…2017), β denotes the to be estimated models parameters, Σβjit represent a vector of macroeconomic variables and ΣMjit represents a vector of macroeconomic variables and ɇjit represents random or error term. Source: Authors

TABLE 6.: BALANCED GMM MODEL CONVENTIONAL VERSUS ISLAMIC BANKS

Indepen- Dependent variables dent variables Proﬁtability Risk Ļ ROA ROA ROE ROE IMLGL IMLGL Z-score Z-score

CB IB CB IB CB IB CB IB Lag of 0.034074 0.202080 0.568369 1.104146 0.896670 0.786426 0.490667 0.575680 depen- (0.0000) (0.0000) (0.0000) dent (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) 8.909497 15.53008 17.78474 variable 27.38593 9.280166 45.64562 16.10699 49.76959 -0.005251 -0.181656 0.033302 -0.107937 0.011340 -0.011706 -4.892428 -2.672529

SIZEBQ (0.0208) (0.0000) (0.0042) (0.0154) (0.0258) (0.0010) (0.0000) (0.0000)

-2.314107 -8.696377 2.864599 -2.431225 2.230596 -3.299583 -4.618239 -5.033638 0.194883 0.021031 0.718184 -0.463064 -0.047059 -0.151505 101.2973 51.43166

CTA (0.0000) (0.7943) (0.0000) (0.1683) (0.0584) (0.0000) (0.0000) (0.0000)

31.73426 0.260910 5.679053 -1.379558 -1.893796 -9.125383 9.596534 18.29980 0.001838 2.695618 0.005815 3.147224 0.000633 0.007881 -2.301607 0.206235

LQATA (0.4587) (0.0000) (0.7353) (0.0000) (0.9338) (0.0737) (0.1417) (0.1866)

0.741178 225.7149 0.338194 47.47153 0.083134 1.791527 -1.470146 1.322405

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5.90E-05 -5.02E-05 0.000268 2.22E-06 0.000320 0.000294 -0.045488 0.008027

LOAD- (0.8685) (0.4121) (0,7805) (0.9862) (0.5218) (0.0000) (0.5128) (0.0000) STF 0.165632 -0.820812 0.278758 0.017259 0.640719 23.93053 -0.654597 5.931110 -0.000717 0.001674 -0.010879 0.024112 0.004277 0.013516 -0.158452 -0.100937

LLPNII (0.6842) (0.7768) (0.0522) (0.0894) (0.1156) (0.0000) (0.3215) (0.4703)

-0.406790 0.283687 -1.943184 1.701473 1.574434 8.165154 -0.991659 -0.722484 -0.016619 0.303723 -0.043014 -0.586777 0.789478 0.262474 6.895864 2.753237

LLRGL (0.2741) (0.0000) (0.6964) (0.0000) (0.0000) (0.0000) (0.0746) (0.0025)

-1.094092 7.357552 -0.390236 -5.822537 21.01028 7.536182 1.784224 3.034590 -0.007655 0.040702 -0.079537 0.045582 0.044122 0.026894 6.994084 0.011999

NETLTA (0,0991) (0.0244) (0.0001) (0.0253) (0.0919) (0.0000) (0.0003) (0.9252)

-1.650205 2.255941 -3.962713 2.242915 1.686289 29.26828 3.640404 0.093886 0.000173 0.055172 0.000633 0.024258 -0.000541 -0.003662 -0.000391 0.304858

LLRIML (0.0000) (0.0000) (0.0000) (0.0004) (0.0000) (0.0795) (0.8888) (0.0002)

5.367363 27.51012 8.070864 3.568106 -10.41101 -1.756772 -0.139825 3.755981 -0.146786 -0.138308 -0.851875 -0.143784 0.207600 0.003093 -4.666459 -0.340638

LLPNL (0,0004) (0.0000) (0.0026) (0.0000) (0.0026) (0.2861) (0.2196) (0.0032)

-3.551885 -32.12611 -3.018114 -9.633306 3.010993 1.067757 -1.228067 -2.958572 -9.25E-06 -0.008066 -0.000155 -0.006890 -0.000487 -0.001184 0.030774 0.110251

GGDP (0.8564) (0.0000) (0,7332) (0.0164) (0.0064) (0.0000) (0.1866) (0.0041)

-0.180990 -4.737744 -0.340885 -2.407598 -2.731923 -5.561811 1.321211 2.882587 -1.11E-06 -1.11E-05 -1.21E-05 3.19E-07 -2.02E-07 -1.08E-05 -0.000137 -0.000202

FXRATE (0.0049) (0.0119) (0.0051) (0.9320) (0,9059) (0.0000) (0.4819) (0.0010)

-2.820522 -2.522259 -2.801410 0.085419 -0.118219 -35.37685 -0.703373 -3.296021

195 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

-0.000159 -0.001595 -0.001523 -0.000247 1.01E-05 0.000508 -0.027107 -0.010279

INF (0,0000) (0.0558) (0.0000) (0.8257) (0.9311) (0.0000) (0.0018) (0.4759)

-5.080263 -1.916699 -5.902220 -0.220338 0.086432 6.602291 -3.119817 -0.713317 Source: Authors Research results

TABLE 7.: UNBALANCED GMM MODEL CONVENTIONAL VERSUS ISLAMIC BANKS

Dependent variables Proﬁtability Risk Inde- pendent ROA ROA ROE ROE IMLGL IMLGL Z-score Z-score variables CB IB CB IB CB IB CB IB Lag of 0.086215 0.647066 0.209219 0.491524 0.456745 0.625478 0.230445 0.294667 dependent (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000)

variable 9.704246 13.71687 14.06719 9.403087 11.36441 13.89287 10.50927 41.62345 0.011733 -0.091653 0.040995 0.058497 0.007030 -0.027366 -4.422166 -1.731697

SIZEBQ (0.0000) (0.0085) (0.0002) (0.1933) (0.1032) (0.0010) (0.0000) (0.1941)

5.031508 -2.638847 3.727235 1.301834 1.630378 -3.306744 -5.523002 -1.299355 0.136282 -0.243708 0.197362 -0.177697 0.025176 0.000874 93.27355 75.60320

CTA (0.0000) (0.0765) (0.0074) (0.5091) (0.3004) (0.9778) (0.0000) (0.0000)

6.763616 -1.773051 2.681971 -0.660501 1.035919 0.027855 10.78974 10.83570 -0.000641 2.592686 -0.012704 2.954191 -0.002246 0.007420 -0.747603 0.065065

LQATA (0.8190) (0.0000) (0.4629) (0.0000) (0.7668) (0.2729) (0.5119) (0.6762)

-0.228879 81.09700 -0.734204 19.20396 -0.296583 1.097060 -0.655977 0.417814 -0.000395 6.67E-06 -0.000759 1.86E-05 -6.07E-05 0.000141 -0.003461 -0.004642

LOAD- (0.0613) (0.8951) (0.4051) (0.8655) (0.5240) (0.0260) (0.8286) (0.4524) STF -1.872375 0.131849 -0.832772 0.169476 -0.637293 2.229001 -0.216520 -0.751695 -0.000111 -0.005693 -0.005975 -0.002451 0.001608 0.009935 -0.080939 -0.091842

LLPNII (0.7542) (0.5641) (0.061) (0.8577) (0.0355) (0.0084) (0.1167) (0.4445)

-0.313198 -0.577018 -2.746046 -0.179359 2.103877 2.640523 -1.569260 -0.764922 0.034235 -0.305937 0.278599 -0.802798 0.898455 0.390710 14.79109 -1.086895

LLRGL (0.0122) (0.0003) (0.0185) (0.0000) (0.0000) (0.0000) (0.0000) (0.6583)

2.509620 -3.672078 2.356662 -4.500045 14.26287 4.462203 4.231382 -0.442435 NETLTA 0.006690 0.018102 0.008509 0.075556 0.041466 0.012949 5.806343 -0.957848

(0.1098) (0.6630) (0.7922) (0.1099) (0.0117) (0.0001) (0.0001) (0.1637)

1.599726 0.435860 0.263528 1.600302 2.522297 3.980169 3.824176 -1.393831 0.000121 0.002844 0.000499 -0.003927 -0.000570 -0.000451 -0.001861 0.206176

LLRIML (0.0000) (0.5175) (0.0000) (0.3900) (0.0000) (0.6846) (0.7768) (0.0002)

5.444767 0.647419 6.765925 -0.859973 -8.443491 -0.406272 -0.283470 3.680422

196 Manuel Benazić MICROECONOMIC MODEL: GMM MODEL CONVENTIONAL BANKS VERSUS ISLAMIC BANKS... (167 - 198)

-0.132211 -0.132457 -1.156677 -0.152506 0.253760 -0.005206 -9.783728 -0.252694

LLPNL (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.4898) (0.0007) (0.0849)

-5.337886 -14.58014 -4.959391 -9.145400 4.229854 -0.690963 -3.399092 -1.724716 -0.000111 -0.003733 -0.000905 -0.000495 -0.001047 -0.000879 0.001461 -0.023253

GGDP (0.0982) (0.0497) (0.1657) (0.8489) (0.0002) (0.0983) (0.9359) (0.3108)

-1.654131 -1.964836 -1.386550 -0.190567 -3.773084 -1.654857 0.080384 -1.014096 -1.86E-07 -9.07E-06 -2.69E-06 -8.28E-06 -1.31E-06 -2.55E-06 2.80E-05 0.003242

FXRATE (0.5090) (0.0575) (0.2299) (0.1470) (0.5411) (0.0899) (0.8778) (0.0000)

-0.660558 -1.901541 -1.200876 -1.451337 -0.611257 -1.697678 0.153754 20.45345 -0.000115 -0.000230 -0.001345 0.001305 0.000236 0.000643 -0.014436 -0.007060

INF (0.0007) (0.7315) (0.0003) (0.3586) (0.0705) (0.0091) (0.0286) (0.6775)

-3.380101 -0.343265 -3.594486 0.918561 1.809795 2.612992 -2.190673 -0.415986 Source: Authors Research results

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Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

ARTICLE INFO Received: 20.11.2018. Accepted: 20.3.2019. JEL Classiﬁcation: A11, A12, A23, G21, G32

Keywords: Risk Management; Austrian Banks; Finance Education; Requirements

AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS: A MIXED METHODS STUDY

Victoria Petsch [email protected]

199 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

$is paper offers an analysis of the changing requirements of risk management in Austrian banks. $e last global financial crisis was the trigger for the critique and the resulting transformation of risk management. Consequently, not only banks should rethink their risk analysis, also the academia in the field of finance and economics should adapt to the latest changes. $is mixed-method research study analyses which requirements graduates from a finance study should bring along to start a career within the risk management department of a bank. 12 expert interviews with risk managers (m=10, f=2) working in 12 different Austrian banks were performed. $e wide-ranging questionnaire consists of four requirement-blocks (risk categories, regulatory guidelines, fundamentals in economics, tools and models). $e participants rate the relevance of every item on a Likert scale. $e inquiry shows that the experts focus on basic knowledge regarding risk and different risk categories, as well as knowledge in regulations and fundamentals in economics. A special attention of many experts focus on so&skills and competencies like IT, English and communication skills. Attributes like an openness to change, flexibility to continuous improvement and learning-on- the-job are requested.

200 Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

I. INTRODUCTION

Within this study, the current requirements for graduates of a finance and banking program are ascertained. For this purpose, interviews are held with experts in management positions in the field of risk management in Austrian banks. %e analysis of the results will provide an insight into the changing requirements of risk management and will support Austrian universities of applied sciences in expanding their education spectrum in risk management. %is paper looks at the market side and analyzes the demand for graduates in risk management for banks. Exactly this consideration is linked with applied research and should provide suggestions for future curricular. %e question comes up, what skills and which knowledge are necessary for the market and how this can be offered in a curriculum at an Austrian university of applied sciences. %e aim of the study is to empirically determine which practice-relevant requirements for risk managers in Austrian banks are considered important for graduates. %e risk managers of banks are interviewed. %e largest and most relevant banks are considered to ensure the validity of the results. %is analysis deals exclusively with risk management practice and risk management education at the Austrian level. %e national consideration excludes international banks and international education institutes with risk management education. %e focus lies on Austrian banks and Austrian universities offering a program in finance and banking. To respond to the expertise of the participants and still can achieve comparability, a mixed-methods approach is used. %is empirical concept incorporates both quantitative and qualitative aspects (Teddlie & Tashakkori, 2010, pp. 7-8). %e participants answer a comprehensive and closed questionnaire, but also can respond to open questions. %e questionnaire was designed by intensive literature review to represent areas that could be relevant for a career in risk management in banks. %e knowledge and skills are divided into four broad areas: risk categories, regulatory guidelines, fundamentals in economics, tools and models. %e results of the empirical survey can serve as a basis for refocusing Uni- versity programs. %e elaborated requirements represent the practical relevance on the financial market and provide the basis for adapting practice-oriented content. Furthermore, this paper will explain the current orientation and focus of risk management of banks in Austria. %e results of the empirical survey are used to combine practical approaches into theory at universities. %e following analysis deals exclusively with banking risk management.

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Literature review %e financial crisis of 2008 and 2009 has provoked global and drastic consequences for the entire world economy. %is financial crisis revealed that the methods used for early risk detection and risk analysis were insufficient. Preventing crisis requires effective recognition of emerging financial bubbles and economic dependencies. %e banks are still seen as the main cause for the biggest crisis a'er the world economic crisis of 1929. %e European and national security standards, such as the requirements of Basel II and the minimum requirements of financial market supervision, have existed but the banks have nevertheless destroyed several trillion US dollars. %e implosion of the financial system and the decreasing trust into the banking system were the consequence. %is laid the foundation for a sustainable realignment and further development of risk management practices in banks (Jacobs, Riegler, Schulte-Mattler, & Weinrich, 2012, p. 6). %e following authors have analyzed the financial crisis from 2008 onwards and have specifically addressed the role of the banks. Special attention was paid to risk management and the early detection of crises. Jacobs et al. (2012) show that the methods used for risk detection and risk analysis were inadequate during the financial crisis. Mertzanis (2013) also examines the past financial crisis and the need to adapt risk measurement to extreme conditions. %e major mistakes that led to the collapse of the entire financial systems were not made in a crash but during a high phase. Taking risks in the boom were underestimated and overesti- mated in a crash, which led to a constant misperception of risk. Changing market conditions have also changed investors’ attitudes towards risk (Mertzanis, 2013, p. 298). Risk is a situation involving exposure to danger. Transferred to the banking business, risk management is the handling of uncertain values in order to increase the equity (Strauß, 2009, pp. 33-34). %ese developments raise doubts about the traditional role of risk management elements. Huber and Scheytt (2013) wonder why risk management has remained important a'er the malfunction during the financial crisis in 2008. One multiplier during the crises was the mentality of credit institutions driven by monetary incentives (Jacobs et al., 2012, p. 299). Excessive risk-taking among investors played a key role (Huber & Scheytt, 2013, p. 91). To offer a practical education in the field of banking and finance, science and academia should adapt to the changes on the financial market. %e changing requirements for the Austrian banking sector should be provided by the universities. %e knowledge and competencies learned should be rethought and adapted to the current needs of the market. %e contents of a finance and economics study should optimally prepare for a career in the financial market and require a combination of theoretical and practice-relevant knowledge. Considering the changes in risk

202 Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

management should also include academic approaches. %e following articles address the criticism of academic teaching in the context of risk management and banking. %e authors take up this criticism that emerged during the financial crisis and offer a broad analysis. It is clear that a reorientation of the content and the practical relevance of the theory learned are necessary. Peterson (2013) states in his study that the economic crisis has brought much criticism of the economic professions. %is critique opened discussions about the adequacy of the traditional academic business education (Peterson, 2013, p. 401). Blinder (2010) states in his article that the recent events should encourage any professor of a macroeconomics or finance course to rethink their contents taught (Blinder, 2010, pp. 385-386). Friedman (2010) says that the lessons learned from the recent financial crisis should be taken as an impulse to redesign the economic views taught at the universities. %e experiences from the recent financial crisis should change the thinking of the economics profession significantly. %e newly gained insights should also accompany students on their way to the profession of an economist (Friedman, 2010, p. 391). Traditional approaches within economic education focus primarily on basic knowledge that neglects practice-oriented learning (McGoldrick & Pe- terson, 2011, p. 16). McGoldrick and Peterson (2011) also argue that the recent financial crisis created a divergence between the economic doctrine and real economic developments. %e pedagogical approaches should be constantly adapted to the economic changes and crises (McGoldrick & Peterson, 2011, p. 18). Solow (1983) claims that students’ dissatisfaction can be traced back to short-term models that cannot be applied to practical life. Economics is looking for simple ways of thinking to explain complex phenomena. However, simple and one-dimensional structures do not adequately reflect reality. %is is the reason why it is necessary to repeatedly reject and reformulate models. Peterson and McGoldrick (2009) argue that a'er completing university, students should be prepared for real economic life and economic conditions. Finally, Shiller (2010) expresses in his study the dissatisfaction with the teaching of economic - especially macroeconomic - content. Students of business schools perceive their lectures as irrelevant to current crises outside the academic institution. Shiller highlights many complaints regarding the missing correlation between economic education and practice. Obsolete economic content should be discarded on an ongoing basis and the teaching should be supplemented by new relevant topics in order to offer content with a high degree of practical relevance (Shiller, 2010, p. 403). Peterson (2013) looks at how criticism of economic education triggered by the crisis can provide a useful framework for the reorientation of economic education. %e correspondence of theory and practice with new pedagogical ap-

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proaches can promote the necessary sustainability of learning. Expanding and enriching students’ basic knowledge can foster the development of critical thinking. %eories should be explored by questioning and evaluating underlying assumptions. %e combination of theory and practice, should provide a wide range of pedagogical strategies (Peterson, 2013, p. 405). Due to the complexity of the real world, pluralism of theory and methodology should be a part of economic education. Graduates are encouraged to make decisions and distinguish between competing alternatives (Groenewegen, 2007, pp. 22-36). %e crisis highlighted the need for developing the ability to ask questions, find solutions, and apply them to existing problems. %e big criticism during the crisis is the exaggerated self- confidence and arrogance of the involved decision-makers. %is emphasizes the need for a stronger focus on the social dimension in economics (Peterson, 2013, p. 404). %e theory of significant learning by Fink (2013) provides a framework for rethinking economics education and is seen as a response to the criticisms during the recent economic crisis. Streimikiene, Girdzijauskas, and Moskaliova (2014) write that bubbles in the asset market are the main cause for unstable situations in the economy. %e exploding of a bubble has far-reaching consequences and can trigger global crises, such as in 2007. Due to globalization, the effects are not only noticeable in separate economic sectors, but also affect the entire global economy (Streimikiene et al., 2014, p. 13). %is is one of the reasons why the recognition of bubbles and unstable situations is considered an important part of the academic education. Karamouzis and Minsky (1987) claim that crises do not develop according to classic or neoclassic theory. It is a cycle of investing and speculating. With stable economic growth, this speculative financing is profitable and leads to a pyramid scheme. %e education at a University of Applied Sciences especially in Austria has exactly this pluralistic approach as their goal. Students are prepared for actual work environment through practical content during their studies (Brugger, 2014). %e literature shows that in certain areas the academic business education is inadequate for the changing market situation. %ere is a need to fill these gaps and determine which requirements are relevant for Austrian banks. To analyze the requirements and adapt the education in finance and banking, the following questions should be answered during the research.

Research Questions (1) Which requirements in the form of knowledge and skills in risk management are requested by risk managers from Austrian banks to ﬁnance and banking graduates?

204 Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

(a) Which of the requested requirement blocks (risk categories, regulatory guidelines, fundamentals in economics, tools and models) are the most important for the risk management experts? (b) Which knowledge and competencies have the most relevance within the different blocks? (2) What additional skills, competencies and knowledge about the content of (a) should be acquired during a study in finance? %is paper offers a look at the market side and questions the necessary content at the universities to be able to satisfy the market. Exactly this consideration is linked to a targeted research. Relevant content for the curriculum of a university program should not be generated from textbooks, but determined directly from the market. %is results in a combination of market and research side. New insights are expected on the focus of the market side for education, i.e. what knowledge and skills are demanded in Austrian banks. %e added value of this research is the focus on the market to address the need for graduates with financial degrees. %e expected results can change the focus of the future curriculum of higher education studies to a practice-oriented and market-adapted education.

II. METHODOLOGY

Research Method & Sample To answer the research questions and to choose the best possible design for the research, the mixed-methods approach is chosen. %is combines the use of quantitative and qualitative methods. In the same research project both approaches with their procedures and techniques are integrated into each other. %e mixed-methods design subordinates the method to the objective of the research. %rough this multimethod approach a better understanding of complex problems is provided (Baur & Blasius, 2014, p. 153; Kuckartz, 2014, pp. 30-33). %e mixed- methods research design is used to conduct complex research. O'en, research problems cannot be examined suﬃciently by quantitative or qualitative methods alone. Monomethod designs are o'en inadequate for dealing with complex and application-oriented problems. %e immediate practical relevance and the application of the results are prioritized within mixed-methods. Complex problems can be better understood through the combination of qualitative and quantitative approaches. %is multi-method approach enables broader and more comprehensive results and creates a complete picture (Kuckartz, 2014, pp. 51-54). Selecting the participants and interviewing experts represents the qualitative aspect. %e quantitative design of the survey instrument gives numeric values.

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%is novel approach offers an individual design of the survey tool. It combines the advantages of both traditional quantitative and qualitative approaches (Teddlie & Tashakkori, 2010, pp. 7-8). By applying descriptive and qualitative methods of analysis, the results are presented both narratively and numerically. %e analysis of the changing requirements in risk management in Austrian banks and elaborating practice-relevant requirements for graduates of a finance study represents a complex problem. It is necessary to find concrete comparable numerical values for the requirements, as well as individual and subjective assessments from the experts in the risk management of the banks. Furthermore, the practical relevance and the application orientation of the research results for Aus- trian universities of applied sciences and their finance studies are important. For this reason, choosing a mixed-methods research design is ideally suited for the empirical collection of the data for this study. %e relevant sample includes Austrian banks, as the focus of the analysis is on national risk management practices. To ensure the validity of the results, the largest and most market-relevant banks are considered. %e representativeness of the sample is determined based on the size of the balance sheets of the Austrian credit institutions. Both, big banking houses and private banks are included in the sample, with a focus on big banking houses. To achieve statistical relevance, the market of Austrian credit institutions should be adequately covered. %is is achieved when the decision-making risk managers of the market-relevant credit institutions act as participants. %e risk managers of the Austrian banks are the experts used for the following investigations. Due to the status and the expertise of the participants, the personal survey is a qualitative expert interview. Kaiser (2014, p. 41) identifies experts about position, status and attributed knowledge. All respondents are specialists in risk management, have an intensive background in the banking sector and provide subject-specific knowledge in this area. %e individual expert knowledge results from the professional position and the ongoing further education (Baur & Blasius, 2014, pp. 570-571). To best answer the research question and to generate expert knowledge, the participants are systematically selected. %is corresponds to a criteria-driven selection of the sample. %e quota sample is compiled on the basis of theoretical considerations and selected characteristics (Baur & Blasius, 2014, p. 273). For the research process of this study, the participants were selected as a quota sample. Criteria such as the total size of the balance sheet, the market relevance and the sector (private and large banks) of the respective bank play a role in the selection. All 12 participants hold senior management positions in risk management at Austrian banks. Furthermore, all have completed an academic career. Two women

206 Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

and ten men represent the 12 participants. For reasons of anonymity, both the name of the participants and the name of the banks are treated strictly conﬁdential and are not mentioned in this paper. %e trend.Top 500 publishes an annual ranking of Austria’s largest companies. In the banking category, the 17 largest Austrian banks are listed on basis of their balance sheet (trend.Top 500, 2016). Nine out of the 17 listed banks fall into the chosen sample, which represents a percentage of the total balance sheet of 85.29%. Nine major banks and three private banks are considered to expand the range of diﬀerent aspects.

Research Instrument & Procedure Due to the limited time of the participants and the analytical orientation of their position, the questionnaire was chosen as a suitable method. It breaks the complex research topic down to easy-understandable questions, provides a closed framework through its structure and gives the opportunity to quickly access relevant data. %e requirement to compare the answers is given and it focuses the attention of the participants on the presented topic (Petersen, 2014, pp. 17-18). %e survey tool is a questionnaire that has mostly quantitative aspects to ensure comparability of the results. In the questionnaire, the most important aspects of risk management are queried using Likert scales. In addition, weightings and rankings of individual areas are added. %e questionnaire is divided into four blocks: risk categories, regulatory guidelines, fundamentals in economics, tools and models. At the end of each block and at the end of the entire questionnaire there are open questions to encourage participants to make additional comments. %ese supple- ments are noted and used for qualitative data analysis. %e content of the entire questionnaire was compiled through an intensive preliminary search. Here, the ﬁnancial risk of banks was presented in a tree diagram and broken down to its individual components. %is risk tree is the basis of the four risk blocks and was used to select the items. %e survey was held in person of the two-person research team to be able to respond perfectly to questions during the interview. One person takes the role of the interviewer and asks the questions. %e second person of the research team - in the role of the observer - notes all additions, reactions and comments from the expert and acts as a support. Answering the 11-page questionnaire takes about 30 minutes. In the evaluation of the results, both quantitative and qualitative analysis methods are used. %e weights and values from the Likert scales give concrete numeric values and the importance of the individual areas is presented in points. %is ensures a comparability of the resulting values. %ese results are presented as a

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descriptive and explorative analysis. %e additional open and written information were analyzed qualitatively through coding. %e quality criteria of research ensure the quality of the method used. Ob- jectivity, validity and reliability are the classic quality characteristics of a test (Schmidt-Atzert, Amelang, Fydrich, & Schmidt-Atzert-Amelang, 2012, p. 131). %e objectivity was ensured. %e reliability was tested through the split-half reliability (0.868), the Cronbach’s alpha coeﬃcient (0.906) and the Spearman-Brown reliability (0.929). %e validity was ensured through content validity, criterion validity and construct validity.

III. FINDINGS

%e graph below (Figure 1) shows the average rating of the importance of the requirements within all 61 items from all 12 experts. %e highest ranking of the items is within block A “Risk Categories”. %e value of 3.86 indicates the average value of all 12 experts in risk management. %e second and third place are blocks C and B. Block D, “Tools and Models”, was ranked as least important. Figure 1

Source: Researched results

As a further presentation of the results, the average values of the individual items within the blocks are analyzed. Here, the focus is especially on particularly high and low values. In this case, values greater than 4.3 are considered particu-

208 Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

larly high and values less than 2.8 are considered particularly low. %ese limits were deliberately determined to show a tendency within the individual blocks. A comparison within and between the blocks is possible. Figure 2 below shows and compares the selected values. Figure 2

Source: Researched results

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In block A, the “ liquidity risk” and “default risk” are rated as most important. “Equity risk” and “operational risk” are considered to be least relevant. %e average importance rating as a requirement within Block B is greatest for “EU Directives”. Less important from block B are “international guidelines” and “Austrian standard procedures”. %e average assessment of importance as a requirement within Block C is greatest in “investment theory / discounted cash flow analysis” and “basic statistics”. Less important from block C are “dynamic balancing” and “US-GAAP”. %e average importance rating within Block D is greatest in “MS Office”. Less important from Block D are “so'ware development”, “macroeconomic models” and “so'ware architecture”. A comparison between the items shows that the average importance rating across the entire questionnaire is greatest for “MS Office” and “EU Directives”. %e least important of all items is rated “US GAAP”. %e open comments from the risk managers were collected, coded and evaluated. Figure 3 shows the main categories which emerged during the qualitative content analysis. %e value in the category is the product of the number of statements on a specific topic and the number of participants who have addressed the respective topic. %is parameter compares how o'en and how much the risk experts talk about a specific topic. However, a low value does not indicate the irrelevance of the topic. Figure 3 shows this created parameter in a comparative diagram. Figure 3

Source: Researched results

210 Victoria Petsch AN ANALYSIS OF CHANGING REQUIREMENTS IN RISK MANAGEMENT IN AUSTRIAN BANKS... (199 - 216)

Answering the research questions (1) Which requirements in the form of knowledge and skills in risk management are requested by risk managers from Austrian banks to finance and banking graduates? (a) Which of the requested requirement blocks (risk categories, regulatory guidelines, fundamentals in economics, tools and models) are the most important for the risk management experts? Figure 1 shows the average score of the individual blocks, which is the average score of all questions given by all interviewed experts summed up within the blocks. %is presentation places “Block A: Risk Categories” in the first place, “Block C: Fundamentals in Economics” in second place, “Block B: Regulatory Directive” in the third place, and “Block D: Tools and Models” in the last place. (b) Which knowledge and competencies have the most relevance within the different blocks? As presented in Figure 2, the average performance values of the categories within Block A have shown that “liquidity risk” and “default risk” are rated highest. %e experts feel the least relevant is the “market risk”. Banking regulations reached the highest levels within block B. %e last is the “Austrian standards procedures”. Within Block C, the legal bases and statistics have reached the highest levels. Ac- counting has the lowest average value. %e average score in block D is highest for “parametric models” and basic IT skills. %e lowest value is given by the “macroeconomic models”. (2) What additional skills, competencies and knowledge about the content of (a) should be acquired during a study in finance? %e experts have particularly emphasized the importance of a basic business education. An understanding and a basic knowledge is of great importance to be able to specialize. %is specialization is achieved through learning-on-the-job and requires continuous further education. Furthermore, it has o'en been mentioned that flexibility and the application of knowledge to different situations are important for the practice. One of the experts proposes learning through case studies while studying. For some of the risk managers, a comprehensive understanding of the overall process is very important. Especially so' skills should be taught more during the studies. English, analytical thinking, communication skills and the ability to summarize are the main approaches. Furthermore, the area of IT knowledge has a strong focus for the participants. Students should develop the handling of data and Excel to very good level. Oc- casionally, programming, prototyping and dealing with core banking systems are assumed.

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Regulations, directives and laws are of massive importance for a banks’ risk management. %is area should, according to the respondents, be a main part of a university curriculum in finance and banking. However, the experts also assume that it will not be possible to convey the complexity of the regulatory system to an appropriate extent. Another addition to a banking and finance program could be the specialization of certain occupational groups within risk management. %e participants distinguish two groups: legal experts and “quants”. Each of these two professions requires the basics, but should specify into the legal or mathematical field.

IV. CONCLUSION

As mentioned before, Peterson (2013) sees the expansion and enrichment of students’ basic knowledge as necessary to promote critical thinking. She believes that future decision-makers in business and banking should be humbler and more skepti- cal. During their studies, students should make a development into critical, creative- thinking and practical-oriented individuals. %e mindset and attitude of students should be adapted to deal with crises more appropriately in the future. %eories should be explored by questioning and evaluating their underlying assumptions. %e big picture should be captured by combining and integrating different approaches. Just like Peterson, the participants, which are experts in risk management, have a similar view. %e focus should be on a broad base of knowledge and a specialization going into detail. Furthermore, critical thinking and questioning is an important learning process to succeed in decision making. Especially the learning-on-the-job was emphasized. Peterson and McGoldrick (2009) highlight the relevance of integrating pedagogical approaches into content. %e application of active learning, experiments, simulations, field work and cooperative work offer the opportunity to capture and support the interests of students. %e results have shown that knowledge of risk categories is most important for a job in the risk management of a bank. %is suggests that, despite a strong focus on so' skills and communicative competences, the know-how aspect has remained as important as ever. It seems that being an expert within the core issues of risk management should be a basic requirement. %is can also be combined well with the result that the basic education is regarded as the most important requirement by the participants. %e results of this research should serve Austrian universities of applied sciences to rethink the curriculum of their studies in fi nance, banking or risk management and adapt it to the current requirements. %e universities can thus adapt

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the ﬁnancial studies to the market demands and use information directly from the experts in risk management in banks.

Limitations During the interview the research team received the feedback, that some experts see a big difference between theory and practice. Some necessary knowledge, which is of great importance in a bank, cannot be taught at a university because of its complexity and specialization. %e focus of the questionnaire could have been worked out more clearly in advance to minimize the need for explanation during the survey. Another methodological critique is the open design of the qualitative questions. A'er each block open supplementary questions were asked to gain additional inputs. Although the information generated is very valuable, it is broad and difficult to pool. A restriction to concrete and specific open questions would have made the evaluation process much easier and focused attention on the essential.

Further Research %e research on “Requirements for risk management” could be deepened by supplementary analyzes. • A survey of new entrants in the risk management department in a bank would be an appropriate supplement to the survey of managers. %is could probably bring new insights or reinforce the results already found. • In addition, discussions could be done with the human resource department of the respective bank or with external recruiters. %ese experts bring a different perspective on requirements and competencies and could also provide complementary results. • An analysis of job postings from entry-level positions could define the skill set for risk management jobs in the bank. On advertisements for the respective position the requirements are very narrowly worded. %e necessary competencies selected by human resource show the relevant requirements for the job. • %e internal development and training programs of a bank also show in which direction employees should develop. %e training courses for young entrants in risk management reveal the importance of different skills for the job. For this reason, an analysis of the internal training programs could enhance the findings of the survey conducted. • An adaption of the research on an international base could bring new insights and compare different approaches of universities. Based on the results found, a curriculum for a university program in the field

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of banking, finance and risk management could now be refined. %e content could be adapted to the market and corresponded to the requirements of future entrants and newcomers to risk management in Austrian banks. A practice-oriented design of the teaching contents and the educational approaches could offer the university a clear added value of training for the financial market.

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REFERENCES

Baur, N., & Blasius, J. (Eds.). (2014). Handbuch Methoden der empirischen Sozialforschung. Wiesbaden: Springer VS. Retrieved from http://dx.doi.org/10.1007/978-3-531-18939-0 Blinder, A. (2010). Teaching Macro Principles a'er the Financial Crisis. %e Journal of Economic Education, 41(4), 385-390. https://doi.org/10.1080/00220485.2010.510394 Brugger, M. (2014, December 9). FHs versus Universität: Der ewige Clinch. derStandard.at. Retrieved from http://derstandard.at/2000009145226/FHs-versus-Universitaet-Der-ewige-Clinch Fink, L. D. (2013). Creating significant learning experiences: An integrated approach to designing college courses (Revised and updated edition). Jossey-Bass higher and adult education series. San Francisco: Jossey-Bass. Friedman, B. M. (2010). Reconstructing Economics in Light of the 2007-? Financial Crisis. %e Journal of Economic Education, 41(4), 391-397. https://doi.org/10.1080/00220485.2010.510397 Groenewegen, J. (Ed.). (2007). Teaching pluralism in economics. Cheltenham: Edward Elgar. Huber, C., & Scheytt, T. (2013). %e dispositif of risk management: Reconstructing risk management a'er the financial crisis. Management Accounting Research, 24(2), 88-99. https://doi.org/10.1016/j. mar.2013.04.006 Jacobs, J., Riegler, J., Schulte-Mattler, H., & Weinrich, G. (2012). Frühwarnindikatoren und Krisenfrühau8lärung: Konzepte zum präventiven Risikomanagement (1. Aufl.). Wiesbaden: Gabler Verlag. Kaiser, R. (2014). Qualitative Experteninterviews: Konzeptionelle Grundlagen und praktische Durchführung. Lehrbuch. Wiesbaden: Springer VS. Retrieved from http://dx.doi.org/10.1007/978-3- 658-02479-6 Karamouzis, N., & Minsky, H. P. (1987). Stabilizing an Unstable Economy. Southern Economic Journal, 54(2), 506. https://doi.org/10.2307/1059346 Kuckartz, U. (2014). Mixed Methods: Methodologie, Forschungsdesigns und Analyseverfahren. Wiesbaden: Springer VS. Retrieved from http://dx.doi.org/10.1007/978-3-531-93267-5 McGoldrick, K., & Peterson, J. (2011). Significant Learning and Civic Education: Shi'ing Frameworks for Teaching in Light of Learning about the Financial Crisis. Journal of Social Science Education, 10(3), 16-25. https://doi.org/10.4119/UNIBI/jsse-v10-i3-1172 Mertzanis, C. (2013). Risk Management Challenges a'er the Financial Crisis. Economic Notes, 42(3), 285-320. https://doi.org/10.1111/j.1468-0300.2013.12011.x Petersen, T. (2014). Der Fragebogen in der Sozialforschung. utb-studi-e-book: Vol. 4129. Konstanz, Stuttgart: UVK-Verl.-Ges; UTB. Retrieved from http://www.utb-studi-e-book.de/9783838541297 Peterson, J. (2013). Economics Education a'er the Crisis: Pluralism, History, and Institutions. Journal of Economic Issues, 47(2), 401-410. https://doi.org/10.2753/JEI0021-3624470213 Peterson, J., & McGoldrick, K. (2009). Pluralism and Economic Education: A Learning %eory Approach. International Review of Economics Education, 8(2), 72-90. https://doi.org/10.1016/s1477- 3880(15)30067-0 Schmidt-Atzert, L., Amelang, M., Fydrich, T., & Schmidt-Atzert-Amelang. (2012). Psychologische Diagnostik (5., vollständig überarbeitete und erweiterte Auflage). Springer-Lehrbuch. Berlin: Springer. Retrieved from http://dx.doi.org/10.1007/978-3-642-17001-0

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Shiller, R. J. (2010). How Should the Financial Crisis Change How We Teach Economics? %e Journal of Economic Education, 41(4), 403-409. https://doi.org/10.1080/00220485.2010.510409 Solow, R. M. (1983). Cowles and the Tradition of Macroeconomics. Cowles Foundation for Research in Economics, New Haven. Retrieved from http://cowles.yale.edu/sites/default/files/files/ conf/50th/50th-solow.pdf Strauß, M. (2009). Wertorientiertes Risikomanagement in Banken: Analyse der Wertrelevanz und Implikationen für %eorie und Praxis. Univ., Diss.--Marburg, 2008 (1. Aufl.). Gabler Edition Wissenscha'. Wiesbaden: Gabler Verlag / GWV Fachverlage GmbH Wiesbaden. Retrieved from http://dx.doi.org/10.1007/978-3-8349-9961-0 Streimikiene, D., Girdzijauskas, S. A., & Moskaliova, V. (Eds.). (2014). Economic bubbles and financial pyramids: Logistic analysis and management. Economic issues, problems and perspectives. Hauppauge, New York: Nova Science Publishers Inc. Retrieved from http://search.ebscohost.com/ login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=851319 Teddlie, C., & Tashakkori, A. (2010). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences ([Nachdr.]). Los Angeles: SAGE Publ. trend.Top 500. (2016). Leitfaden: trendtop500.at. Retrieved from http://www.trendtop500.at/leitfaden/

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Damira Keček* DATA PREPARATION AND HARMONIZATION FOR CONSISTENT... (217 - 226)

ARTICLE INFO Received: 20.9.2018. Accepted: 15.2.2019. JEL Classiﬁcation: C67

Keywords: ICT sector; input-output analysi; input-output table

DATA PREPARATION AND HARMONIZATION FOR CONSISTENT AND COMPREHENSIVE ESTIMATE OF ICT SECTORS CONTRIBUTION TO NATIONAL ECONOMY

Damira Keček* Valter Boljunčić [email protected]

217 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

Nowadays, information and communication technology (ICT) is one of the most important drivers of continuous growth and development of almost every national economy. $e most common approach that quantiﬁes the contribution of ICT sectors to the national economy and analyses the interdependence among ICT sectors and other sectors of a national economy is input-output (IO) analysis. $e precondition for IO analysis application is the existence of the IO table, the statistical-information basis of the IO analysis. In this paper, the improvement of data preparation and harmonization methodology from available data sources necessary for consistent and comprehensive estimate of ICT sectors contribution to the national economy is described.

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I. INTRODUCTION

Information and communication technology (ICT) is crucial for continuous growth and development of almost every national economy. %e development of the ICT positively contributes to competitiveness, productivity and innovation both at national and international economic level [1], [2], [3]. %e effects of the ICT on economic growth and development can be monitored through the investments in ICT, the production of ICT goods and services and the use of ICT [4], [5]. As a general purpose technology, ICT is implemented and used in almost every segment of business and private life [6]. By incorporating ICT in an increasing number of goods and services as well as creating new goods and services, ICT enables greater production efficiency in the ICT sector and in other productive sectors, i.e. throughout the economy. Over the time, different methods and approaches of quantitative macroeconomic analysis for measuring the economic effects of individual sectors to the growth and development of the national economy have been developed. %e most common approach that quantifies the direct, indirect and induced effects of a particular sector to the national economy is input-output (IO) analysis. %e IO analysis is also known as the cross-sectoral analysis since it analyzes the interdependence between sectors of interest and other sectors of the national economy. It is significant in various aspects of economic development planning [7]. Its importance reflects in the construction of instruments and monitoring of economic policy measures results oriented towards the improvement of the performance of individual economic sectors, competitiveness increase and ensuring a sustainable well-being of society [8].

II. INPUT,OUTPUT TABLES

%e precondition for IO analysis application is the existence of the IO table. %e IO table is the statistical-information basis of the IO analysis, in which the whole productive system of the economy is broken down into a certain number of productive sectors. Wassily Leontief (1906.-1999.) is considered the author of the modern IO analysis. He made the ﬁrst IO tables for the United States national economy for 1919 and 1929. In 1973 he received the Nobel Prize for Economics for the development of the IO methodology and contribution to the economic analysis. Because of great signiﬁcance, IO analysis has nowadays been adopted all over the world as a method for analyzing economic growth and development of the national economy.

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%e importance of the IO table compilation is prescribed by the Regulation of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union [9] according to which every European Union member country is obligatory to compile IO table in every ﬁve years [10]. IO tables are made based on supply and use tables according to the methodology of the European system of national and regional accounts, ESA 2010, a harmonized methodology that generates data about national accounts in the European Union. For the transformation of supply and use tables into IO tables, four basic models are used. Transformation models A, B, C and D are used in generating the product-by-product IO table or activity-by-activity IO table. In the compilation of Croatian IO table Croatian Bureau of Statistics applies B model of transformation which is based on the technological assumptions. IO table of an open economy is made with a separate domestic and import ﬂows. IO table for domestic production is shown in Table 1. Generally, in IO table for domestic production, the whole economy is broken down into productive sectors. IO table for domestic production comprises of three parts. First Table 1.: IO table for domestic production

Source: according to Miller and Blair [8]

part of the IO table shows deliveries of sector i to sector j, noted as , where deliveries of sector i to sector j are determined by the production of the sector j. If production of sector j increases, demand of sector j for inputs delivered by sector and all other sectors of the national economy will also increase. %e second part of the IO table shows the structure of ﬁnal uses , and the third part represents the gross value added structure, .

220 Damira Keček* DATA PREPARATION AND HARMONIZATION FOR CONSISTENT... (217 - 226)

%e main equations in the IO model that describe the ﬂows of goods and services between productive sectors are:

(1)

where represents total production of sector , represents final uses of sector satisfied with domestic goods and services. Sum is intermediate consumption, the sum of the goods and services produced by the sector , which are used as intermediate consumption in the production of goods and services of sector and all other sectors. Technical coefficient is defined as a ratio of a product from sector i that is required by sector j in order to produce one unit of its product. In the matrix form, the system of equations (1) can be written as: X = AX + Y (2) where is column vector of outputs, column vector of final uses and is a square n-by-n matrix of technical coefficients, called technology matrix. %e solution to the system (2), where is I an n-by-n identity matrix, is: X = (I - A) -1Y (3) Matrix L= 0 (I - A) -1 is known as a multiplier matrix or Leontief inverse matrix, whose elements aij represent total direct and indirect output of sector per one unit of final demand in sector j. IO model quantifies direct, indirect and induced effects of each productive sector of economy to the overall economy. %e contribution of sector of interest is equal to the sum of direct, indirect and induced effects of that sector to the overall economy. Two types of IO model differ. IO model in which final consumption is considered as an exogenous variable is called open IO model. Open IO model is used to quantify direct and indirect effects and indicators that determine those effects are called multipliers type I. For their calculation Leontief inverse matrix L= 0 (I - A) -1 is used. If some components of final consumption, mainly households, are considered as endogenous variables, than IO model is called closed IO model. In the closed IO model technology matrix # is expanded in matrix $ with one more row and one more column. Closed IO model enables quanti- fication of direct, indirect and induced effects. Indicators that, except direct and indirect effects, involve also induced effects are called multipliers type II. For the multipliers type II calculation, a square n-by-n matrix , a sub-matrix of matrix , is used.

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III. DATA PREPARATION AND HARMONIZATION

%is research primarily focuses on the improvement of the data preparation and harmonization methodology from available data sources necessary for consistent and comprehensive estimate of the contribution of sectors of interest, i.e. ICT sectors to the national economy. %e main data source in this research is IO table of the Croatian economy for the domestic production for 2010 published by the Croatian Bureau of Statistics [11]. %is IO table is made based on 64 productive sectors that are linked to the NCA 2007 classification sections. Namely, NCA 2007 is characterized by classification system based on four levels. %ose four levels are: section level (one-letter mark), division level (two-digit number), group level (three-letter number) and class level (four-digit number). As the main activities of interest in this research are ICT activities, it is firstly necessary to define ICT activities. Definition for the ICT economic activities identification, accepted by the International Standard Industrial Classification of All Economic Activities (ISIC) Rev. 4 [12, p. 278], is as follows: “%e production (goods and services) of a candidate industry must primarily be intended to fulfil or enable the function of information processing and communication by electronic means, including transmission and display.” %is definition includes ICT activities on the class level and this definition is the basis for the ICT sectors in the IO table identification. Sectors correspondent with the identified ICT classes in the available IO table for the year 2010 are recognized for Croatia. %eir codes and descriptions are: C26 - Computer, electronic and optical products, G46 - Wholesale trade services, except of motor vehicles and motorcycles, J58 - Publishing services, J61 - Telecom- munications services, J62_J63 - Computer programming, consultancy and related services; information services and S95 - Repair services of computers and personal and household goods. Sector codes C26, J61 and J62_J63 are relatively homogeneous and almost completely cover the activities that belong to the ICT activities. In sector codes G46, J58 and S95, classes that do not have features of the ICT are included. For example, as it can be seen in Table 2, in sector code S95, out of eight classes, first two classes are related to ICT activities, that is apart computer and communication equipment repairs, in this sector repairs of other goods that are not ICT related are also included. %erefore, a certain transformations of original data in sector codes G46, J58 and S95 are required to enable the application of the IO table for further calcula-

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tion purposes. Integration of IO tables and Structural business statistics data [13] enable extraction of ICT activities in the heterogeneous sectors by applying the appropriate mathematical techniques. Table 2.: SECTOR CODE S95

Code Description S95 Repair of computer and personal and household goods S9511 Repair of computers and peripheral equipment S9512 Repair of communication equipment S9521 Repair of consumer electronics S9522 Repair of household appliances and home and garden equipment S9523 Repair of footwear and leather goods S9524 Repair of furniture and home furnishings S9525 Repair of watches, clocks and jewelry S9529 Repair of other personal and household goods

Source: Structural business statistics [13]

Additionally, data preparation includes application of appropriate statistical techniques for indirect identification of data that are not officially published in the additional databases, for example Eurostat database, because of data confidentiality. In the Eurostat database, data for some sectors are missing due to the confidentiality purposes, i.e. only a few firms are active in those activities. Without missing data, calculations of the contribution of sectors of interest will not be realistic nor valid.

IV. CONCLUSION

%e IO table, the statistical-information basis of the IO analysis, is for Euro- pean Union member countries available for a limited number of productive sectors, i.e. they are usually available for 64 productive sectors. Furthermore, they are available only for certain periods, i.e. they are usually compiled in every five years. %e problem in the analysis of the ICT sectors contribution is the incompatibility of the definition of the ICT sector with a limited number of sectors available in the IO tables. Furthermore, for the years for which there is no official IO tables there is the problem of limitations of the available ICT goods and services data. %erefore, to obtain a better information base and quality of results for the ICT sectors contribution, it is necessary to prepare and harmonize data. Without data preparation and harmonization, which consists of identification of the ICT

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activities in the heterogeneous sectors, substitution of the missing data and data conversion, the methodology for calculation the contribution of ICT sectors could not be applied appropriately and obtained results would not be realistic nor valid.

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REFERENCES

[1] Iskra Popova, Oliver Popov, and Rolf Dalin, “ICT knowledge 4 ICT diffusion,” Information and Communication Technologies and the Knowledge Economy 2, (2005): 792-799.[2] Michel J. Menou, and Richard D. Taylor, “A grand challenge: Measuring information societies,” %e Information Society 22, no. 5 (2006): 261-267. [3] Mohamed Neffati, “ICT, informational innovation and knowledge-based economy,” Annales Universitatis Apulensis Series Oeconomica 14, no. 1 (2012): 242-251. [4] OECD. ICT and Economic Growth: Evidence from OECD countries, industries and firms. Paris: OECD Publishing, 2003. [5] van Ark, Bart., and Robert Inklaar, R. Catching Up or Getting Stuck? Europe’s Troubles to Exploit ICT’s Productivity Potential. Research Memorandum GD-79, Groningen Growth Development Center: University of Groningen, 2005. [6] Ranfeng Qiu, and John Cantwell, “Revisit the Classification of General Purpose Technologies (GPTs) in Corporate Innovation Research Using Patent and Patent Citation Data,” International Information Management Association, (2015): 87-105. [7] ten Raa, %ijs. %e Economics of Input-Output Analysis. Cambridge: Cambridge Univeristy Press, 2005. [8] Miller, Ronald E., and Peter D. Blair. Input-Output Analysis: Foundations and Extensions. New York: Cambridge University Press, 2009. [9] European Parliament, “Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union,” Official Journal of the European Union 56, (2013): 1-727. [10] Eurostat. European system of accounts ESA2010. Luxembourg: Eurostat, 2013. [11] Croatian Bureau of Statistics. “Tablice ponude i uporabe i input-output tablica za 2010.” Available at: http://www.dzs.hr/Hrv\_Eng/publication/2015/12-01-04\ _01\_2015.htm. Accessed on March 13, 2018. [12] United Nations. International standard industrial classification of all economic activities. Statistical papers, Series M No. 4/Rev.4, Revision 4, New York: Department of Economic and Social Affairs, 2008. [13] Croatian Bureau of Statistics. (2017). Strukturne poslovne statistike. Available at: http://http://www.dzs.hr/Hrv/DBHomepages/Strukturne\%20poslovne\ %20statistike/metodologija.htm. Accessed on March 13, 2018.

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Doris Cerin Otočan HRM AND CULTURAL CAPITAL . INNOVATIVE APPROACH FOR THE DEVELOPMENT... (227 - 246)

ARTICLE INFO Received: 20.9.2018. Accepted: 23.9.2019. JEL Classiﬁcation: C67

Keywords: Human Resource, Cultural Capital, Cultural Tourism, Interdisciplinary Training, Intellectual Capital.

HRM AND CULTURAL CAPITAL & INNOVATIVE APPROACH FOR THE DEVELOPMENT OF CULTURAL TOURISM ON THE EXAMPLE OF THE REGION OF ISTRIA

Doris Cerin Otočan [email protected]

227 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

ABSTRACT

$e paper reﬂects upon the model for development of human and cultural resources for the tourism sector in Istria, Croatia, confronting global trends. $e author set the hypothesis that the planned investment in human resources and into their education in cultural tourism sector, leads to job creation for locals without brain drain, decreases the unemployment rate and strengthens the economy of the territory. $e purpose of this paper is also to elaborate the sector of human and cultural capital, with a special emphasis on domicile human potentials as a fundamental strength of development and employment. $e oﬀer created and shaped in the destination by various factors needs newly-created expert human resources formed and educated abroad (e.g. the Croatian region of Istria), thus gathering numerous best practices whose adaptation will be applicable and implementable on home ground. It is therefore important for the young working population to complete internships in European destinations. $e last part of the research focuses on the added value created by intellectual capital in tourism companies. By investing in intellectual capital, the economic value of the company grows. $e conducted research indicated the advantages of investing in interdisciplinary human resource training and education for the greater competitiveness of the cultural tourism sector in the global race for the market. $is research has made a theoretical contribution and has reached the following conclusions, as well as recommendations for future research within the area: interdisciplinary education of personnel in cultural tourism; investing in the creation of new personnel programs, practices and training systems to achieve competitiveness; valorisation of intellectual capital for improvement business in the tourism sector.

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". INTRODUCTION

Human resources are considered as one of the most important factors for new tourism development. Human potentials planning and education are a recent skill and business technique which contributes to the actualisation of change and realization of competitive advantages and profitability in the cultural tourism sector. For example, Marler (2009) connects human resource management (e.g. policies and practices) also to business strategy and competitive advantages. On the other hand, in terms of cultural tourism, managing cultural capital implies placing cultural assets on the market, making profit and new investments on the territory. World knowledge is increasing, human horizons are expanding and development takes place alongside modernisation and globalisation in the sector of education as well. Human potentials are a strategic factor for the development of cultural tourism, and hence require special attention and participation of the highest management of each organisation or institution in making decisions concerning the activities in the process of education, training and development of human potentials, which globally imply the link of competiveness of a territory or tourist destination. Moreover, human potentials are the key factor of the success of hotels, cultural and tourist institutions and agencies, particularly in complaisance with trends and new philosophies on using human resources presented on the global market. Implemented by the most successful companies, they can provide guidelines and suggestions for the development of an efficient management of human potentials in the tourism sector of the Republic of Croatia. %e author has tried to find the optimal model of human resources management which would allow the competitive development of cultural tourism towards competitors. %e proposed hypothesis is that the planned investment in human resources and into their education in cultural tourism sector, can change and improve the local community, creating new jobs for locals without brain drain, decreases the unemployment rate and strengthens the economy of the territory which improves also social conditions and increase the quality of life of locals. %e focus of this paper is the region of Istria, as the most successful tourism region in Croatia; with the highest number of tourist arrivals and overnight stays. By creating regional strategic documents for tourism development, such as the Master Plan of Tourism of the Region of Istria 2015-2025, the Regional Develop- ment Strategy of the Region of Istria until 2020 and the Istrian Cultural Strategy 2014 - 2020, Istria actively wants to define and manage the future development of tourism and culture as well. Among other elements of development, the documents cited a lack of workforce to perform tourism activities, as well as a lack of hu-

229 !TH INTERNATIONAL SCIENTIFIC CONFERENCE FOR DOCTORAL STUDENTS AND YOUNG RESEARCHERS

man resources to carry out organizational work in culture. It is therefore necessary to build new tourism and cultural infrastructure, with an emphasis on education. According to Baum (2012:126), the skills profile of tourism, in turn, is influenced by the labour market that is available, both in direct terms and via educational and training establishments. %e weak internal labour market characteristics in themselves impose downward pressures on the skills expectations that employers have of their staff and this, in turn, influences the nature and level of training which the educational system delivers. In line with the current economic situation in the Region of Istria, as well in the other region in Croatia and South Eastern European countries, the insufficient support from local and regional sources of funding for human and cultural infrastructures is also supported from European Union funds. On the other hand, the situation in practice is alarming, the problem in the hospitality industry is not only the under-educated tourism staff, but also the lack of staff for the needs of Istrian tourism in general. %erefore, the Government of the Republic of Croatia is finding various short-term solutions for ad hoc problem solving by increasing the quota for importing foreign workers into the country.

#. DEVELOPMENT CODE: EDUCATED HUMAN RESOURCES

In today’s instable and insecure market, the constant is visible only in change and adjustment, which is the precondition for survival in the European and global tourism market; accepting and looking at changes as suitable business opportunities. According to Kayode (2012), the transformation of human resources today is a direct call of the rapid changes within business due to factors such as globalization. %e new global world has widened the talent pool for excellent and marginal workers, and for permanent and fluid workers, which is especially reflected in the tourism sector. %e importance of human resources is more pronounced in the tourism sector, because the man is the holder and executor of activities, and when the said activities are executed, special emphasis is placed on individual work and capability of group work; flexibility, innovativeness, and, most of all, creativity of employees. Human potentials are thus transformed into a growing value in the overall development of territory. Considering the adjustment to turbulent times in the global economy, in his book on staff, author Sikula (1976), as early as the 1970s defined the human factor as the “man-plan”, anticipating future activities of the organisation and business environment, as well as the relative human strength adapted to given conditions (Sikula, 1976:146). According to Becherel and Cooper (2002), globalisation also leads to the demand for highly skilled labour in order to

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generate world-class competitiveness. %erefore, when we combined globalisation with competitive recruitment environments, government legislation is leads to a new generation of personnel policies. In terms of human potential, we have the next situation: increasingly personnel managers have to be aware of global demographics, skill shortages, training needs and supply, unemployment patterns and wage rates. %ere is a two-way investment in cultural tourism; investment from the tourism institutions and companies and from cultural institutions and industry, which leads to creating particular personnel with interdisciplinary education and training in the spheres of culture and economy and tourism, which we call a new generation of cultural tourism managers. According to authors Nadler and Nadler (1991), there are as many as 38.5% of economic entities without strategic planning, while 30.8% of companies do not have an organisational unit in charge of performing activities related to management of human resources, and the said function is covered by managers in collaboration with their partners. Vacancies in cultural tourism, and in the tourism sector in general, are filled using the method of interview, whereas other methods are largely neglected. A'er a company or institution has created a description of work tasks and listed specifications for needed employees, according to authors Van Der Wagen and Carlos (2008), they undertake the usual approach which implies advertising tender announcements in the local or major newspapers, on the website or notice board. %e announcements are now international and published in English, accessible on specialised internet sites dealing with international human resource management. Demand and supply of workforce in the tourism sector is fairly widespread and essential. Today’s fluctua- tion of human resources is a vital process. On the other hand, when candidates become employees, the system of motivation is one of the factors of attracting and keeping skilled individuals in the company, in addition to the stimulation of their productivity and innovativeness. Without these elements, the new generation of employees will not stay in a workplace for a long time, regardless of their wage. Besides a permanent education, possibilities for advancement are another factor keeping employees in their workplace. “In deciding about promoting employees, great attention is also paid to their education, which results in the importance of implementation of professional training into the organisation. Planning the training needs results from the previously performed analyses based on which the management has to define priorities” (Nadler and Nadler, 1991:231) related to human resource management. An individual in the organisation is a central element of success of a company, organisation and/or institution because the man and his brain are irreplaceable

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for timely and accurate decision-making and creation of development guidelines. Personal development is therefore very important for growth and development of companies, especially in the tourism sector, an environment that constantly changes due to increased demand and creation of competitive contents aimed at attracting new visitors to the destination. %erefore, according to Jinadasa’s (2015:106) the five-dimensional model for success and leadership, comprises five key attributes symbolized by: heart, mind, passion, focus, and health. %ese five symbolic attributes appear to govern the success of individuals and organizations under most conditions. %e five elements are: 1. Heart - governs the emotional intelligence needed for empathizing with the others in the company, organization or institution; 2. Mind - governs concrete and abstract intelligence, innovation and creativity for individual and organizational success in today’s highly complex and competitive environments. 3. Passion is what drives people to achieve extraordinary results by aligning their hearts, minds, beliefs, and efforts (passion combined with talent can produce strategies that can transform education, business, and communities in the 21st century). 4. Focus is the convergence of beliefs, resources, and effort that make individuals and organizations strive until they achieve ambitious goals, despite setbacks. 5. Health of both individuals and organizations is the overarching foundation of the other four dimensions, since it can affect all of them positively or negatively. For organizations, health symbolizes sustainability determined by profitable growth, net asset value, liquidity, resilience, innovativeness, and motivated workforce. Organizational health is analogous to a healthy person having a strong immune system that can defend against attacks from most pathogens. Jinadasa (2015:108) also mentions the importance of the IQ (intelligence quotient), which was considered very important element in hiring employees and in the early part of the 20th century it was the only criterion used in selecting and promoting people.

$. THE ROLE OF CULTURAL CAPITAL IN THE DEVELOPMENT OF CULTURAL TOURISM

%e management of cultural capital implies using tangible and intangible culture. Cultural assets require sophisticated management because they are the main resource that can be used, alongside other assets of the territory, in the oﬀer of cultural tourism and tourism in general. We can therefore say that cultural tour-

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ism is in fact heritage tourism, which Jelinčić (2010:39) holds important for several reasons, i.e. it has positive economic and social benefits, it builds and emphasises identity, helps preserve cultural heritage, with culture used as an instrument of harmonization and understanding among people, provides support to culture and helps renew tourism. In the context of sustainable and responsible development, if we discuss cultural capital, other important elements of conservation of cultural resources are an accurate interpretation of resources, an authentic experience of visitors and stimulation of income from cultural goods. All of these require expert teams of people (employees and workers in the sectors of tourism and culture), whose knowledge and acquired practice will create, develop and implement various programmes and cultural tourism projects. %ese working models are considered competitive and profitable, in the sense role of management and the use of cultural heritage, as well as all other cultural assets. Members of cultural working teams are sometimes external expert collaborators or consultants, whom authors Dragičević Šešić and Stojković (2013) consider to be a possible threat to employees and a signal that their knowledge is insufficient, which can threaten their workplace. Permanent education is therefore strongly encouraged through (Dragičević Šešić and Stojković, 2013:85): • attending seminars (paid and unpaid), lectures and the like, • participation of various representatives of institutions in the encounters of national and international networks (networking); • organizing workshops, lectures, meetings within the institution, • occasional teamwork with guests-directors (in the case of theatre), editors and the like, which contributes to creating new insights and standpoints, • changes of work tasks as forms of getting acquainted with the “meeting” work processes (and creating possibilities of replacement in the event of indispensability, e.g. in the theatre), • subscription to professional journals and book publications, • involvement of employees in self-evaluation processes, • debate on changes of objectives and essence of the programme of the institution etc. According to Kot (2009:460), all products on the tourism market have one common and unique feature - their production and consumption are simultane- ous. %at is why they must arise from the creativity and knowledge of the people, who create them. Professionalism and individual know–how of every employee are essential to provide customers with the highest quality products and to satisfy their expectations. %erefore, the quality of the dreams bought by customers and

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served by employees depends on their intellectual potential as specialists in tourism, particularly in cultural tourism. Cultural tourists want more, they are looking for the history and tradition of the destination; they get immersed in folklore elements and customs of the territory, tasting wine and gastronomy delicacies and becoming a part of the space where they are staying, creating a shared present, merging into the daily routine of their respective destination. Each tourist/visitor leaves a part of themselves in the community that they visit. %ere is also an exchange of knowledge between domicile population and consumers. %e destination is becoming enriched, more modern and more contemporary. On the other hand, more intense development of cultural industry which produces and distributes cultural products and services worldwide has brought about the creation of joint projects in tourism, culture and economy. For this reason, managers in cultural tourism had to be additionally educated for work and creation of new modern programmes and projects, acquiring new knowledge and work techniques. For example, the Region of Istria has been using pre-accession assistance of the European Union for the past ﬁ'een years through projects in the very segment of cultural tourism (best practices: %e Municipality of Svetvinčenat with the medieval festival and the reconstruction of Grimani Castle). %erefore, through local and regional administration and regional agencies active in the area of culture, economy and tourism (IKA – Istrian Cultural Agency, IDA – Istrian Development Agency and IRTA – Istrian Development Tourism Agency), a large number of staﬀs have been given interdisciplinary and multidisciplinary education. %ese experts create and develop new projects and implement approved projects. %ere have also been great innovations in project partnership, which implies collaboration based on the public-private partnership model known as 3P (Private Public Partnership) between public administration entities, private companies and non-governmental sector through various civil society associations. %e same model is used for the festivals.

%. HUMAN POTENTIALS- KEY DEVELOPMENT COMPONENT

Cultural tourism in Istria is becoming a three-fold link of economy, i.e. small and medium enterprises; tourism as a social phenomenon and culture, and therefore eﬀorts are invested in educating and training cultural tourism personnel on an interdisciplinary basis. For the best quality of employees in tertiary activity it is needs separate educational directions and HR (human resources) activities. A general problem in Istria and in all of Croatia is whether business entities in culture

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and tourism (primarily cultural institutions and cultural industry in general, hotel companies and tourism factors) possess expert personnel for work in cultural tourism; as well as whether the existing human resources are adequately used in the development of cultural tourism and how to improve the strategy of managing human - potential policy in the segment of cultural tourism? Administrations at all levels, the leadership of tourism companies and representatives of cultural institutions are working to resolve the mentioned problem, because according to Brownell (2008:28), human capital is undeniably a hospitality organization’s most valuable resource and has the potential to provide one of the most sustainable competitive advantages in today’s marketplace. Certainly, one of the solutions is ongoing staff training. %ere is a growing need for knowledge and expert management in the tourism sector. According to Nadler and Nadler (1991:1-2), in time, teaching people how to do their job has become an increasingly more sophisticated need, which is the case in numerous areas of human endeavours and attempts. As the society kept becoming more complex, it affected the growth of providing adequate knowledge and practical skills for people in relation to economic changes. %ere is an interesting specific definition of the manner of creating and developing human potentials, which according to Nadler and Nadler (1991:6) occurs through: 1. organised learning of practice necessary for the employees, 2. with a defined specific timeframe; 3. finding possibilities of professional implementation and/or personal development. However, in terms of human resource management, it is necessary to place emphasis on training, education and development. %e said roles of individuals and groups are used in different ways, though the objective remains the same, namely getting specific employees/ working generation and efficient working teams capable of working and justifying the invested means and time invested in education and development of human potentials. For instance, large tourism companies are developing special centres for development of human potential in the form of improvement of the existing employees and in the form of creating and forming a new generation of employees. Furthermore, concerning the above mentioned “new generation of employees”, there is the example of hotel complexes that hire interns who have completed their education and had the experience of study abroad programmes and internships in European destinations with the final objective of their employment. Training also implies organising conferences, panels and various research activities within the company domain, depending on the segment of work and activities of companies, institutions, agencies or companies at congress centres, hotels to

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create an optimal environment in which the employees will progressively keep acquiring knowledge with as little as possible invested time. Around the world, there are the so-called “knowledge villages”, where large companies use innovative and modern conditions to educate and train their employees, which creates a sensitivity for the society, the entire community of the territory where these companies are active, as well as the business world in general. %e workplace is therefore turned into another home, a space where human resources become the primary element of work and activity, an element which makes profit in a positive and, most of all, creative environment. A growing number of training projects is being developed in the private-public partnership as well, which contributes to the development of destination and the administrative functionality of towns and municipalities, but primarily to creating a shared vision of development. %is is the way to achieve interdisciplinary knowledge throught collaboration of entities in the sector of tourism and culture and a shared promotion of the destination (e.g. the City of Pula and the Region of Istria). Time is money. Investments into knowledge are investments into future creation of profit for companies and destinations in general. Creation of competitive advantages in the global tourism market entails the realisation of the vision and implementation of modern development models, even for a specific development link like human resource management (HRM). %erefore, according to Cross and Carbery (2013:13), the integration between HRM and business strategy is believed to contribute to the effective management of HR, an improvement in organizational performance and the success of a particular business or sector like tourism industry. Cross and Carbery (2013) argue that this is good for the organizations’ competitive advantage, with the possibility of creating a unique HRM system, which is made just for that organization or institution. %is in turn increases competitiveness of a business entity and makes it possible to cope more easily with the quick and sudden changes in today’s turbulent world of economy and business.

&. DOMICILE HUMAN POTENTIALS AND NEWLY CREATED HUMAN RESOURCES AS A BASIC FORCE OF TERRITORIAL DEVELOPMENT

%e wealth of a given territory is reﬂected in the wealth of resources at the dis- posal of a territory. Naturally, the primary resources of cultural tourism are natural and cultural heritage. %e man as an individual or a member of a group is a resource that revives and (re)invents the primary cultural resource, the cultural heritage of the destination. %erefore, as fast and as homogeneous, modern, strategic

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and other development of the territory requires domicile population in the role of human potential as a base form of development. In today’s globalisation, even the management of human potential has changed and adapted to the newly created demand of employees, which is particularly visible in strong and large global tourism destinations where the local population does not suffice to fulfil all the needs for employees in tourism. %is has been happening for a decade in the region of Istria, where one third of overall tourism of Croatia is realised. %e lack of workforce leads to national and international fluctuations of workforce, especially from May to September, for the needs of the tourist season. On the other hand, in terms of presentation and promotion of intangible cultural heritage, the domicile population is the most competent, i.e. the subject that authentically tells the stories of the territory, (story-telling). Intangible heritage is sometimes presented as an “independent cultural asset” (for instance, shoemaking in the city of Vodnjan through a little museum or the making of the batana vessel in the city of Rovinj, also through the eponymous museum, where the locals play the role of initiators of these projects, privately owned or else created in private- public partnership), through stories of autochthonous inhabitants of the destination so that the absorption and acquisition of the territory occurs unconsciously for the tourists. In fact, Jelinčić (2010:80) argues that without a prior intention of participating in the local way of life, the tourist is exposed to local customs, traditions, even language during his stay in a destination, exactly through the domicile population. It is about senior citizens evoking stories and customs from the past involved in folklore societies or various communities and associations engaged in creating cultural and historical contents rooted in tradition. Yet, when we speak about newly created human resources, we mean new expert personnel educated and trained in conformity with the needs of the territory of work and residence. For example, the rural part of the region of Istria over the past twenty years has grown into a world-renowned wine destination (especially for Teran and Malvasia wine varieties), extra virgin olive oil, truffles, prosciutto, sheep’s milk cheese and acacia honey, as well as numerous cultural festivals and events featuring world renowned show business names (festivals like Outlook, Di- mension, Seasplash or concerts of Sting, Zucchero, Elton John, Luciano Pavarotti, Foo Fighters, etc.). Development stimulates the creation of new professions and needs workforce with new and modern knowledge and skills. %is creates new professions, for instance, managers in the cultural and tourism sectors, cultural intermediators, winemakers, olive growers, sommeliers, oil and honey tasters, and exquisite culinary and baking master chefs. New agritourism and rural holiday houses are being built, as well as the small plants for the processing and production

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of typical wine and gastronomic products of Istria. New workplaces are created for the domicile population, so that young and educated human resources remain in the region, whereby they enrich it socially and economically creating a positive demographic picture of the region of Istria, keeping pace with time and contemporary development. %e same thing started happening in the urban part of the peninsula with the establishment of new little family-owned hotels, restaurants, private museums (e.g. the Olive Oil Museum in the City of Pula) and galleries, as well as fashion brands in the textile industry. Jewellery making is also getting a more modern status in terms of creating traditional gold and silver jewellery as well as in the original olive tree jewellery. We can say that although this is a post-recession economic period, it is at the same time an age of revival and renaissance of cra's and small and medium entrepreneurship in Istria. Furthermore, numerous young people from Istria study in European and world-renowned university centres. A growing number of them a'er the completion of studies or internships, as well as a'er attending various professional courses, keep returning to Istria. In their homeland, they materialise the newly acquired innovative knowledge and invest in new programmes, projects and innovations, which contributes to the development and production, creation of economic benefits for the territory and added value in the culturological and economic sense. Still, Istria makes up one third of the overall tourism in Croatia (as already mentioned above), so that domicile workforce does not suffice to fulfil the needs for employees in the destination. %erefore, human potentials for the summer months are not sought only nationally, but especially a'er the Republic of Croatia joined the European Union in July 2014, workforce is also sought in the labour market of the European Union member countries. FIGURE 1.: Model for development of human resources in Istria

Source: Author

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%e model of creation, growth and development of human resources in the territory of Istria can be explained with Figure 1.: domicile human resources and newly developed professional human resources through the interdisciplinary education and training in the ﬁelds of management, culture, tourism and economy creates destination HRM.

'. CREATING NEW MANAGERS

In managing cultural assets, the profile of cultural manager largely differs from the classical scheme of formal education as it implies continuous work on improving one’s knowledge and skills. In this day and age, it is not only about the need to have additional formal knowledge in various areas, in this case, in the field of culturology and economy, but about acquiring various techniques of creative thinking, psychological analyses, market approach and the like. In this regard, Na- dler and Nadler (1991) claim that “managerial knowledge is only the starting point in a proper management of cultural assets which allows the individual to develop creativity, i.e. adjust to a specific case.” %e Region of Istria which comprises various tourism and cultural institutions, associations, agencies and companies engaged in cultural tourism, invests great efforts in creating managers with the new skills necessary for the region to be competitive in the European and global regions and the tourism market, using the development strategy based on new knowledge, experiences, methods and technologies, implementing strategic management of cultural tourism. In a competitive environment, managers have to focus on organisational activities as well as the development of individuals. %rough its Department of International Relations and EU Integrations, Istria has been a fi'een-year-long partner in the realisation of projects related to the internship of university students in European destinations/regions at various cultural, tourism and economic entities, as well as municipal, town, and regional administrations aimed at creating and training new personnel and experts in various fields related to tourism. One such example is the Eurodyssey project, the international youth exchange programme for member regions of the Assembly of European Regions (AER), enabling young people aged 18-30 to acquire professional experience in various areas of activity such as tourism, culture, media, science, IT, agriculture, administration, along with learning or improving the foreign language spoken in the European host region (lasting from 3 to 6 months). %e project involves 40 European regions with the objective of international collaboration, as well as enabling a faster and quality employment upon their return to

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their respective home region. So far, over 200 young people have completed the Eurodyssey project (internship from Istria to Europe and from Europe to Istria). %ere is also the Erasmus programme established in 1987, another interesting programme of student exchange for education, training, youth and sport, available in Croatia since its accession to the European Union in 2014.

*. THE IMPORTANCE AND THE ROLE OF INTERDISCIPLINARY EDUCATION

%e right name for economy, according to Drucker (1993), is “knowledge economy”, in which the only reasonable resource is knowledge, with the “knowledge worker” as its greatest institution or company asset. Drucker claims that “the company business is starting to be about selling knowledge. Learning and new knowledge are becoming a key to success” (Drucker, 1993). Implementation of education in organisations is a complex activity, a task developed and performed within the management of human potentials and one of its most important sub- functions. Moreover, Bahtijarević-Šiber (1996) maintains that education makes it possible for the individual to take over complex new tasks and positions preparing him or her for the future and for the coming requirements. When tourism companies invest in physical (tangible) capital, they perform “a reconstruction” of the company whose increase of quality leads to increasing the revenue. Investments into “intangible” capital, people and knowledge, are at the same time investments into education, research and development. It is necessary to invest time and money into each employee for him or her to become a good expert. In the field of hospitality like tourism, there are several steps in staff education, from tourist guides or reception managers to gallery owners/curators, to the leading top management, people who create and strategically plan work and activities of tourist giants. By the same token, there are various levels of staff, particularly in terms of training in cultural institutions where methods of multidisciplinary acquisition of new knowledge in the sphere of culture and tourism and economy in general are already being implemented. In other words, the link between all forms of acquisition of knowledge (education, training, internship) in cultural tourism is interdisciplinarity. In tourism, the primary branch of development of Istria and Croatia in general, interdisciplinarity is one of the keys to success and a logical follow-up to work and activities following European and global trends and needs, as well as the supply and demand of important tourist markets. Scholarly and/ or didactic approach to education in relation to tourism and/or culture must be

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interdisciplinary. A good practice example in Istria is introducing the Department of Culture and Tourism at the Juraj Dobrila University in the City of Pula, which generated a new generation of interdisciplinary experts for work in the segment of cultural tourism.

+. THE VALUE OF INTELLECTUAL CAPITAL IN CULTURAL TOURISM

In a new economy, the concept of capital changes considerably. %e capital of knowledge makes up added, created value, i.e. value above traditional and “measured” value, and employees are bearers of the said knowledge. %eir knowledge, business experience, ideas, innovations, emotional intelligence, motivation, readiness for team work initiative and loyalty to the institution/company enrich the organisational culture and work process and communication within the company. Developed countries, in the words of Bahtijarević-Šiber (1996), now “produce” and sell knowledge, intellectual activities and services, i.e. brain and “intelligence quotient” products, while direct production and products of “hands and muscles” in general are moved towards less developed countries. Consequently, the USA is selling the world knowledge, design, engineering, organisation, management and etc, i.e. intellectual products or so'ware (Bahtijarević-Šiber, 1996:110). %ere is the shi' from the technological world to the world of digitalisation. Modern managers must be able to cope with the implementation of knowledge and intellectual capital. According to Brajša (1997), these managers, in addition to braveness, readiness to take a risk and use novelties and vision, will be rewarded with success. “Successful management depends on successful use of brain” (Brajša, 1997:60). Along with the aforementioned capital of knowledge, the capital of modern companies also possesses the mobile “just-in-time” capital (e.g. Internet company Yahoo with web pages) and intangible capital. Mobile capital is a capital that must be accelerated, made mobile, because the perception of values changes from static to dynamic forms. Looking at the segment of cultural tourism, intangible capital consists of image, tradition, customer/consumer relations, connections with partners, as well as experience and skills in business activities, acquired knowledge and skills of employees. %erefore, the greatest competitive factor today is personnel, with inbuilt motivation and hard work. Di Campo (1999) believes that the way the employees are treated will mirror their behaviour to customers (in this case, tourists-consumers), which will also aﬀect the creation of motivation and innovative possibilities, i.e. the elements that label and deﬁne an organisation. Further, according to Zeglat and

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Zigan (2014), intangible resources (e.g. knowledge and customer relationships) are key performance drivers in many organisations that create intellectual capital. Rastogi (2003:30) describes IC (Intellectual Capital) as the holistic or meta-level capability of an enterprise to co-ordinate, orchestrate, and deploy its knowledge resources toward creating value in pursuit of its future vision. By the same token, economic value of intellectual capital is important in generating revenue and better performance. In fact, the market price of tourism companies was once derived from the price of hotel complexes as real estate. Today’s situation is different. For instance, if a hotel company or complex has been taken over by a new owner through privatisation or regular purchase, in addition to the image of the hotel (deserved influence and value created by the hotel over the years through positive and good work), the existing human potentials are also valued, along with the sum of intellectual capital, personnel whose know-how contributes to the image and better and more efficient business activities. %is explains the fact that the profit, the main result of a large quantity of activities, according to Di Campo (1999), is also created with intangible assets, the things people know and do. People are not an expense, but generators of company profit, the so-called intangible property monitors. Such company approach focuses on knowledge and preventing the outpour of human energy from companies. %e said items lead to the conclusion that the quality of human potential is a significant key to success of companies and institutions. %e process of forming human capital is a long-term process and it requires much larger resources as opposed to physical capital. Hu- man capital is characterised by a longer expiry date than the useful life of machinery and equipment, claims Di Camp (1999). An expansion of skills, knowledge and possibilities of individuals, variables which affect the overall growth of human capital at the individual level, is the most important element of economic growth and the respective growth of the standard of living. To realise and complete the cycle connected with creating, shaping, using and evaluating intellectual capital in cultural tourism, it is necessary to build a functional, quality and developmentally adaptable educational system, which implies increasing budget allocations for the needs of education at all authority levels, as well as in all segments of private and public activities in tourism. It would systematically be aimed at creating quality human resources.

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.. CONCLUSION

Istria has created a brand of an advanced region whose development is based on tourism, especially cultural tourism, with culture and human potential as the strongest links of growth and development. As already stated herein, in tourist business operations where a unique cultural and tourism product is sold under the umbrella of cultural tourism, a significant role is played by contemporary interdisciplinary educated personnel and experts. It follows from the research that constant changes in tourism trends affect employees who adapt to the economic, political and sociocultural changes in order to offer to the customers as diverse products and services as possible. In the presented research author shows that human and cultural capital also created added value for the companies which is realized through greater economic profits. %e results of research indicate that the planned investment in human resources and into education in cultural tourism sector creates new jobs, reduce the unemployment rate, strengthens the local economy and attracts investors. Confronting global trends, in this paper the author proposes a model for development of human resources for the tourism sector in Istria that summarises domicile human resources and newly developed professional human resources through the interdisciplinary education and training in the fields of management, culture, tourism and economy which creates destination HRM.

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REFERENCES

Bahtijarević-Šiber, F., (1996), „ Značaj i uloga obrazovanja u poduzećima“, RRIF, Vol. 42, No. 5, Zagreb, May, pp. 109-117. Baum, T. (2012). Human resource management in tourism: a small island perspective. International Journal of Culture, Tourism and Hospitality Research, 6(2), pp. 124–132. Becherel, L., Cooper. C., (2002), „%e Impact of Globalisation on Human Resource Management in the Tourism Sector“. Tourism Recreation Research, Vol. 27 (1), pp. 1-12. Brajša, P., (1997), Sedam tajni uspješnog managementa, Zagreb, Alineja. Brownell,J.(2008),“Leading on land and sea: competencies and context”, International Journal of Hospitality Management, Vol. 27 No. 2, pp. 137-150. Cross, C. and Carbery, C., (2013), „Introducing Human Resource Management“ in Human Resource Management, New York, Palgrave MacMillan. Di Camp, (1999), %e 21th Century Manager. Future-focused skills for the next millenium, London, Kogan Page. Dragičević Šešić, M. and Stojković, B., (2013), Kultura / menedžment / animacija / marketing, Zagreb, KIC. Drucker, P.F., (1993), Post-Capitalism Society, New York, Harper-Collins. Istarska županija, (2014), Istarska kulturna strategija 2014.-2020. http://www.istra-istria.hr/uploads/media/20140314_IKS_X2_14_01.pdf (download 25/8/2019). Istarska županija, (2014), Master plan turizma Istarske županije 2015-2025, Horwath HTL. http://www.istra.hr/.app/upl_ﬁles/Master_Plan_Turizma_Istarske_Zupanije_2015-2025.pdf (download 25/8/2019) Istarska županija, (2016): Županijska razvojna strategija Istarske županije do 2020. godine. http://www.ida.hr/ﬁleadmin/sadrzaji/datoteke/ZRS/ZRS_2020__Nacrt__16.2.2016..pdf (download 25/8/2019) Jelinčić,D.A., (2010), Kultura u izlogu, Zagreb, Meandarmedia. Jinadasa, A.N., (2015), „Human Potential Development: A New HRD Model for Turbulent Times“. China-USA Business Review, February 2015, Vol. 14 (2), pp. 100-116. Kayode, O., (2012), Impact of Globalization on Human Resourse Management, Science Journal of Business Management, 3. Kot, E.M., (2009), How to Conduct the Audit of Intellectual Capital in Polish Tourism Business?, Electronic Journal of Knowledge Management, Vol. 7 Issue 4, pp. (459-468), available online at www.ejkm.com. Marler, J. H. (2009). Making human resources strategic by going to the Net: reality or myth? %e International Journal of Human Resource Management, 20(3), pp.515–527.

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Nadler, L. and Nadler, Z., (1991), Developing Human Resources, San Francisco, Oxford,Jossey-Bass Publishers. Rastogi, P.N., (2003), %e nature and role of IC: Rethinking the process of value creation and sustained enterprise growth. Journal of Intellectual Capital, Vol. 4(2), pp. 227–248. Sikula, A.F., (1976), Personnel – Administration and Human Resources Management, USA, John Wiley & Sons. Van Der Wagen, L. and Carlos, B.R., (2008), Event Management Upravljanje događajima za turistička, kulturna, poslovna i sportska događanja, Zagreb, Mate d.o.o.. Zeglat, D. and Zigan, K., (2014), „Intellectual capital and its impact on business performance: Evidences from the Jordanian hotel industry“, Tourism and Hospitality Research, Vol. 13(2), pp. 83–100.

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Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

ARTICLE INFO Received: 25.9.5018. Accepted: 11.6.2019. JEL Classiﬁcation: M41, O1, P45, N5

Keywords: Blockchain; Bitcoin; Cryptocurriencies; Decentralized

BLOCKCHAIN IN A NUTSHELL & AN INTRODUCTION TO COMMUNITY BASED DECENTRALIZED OPEN LEDGER TECHNOLOGIES

Markus Schindler [email protected]

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ABSTRACT

Cryptocurrencies as applications on the Blockchain and community based decentralized open ledger technologies have been very controversial issues ever since they have come into existence. $e underlying technology of cryptocurrencies, the Blockchain, may be an as disrupting technology leap as the invention of the Internet. In simple terms, Blockchain technology is a concatenation of blocks of information – transactions in the case of cryptocurrencies – with certain hashing algorithms using the hash values of previous blocks in the following ones. A copy of the entire Blockchain is stored on each participant’s computer. In case any Blockchain copy is manipulated, for example by changing the transactions data, the other participants will notice this manipulation and overwrite the faulty information. Blockchain technology is claimed to be a very secure technology for storing information. $e aim of this paper, which is part of the research for my doctoral thesis, is to create a deeper understanding of what the Blockchain actually is and how its technology is capable of changing the way people interact with each other without a centralized trusted third party.

248 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

I. BITCOIN, ALTCOINS AND THE BLOCKCHAIN

Cryptocurrencies like Bitcoin and Ethereum are experiencing a veritable boom. However, the prevailing opinion among many investors and consumers, is that these digital currencies are only for computer experts, with no potential as a means of transaction or as an investment. Meanwhile, cryptocurrencies are well known to many, but so far, they are not widely used. Nevertheless, bitcoin and other digital currencies offer countless possibilities for modern payment, investment or transfers, which at the moment are not used by consumers and investors o'en.1 In simple terms, cryptographic currencies are a kind of digital money. %ey are especially versatile on the Internet. %ese currencies, such as Bitcoin, Ethere- um, or Dash, to only name a few, are being generated on a blockchain, an infinite code chain that is constantly being solvable, distributed, and converted by different high-performance computers (a process called ‘mining’). %ey can be freely purchased without restriction, in order to make purchases online or to send money worldwide within minutes. In addition, they are traded on the currency market like classic currencies and used by many investors for speculation.2 %e main difference between cryptocurrencies and fiat money is the regulation, as well as the origin of the money. Traditional money is issued and regulated by a central bank on the basis of investments and debts. By contrast, cryptocurrencies are created as part of the blockchain process. For most cryptocurrencies, the quantity is determined.3 %e storing of cryptocurrencies is different to ordinary money. Cryptocur- rencies exist only on the blockchain in the form of an access code. Since cryptocurrencies are decentralized, they are always owned by the owner of the private key. Usually, cryptocurrencies are kept in so-called wallets, a kind of online access to the Blockchain for managing the digital balance.4 %e price performance of a cryptocurrency is similar to traditional currencies, but it is more volatile and more sensitive to daily news, supply and demand. Anyone who has been closely observing bitcoin development since its beginning is aware of the volatile movements, which has caused the price of the digital currency to ultimately surpass the value of 20.000 Dollar at one point, a'er a lot of ups and downs. Generally, as with other currencies, the basic law of supply and demand ap-

1 Andreas Antonopoulos, Mastering Bitcoin: Programming the open Blockchain (Sebastopol: O’Reilly Media, Inc, 2017), 4. 2 Swan Melanie, Blockchain: Blueprint for a new economy (Sebastopol: O’Reilly Media, Inc., 2017), 2-4. 3 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 80-4. 4 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 5-9.

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plies. In addition, an elevated market value o'en reflects increased investor confidence. Decreasing investor confidence will result in mass selling and a devaluation of the market value - just like a normal currency, only more volatile.5 Cryptocurrencies are versatile and in some cases a very attractive alternative to money. With their low transaction costs, they offer both companies and individuals the ability to send money easily and quickly. Because unlike traditional cash, crypto coins do not exist in a specific location, but only as a line of code on the blockchain, they can move from the sender to the recipient within minutes, or in some cases even seconds - a transaction that would take several days and significantly higher costs with an ordinary bank.6 %e area of cryptocurrencies is still very young and somewhat volatile. Be- cause digital currencies are not regulated, their price performance is even more unpredictable than that of a common currency or stock. For example, if an investor chooses to sell a cryptocurrency in bulk, it has an even greater devaluation effect than it would have on a common currency.7

II. A BRIEF DESCRIPTION OF CRYPTOCURRENCIES HISTORY

%e history of cryptocurrencies is now almost ten years old. %e first concept for the first cryptocurrency was created in 2008. %is is the concept known as Bitcoin. %e inventor is not known to the public until now. %e only reference to the creator(s) is the pseudonym Satoshi Nakamoto under which the first paper on the matter was published in 2008 titled “Bitcoin: A Peer-to-Peer Electronic Cash System”.8 %e history of cryptocurrencies is also the history of Bitcoin. Bitcoin was the first ever digital currency and is still the most best-known crypto coin worldwide. %e first idea of a digital currency based on cryptography dates back to the end of the last millennium, specifically to the year 1998. At that time, Nick Szabo published his ideas on a purely digital currency and in that context spoke of the “bit gold”. A'er that, it took another ten years for Satoshi Nakamoto to develop the first concept for Bitcoin as a digital currency. %e Bitcoin network itself started one year later, in 2009. In January that year, the first 50 Bitcoins were created by the

5 Andreas Antonopoulos, Mastering Bitcoin: Programming the open Blockchain (Sebastopol: O’Reilly Media, Inc, 2017), 9-11. 6 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 80. 7 ose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 5-6. 8 Satoshi Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System”, accessed May 19, 2018, https:// bitcoin.org/bitcoin.pdf.

250 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

so-called mining process. At that time no one expected what enormous value increases would be ahead.9 A'er the introduction of Bitcoin, it took two more years until with Litecoin another cryptocurrency was developed. Overall, there existed barely more than ten digital currencies until 2014, but the “hype” began slowly, starting in 2015. Among the historically earliest digital currencies with the respective year of publication belonged: • Bitcoin: 2009 • Litecoin: 2011 • Bytecoin: 2012 • Ripple: 2013 • Dogecoin: 2013 • Dash: 2014 • Ethereum: 201510 %e history of Bitcoin is still representative for the history of cryptocurrencies as such. %erefore, a look at the history of digital currencies definitely includes a look at the price trend Bitcoin has had over the past decade. In the first year, in 2009, there was still no value relationship with a known central bank currency. For the first time in 2010, some market participants began to place the Bitcoin in relation to the US dollar. Between 2010 and 2013, one Bitcoin - except for short interim jumps – was rarely worth more than a dollar.11 However, there was a veritable price explosion in 2014, when Bitcoin first jumped over the mark of 1,000 Dollars. Nonetheless, the value dropped relatively quickly back to below 500 Dollar. One bitcoin had not yet passed the 1,000 Dol- lar mark in early January of the year 2017 but in late 2017 it was worth more than 20,000 Dollar for a short period of time, followed by a dramatic decrease in price.

9 Swan Melanie, Blockchain: Blueprint for a new economy (Sebastopol: O’Reilly Media, Inc., 2017), 3-4. 10 “Cryptocurrency Overview”, Cryptocompare, accessed May 7, 2018, https://www.cryptocompare. com/coins. 11 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 1.

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FIGURE 1.: Bitcoin Price-Chart (USD)

(Source: coinmarketcap.com, Accessed May 5, 2018) III. BITCOIN & ALTCOINS TECHNOLOGY

A. An Introduction to the Blockchain

While Bitcoin is by far the best-known and most successful example of blockchain-based technologies, the two terms are not synonymous. %e scope of blockchains goes far beyond crypto-currencies: “smart contracts,” administrative bureaucracy, online voting, or, more broadly, a new form of the Internet - not just the ﬁnancial sector may face a blockchain-induced upheaval. At the beginning of each Blockchain is a network of users (nodes) that are interconnected (a peer-to-peer network) and in some way have transactions based on trust. %ese can be ﬁnancial transactions, but also the conclusion of an insurance or the reallocation of a property or any other information.12 Usually, for such a business, a middleman is installed, a so-called “trusted third party”. In the case of a money transfer, this would be, for example, the banks where the paying party and the recipient have their accounts. For other payment transactions, other service providers, such as credit card providers, are interposed. All these middlemen slow down the process of the transaction; they also charge fees for their services, making the transaction even more expensive. With a blockchain, there is no need for a “trusted third party”, which is why we speak of a “trustless system”.13

12 Swan Melanie, Blockchain: Blueprint for a new economy (Sebastopol: O’Reilly Media, Inc., 2017), 94. 13 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 140-3.

252 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

To understand a Blockchain, it is necessary to understand the technical and mathematical foundations. At the beginning of each Blockchain there is a record, which, as mentioned above, can be different things, for the sake of clarity, we assume a financial transaction in this example.14 For each transaction a hash value is being calculated. In the case of financial transactions, the data of the transaction is assigned a string with a defined length by a hash function. %is can be a larger amount of data, summarized by a smaller one - the hash value. Since this is a mathematical function, it always remains comprehensible which record hides behind the hash value. Because of this property, the hash value is also referred to as a “fingerprint of digital data”. Several of these transactions are combined into one block. Each block can be identified by a specific string. %is string, the so-called “block header”, also contains a hash value. %is hash value results from the summary of the hash values of all transactions of the block. %ese blocks are then linearly concatenated. In addition to the information about the transactions of the block, the block header also contains the hash value of the preceding block.15 In this system, individual transactions cannot be changed without changing the entire chain. %is is because changing the transaction data also changes their hash value and thus also the hash value in the block header of the respective block and subsequently also all subsequent blocks. Each new transaction carries the sum of all previous transactions.It is therefore not necessary to involve a third party to ensure whether the counterparty actually has the financial means to pay a certain amount. Since all previous transactions are available on the Blockchain, it can easily be verified at any time how much money each participant of the network possesses. For privacy reasons, all agents on the Blockchain appear under a pseudonym. %us, the blockchain is fraud-proof because it is always possible to track all transactions while hiding the identity of the participants. %is system on its own would not be completely tamper-proof. An even more secure Blockchain must prevent new blocks from being created as desired. %erefore, creating new blocks on the blockchain is tied to a mathematical puzzle. Extensive testing requires finding a specific combination of characters that corresponds to a predetermined target value. %is process is called mining. %e dif-

14 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 27-30. 15 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 106.

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ficulty of the puzzle is steadily adjusted by an algorithm to create new blocks at regular intervals.16 Solving this puzzle takes time and computing power. %e one who delivers the right solution first gets a reward. What exactly this reward looks like differs from Blockchain to Blockchain, on the bitcoin Blockchain miners are rewarded with newly created bitcoins. A further result of mining is, that it validates the transactions in the newly created block. Since mining is very costly and time-consuming, larger blockchains will not allow ordinary users to participate in it – without economical disadvantages - bitcoin mining is taking over commercial data centers with specialized hardware.17 In the original Blockchain concept by Satoshi Nakamoto, Miner, Nodes and User were identical. To use Bitcoin, a node had to be set up first. To do this, you had to download and save the entire blockchain with all the transactions and then participate in verifying transactions and blocks, meaning each node could (and should) act as a miner.18 However, with the specialization and commercialization of mining, the roles soon separated. Specialized hardware and ever-increasing technical requirements meant that mining could only be reasonably and profitably operated by data centers.19 At the same time, better and better wallets have been published, enabling trading on the Bitcoin Blockchain without even participating in the network. Wallets are applications that serve only to initiate transactions on the blockchain. A single server assumes the role of a node, through which various users can communicate with the network without having to store the blockchain itself.20 Only the nodes ensure that the blockchain is replicated. %ey ensure that the blockchain remains tamper-proof by downloading and saving the blockchain and reviewing and distributing the ever-growing stream of transactions.

i. What is a Hash? Hash value is a term used in computer technology in the ﬁeld of cryptology and denotes an alphanumeric value that is generated by a special form of the hash function. %e peculiarity of this mathematical function is, that it maps an arbi-

16 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 49. 17 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 76. 18 Satoshi Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System”, accessed May 19, 2018, https:// bitcoin.org/bitcoin.pdf. 19 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 33. 20 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 5-9.

254 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

trarily long string to a string of fixed length. In practice, the hash value is o'en a string of 32 or 64 characters. %e hash has a one-way character.21 %is means that although the same hash value always arises from a certain string of data with defined character length, conversely, from this figure it is not possible to recalculate the original value. %ese properties make hash values attractive for a variety of applications, such as the following: • Storage of passwords: Instead of the password itself, in computer applications with required login, the hash value of a password is o'en stored instead of the password itself for the authentication. If the password is entered when logging on to the system, the hash value is generated from this and compared with the already stored hash value. • Data integrity: Since hash functions applied to identical data always provide the same values, it can be checked in this way whether data has been dis- torted during transmission over an insecure network.22 An example for hash algorithm is SHA-256 used within the Bitcoin network. FIGURE 2.: SHA256 Hash Value of a datastring

(Source: Own Research)

%e ﬁgure above shows the hash value of the data input “Blockchain” as an output of the SHA256 hash algorithm.

21 Akashi Staoh, ”Uniﬁed Hardware Architecture for the Secure Hash Standard,” in Embedded Cryptographic Hardware: Methodologies and achitectures, ed. Nedjah and de Macedo (New York: Nova Science Publishers, Inc, 2004), 1-16. 22 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 82-5.

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ii. What is a Block? Basically, blocks exhibit a very simple structure. %ere is an area with metadata, the header, as well as an area for the payload, the individual transactions that are combined in one block. %e average number of transactions fluctuates greatly, with between about 1,300 and 2,100 transfers per block over the past year on the Bitcoin Blockchain.23 %e header of a block contains a dozen of fields that are only partially self-explanatory. On the one hand there is pure informational data, on the other hand the hashes. %e block information includes data such as creation date, size or number of transactions. %e hashes ensure the integrity of the database. Since the hash of the current block has processed the data from the previous block, the integrity of the blockchain is ensured - one could not change a block hash without also changing the block before and of course subsequent blocks.24 %ere is one thing special about the hashes within the Bitcoin Blockchain, since they all start with “00000000000000000”. %is is the result of the proof-of- work consensus algorithm, the cryptographic puzzle that must be solved to create a new block. %e goal is to find a hash to a block that just begins with this series of zeroes. %is works changing the so-called Nonce as long as the whole data string gets a specific value without changing the transactional data.25 FIGURE 3.: SHA256 Hash Value of a datastring

(Source: Own Research)

23 Meinel and Gayvoronskaya and Schnjakin, Blockchain: Hype oder Innovation (Potsdam: Universitätsverlag Potsdam, 2018), 36-40. 24 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 71-2. 25 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 90.

256 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

Figure 2 shows the schematic structure of a block. %e figure shows the most important values such as the number of blocks, the nonce, the data, the hash value of the previous block and the new hash value of the current block. %e picture shows, that block “3” is containing the previous hash value information to become a chain of blocks. In addition to the hashes, a “Merkle Root” is also specified. %is hash tree root is used to cryptographically secure the transactions in the block and their correct order. So not only blocks cannot be changed, also the transactions within the blocks are safe.26 %e header contains all sorts of metadata that is relevant for analysis and understanding. Particularly important from a management point of view are the number of transactions, the transfer volume, the transaction fees and the so-called block reward, the reward the miner gets for the creation of the block, so ultimately finding the hash with the leading zeros. Actually, the block reward is 12.5 BTC (Bit- coin) per block. Every 210,000 blocks the reward is halved.27 For understanding the cryptographic puzzle there are at two important values: difficulty and nonce. %e difficulty (of the cryptographic puzzle) is a value that ensures blocks emerge every 10 minutes. In addition, in the case of competing blocks, the one with the higher difficulty is preferred.28 Of course, a block has a specific hash by default, which usually does not start with a bunch of zeros. To achieve a hashing with leading zeros, an additional date is appended to the hash block - until the hash is just “00000000000000000XYZ”. %e other values in the header are basically: timestamp, receive time, bits, size and version of the block header.29 Behind the header there is the actual information data. Transactions consist of one or more sending and receiving accounts, represented as hashes, the IDs of the users or wallets. In a Blockchain explorer, all of these accounts and transactions are clickable links, so it’s easy to see in the browser who sent what and when. Noticeable is the first transaction of each block. Here is usually a message such as “No inputs (newly generated coins)”. %is so-called Coinbase transaction is the transfer of the block rewards for the miner - so there are no existing coins transferred, but new coins generated.

26 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 92. 27 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 39. 28 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 105. 29 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 11.

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Internally, transactions also have all sorts of data ﬁelds such as size, date, block number or number of incoming and outgoing accounts as well as hashes of themselves and the preceding or following transaction.30

iii. Smart Contracts • A Smart contract, besides being a platform for currencies, is one of the most promising applications of a Blockchain. In smart contracts, a contractual rule is written down as code that follows a conditional logic, it follows an “if-then” pattern: if certain conditions are met, a speciﬁc contract term automatically comes into force. While third parties, such as attorneys, usually guarantee that a contract is being honored, smart contract technology ensures compliance with the contract - so there is no need to interpose an intermediary institution to ensure trust between contractors. 31 • Supporters of smart contracts are hoping the technology will ease business processes and fulﬁllment, as well as enhancing contract security • %e Blockchain Ethereum serves as a platform for crypto-currency ethers, while the Blockchain Smart Contracts can be used to create, manage and execute. In Ethereum, Smart Contracts exist as accounts that resemble those of users (user accounts), but are not controlled by a private key, but by the code contained within them. • Currently, the blockchain Ethereum has become the platform for smart contracts. %is is primarily because the oldest and largest blockchain Bit- coin is not designed for the use of smart contracts in its protocol. • You can communicate with these smart contracts, just like any other account, but the contract itself cannot be changed once it’s created and stored on the Blockchain. %at makes it immune to hacker attacks from the outside. • %e contracts could then be traded like cryptocurrencies, but their content would not be a static monetary value, but a particular code that responds to “if-then” events as described above.32 • It is currently not clear which route the development of smart contract technology will take. However, there is a whole lot of possible applications.

30 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 122. 31 Meinel and Gayvoronskaya and Schnjakin, Blockchain: Hype oder Innovation (Potsdam: Universitätsverlag Potsdam, 2018), 64-5. 32 Sunith Shetty, ed., Ethereum Smart Contract Development (Birmingham: packt Publishing Ltd., 2018), 3-5.

258 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

Dapps (distributed apps) can be created on the basis of various smart contracts that are linked to each other.33 • Of course, any form of purchase or lease could be handled through a blockchain and even political elections could be held through blockchains. In theory, this is faster, cheaper, and more eﬃcient, as bureaucratic administrative structures could be saved, and third parties that previously provided security for contractors (such as lawyers, banks, or insurance companies) would become redundant. In practice, however, we are still a long way from that.34 B. Centralized vs. Decentralized vs. Distributed • In a decentralized or distributed structure, there is no institution or center that controls and monitors the monetary system. %is happens with decentralized networks like Bitcoin by the members themselves (P2P). 35 FIGURE 4.: Zentralized vs. Dezentralised Design

(Source: Own Research) For decentralized cryptocurrencies there is no single point of failure. If one component of the system fails, it can still exist. %is is usually not the case with

33 Sunith Shetty, ed., Ethereum Smart Contract Development (Birmingham: packt Publishing Ltd., 2018), 39. 34 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 27-30. 35 Meinel and Gayvoronskaya and Schnjakin, Blockchain: Hype oder Innovation (Potsdam: Universitätsverlag Potsdam, 2018), 221-3.

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banks. As we learned in 2008 and beyond, in the end, citizens had to pay for the system. Systemically, important banks were saved by the taxpayer – the motto: “too big to fail”.36 Although most cryptocurrencies are decentralized, not all cryptic currencies are created decentrally. Some are centrally produced by owner-managed, private- sector companies, such as the Ripple.37 %e Ripple (XRP) is created by the for-proﬁt company Ripple Labs, which retains 80% of new issues and distributes them at its own discretion.38

C. Security, Cryptography and Anonymity

All Bitcoin transactions are publicly and permanently stored on the network, which means that anyone can see the balance and transactions of each Bitcoin address. However, the owner’s identity cannot be associated with the Bitcoin address until the owner reveals information as part of a transaction or otherwise.39 Cryptography is at the heart of Bitcoin. %e only problem is that modern cryptography is hard to understand. %e simplest deﬁnition of encryption is that it should protect information from third parties. It has been like that for a long time and always will be. Whether in war, in diplomacy or on the Internet. If you want to entrust a person with a secret, it is best to meet privately with this person in a safe room. For obvious reasons, this is not always possible. Even the ancient Romans knew this problem. How does the emperor tell his troops in Germania that they should withdraw? If one writes this command on a parchment and lets a rider carry this over, one runs the risk that the rider is overwhelmed by the enemy and the message is used against the Roman troops. %e Romans have therefore used a simple encryption, which is named a'er the great commander of the Caesar code: Each letter in the alphabet is replaced by another letter. ABCDEFGHIJKLMNOPQRSTUVWXYZ becomes FGHI- JKLMNOPQRSTUVWXYZABCDE. Each letter is shi'ed 5 letters to the right. %e number 5 in this system is the secret key known to both the emperor and the

36 Swan Melanie, Blockchain: Blueprint for a new economy (Sebastopol: O’Reilly Media, Inc., 2017), 5. 37 Meinel and Gayvoronskaya and Schnjakin, Blockchain: Hype oder Innovation (Potsdam: Universitätsverlag Potsdam, 2018), 74. 38 Schwartz and Youngs and Britto, “%e Ripple Protocol Consensus Algorithm”, accessed May 2, 2018, https://ripple.com/ﬁles/ripple_consensus_whitepaper.pdf 39 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 111-3.

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commanders. However, in modern days this is not an efficient way of encrypting data.40 Cryptography is mathematics. Asymmetrical encryption works by encrypting with one key and decrypting with the other. Blockchains are based on an asym- metric cryptographic method that differentiates between public and private key. When sending the digital fingerprint of a data string, the data has to be protected from getting manipulated. Each member of the blockchain has a private and a matching public key. A private key creates a unique digital signature of the data. %e hash of the data is encrypted with an associated public key. %e resulting string is equated with a signature. %e recipient of the digital fingerprint will also be sent the public key within the transaction. %is is a derivation of the private key and makes it possible to verify the created signature. Consequently, the receiver gets the hash of data.41 %e recipient of the public key can also verify in this way that only the sender could have signed this hash. Only the published public key of the sender can decrypt the encrypted hash. %us, ownership rights in the blockchain are clearly disclosed.42 However, it is impossible to guess through the public key what the matching private key looks like. Namely, the creation of a public key is based on a similar method as the generation of the character string by the block signing hash algorithm. Whoever is in control of the private key, controls the assets it is linked to.43

IV. IV. ATTACK POINTS OF A BLOCKCHAIN

Blockchain systems are based on proven encryption systems, which basically prevent many attacks. For example, attackers are unable to generate transactions from accounts whose credentials they do not own. Outgoing transactions must be cryptographically signed with these access data. However, relevant blockchain systems are complex and geographically dis- persed, theoretically allowing some kind of attacks. Regardless of their technical vulnerability, blockchain deployments are o'en largely unregulated and prone to fraudulent trades.

40 R. F. Churchhouse, Codes and ciphers: Julius Ceasar, the Enigma, and the Internet (Cambridge: Cambridge University Press. 2002), 1-3. 41 Meinel and Gayvoronskaya and Schnjakin, Blockchain: Hype oder Innovation (Potsdam: Universitätsverlag Potsdam, 2018), 21-2. 42 Daniel Drescher, Blockchain Basics: A non-technical introduction in 25 Steps (Frankfurt am Main: Springer Verlag, 2017), 100. 43 Narayanan et al., Bitcoin 12.5: A Compehensive Introduction (New Jersey: Princeton University Press, 2016), 80-82.

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• If an attacker controls the Bitcoin network, for example by taking over more than 50 percent of the computing power of the network, a fraudulent attack is possible. %e attacker can isolate his part of the network, send a transaction to the smaller remainder of the network, and have it validated. However, the attacker’s network may continue on an alternative blockchain without the transaction and transmit it to the smaller part of the network at any time. Since the alternative blockchain involves more computational power, it overwrites the blockchain that contains the transaction - it has been conﬁrmed, done, but in retrospect it did not happen.44 In practice, no hack of a blockchain is known yet. However, many people lost their funds by careless handling of their private key. Attackers can also take control of computers by phishing or exploiting vulnerabilities. %en it is easy for the attacker to read access data stored on the computer. A remedy is to set passwords for access to access data or to use a hardware wallet that signs the transactions without the access data ever being stored in the memory of the computer being used.45 %ere have also been attacks on crypto-exchanges. Around 850,000 Bitcoin attackers were able to take over in 2014 by hacking the Bitcoin exchange Mt. Gox. Bitcoin exchanges need to store the credentials themselves to manage the accounts for their clients - and may therefore lose them. %e hack of Mt. Gox is not the only known hack of an exchange.46

V. OBTAINING CRYPTOCURRENCIES

A. Crypto-Exchanges

Cryptocurrencies can be bought online on so-called exchanges. Enthusiasts and digital currency investors are meeting there to purchase and trade cryptocurrencies. Bitcoin, Ethereum and other currencies are directly interacting with each other, so that the price is formed by supply and demand, On these exchanges, registered users may submit offers to buy or sell Bitcoins with a different currency. A deal is made as soon as an offer is accepted by the buyer and the seller. Depending on the marketplace, the operators charge a small fee for the successful brokerage of the trade. Buyers and sellers usually pay half of each of these fees.

44 Meinel and Gayvoronskaya and Schnjakin, Blockchain: Hype oder Innovation (Potsdam: Universitätsverlag Potsdam, 2018), 49-51. 45 Swan Melanie, Blockchain: Blueprint for a new economy (Sebastopol: O’Reilly Media, Inc., 2017), 82-3. 46 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 163-8.

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Trading on the crypto exchanges is automated. %e trades on a marketplace, however, are handled manually, so you have to search for a suitable oﬀer yourself. %e conventional currencies US dollar or euro can be exchanged on the crypto exchanges against Bitcoins or other Internet currencies.47 Table 1.: TOP 10 Cryptoexchanges (VOLUME USD)

Exchange Rank Markets 24h Trades 24h Volume Marketshare Name 1 Bitﬁnex 143 >314,511 $1,506,074,538 33% 2 Binance 224 >3,256,420 $1,194,297,329 26% 3 HitBTC 311 >423,266 $257,487,868 6%

Coinbase 12 >162,281 $254,193,290 6% 4 GDAX 5 Quoine 26 >110,218 $226,196,403 5% 6 Bithumb 12 >183,876 $157,016,102 3% 7 Bitstamp 11 >68,236 $141,723,539 3% 8 coinone 6 >168,901 $125,349,982 3% 9 EXX 30 >54,354 $84,408,697 2% 10 BTC-e / WEX 26 >40,980 $82,357,298 2%

(Source: https://cryptocoincharts.info/markets/info, accessed May 19, 2018) Table 1 shows the top 10 biggest crypto-exchanges ranked by trading volume in USD per day. Actually, there are 200 existing crypto exchanges with a total day volume of 4,80 billion USD.

B. Mining

Miners act as auditors on currencies such as Bitcoin and Ethereum. %ey con- ﬁrm the correctness of the transactions, as a kind of witness that person A has sent person B a certain amount of Bitcoin. One block on the Bitcoin Blockchain contains one megabyte of data. Depend- ing on how much information the transactions contains, one megabyte could theoretically be just one transaction but mostly there are several hundreds. %ere is also a reward for veriﬁcation of the transactions contained in the mined block. Depending on the transaction volume, this is currently between 0.4 and 2 Bitcoin. Additionally, they get 12.5 bitcoin to create a block. 48

47 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 71. 48 Elfriede Sixt, Bitcoin und andere dezentrale Transaktionssysteme: Blockchains als Basis einer

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%e reward for creating the block is to ensure that as many people as possible are mining. %at’s an extra safety measure. For if a miner should verify a block that is flawed, indicating a manipulation, all miners will vote on whether the block is accepted. %e more computational power a miner spends on building blocks, the greater his voting power is within the network. 49 Because it takes a lot of computational power to create a block, it is highly unlikely that a single miner will have 51 percent of the total computing power in the Bitcoin network. If a miner had that much power, a so-called 51-percent attack would be possible.50 %e high rewards of 12.5 Bitcoin, equivalent to $ 125,000 at $ 10,000, attract many miners. Many different miners mean a decentralized distribution of computing power. %is makes it harder for a single miner to reach 51 percent. 12,5 BTC as a reward may look strange at first sight. %e amount of the reward is halved every 210,000 blocks. In 2009 there were 50 Bitcoin as a reward, in No- vember 2012, the cut came to 25. Since mid-2016, there are 12.5.51 %e next halving is expected in mid-2020. At bitcoinclock.com there is a countdown until the next cut.52 As the reward system adds only incremental units of the cryptocurrency, strong inflation is prevented. %eoretically, it should also work in the opposite direction: With the increasing interest in Bitcoin, there are more users and thus more demand. More offered coins should satisfy the demand and counteract a dramatic price increase. %is has not worked out due to the Bitcoin hype: In early 2017, the price was under $ 1,000, in December 2017, the $ 20,000 mark was cracked. In addition to halving, there is also a limit on the maximum amount of eligible coins. %ere will be 21 million bitcoins, a'er which there will be no more rewards for building blocks. %is is expected to happen in 2140. Presumably in the year 2032 99 percent of all Bitcoin will be in circulation. At this time, the reward will have fallen to less than one bitcoin per block.53 With more Bitcoin in circulation, the transaction volume is expected to be higher. As a result, miners are collecting more bitcoin from the transaction fees and will continue to mine, keeping the blockchain alive.

Kryptoökonomie (Wiesbaden: Springer Gabler, 2017), 101. 49 Jose Pagliery, Bitcoin: And the Future of Money (Chicago: Triumph Books LLC, 2014), 44. 50 Elfriede Sixt, Bitcoin und andere dezentrale Transaktionssysteme: Blockchains als Basis einer Kryptoökonomie (Wiesbaden: Springer Gabler, 2017), 106. 51 Antony J. Malone, Glossary of Bitcoin terms and deﬁnitions (Toluca Lake: NoHoMedia, 2015), 3. 52 Albert Szmigielski, Bitcoin Essentials (Birmingham: Packt Publishing Ltd., 2016), 25-9. 53 Antony J. Malone, Glossary of Bitcoin terms and deﬁnitions (Toluca Lake: NoHoMedia, 2015), 1.

264 Markus Schindler BLOCKCHAIN IN A NUTSHELL . AN INTRODUCTION TO COMMUNITY... (247 - 268)

%e actual task, verifying the transactions in size of a MB, takes only 0.2 to 0.4 seconds and can be done with a regular computer. Why is so much talk about the high computational effort and power consumption in mining? To maintain the decentralized structure of Bitcoin and prevent the 51 percent attack from occurring, the miners compete against each other to receive the reward. Although this competition is o'en referred to as “solving mathematical puzzles”, it is actually a guessing game. %is concept is called “proof of work”.54 %e first miner to guess the given hexadecimal number, called Target Hash, or a value below, is the winner. If there is a tie, the Bitcoin network decides by a majority vote. Usually, the miner that has invested the most computing power gets the price. Miners need to guess a number-of-only-used nonce, which is 32-bit in Bitcoin. %e nonce is added to the known values of the creating block. %e whole thing is then hashed again. If the result matches the target hash the block is signed.55 %e chance to guess the right nonce is influenced by the level of difficulty. %is level of difficulty depends on the total computing power in the Bitcoin network and is adjusted every 2,016 blocks. If there are fewer miners and the computing power drops, the difficulty level drops. If there are more miners, it will rise. %e difficulty level varies to maintain an average time of ten minutes per new block. %e ten-minute interval was set by Bitcoin inventor Satoshi Nakamoto. When creating the concept for bitcoin, he thought that it takes a minute for all miners to know that a new block has been created and can therefore proceed with the creation of the next block. %e one minute in which they unnecessarily dig for a block that already exists, at the ten-minute interval is a waste of 10 percent of the computing power of the network.56

VI. CONCLUSION

Data security is the major issue and the great strength of Blockchain: every user may download a complete copy of the blockchain. So, every peer can see all the blocks with all the stored information. As a result, all data entries for each participant are traceable at any time and cannot be manipulated. %is structure protects the blockchain from malicious activities and provides transparency. Another possible advantage is the network structure.

54 Albert Szmigielski, Bitcoin Essentials (Birmingham: Packt Publishing Ltd., 2016), 85. 55 Albert Szmigielski, Bitcoin Essentials (Birmingham: Packt Publishing Ltd., 2016), 15. 56 Elfriede Sixt, Bitcoin und andere dezentrale Transaktionssysteme: Blockchains als Basis einer Kryptoökonomie (Wiesbaden: Springer Gabler, 2017), 41.

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All transactions are carried out directly (peer-to-peer principle) between peer participants. %is makes middlemen, such as banks or notaries, superfluous. All participants log the information traffic and there is consensus on the “correct” content. %e consensualization ensures the integrity of the data throughout the system. Blockchain technology is a young technology that is still in its infancy. %ere are many conceivable application areas apart from the use of cryptocurrencies. %e possibilities of Blockchain will affect many industries. In particular, industries with intermediaries in which trust is essential, could soon face tremen- dous upheavals, as blockchain technology offers the possibility of keeping trade repositories forgery-proof - without the effort of central authorities such as central banks, central registers, land registries and notaries. %us, any form of trade currently performed by intermediaries can be mi- grated to dramatically lower transaction costs on a blockchain platform.

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REFERENCES

Antonopoulos, Andreas. Mastering Bitcoin: Programming the open Blockchain. Sebastopol: O’Reilly Media, Inc, 2017. Churchhouse, R. F. Codes and ciphers: Julius Ceasar, the Enigma, and the Internet. Cambridge: Cambridge University Press, 2002. Cryptocompare. “Cryptocurrency Overview.” Accessed May 7, 2018. https://www.cryptocompare. com/coins. Cryptocoincharts. “Exchange, Volume.” Accessed May 19, 2018. https://cryptocoincharts.info/ markets/info. Drescher, Daniel. Blockchain Basics: A non-technical introduction in 25 Steps. Frankfurt am Main: Springer Verlag, 2017. Meinel, Christoph, and Tatiana Gayvoronskaya, and Maxim Schnjakin. Blockchain: Hype oder Innovation. Potsdam: Universitätsverlag Potsdam, 2018. Malone, J. Antony. Glossary of Bitcoin terms and definitions. Toluca Lake: NoHoMedia, 2015. Nakamoto, Satoshi. “Bitcoin: A Peer-to-Peer Electronic Cash System”, Accessed May 19, 2018. https:// bitcoin.org/bitcoin.pdf. Narayanan, Arvind, and Joseph Bonneau, and Edward Felten, and Adrew Miller, and Steven Goldfeder. Bitcoin 12.5: A Compehensive Introduction. New Jersey: Princeton University Press, 2016. Nedjah, Nadia, and de Macedo Mourelle, Luiza, 1-16. New York: Nova Science Publishers, Inc, 2004. Pagliery, Jose. Bitcoin: And the Future of Money. Chicago: Triumph Books LLC, 2014. Schwartz, David, Noah Youngs, Arthur Britto. „%e Ripple Protocol Consensus Algorithm”, Accessed May 2, 2018. https://ripple.com/files/ripple_consensus_whitepaper.pdf Shetty, Sunith, ed. Ethereum Smart Contract Development. Birmingham: packt Publishing Ltd, 2018. Sixt, Elfriede. Bitcoin und andere dezentrale Transaktionssysteme: Blockchains als Basis einer Kryptoökonomie. Wiesbaden: Springer Gabler, 2017. Staoh, Akashi. ”Unified Hardware Architecture for the Secure Hash Standard.” In Embedded Cryptographic Hardware: Methodologies and achitectures, edited by Swan, Melanie. Blockchain: Blueprint for a new economy. Sebastopol: O’Reilly Media, Inc, 2017. Szmigielski, Albert. Bitcoin Essentials. Birmingham: Packt Publishing Ltd, 2016.

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Gerald Seidler BACK-RESHORING & INDUSTRY /." . A RELATIONSHIP FOR THE FUTURE? (269 - 292)

ARTICLE INFO Received: 22.9.2018. Accepted: 15.7.2019. JEL Classiﬁcation: F21, L23, O14, O30

Keywords: Back-reshoring; Cyber-physical ; Industry 4; Internet of %ings; Reshoring

BACK!RESHORING & INDUSTRY 4.0 & A RELATIONSHIP FOR THE FUTURE?

Gerald Seidler [email protected]

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ABSTRACT

A&er a wave of off-shoring manufacturing and services in former decades a new trend to bring outsourced businesses back home (“back-reshoring”) has emerged within the last years. In parallel, Industry 4.0 and the Internet of $ings (IoT) have started to become increasingly important for today’s industry and economy. $is paper first answers the question whether there is a correlation between both topics by conducting a quantitative analysis based on existing publications. Secondly a qualitative analysis confirms that Industry 4.0 is a possible driver for back-reshoring. Demonstrating a relationship in two ways, the results may act as a cornerstone for further research in the combined field of Industry 4.0 and back-reshoring.

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I. INTRODUCTION

Industry 4.0 – the fourth industrial revolution – has been influencing the economy for several years, and probably will do in the future, with huge impacts on manufacturing, business models, employment, as well as on the service sector. %e question whether the manufacturing location decision is influenced by the advances, changes and disruption of Industry 4.0 is the main focus of this paper. %e starting point and underlying theory is that Industry 4.0 leads to back-reshoring of previously off-shored businesses back (or near) to the company’s home country. Derived from this, two main research questions are investigated: RQ1: Is there a correlation between back-reshoring and Industry 4.0? RQ2: Is Industry 4.0 a driver for back-reshoring? First, an overview about and definitions for the topics back-reshoring and In- dustry 4.0 are provided. In the main part, the question of relationships between both topics is investigated by conducting a quantitative analysis based on the number of publications found in the research databases of Google Scholar and Web of Science. It is divided into three steps: 1. Definition of keywords 2. Search process 3. Presentation and discussion of search results In a complementary investigation the qualitative link between back-reshoring and Industry 4.0 is presented. It answers the question whether Industry 4.0 is a potential driver for back-reshoring by showing relationships between effects of In- dustry 4.0 and already identified back-reshoring drivers. Finally, the conclusions are presented and limitations are highlighted.

II. OVERVIEW

For both main topics - Industry 4.0 and back-reshoring – an inconsistent use of the terms is present in academic (and non-academic) literature. In the following, the understanding of both topics in the context of this work is explained.

A. Industry 4.0

%e roots of Industry 4.0 are located in Germany, where the (German-speaking) term Industrie 4.0 was introduced in April 2011. At this time, Industry 4.0 was used to describe an initiative of the German government to improve and

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accelerate the digitization of the German manufacturing industry.1 Already in their first (non-academic) publication in the German VDI magazine the founders of this initiative – Kagermann, Lukas and Wahlster - predicted the chance of new business models based on cyber-physical systems in 2011.2 In their vision the technology of Internet of %ings (IoT) is the enabler for this fourth industrial revolution. Following the German-speaking Gabler Wirtscha'slexikon (economic encyclopaedia) there is no fixed definition available today as Industry 4.0 is a marketing term that is also used in academic communication.3 Lasi et al. summarise the definition problem: “$e term Industry 4.0 collectively refers to a wide range of current concepts, whose clear classification concerning a discipline as well as their precise distinction is not possible in individual cases.” 4 For this publication, Industry 4.0 is understood as the digitization of manufacturing supported by IoT, Artificial Intelligence and Big Data leading to cyber- physical systems in Smart Factories.

B. Back-reshoring

Another new field of public interest and academic research is the area of back- reshoring. A bundle of terms like re-shoring, reshoring, in-shoring, near-shoring or back-shoring have been used inconsistently in the past - as well as by the economic press and academic researchers. In order to implement a well-defined term back- reshoring was introduced in 2013 by Fratocchi et al. as “voluntary corporate strategy to partially or totally relocate the production (in-sourced or out-sourced) to its home country to serve the local, regional or global demand” 5. In the same paper Fratocchi et al. 6 summarise (based on a literature research) the main motivations for back-reshoring: • labour costs • freight costs • operational flexibility • supply chain coordination

1 Siepmann and Graef, “Industrie 4.0 – Grundlagen Und Gesamtzusammenhang,” 20. 2 Kagermann, Lukas, and Wahlster, “Industrie 4.0: Mit Dem Internet Der Dinge Auf Dem Weg Zur Vierten Industriellen Revolution.” 3 Gabler Wirtscha'slexikon, “Stichwort: Industrie 4.0.” 4 Lasi et al., “Industry 4.0,” 240. 5 Fratocchi et al., “Manufacturing Back-Reshoring - An Exploratory Approach for Hypotheses Development,” 2. 6 Fratocchi et al., 32.

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• product quality • availability of well-educated workers • relocation discounts • un-/employment • laws and regulatory conditions • exchange rate risks • know-how transfer Supplementary Ellram et al. list the following “drivers of the global manufacturing location decision” 7:“ 1. %e rising cost of labor in low-cost countries […] 2. %e improving ratio of U.S. labor output/productivity per labor dollar […] 3. %e growing concern toward environmental issues […] 4. %e fast response time and leaner supply chain associated with locating manufacturing closer to the end customer/consumer” In contrast, there are valid reasons for leaving oﬀ-shored manufacturing far away from the home country of a company, for example: • closeness to customer • closeness to supplier • dependence on regional raw materials.

$. CHRONOLOGICAL ANALYSIS REGARDING RESEARCH AREAS

To show the historic development of academic research in both areas – Industry 4.0 and back-reshoring – a quantitative analysis investigating the number of occurrences of publications per year is carried out. %e following process model is formulated: 1. Deﬁne Keywords a. for Industry 4.0 b. for back-reshoring 2. Search a. Web of Science (WoS) Core Collection8 i. with Industry 4.0 keywords ii. with back-reshoring keywords iii. combined with Industry 4.0 and back-reshoring keywords

7 Ellram, Tate, and Petersen, “Oﬀshoring and Reshoring: An Update on the Manufacturing Location Decision,” 14–15. 8 Clarivate Analytics, “Web of Science Core Colletion - Clarivate.”

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b. Google Scholar9 i. with Industry 4.0 keywords ii. with back-reshoring keywords iii. combined with Industry 4.0 and back-reshoring keywords %e reason for searching Google Scholar too is to also find pre-publications and not WoS-listed articles. %e goal is to demonstrate a reflection of research interests in both research areas – not only for high-level research. 3. For Web of Science results: analyse directly on Web of Science, sort by year of publication, download result for data clean-up and unified visualisation in SPSS 4. For Google Scholar: retrieve results from Google Scholar per year and collect the results for analysis in SPSS 5. Copy results (from Web of Science and Google Scholar) to SPSS 6. Show single and combined results in diagrams

A. Deﬁnition of keywords

In the first step keywords are to be defined by area of research. %e selection of related keywords is based on preliminary literature research. %e reason for the selection of each keyword is displayed in the following tables. i. Keywords for back-reshoring For back-reshoring the following keywords are defined. Table 2.: Search keywords for back-reshoring

Keyword Reason “back-reshoring” Reshoring is used in literature with the same meaning as back-reshoring 10 reshoring Other variants (like “near reshoring”) are also covered with this keyword. Alternative spelling to reshoring; also “re- “re shoring” shoring” is considered by both search engines when searching for “re shoring”

9 Google LLC, “Google Scholar.” 10 Wiesmann et al., “Drivers and Barriers to Reshoring: A Literature Review on Oﬀshoring in Reverse,” 23. 11 Wiesmann et al., 23.

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Keyword Reason Backshoring is used in literature with the same meaning as back-reshoring11 “back shoring” is not considered as keyword backshoring as there are too many false positives in regard to shoring as discipline of engineering (construction). Onshoring is used in literature with the same meaning as back-reshoring “on shoring” is not considered as keyword as onshoring there are too many false positives in regard to shoring as discipline of engineering (construction). Near-shoring means outsourcing to a country/ region near home. As this paper focusses on the decision to re-locate close to the home market, nearshoring a location in a neighbouring country may be as close as somewhere else in the home country itself. Alternative spelling to nearshoring; also “near shoring” “near-shoring” is considered by both search engines when searching for “near shoring”

Source: Author’s editing ii. Keywords for Industry 4.0 For Industry 4.0 the following keywords are deﬁned. Table 3.: Search keywords for Industry 4.0

Keyword Reason “Industry 4.0” German-speaking root, also used in English- "Industrie 4.0” speaking publications Cyber-physical systems are the basis for Industry 4.0. Both search machines ﬁnd as well “cyber physical” as “cyber-physical” results with this search term. It also covers the term cyber-physical production “cyber physical” systems, which especially German-speaking researchers use when writing English publications. English-speaking (especially) US- based researchers prefer the term manufacturing instead of production. Smart factories are (a vision for) the “smart factory” manufacturing entities of Industry 4.0

12 Wiesmann et al., 23.

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Keyword Reason “Smart Manufacturing, which is the fourth revolution in the manufacturing industry and is also considered as a new paradigm, is the collection of cutting-edge technologies that support eﬀective “smart manufacturing” and accurate engineering decision-making in real time through the introduction of various ICT technologies and the convergence with the existing manufacturing technologies.” 13 %e Internet of %ings (“IoT”) “refers to the networked interconnection of everyday objects, which are o&en equipped with ubiquitous intelligence.” 14, applied to industry it is called Industrial Internet of %ings (“IIoT”). % “industrial internet of things” “ e IIoT is a new revolution resulting from the convergence of industrial systems with advanced computing, sensors, and ubiquitous communication systems. It is a transformative event where countless industrial devices, both old and new, are beginning to use Internet Protocol (IP) communication technologies.” 15

Source: Author’s editing

B. Search process

%e search is conducted using the search databases Web of Science and Goog- le Scholar. For Web of Science results are represented differentiated by: • Database: Web of Science Core Collection • covering all databases • 1. Topic (including title, abstract, keywords) and • 2. Title only %e search on Google Scholar is conducted without considering patents and citations differentiated by: • 1. Whole text • 2. Title only %e tables in the following chapter show the search results for each single keyword and for the combination of all keywords, first by research area (back-reshoring, Industry 4.0) and a'erwards with the combined result of both areas. %e search strings used for single key word searches and especially for the combined searches are mentioned directly within the result tables.

13 Kang et al., “Smart Manufacturing: Past Research, Present Findings, and Future Directions,” 111. 14 Xia et al., “Internet of %ings,” 1101. 15 %ames and Schaefer, “So'ware-Deﬁned Cloud Manufacturing for Industry 4.0.”

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To cover only full years, search results are considered up to the year 2017.

C. Search results and Discussion

First, the results per keyword are presented grouped by area, search database and search type to provide a general overview about the frequencies of according literature. In a second step results are investigated on a chronological basis (by year) to show the trend development for each topic (Industry 4.0 and back-reshoring) as well as for the combination of both topics. i. Results by keyword, search type and search database

Back-reshoring Table 4.: Back-reshoring - Web of Science

Keyword Number of results (topic) Number of results (title) “back-reshoring” 4 1 reshoring 128 69 “re shoring” 19 7 backshoring 22 13 onshoring 23 9 nearshoring 48 22 “near shoring” 19 9 “back-reshoring” OR reshoring OR “re shoring” OR 230 127 backshoring OR onshoring OR nearshoring OR “near shoring”

Source: Web of Science – 17.4.2018

Table 5.: Back-reshoring – Google Scholar

Keyword Number of results (whole) Number of results (title) “back-reshoring” 341 30 reshoring 3770 392 “re shoring” 1070 46 backshoring 952 64 onshoring 1190 34 nearshoring 2650 89 “near shoring” 1190 16

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Keyword Number of results (whole) Number of results (title) “back-reshoring” OR reshoring OR “re shoring” OR 8140 632 backshoring OR onshoring OR nearshoring OR “near shoring”

Source: Google Scholar – 17.4.2018 %e comparatively small number of results for “back-reshoring” itself reﬂects the fact that this term was introduced in 2013 to represent a new deﬁnition covering the other related topics. Reshoring (also as a part of most of the keywords) holds the highest frequency, but also “nearshoring” is treated in a large number of publications.

Industry 4.0 Table 6.: Industry 4.0 - Web of Science

Keyword Number of results (topic) Number of results (title) “Industry 4.0” 1858 682 “Industrie 4.0” 302 102 “cyber physical” 9431 4223 “smart factory” 496 193 “smart manufacturing” 521 196 “industrial internet of things” 480 180 “Industry 4.0” OR “Industrie 4.0” OR “cyber physical” OR “smart factory” OR “smart 11978 5500 manufacturing” OR “industrial internet of things”

Source: Web of Science – 17.4.2018

Table 7. : Industry 4.0 – Google Scholar

Keyword Number of results (whole) Number of results (title) “Industry 4.0” 18200 1800 “Industrie 4.0” 19000 1960 “cyber physical” 76700 7280 “smart factory” 6490 370 “smart manufacturing” 6750 525 “industrial internet of things” 5110 322

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Keyword Number of results (whole) Number of results (title) “Industry 4.0” OR “Industrie 4.0” OR “cyber physical” OR “smart factory” OR “smart 17200* 8710 manufacturing” OR “industrial internet of things”

Source: Google Scholar – 17.4.2018

For “Industry 4.0” - as a term introduced in 2011 - the number of publications compared to the (still most frequently found) keyword “cyber physical” is at about a ﬁ'h. But it is already ranked at the second place, far beyond e.g. “smart manufacturing“. %is shows the high relevance the term Industry 4.0 has reached. *Note: As a non-comprehensible eﬀect of the usage of Google Scholar, the search over all keywords provides 17200 results, which is lower than the number of results for single keyword searches like for “Industry 4.0” or “cyber physical”.

Industry 4.0 & Back-reshoring – combined %e latter four tables show that there are much more publications treating the emerging topic of Industry 4.0 than focussing on back-reshoring activities. %e next two tables show the results for the combined search of both areas – Industry 4.0 and back-reshoring. Table 8.: Industry 4.0 and Back-reshoring – Web of Science

Keyword Number of results (topic) Number of results (title) (“Industry 4.0” OR “Industrie 4.0” OR “cyber physical” OR “smart factory” OR “smart manufacturing” OR “industrial internet of things”) 2 0 AND (“back-reshoring” OR reshoring OR “re shoring” OR backshoring OR onshoring OR nearshoring OR “near shoring”)

Source: Web of Science – 17.4.2018

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Table 9.: Industry 4.0 and Back-reshoring – Google Scholar

Keyword Number of results (whole) Number of results (title) (“Industry 4.0” OR “Industrie 4.0” OR “cyber physical” OR “smart factory” OR “smart manufacturing” OR “industrial internet of things”) AND (reshoring OR “re shoring” OR backshoring OR onshoring OR nearshoring) Note: %e search string had to be shortened as the Google 456 2 Scholar query length is limited.

Source: Google Scholar – 17.4.2018 %e results for both search engines show that there are only a limited number of publications available that combine both areas. %e result of the Google Scholar search indicates that there are already several publications listed that cover both topics, and that there are already two publications available targeting this combined research topic in the title, both were published in 2017: 1. Industry 4.0 and its impact on reshoring decisions of German manufacturing enterprises16 2. Bringing it all back home? Backshoring of manufacturing activities and the adoption of Industry 4.0 technologies17 ii. Results compared on chronological basis To go into more detail, in this section the results are investigated chronologi- cally on a yearly basis.

Back-reshoring %e following ﬁgure shows the number of publications for back-reshoring keywords on yearly basis for Google scholar searches (full text and title only search) and Web of Science search (topic).

16 Müller, Dotzauer, and Voigt, “Industry 4.0 and Its Impact on Reshoring Decisions of German Manufacturing Enterprises.” 17 Dachs, Kinkel, and Jäger, “Bringing It All Back Home? Backshoring of Manufacturing Activities and the Adoption of Industry 4.0 Technologies.”

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Figure 1.: Back-reshoring – Web of Science & Google Scholar

Source: Web of Science and Google Scholar - Author’s calculation

A strong increase of interest in back-reshoring is observable starting in 2003, when the number of publications found by Google Scholar full search rose to thir- teen, then in the following year growing to 62 and in 2008 already to 274 publications per year. %e Google Scholar title only search follows a similar trend – although about two years later. Justified by the type of search (title only) the number of publications is smaller compared to the full search. A'er reaching a first step to five publications in 2004, it doubled in 2006 and once again by 2010 with 20 publications per year. %e further development shows the next strong increase in 2012 with 53 publications followed in 2014 with a peak of 96 publications per year. %e Web of Science topic search shows a similar trend to the Google Scholar title only search. Due to the fact that the publications listed in Web of Science are subject to higher requirements of academic rigor and quality, the database contains a lower quantity of publications in general – subsequently leading to a lower number of results. A'er reaching three publications per year in 2004 the next increase is observable in 2007 to eight publications. A'er a 50 percent decrease in the following year a plateau was reached in 2009 staying more or less constant until 2012 with between nine and eleven publications per year. %e last significant rise is observable 2013 tripling the number to 28. In the following years the value varies in a range up to the peak of 35 publications per year in 2016.

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%e movements of the curves for the Google Scholar title only search and the Web of Science topic search show a correlated development. Considering the logarithmic scale of the chart the Google Scholar full search curve shows a kind of predictive indicator for the two other curves.

Industry 4.0 %e following ﬁgure shows the number of publications for Industry 4.0 keywords on a yearly basis for Google scholar searches (full text and title only search) and Web of Science searches (topic). Figure 2.: Industry 4.0 – Web of Science & Google Scholar

Source: Web of Science and Google Scholar - Author’s calculation

Even though Industry 4.0 was introduced in 2011 as a term, Google Scholar full search, in particular, shows that already in 1983 the first publications are available treating related keywords. In 1989 already 30 publications per year are available, doubling first until 1993 (66 publications), then a second time until 1998 (131 publications) and a third time until 2004 (267 publications). In the following years a continuous immense growth is observable, breaking the mark of 10,000 publications per year in 2014 and reaching the peak in 2017 with more than 17,000 publications. %e Google Scholar title only search and the Web of Science topic search show a similar development. In 2006 respectively 2007/8 the first steps for the strong in-

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crease are taken, reaching about 50 publications per year. In 2010 both searches show about 200 publications per year, and doubled in 2011, breaking the mark of 1,000 publications ﬁrst in 2014 and ending at about 3,000 publications per year in 2017. Additionally, the results indicate that there was a shi' in 2016 among the searches. Since then the Web of Science search present more results than the Google Scholar title only search (2016: 2993 vs. 2320; 2017 3625 vs. 2860. As already observed while investigating the back-reshoring results, for the area of Industry 4.0 a very strong correlation between the Google Scholar title search and the Web of Science topic search is visible in the ﬁgure above.

Back-reshoring compared to Industry 4.0 A'er investigating each area separately, the search results for both areas – back-reshoring and Industry 4.0 – are compared directly. To preserve readability the results the following ﬁgures are separated by search type (Web of Science topic search, Google Scholar full search, Google Scholar title search). Figure 3:. Back-reshoring and Industry 4.0 – Web of Science

Source: Web of Science - Author’s calculation

From 1999 to 2007 both Web of Science topic searches – for back-reshoring and for Industry 4.0 keywords – show a similar development of the curves. Start- ing from 2008 the rapid rise of interest in Industry 4.0 topics is recognizable. For

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back-reshoring the greatest step is perceivable in 2013 from 9 to 29 publications per year. Figure 4.: BACK-RESHORING AND INDUSTRY 4.0 – Google Scholar title only

Source: Google Scholar - Author’s calculation

%e results for the Google Scholar title search show that in 2004 the number of publications for back-reshoring were on the same level as for Industry 4.0 (about ﬁve publications per year). In the following year a decline for both areas is visible, but it represents a starting point for a continuously increasing number of publications in subsequent years for both areas. %e rise of Industry 4.0 – based on the broader ﬁeld of research – is substantially larger than the upward trend for back-reshoring.

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Figure 5.: BACK-RESHORING AND INDUSTRY 4.0 – GOOGLE SCHOLAR full

Source: Google Scholar - Author’s calculation

%e Google Scholar full search shows again the ﬁrst rise of interest in the In- dustry 4.0 topic, starting in the early 1980s. Within the early 2000s a huge increase of interest in back-reshoring is observable, bringing the curve closer to the Indus- try 4.0 curve. Starting from this point in time a continuous increase in the number of publications for both research areas is observable.

Back-reshoring combined with Industry 4.0 A'er the separate investigation of the search results for each single area ﬁrst, and a'er comparing both areas in the latter step, the results for the combination of both topics – back-reshoring and Industry 4.0 – is investigated.

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Figure 6.: Back-reshoring and Industry 4.0 - combined search

Source: Web of Science and Google Scholar - Author’s calculation

For the combined search, the Google Scholar full search provides the ﬁrst results starting in 2011 followed by a massive increase in the subsequent years. Google Scholar title search and Web of Science topic show the same quantitative result – with two publications covering both topics starting in 2017. To represent this data in another way the following bar chart shows the number of results for each combined search.

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Figure 7:. BACK-RESHORING AND INDUSTRY 4.0 - COMBINED SEARCH – bar chart

Source: Web of Science and Google Scholar - Author’s calculation In this figure (with linear scale) the development of research covering both topics Industry 4.0 and back-reshoring is shown. %e Google Scholar full search – used as a kind of predictive indicator (derived from the findings above) – indicates the increasing relevance of the combination of both topics, underlined by the results of the two other combined searches – each with the first two publications in 2017.

IV. INDUSTRY (.) AS A /POTENTIAL0 DRIVER FOR BACK, RESHORING

%e previous chapter presented ﬁndings about the quantitative correlation between back-reshoring and Industry 4.0. In this second part a qualitative examination is conducted targeting the question whether Industry 4.0 is a potential driver for back-reshoring. Industry 4.0 as well as back-reshoring are quite young research topics that have been gaining increasing interest and attraction within the last ten years. As shown in the quantitative analyses, there is only limited (academic) literature available focusing on the interrelationships between these two topics. Nevertheless,

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deduction and combination from existing research and knowledge of each single area lead to inter-connecting findings. %e basic idea for gaining new insights is to test whether commonly known effects of Industry 4.0 match with back-reshoring drivers (that were already identified in preceding research). For the first steps the following characteristics for Industry 4.0 are identified: Table 10.: Effects of Industry 4.0

Full automation and digitization of manufacturing in smart factories lead to 4.0 • lower employment needs/rates (especially) aﬀecting low-cost workers, • increasing product quality (as human errors are avoided, assuming mature cyber-physical manufacturing capabilities), • higher ﬂexibility in manufacturing (provided that smart factories are self-organized), • increasing need of well-educated technology-, robotics- and data- specialists and • rising productivity (as robots are able to work 24 hours a day, without vacancies or sick-leaves – only suspended for maintenance breaks)

Source: Author’s editing

%e overview of drivers for back-reshoring has already been presented in the introductory chapter II.B Back-reshoring. In the table below these drivers are linked to the characteristics of Industry 4.0 listed in Table 9. (from the perspective of a high-developed country like Germany or USA) to show relationships. Table 11.: Industry 4.0 and the motivations for back-reshoring

Industry 4.0 Motivators for back-reshoring • labour costs (if savings are higher than costs for additional high-level technicians) • less low-cost workers • rising costs of labour in low-cost countries • need for high-level technicians • no know-how transfer to another country • availability of well-educated workers

• product quality • operational ﬂexibility • fast response time • increasing product quality ﬂ • leaner supply chain • exibility in manufacturing • supply chain coordination (probably more complex for Industry 4.0 – but assumed to be handled fully-automated by machines) • improving ratio of U.S. labour output per • rising productivity labour dollar

Source: Author’s editing

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%is comparison demonstrates that there are main characteristics and consequences of Industry 4.0 available that ﬁt to the attributes of the drivers for back- reshoring.

V. CONCLUSION & LIMITATIONS

%e main goal of this publication was to explore whether there is a correlation between back-reshoring and Industry 4.0. Firstly, a qualitative analysis of publications by topic and year was conducted using the research databases Google Scholar and Web of Science. As Google Scholar also includes papers, studies and other publications that are not (yet) published in peer-reviewed high-quality journals (and also grey literature) it offers the opportunity to show trends of interest in specific topics earlier than Web of Science. Web of Science on the other hand provides high-quality publications. By using the mix of both search databases Google Scholar was identified as a kind of predictive indicator for the development of the number of publications in subsequent years – at least in these specific areas of research, where relatively new topics are investigated. In general, Industry 4.0 represents a much wider area of research compared to back-reshoring. A'er investigating each single topic separately, the results of both areas were compared on a yearly basis and a correlating trend was observed. %e final quantitative analysis targeted publications that cover back-reshoring and In- dustry 4.0 topics. Only two publications were found in Web of Science published in 2017, and these were the first. Accompanied by the Google Scholar search, which shows the first results in 2011 and already presents more than 170 publications in the year 2017, the results underline the conclusion that this combined field of research – Industry 4.0 and back-reshoring - is relatively new and indicates mas- sively increasing interest. Besides the advantages of the usage of Google Scholar in this study, there are also several limitations to consider. Google Scholar provides only estimates of the number of results, so it is not exact. Furthermore, for the integration of publications in the search database there is no comprehensible quality assurance mechanism available. Additionally, there are only limited possibilities for restricting the search available, e.g. no abstract-only search (comparable to topic in Web of Sci- ence). Also, the length of the search string is limited, which affected the study directly as the more complex and longer search string had to be amended. Finally, the supplementary qualitative investigation showed that Industry 4.0 is a potential driver for back-reshoring. As soon as the path to digitization - introduced with Industry 4.0 supported by the Internet of %ings, Artificial Intelligence,

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Big Data and robotics - accelerates, also the resulting impacts on our economy will become increasingly intensive. %at may lead to an increasing influence of back- reshoring drivers and consequently to a higher degree of back-reshoring. Surrounded by an increasingly complex and volatile world and economy, In- dustry 4.0 can only be one potential driver for a management decision to start back-reshoring. It is not the intention to cover all possible influencing factors for back-reshoring, which would go beyond the possible scope for this research paper and could be topic for further research. Another approach to go more into detail and to strengthen the theory of a correlation between Industry 4.0 and back-reshoring could be a statistical time-series comparison, with the prerequisite to find a suitable method combined with the availability of required data. Furthermore, additional research about the intrinsic and essential relationships between back-reshoring an Industry 4.0 is suggested. A suitable strategy could be a review of the publications that relate to the quantitative analysis carried out in this paper. Finally, another starting point for further research based on real reshoring cases could be the public available collections provided by the European Reshoring Monitor18 focusing on European examples and the Main Reshoring Library of the Reshoring Initiative19 centring mainly on cases from North America.

18 Eurofund, “European Reshoring Monitor.” 19 Reshoring Initiative, “Main Reshoring Library.”

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REFERENCES

Clarivate Analytics. “Web of Science Core Colletion - Clarivate,” 2018. https://clarivate.com/products/ web-of-science/web-science-form/web-science-core-collection/ Dachs, Bernhard, Steffen Kinkel, and Angela Jäger. “Bringing It All Back Home? Backshoring of Manufacturing Activities and the Adoption of Industry 4.0 Technologies.” MPRA Munich Personal RePEc Archive, no. 28953 (2017): 1–31 Ellram, Lisa M., Wendy L. Tate, and Kenneth J. Petersen. “Offshoring and Reshoring: An Update on the Manufacturing Location Decision.” Journal of Supply Chain Management 49, no. 2 (2013): 14–22. https://doi.org/10.1111/jscm.12019 Eurofund. “European Reshoring Monitor.” European Reshoring Monitor, 2018. https://reshoring. eurofound.europa.eu/ Fratocchi, Luciano, Paolo Barbieri, Carmela Di Mauro, Guido Nassimbeni, and Matteo Vignoli. “Manufacturing Back-Reshoring - An Exploratory Approach for Hypotheses Development.” RSA AiIG 2013, no. Ocotober (2013): 1–35 Gabler Wirtscha'slexikon. “Stichwort: Industrie 4.0.” Gabler Wirtscha'slexikon, 2017. http:// wirtscha'slexikon.gabler.de/Archiv/-2080945382/industrie-4-0-v2.html Google LLC. “Google Scholar,” 2018. https://scholar.google.com Kagermann, Henning, Wolf-Dieter Lukas, and Wolfgang Wahlster. “Industrie 4.0: Mit Dem Internet Der Dinge Auf Dem Weg Zur Vierten Industriellen Revolution.” VDI Nachrichten. Berlin: VDI Verlag GmbH, April 2011 Kang, Hyoung Seok, Ju Yeon Lee, SangSu Choi, Hyun Kim, Jun Hee Park, Ji Yeon Son, Bo Hyun Kim, and Sang Do Noh. “Smart Manufacturing: Past Research, Present Findings, and Future Directions.” International Journal of Precision Engineering and Manufacturing-Green Technology 3, no. 1 (January 23, 2016): 111–28. https://doi.org/10.1007/s40684-016-0015-5 Lasi, Heiner, Peter Fettke, Hans Georg Kemper, %omas Feld, and Michael Hoffmann. “Industry 4.0.” Business and Information Systems Engineering 6, no. 4 (2014): 239–42. https://doi.org/10.1007/s12599- 014-0334-4 Müller, Julian, Verena Dotzauer, and Kai-Ingo Voigt. “Industry 4.0 and Its Impact on Reshoring Decisions of German Manufacturing Enterprises.” In Supply Management Research: Aktuelle Forschungsergebnisse 2017, 165–79. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. https://doi. org/10.1007/978-3-658-18632-6 Reshoring Initiative. “Main Reshoring Library.” Main Reshoring Library, 2018. http://www. reshorenow.org/main-reshoring-library/ Siepmann, David, and Norbert Graef. “Industrie 4.0 – Grundlagen Und Gesamtzusammenhang.” In Einführung Und Umsetzung von Industrie 4.0, 17–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. https://doi.org/10.1007/978-3-662-48505-7_2 %ames, Lane, and Dirk Schaefer. “So'ware-Defined Cloud Manufacturing for Industry 4.0.” Procedia CIRP 52 (2016): 12–17. https://doi.org/10.1016/j.procir.2016.07.041 Wiesmann, Benedikt, Jochem Ronald Snoei, Per Hilleto'h, and David Eriksson. “Drivers and Barriers to Reshoring: A Literature Review on Offshoring in Reverse.” European Business Review 29, no. 1 (January 9, 2017): 15–42. https://doi.org/10.1108/EBR-03-2016-0050

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Xia, Feng, Laurence T. Yang, Lizhe Wang, and Alexey Vinel. “Internet of %ings.” International Journal of Communication Systems 25, no. 9 (September 2012): 1101–2. https://doi.org/10.1002/dac.2417

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