Masaryk University Faculty of Economics and Administration Field of Study: Business Management

QUANTITATIVE MARKETING RESEARCH

Master Thesis

Thesis Supervisor: Author: doc. Ing. Radoslav ŠKAPA, Ph.D.. Mark RATILLA, 440120

Brno, 2016

MASARYK UNIVERSITY

Faculty of Economics and Administration

MASTER’S THESIS DESCRIPTION

Academic year: 2015/2016

Student: Mark Ratilla, B.Sc.

Field of Study: Business Management (Eng.)

Title of the thesis/dissertation: Quantitative marketing research

Title of the thesis in English: Quantitative marketing research

Thesis objective, procedure and methods The aim of the thesis used: The aim of the thesis is to conduct an individual research project that will focus on some marketing problem.

Research design

The author is expected to (1) suggest a marketing- related research topic (e.g. consumer behavior research), (2) to prepare a research de-sign that utilizes the quantitative analytical methods, (3) to collect the data,(4) to analyze the data using statistical methods and (5) to interpret the results.

Extent of graphics- According to thesis supervisor’s instructions related work: 60 – 80 pages

Extent of thesis SMITH, Scott M. and Gerald S. ALBAUM. Fundamentals of without marketing research. Thousand Oaks: Sage, 2005. xii, 881. supplements: ISBN 0761988521. Literature: EASTERBY-SMITH, Mark, Richard THORPE and Paul JACKSON. Ma-nagement research. 4th ed. Los Angeles: Sage, 2012. xvi, 371. ISBN 9780857021168.

MALHOTRA, Naresh K. Marketing research :an applied orien-tation. 6th ed., Global edition. Boston: Pearson, 2010. 929 s. ISBN 9780136094234.

HAIR, Joseph F., Robert P. BUSH and David J. ORTINAU. Marketing research :within a changing information environment. 3rd ed. Bos-ton: McGraw-Hill, 2006. xxvii, 700. ISBN 0072830875.

SAUNDERS, Mark, Philip LEWIS and Adrian THORNHILL. Research methods for business students. 6th ed. Harlow: Pearson, 2012. xxxi, 696. ISBN 9780273750758.

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Thesis supervisor: doc. Ing. Radoslav Škapa, Ph.D.

Thesis supervisor’s department: Department of Corporate Economy

Thesis assignment date: 2015/04/15

The deadline for the submission of Master’s thesis and uploading it into IS can be found in the academic year calendar.

...... prof. Ing. Antonín Slaný, CSc. dean Head of department

In Brno, date: 2016/04/08

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STATEMENT OF AUTHORSHIP

I hereby declare that the Master thesis “Quantitative Marketing Research” and relevant research in its background is entirely my own work, supervised by doc. Ing. Radoslav ŠKAPA, Ph.D..and has not been taken out of the work from others. The used literary resources and other specialist resources have been cited and acknowledged within the text of the thesis and listed in the References according to the relevant legislation and regulation.

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ACKNOWLEDGEMENT

“Try not to become a man of success. Rather become a man of value.”

Albert Einstein

The author would like to recognize with sincere gratitude the people who provided their assistance and shared their knowledge, time and effort for the success of this diploma thesis:

doc. Ing. Radoslav ŠKAPA, Ph.D, thesis supervisor, for the opportunity to work on a study on quantitative marketing research. Your guidance, patience, encouragement and supervision were of great help in finishing this piece of work;

To Ms. Jana Nesvadbová, international students’ coordinator of the faculty of

Economics and Administration, thanks for the help in distributing the survey questionnaire to all students in the faculty;

To all the faculty and staff of the faculty of Economics and Administration, your warm treatment and friendship extended to the author will never be forgotten;

To the ERASMUS MUNDUS coordinators and EXPERTS4ASIA team and the

European Union, thank you for the financial support given throughout the entire study period;

To his co-Filipino students and friends: Glorybeth, Ate Balot, Ate Ella, Ate Pauline,

Tsend, Hung, Reaskmey; his classmates and all others, thank you for making my thesis experience a memorable one; and, to Gelai, thank you for your unending support, for being there in times when I needed help;

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Heartfelt thanks to his mother and father, for their encouragements and support throughout his studies. Thank you so much for your presence and moral support. Both of you are God’s major blessing to me!

To Kuya Jowa, Ate Dianne, Ther and Agnes, thank you for encouraging me to finish this my diploma thesis on time;

Above all, to the Almighty God, for HIS countless blessings, wisdom and unfailing guidance, in making things possible during the conduct of the study and in the writing of the manuscript;

Finally, to all people whose names are not mentioned here, thank you very much!

Mark C. Ratilla

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TABLE OF CONTENTS

MASTER’S THESIS DESCRIPTION ...... i STATEMENT OF AUTHORSHIP ...... iii ACKNOWLEDGEMENT ...... iv TABLE OF CONTENTS ...... vi LIST OF TABLES ...... viii LIST OF FIGURES ...... ix LIST OF APPENDICES ...... x ABSTRACT ...... xi INTRODUCTION ...... 2 1.1. Objectives of the Study ...... 4 1.2. Time and Place of the Study ...... 4 REVIEW OF LITERATURE ...... 5 2.1. The Growth and Contribution of Online Shopping...... 5 2.2. Fundamentals of Consumer Behaviour ...... 6 2.2.1. Theory and Models on Consumer Purchase Behaviour ...... 6 2.3. Basic Factors affecting Consumer Purchase Behaviour ...... 12 2.4. Consumer Behaviour in the Online Environment ...... 14 2.5. Hofstede’s Cultural Dimension Scores: Philippines Vs Czech Republic ...... 20 2.6. Online Buying Behaviour in Relation to Culture ...... 21 MARKETING RESEARCH CONCEPTS AND PRINCIPLES ...... 26 3.1. Nature of Marketing Research ...... 26 3.2. Classification of Marketing Research ...... 27 3.2.1. Quantitative VS Qualitative Marketing Research ...... 28 3.3. The Marketing Research Process: A Brief Overview ...... 29 3.4. Marketing Research in the Online Environment ...... 35 METHODOLOGY ...... 37 4.1. Site Selection ...... 37 4.2. Research Model and Hypotheses ...... 37 4.3. Research Design ...... 39 RESULTS AND DISCUSSION ...... 43

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5.1 Respondents Profile ...... 43 5.1.1. Internet Use and Experience by Nationality ...... 43 5.1.2. Internet Use and Experience by Gender Differences ...... 45 5.2. Frequency of Online Shopping ...... 45 5.2.1. Internet Use/Experience and Frequency of Online Shopping ...... 46 5.2.2. Products Bought Online ...... 47 5.3. Respondents’ Perception towards the Factors Affecting Online Shopping Adoption ... 49 5.3.1. Perception towards Previous/Current Online Shopping Experience ...... 50 5.4. Hofstede’s Cultural Dimension in the Online Buying Behaviour ...... 59 CONCLUSIONS AND MANAGERIAL IMPLICATIONS ...... 67 6.1. Conclusions ...... 67 6.2. Managerial Implications of the Study ...... 71 6.3. Limitations and Recommendations for Future Study ...... 73 LITERATURE CITED ...... 75 APPENDICES ...... 84

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LIST OF TABLES

Table 1 Online Retail Ranking: Scale and Potential 6 Table 2 Profile of respondents 43 Table 3 Scores of Factors Influencing Online Shopping Adoption 49

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LIST OF FIGURES

Figure 1 Hofstede's Model Score between Philippines and Czech Republic (Source: The Hofstede's Centre, 2015) 20 Figure 2. Chronological Stages of Marketing Research Process 32 Figure 3. Theoretical Model Generated to Facilitate Understanding of Buying Behaviour of Consumers in the Online Environment 38 Figure 4 Time spent per week in surfing the web 44 Figure 5 Gender and time spent per week in surfing the internet 45 Figure 6 Frequency of using the internet for shopping 46 Figure 7 Relation between frequency of online shopping and time per week 48 Figure 8 Products bought in the internet 48 Figure 9 Products bought online by nationality 48 Figure 10 Respondents’ thoughts about perceived ease of use in internet shopping 51 Figure 11 Ease of navigation and frequency of using the internet for online shopping 51 Figure 12 Respondents’ perception towards web site attractiveness 51 Figure 13 Perception towards on time delivery of products 52 Figure 14 Safety Perception towards Online Shopping 53 Figure 15 Online Shopping Scams Experience 54 Figure 16 Product description perception of respondents 55 Figure 17 Online Shopping Frequency and Perception towards product description perception 55 Figure 18 Product Comparison Perception by Nationality 56 Figure 19 Frequency of Online Shopping and Online Product Information 56 Figure 20 Types of Products Bought by Gender 59 Figure 21 Educational Attainment and Frequency of Online Shopping 59 Figure 22 Likelihood of Shopping Alone in the Online Purchase Behaviour 60 Figure 23 Reliance to External Reasons in Making Online Purchase 61 Figure 24 Attention to Brand Name in Making Online Purchase 62 Figure 25 Avoidance to Newly Introduced Products in Making an Online Purchase 62 Figure 26 Preference to Purchase Products Representing Own Status or Referent Group 64 Figure 27 Importance of Superiors' Ideas and Opinions in Making Purchase Decisions 64 Figure 28 Importance of Product Quality and Efficiency in Online Shopping 65 Figure 29 Purchase based on Immediate Needs 66 Figure 30 Purchase based on immediate needs based on nationality and gender 66

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LIST OF APPENDICES

Appendix A 1 Survey Questionnaire 85

Appendix B 1 Cross-tabulation result - Nationality and Length of Internet Use 89 Appendix B 2 Cross-tabulation result - Nationality and Time spent surfing the web 89 Appendix B 3 Cross-tabulation result - Nationality and Often Use Internet for Shopping 90 Appendix B 4 Cross-tabulation result - nationality and web site attractiveness 90 Appendix B 5 Cross-tabulation result - Nationality and Shopping Scams 91 Appendix B 6 Cross-tabulation result - nationality and product description 91 Appendix B 7 Cross-tabulation result - nationality and product comparison 92 Appendix B 8 Cross-tabulation result - nationality and shopping alone 92 Appendix B 9 Cross-tabulation result - nationality and reliance to external reasons 93 Appendix B 10 Cross-tabulation result - nationality and attention to brand name 93 Appendix B 11 Cross-tabulation result - nationality and avoidance to newly introduced products and innovation 94 Appendix B 12 Cross-tabulation result - nationality and products of my own status and referent groups 94 Appendix B 13 Cross-tabulation result - nationality and ideas/opinions of superior people 95 Appendix B 14 Cross-tabulation result - nationality and the value of product quality and efficiency 95 Appendix B 15 Cross-tabulation result - nationality and purchases based on immediate needs 96 Appendix B 16 Cross-tabulation result - nationality and purchase based on immediate needs 97 Appendix B 17 Correlation analysis result between length of time of surfing the web (in years) and the frequency of online shopping 97 Appendix B 18 Correlation analysis results between frequency of online shopping and the respondents’ perception towards safety of shopping online 98 Appendix B 19 Chi-square test result on the perception of internet shopping safety between nationalities 98

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ABSTRACT

Adoption of online shopping varies depending on the culture and the shopper’s exposure to the internet. This study was conducted to: 1) determine the magnitude of online shopping adoption; 2) identify major drivers and barriers affecting online shopping adoption and dis-adoption; 3) explain the impacts of national culture; and 4) propose implications as to how e-marketers should address customers’ behavior to maximize profitability and sustain competitive advantage. Results revealed that Czechs and Slovaks used the internet shopping more intensively compared to Filipinos. Secure payment process was perceived greatly among the three nationalities to highly influence their online shopping engagement. Culture also affects online shopping behavior. Unlike Czechs and Slovaks, Filipinos express high dependence on the influence of interpersonal communication or opinion of friends/relatives including superiors’ ideas and opinions as well as purchase products based on immediate needs. In addition, the emphasis on risk and the initiative to minimize it through minding reputable product brands and avoidance to new products and innovation is less pronounced among Czech and Slovaks. All these results imply that e-retailers should devise strategies to create a more positive online shopping experience to a wide range of customers. These include accurate description of products, on time delivery, offer various payment options and have an effective dispute-resolution facility. Tapping web assurance service is also a good initiative to alleviate consumers’ trust and confidence. As opinions of superiors and the influence of external reasons matter for Filipinos, this enhances the effectiveness e-retailers’ initiative to tap social media to expose customers’ online shopping experiences and initiate word of mouth marketing. E-retailers must also perform a cost-benefit analysis for appropriate decision making. For future study, it is suggested to increase sampling size of respondents for a better generalization of results.

Keywords: Quantitative marketing research, Hofstede’s cultural dimension, online shopping, consumer behaviour, culture, Czech Republic, Slovakia, Philippines

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PART I

INTRODUCTION

The existence of the internet has significantly affected retail businesses nowadays. Since, traditionally, goods and services were only offered in brick and mortar (physical) stores. However, with the presence of technology-driven generations and further heightening of technological development, the internet has driven businesses to transition its typical marketing mode into a more convenient and encouraging way.

Likewise, the internet has able to facilitate companies in streamlining its operations, allowing better communication to customers and reducing unnecessary costs incurred (Millyard, 2015). Besides, a new business function called e-business/e-commerce was created with a platform to facilitate buying and selling of goods and services through the internet (Vitez, 2015). With the nearly 2 billion people using the internet, e-commerce made a strong contribution to economic growth, generating around 3.4% of the GDP across large economies (Manyika and Roxburgh, 2011).

Apparently, e-commerce has been clicking in the market as it continues to provide soaring contribution to the economy. Several reasons can explain why this happened. But obviously, buying and selling on the internet present several advantages primarily to the users as compared to traditional stores. In the online environment, a number of products to choose can be found in just few clicks. It also allows sighting of products with the lowest possible price (Vannier, 2013). With this, brick and mortar businesses have been continuously haunted by this new technology.

In developed countries, internet shopping is obviously voluminous. With fast and cheap internet connection, online retailing is able to attain success. On a report published by Cushman and Wakefield Research Publication (2013), data showed that developed countries have significant involvement in online retail environment. On top was United Kingdom followed by USA and Germany while Czech Republic ranked only 33rd. Moreover, though the internet is able to unite people and businesses, but still in the external environment significant differences were observed on the way how consumers behave and how e-retailers do business in both developed or developing countries. One of reasons might include cultural

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differences. Besides, Park and Jun (2003) mentioned that cultural imperatives pose a strong impact on the adoption and use of internet in marketing of goods and services.

E-retailers still continue to face a number of challenges in the online environment, inhibiting them to craft stable and sound marketing decisions for amplified performance.Thus, to keep up with this dynamic e-business environment, they need timely, accurate and relevant information for better and smart decision making. These informations may include the nature and the behavious of customers (who they are and how they behave), products and services, price and its means of distribution (Shukla, 2008).

In all existing businesses of today, customers as always play a very important role. They are critical determinants for its survival, success and viability. Thus, paying utmost attention to customers, through understanding their behavior in the market as well as how they interact with the dynamic external enviroment, facilitates marketers or businessmen to craft sound marketing decisions. This can be aided by a marketing research which encompasses series of scientific procedures in gathering and analyzing information for a sound marketing decision making. It seeks to uncover marketing opportunities and problems which facilitates the understanding of marketing processes and accordingly find ways of how to do it better (Shukla, 2008).

As internet shopping continues to be renowned, users or customers at different age groups are also soaring up. According to Statistica Inc., (2014), among the users, a significant 26.5 percent were at age between 25 to 34 years old, followed by users between 15 and 24 years old at 25.4 percent; which are common age range for university students. In other words, students represent a significant portion of the target market of e-retailing businesses.

Being aware on every aspect of the targeted consumers (e.g. behaviour, culture, etc) is crucial in attaining business success. Thus, the study aims to explore how do university students in both developed and developing countries behave in online shopping environment. It also seeks to find out motivating and constraining factors affecting them to go online shopping through quantitative marketing research. In so doing, gathered information will be used as basis in crafting suitable marketing decisions and subsequently assist in the development of strategies that upkeep the preferences or needs of the present generation.

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1.1. Objectives of the Study

Generally, the study aimed to examine the online buying adoption and behaviour between university students in the developed and developing countries.

Specificially, it intended to:

1. provide an overview of the basic characteristics and magnitude of online shopping adoption between students in the specified countries; and 2. identify the major drivers and barriers affecting their online shopping adoption and dis-adoption 3. explain the impacts of national culture in relation to internet buying behaviour among students in the specified countries; and 4. develop recommendations as to how e-marketers should adapt the ever changing behaviour of the specified consumers in order to maximize profitability and sustain competitive advantage.

1.2. Time and Place of the Study

The study was conducted in Brno, Czech Republic from November 2015 to June 2016. Online survey application such as “Qualtrics” was used to gather data among respondents in the Philippines and Czech Republic.

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PART II

REVIEW OF LITERATURE

2.1. The Growth and Contribution of Online Shopping

Internet shopping has significantly grown and is increasingly becoming popular since its inception two decades ago. Statistica Incorported (2015) concealed that around 41% of the global internet users have purchased goods and services online and is believed that this number will continue to rise as internet users may also increase in the following years. Placing attention to the countries involved in this study, Czech Republic have around 8 million internet users (34th in rank, 0.25% share of world internet users) and is expected grow annually by 3%. Meanwhile, the Philippines consists of 39 million internet users (16th in rank, 1.38% share of world internet users) and an annual 10% growth is predicted to transpire in the next year (Internet Live Stats, 2016). As the world continues to embrace the Internet, businesses have found new opportunities on establishing internet shopping platforms for the purpose of getting closer to customers and in generating more sales. Statistica Incorporated (2015) reported that global internet shopping sales reached around 839.8 billion dollars in 2013 and forecasted to reach 1.5 trillion dollars on 2018. They further mentioned that North America has the biggest online shopping market which was able to generate sales of around 126 billion U.S. dollars. It is followed by Europe, particularly, United Kingdom generating sales of 107 billion euros. Cushman and Wakefield (2013) indicated that most developed countries in Europe such as United Kingdom, Germany, USA, France, Netherlands dominate the global online retail market (Table 1). These countries are leading in terms of online infrastructure including market size and in exploiting market opportunities. Meanwhile, Czech Republic ranked 29th in terms of online market size and 34th in online infrastructure (Cushman and Wakefield, 2013). Recently this year, China is leading in terms of the number of internet users and internet shoppers. With the economic boom of the country, Asia and Oceana regions are expected to experience 8 times increase in internet shopping sales in 2018 (Statistica Incorporated, 2015). As a matter of fact, Philippines, as a developing country, already landed 48th on the top 50 countries on global online retailing as reported by Cushman and Wakefield (2013). Nevertheless, though the penetration rate and internet shopping infrastructures varies from country to country (i.e. developing vs developed nations), these still represents a huge opportunity to be exploited by businesess in near future. 5

Table 1. Online Retail Ranking: Scale and Potential (Source: Cushman and Wakefield, 2013) Overall Country Market Size (rank) Infrastructure (rank) 1 United Kingdom 2 9 2 USA 1 15 3 Germany 4 14 4 France 3 16 5 Netherlands 9 5 33 Czech Republic 29 34 48 Philippines 46 46

H1: The extent of online shopping adoption among university students in Czech Republic is greater than the Philippines

2.2. Fundamentals of Consumer Behaviour

Basic researches on consumer purchase behaviour aim at understanding how consumers came to a decision to purchase offer paramount importance to marketers as these provide them the framework of how they structure their strategies in relation to product innovations, pricing and promotions to reach the need and desire of the consumers. Aizen (2008) generally referred consumer behaviour as “the act of buying a good or service” while Madhavan and Kaliyaperumal (2015) defined it as “the process which basically involves the peoples’ actions of obtaining, using, and disposing of economic goods and services along the decision process that occurs”. Consumer behaviour is characterized as a process that encompasses activities that are stimulated by particular goal of an individual and differs in different time and complexity setting and is largely influenced by internal or external factors (Madhavan and Kaliyaperumal, 2015). Bisht (2014) stipulated that these factors include socio-economic conditions, cultural environment, literacy level, occupation, geographical location, efforts on the part of sellers, exposure to media etc. However, Stávková, Stejskal and Toufarová (2008) mentioned that among the factors that affect consumer purchase decision, product characteristics and perceived value posed the strongest.

2.2.1. Theory and Models on Consumer Purchase Behaviour

Studies on consumer buying behaviour have long existed several decades ago. Such studies examined factors affecting consumer behaviour, crafted consumer behaviour models, analysed consumer purchase decisions and many others. Though this field of research is not

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new anymore, looking back provides recent researchers a skeletal framework for future consumer researches and so as to have better understanding of consumer behaviour patterns.

The Buying Decision Process Consumers undergo a process to arrive a final purchase decision. The study conducted by Madhavan & Chandrasekar (2015) indicated that there are five stages of buying process: 1) need recognition 2) information search 3) evaluation of alternatives, 4) purchase decision, and 2) post purchase behaviour. The authors further added that the process is forward-moving that starts long hand before the purchase is made and continue even after the purchase is made.

Need Recognition. The buying process commenced when a consumer recognize his/her need to consume/use a particular product as triggered by an internal or external stimuli which send the signals suggesting consumers that they under-consume a product or to replace damaged/outdated product that he/she enjoyed before (Madhavan & Chandrasekar, 2015). Need recognition is a matter of receiving signals, and once consumers receive it, that’s the only time that they start to think why they would buy such product (Puccinelli et al., 2009). Recognizing a need is also exposed to demographic (age, gender, etc), psychological, social and cultural factors (Puccinelli et al., 2009).

Information Search. After the consumer is able to recognize his/her need, the next stage is for him/her to seek information about the product (e.g. attributes or features). Madhavan & Chandrasekar (2015) stated that consumers more often rely information from word-of-mouth, print, visual or online media. However, the quality of information gathered is dependent on the ability of the information channel to convey the right information to consumers as well as the ability of the consumers to pick up the right information (Frambach, Roest and Krishnan, 2007). Madhavan & Chandrasekar (2015) further added that purchase decision is a complex process, wherein, consumers, as a result, need a helping hand throughout the decision process. The authors also mentioed that this can be provided in the form of information channeled in different ways and subsequently, information gathered are evaluated in order to find the best possible solution to the need that the actual consumer is looking for.

Evaluation of Alternatives. As the consumer faces wide range of product choices, he/she must choose the most appropriate product that perfectly meets his/her need or desire (Madhavan & Chandrasekar, 2015). Consumers, usually, are the ones that set the standards

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(minimum requirement) of choosing a particular product to buy (Balaji & Babu, 2015). However, Lee and Lou (2011) pointed out that several consumer characteristics that puts emphasis on price scheme, knowledge as well as involvement levels resulting in the different product attributes in choosing best product that fitted ones needs and desires. Nevertheless, the authors added that products that are able to surpass these standards are likely to be bought. Creusen and Schoormans (2005) found out that product appearance plays a vital role in consumer product evaluation. Berger and Fitzsimons (2008) discovered that favorable product evaluation is highly correlated with a perceptually or conceptually sorrounding environment which enhance product accessibility and allowing consumers to hasten the process to examine or process the choice of products. Govers and Schoormans (2005) added that consumers prefer products with a product personality that matches their self‐image. However, Burson’s (2007) reported that though consumers heavily rely on self-assessment in choosing a productbut they still choose products that do not necessarily match with their skills.

Purchase Decision. Madhavan & Chandrasekar (2015) explained that in this stage, the consumer basically ranked his/her choices, however, he/she doesn’t have to choose the one that ranks first as people pressure and unexpected situational factors affect purchase decission. Lou (2005) found out that the presence of other people significantly influence an individual’s purchase decision. The author added that that an impulse urge to purchase something is improved by the presence of peers rather than with a cohesive group or family. On the other hand, inevitable happenings may arise in the course of making final purchase decision. Even if the consumer had already ranked the best among the products available, but still, it is not an indication that he/she will surely pursue buying the product. Sub-purchase decisions are still to be considered among consumers. These include price, time of purchase, volume, payment method and the means of sale (Madhavan & Chandrasekar, 2015).

Post-purchase Behaviour. This stage is characterized by events that happened after a consumer buys a product. It puts a great deal on understanding satisfaction and post-purchase actions among consumers (Madhavan & Chandrasekar, 2015). Understanding these offer strong importance to marketersas as it facilitates them in devicing ways or strategies to improve products and services so as to encourage consumers to demonstrate repurchase behaviour which is crucial to the success and survival of any businesses. Mugge, Schifferstein and Schoormans (2010) indicated that product’s utility and appearance positively pose strong influence on product attachment and satisfaction. Clottey, Collier and Stodnick (2011) also

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indicated that service and product quality, and brand image are the factors that drive customer loyalty. Moliner et al. (2007) mentioned that other than the desirable product attributes, customer satisfaction is also dependent on the social impact of the purchase -- that is, the emotional aspects involved in the supplier-customer transaction.

Traditional and Contemporary Models Consumer choice and behaviour are complex concepts that are continuously studied by researchers. Meanwhile, marketers plunked huge interest on this area as it helps them develop suitable marketing strategies to enhance profitability and sustain competitive advantage of their respective businesses. Several models were developed to explain the variables and processes that trigger buying behaviour. Jisana (2014) stated that behaviour models on how consumers reach a purchase decision range from traditional to contemporary models Traditional Models. A recent review performed Jisana (2014) enumerated basic traditional models that explain consumers’ buying patterns and decisions. These models include economic, learning, psychoanalytic and sociological models. Economic Model. In this model, consumer buying behaviour is deemed based on an assumption that consumers tend to maximize the benefits derived from a product while minimizing costs (Jisana, 2014). In this sense, given the purchasing power constraints and the unique preferences for each one of them, consumers primarily thrive to maximize their own utility by allocating effectively and efficiently the scarce resources (Jisana, 2014). Learning Model. The first and foremost step in the buying process is for an individual to recognize his/her own need. Abraham Maslow (1943) proposed a theory that describes the needs of human being. These include physiological, safety, love/belonging, esteem and self- actualization needs which he further described that it can be structured like a pyramid wherein basic needs (e.g. food, clothing, shelter, etc) are placed at the bottom while intricate ones are on the top (McLeod, 2007). In the process, consumers tend to satisfy things that would meet the basic needs first and only after that he/she will try to satisfy the others. Psychoanalytic Model. According to this model, consumer behaviour is a function of the conscious and the sub-conscious mind (Jisana, 2014). A foundation of this model is linked to early theory developed by Sigmund Freud in 1856 – Psychoanalytic Personality Theory. is The interaction of id (basic instinct), ego (balance between pleasure and pain), and superego (conscience of the mind) drives human behaviour (Boundless, 2015). Moreover, the model

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considers that consumer behaviour is driven by complex set of deep seated motives and human personality (Vikram, 2013). Sociological Model. As described in this model, every individual, particular his/her buying behaviour is exposed to influences that are derived from another person or from social groups. However, among these, the strongest influence can be derived from the ones that are in very close association with the individual such as family, relatives, close friends and others (Kumar, 2010). With this, he/she is given specific views in relation to the style and behavioural patterns of the associated groups and that he/she can incorporate it in his/her own behaviour.

Contemporary Models. Madhavan & Chandrasekar (2015), enumerated major comprehensive contemporary models for consumer decision making and behaviour. These include the Nicosia model (1966); Engel et al. model (1968); Howard and Sheth model (1969) and the Stimulus-Response Model. Nicosia Model. In 1966, Franceso Nicosia developed one of the earliest comprehensive models that explain consumer buying behaviour. His model places a link between an organization (firm) and its prospective consumer. This link describes the idea that firms are the ones who send messages to consumers and that consumers react to these through elucidating response behaviour (e.g. purchase) (Madhavan & Chandrasekar, 2015). In other words, firms stipulate influence to the consumer; while in return, the consumers influence firms’ decisions and actions (e.g. promotional strategies) (Abdallat and Emmam, 2001). Marketing implications suggest that this model enables marketers to understand and react quickly on the positive or negative progress of their marketing strategies such as campaigns, promotional activities, etc (Orji, 2013). Engel-Kollat and Blackwell Model. This model viewed consumer behaviour as a decision process. As stated by Madhavan & Chandrasekar (2015), there are four stages in the consumer decision process. These include problem recognition, search, evaluation process, and purchase decision, information input, information processing and factors influencing the decision processes. The authors further added that the process basically links to the activities that consumers undergo in reaching purchase intentions or outcomes. The second stage is the information input, which describe how consumers seek information and how it affects the entire decision process. Once information is found and gathered, consumers will process it involving consumer response activities, attention, comprehension, perception, acceptance as well as retention of that information (Madhavan & Chandrasekar, 2015). Lastly, the fourth 10

stage includes the variables influencing decision process. It cannot be denied that that there are several factors (internal or external) that influence decision process. These factors ranged from an individual’s own values, lifestyle and personality to groups and other situational influences (Abdallat and Emmam, 2001). Howard-Sheth Model. This model incorporated sets of variables that tend to explain consumer behaviour. These are inputs, perceptual and learning constructs, outputs and exogenous variables. Inputs are stimuli existing around the buyer’s environment which send messages to consumers in relation to the product attributes (e.g. quality, price, availability, uniqueness) and subsequently influence their respective buying decisions (Jisana, 2014).These stimuli are derived from significative stimuli (physical brand characteristics, symbolic stimuli (verbal/visual characteristics) and social stimuli (Abdallat and Emmam, 2001). Perceptual and learning constructs, on the other hand, is concerned on the psychological variables involved when a consumer faces a situation wherein he/she must make a purchase decision (Abdallat and Emmam, 2001). Perceptual constructs describe the ways how consumer perceives and process the inputs offered while taking into account the stimulus ambiguity and perceptual bias (Abdallat and Emam, 2001). Jisana (2014) mentioned that perceptual construct interact with learning constructs which include the individual’s motives, choice criteria, brand comprehension and confidence in the decision making process. The author added that as consumers respond to these variables, output (final purchase decision) is created, however, the external factors which mostly include personality variables, culture, financial status and importance of purchase present cause direct or indirect influence to a purchase decision. Stimulus-Response Model. This model stipulates that consumer responses are generated by various stimuli that enter and interact with the buyers’ personal characteristics and its decision making process (Jisana, 2014). Based on a review conducted by Jisana (2014), the stimuli that enter the “blackbox” and which produce consumer responses include marketing stimuli (e.g. 4P’s) and major forces or events in the environment such as economic, technological, political, and cultural factors. The author further added that as soon as the stimuli enter the “blackbox” and interact with the specific buyer characteristics and decision processes, observable responses include product choice, brand choice, dealer choice, purchase timing, frequency of purchase and purchase amount and many others.

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2.3. Basic Factors affecting Consumer Purchase Behaviour

Every individual’s purchase decision or shopping habits is affected by various factors that range from personal, cultural, social and psychological factors. In the retailers’ standpoint, it is essential to discover and understand these factors to be able to craft more effective and efficient marketing strategies that will surely meet customers’ needs and wants. Personal Factors. Rani (2014) indicated that these factors include personality, age, gender, occupation and other demographical characteristics of an individual. The author added that since these vary from individual to individual, it is apparent that buying behaviour of consumer groups also differs. Comparing the young to adults, it is probable that adults may prefer different products from the young ones. In food products, adults may prefer to purchase healthier products compared to the young ones. Ricciuto, Tarasuk and Yatchew (2006) found out that older households spent most of their income on vegetables and fruits. Educational attainment is positively linked on purchases on healthy products such as vegetable and fruits. Sorce, Perotti and Widrick (2005) have also found out that factors such as attitude and age differences affect online buying behaviour among consumers. Their findings showed that young people search for more products online compared to the old ones. Younger people find online shopping convenient and informative. Thus, young consumers’ will have high online searching behaviour. However, in terms of products purchased online, the older ones are more likely to purchase the products. Moreover, Bhatnagar, Misra and Rao (2000) found out that older consumers and those who spent more time on the internet were more open to purchase online including.

Social Factors. Family, social groups, social status and roles are just some of the social factors affecting consumers’ purchasing decisions (Bhasin, 2012). Family is the basic unit of society where a person starts to socialize and acquire and develop attitudes, lifestyle, opinions, behaviour and perception of things. Social groups linked to the individual also influence buying behaviour which can be carried out throughout his life (Rani, 2014). A person who is associated by “shopaholic” groups may transform him/her to become a shopaholic person. When a person is surrounded with sports loving group his/her purchase behaviour would be to buy products that the group enjoys. In other words, social factors influence how an individual behave (e.g. including how he/she purchase products) throughout his life. Foucault and Scheufele (2002) pointed out that creating positive social environment increases the likelihood of buying intentions among consumers. Meanwhile, Tang and Farn

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(2005) suggested that group pressure also played a significant role. Hassanein and Head (2007) also found out that consumers’ perceived high social presence, is likely to affect the trust and enjoyment leading to more favourable consumer attitudes. Psychological Factors. Rani (2014) specified that psychological factors include motivation, perception, learning as well as beliefs and attitudes. The author defined motivation as the driving force for consumers to arrive a purchasing decision, however, since it works subconsciously, it believed that a person is more motivated to purchase a product if it has a pressing need for him/her. Learning also influences the buying behaviour. Purchasing a good product beforehand is a learning experience which triggers consumers to repurchase and be able to influence purchase decisions of other people (Rani, 2014). Another psychological factor is perception which is based from experience, state of mind, beliefs and attitudes. Rani (2014) described this factor as a deciding factor to what an individual chooses to act. The author added that it is the ability of a person to process and interpret information to make a meaningful sense. Thus, it is important for marketers to understand these things to conform its strategies to stimulate psychological factors that are intensely affecting consumer purchase behaviour.

Cultural Factors. According to Tanner & Raymond (2012), culture is a collection of beliefs, roles, behaviour, values, customs and traditions that are shared among people in particular society. The authors also mentioned that it is built through the influential force of the surrounding social groups as well as the cultural environment that an individual belongs and prescribes how an individual should live life along with the kind of attitudes, feelings, biases, opinions that he/she should play in the society. Culture tenders huge influence to consumer buying decisions. It sets up the norms or standards of which an individual should follow in buying products and be able to differentiate what is good and what is bad (Monger, 2012). Cultural shifts in a society enable marketers to deepen their understanding on a particular culture and be able to develop effective and efficient marketing strategies that conform to the needs and wants of the consumers.

To recap, fundamental understanding of consumer buying behaviour started several years ago. Findings showed that consumer behaviour is a decision process which follows through different stages from problem recognition, search, evaluation process, and until the consumer arrives at a final purchase decision. The decision process does not happen smoothly. Several factors are affecting consumer buying behaviour wherein basic ones 13

include social, psychological, cultural and personal factors. Moreover, different models (e.g. traditional and contemporary) were also created to understand more fully the buying process and its interrelations to internal and external influences. Traditional models basically assess consumer behaviour as based on learning (ability to recognize a need) and on economical (cost and benefit), sociological (social connections) and psychoanalytical (conscious and the sub-conscious mind) viewpoint. Comprehensive contemporary models were developed to understand better the consumer decision making process. Madhavan & Chandrasekar (2015) mentioned that the most exploited ones include Nicosia model – consumer to firm link (1966); Engel et al. model – decision process (1968); and Howard and Sheth model - inputs, perceptual and learning constructs, outputs and exogenous variable (1969). These contemporary models pose significant importance in field of consumer research. These provide researchers with a framework of understanding consumer behaviour in the current and upcoming years.

2.4. Consumer Behaviour in the Online Environment

The Internet has continuously triggered rapid changes to consumer buying behaviour. Many companies have transitioned itself from using traditional marketing strategies to Internet driven strategies as these help them in cutting costs and in effectively and efficiently communicating product/service information to the customers.

Factors Influencing the Adoption of Internet Shopping The success of the electronic market is highly dependent on the level of acceptance among consumers adopting it (Zhou, Dai and Zhang, 2007). Several studies have uncovered, examined and analysed the factors affecting consumers’ adoption to electronic shopping. After series of reviews on past researches, various factors were classified into three main categories: 1) web site characteristics, 2) consumer characteristics, and 3) product characteristics offered in the web site.

Web site Characteristics These factors comprise the features or attributes of the web site that posits influence to consumers to generate purchase intention and subsequently to actual online purchase. These

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include: perceived ease of use, perceived usefulness, firm’s reputation, privacy, trust, reliability and functionality (Lee et al., 2011). Perceived ease of use pertains to the level of effort exerted by the consumer in navigating through the web site to search the product and information and in making the actual purchase (Chiu et al., 2009). Often, the perception of web site superiority over other retailing channels can be viewed in a way that consumers will be more than willing to pursue online shopping and when the e-retailer is able to match their shopping needs through easy operation of the e-retailing web site (Lian and Lin, 2008). Wakefield, Stocks and Wilder (2004) added that web site attractiveness as conveyed by colour, text formatting, fonts, size, number and variety of graphics also play an influencing role. They mentioned that when a web design meets consumer expectation, the consumer is likely to build a purchase intention or an actual purchase. Hausman and Siekpe (2009) mentioned that other than making appealing graphics and models to attract, retain, motivate consumers to purchase in the site, it is necessary to also include human features such as the use of humour. They also mentioned that the inclusion of human factors in the design of the e-retailing web site posits an enormous impact to purchase and return intentions. Moreover, Ramayah and Ignatius (2005) mentioned that the ease of use of technology and the satisfying online shopping experience among consumers is a crucial factor in deriving online shopping intentions. Thus, e-retailing web sites with complex designs, unfriendly user interfaces and functionalities largely hinder consumers to easily spot products that meet their needs which eventually made them leave the site and find other suitable alternatives (Pearson et al., 2007). Consumers often look at convenience when they shop online. Like for instance, people who don’t have time to go to brick-mortar (physical) stores to acquire their desired products and fulfil other needs often engage in online shopping as these initiative is more convenient for them. It saves, less effort is required with wide product offering are available. This convenience they felt, however, depends on the capacity of the web site to fulfil and enhance the transaction performance of the consumers– perceived usefulness (Chiu et al., 2009). In other words, does the web site provide benefits to the consumers in terms of time, effort, savings or any other gains? In a study conducted by Horrigan (2008), he found out that online shopping provides convenience and time-saving benefits to most consumers. He further mentioned that these benefits can overcome consumers’ security worries in the online environment. Delafrooz et al., (2009), stated that consumers who value the significance of

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convenience, prices and wider selection of products in the internet tend to shop online more often. Firm’s Reputation pertains to how known the company (e-retailer) is in terms of providing consumers with care and concern on their welfare (Lee and Lou, 2011). Nguyen and Leblanc (2001) mentioned that reputation is built through making credible actions in such a way that it performs good transactions over time and able to deliver the promises made to consumers. Meanwhile, Keh and Xie (2009) stated that a favourable company reputation influences customer commitment and that it is a function of building trust and identification among customers. Shiau and Luo (2012) pointed out that when a vendor needs, online buying intentions among consumers are greater. Moreover, they further mentioned that that when customers’ perceived a company with good reputation, they believed that the company is honest in their daily operations and is able to make sound decisions. Horrigan (2008) stated that safety of financial and personal data provided in the online shopping web sites is a widespread concern. Lee, Park and Han (2011) mentioned that online buyers were afraid to purchase products and services online mainly because of privacy issues. Since most online shopping web sites require the consumers to provide personal information, consumers are afraid that online retailers might misuse or may not respect the confidentiality of the information. At the same time, this fear is also coupled with the past fraudulent activities occurring in the online environment. Basically, consumers need privacy. They want that the personal information they provided in the web site will be safe and protected. Tsai and Yeh (2010) mentioned that privacy is strongly related to purchase intention and that strengthening of web site management and placing upgraded network security are necessary. Lee, Park and Han (2011) also mentioned that e-retailing businesses should focus on following appropriate business ethics, ensuring the privacy of information of customers so as to build trust and confidence to customers. Trust is a very important web site characteristic that e-retailers must focus on to succeed in the online environment. An understanding of how trust is built and how it affects internet shopping adoption is essential for e-businesses (Ganguly et al., 2010). According to Lee, Park and Han (2011) (2011), trust means transparency on the communication between the buyers and the e-retailers. They added that promises made by e-retailer must be fulfilled to prevent customers to feel certain level of uncertainty. Trust is determined by the web security, privacy policies and service quality provided by the e-retailers (Martín and Camarero, 2008). This can be observed when the e-retailers are keeping good ethical performance, stating

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privacy policies and describing products appropriately (Yang et al., 2009). Consumers often value security the most in purchasing goods and services online (Chen et al., 2010). As mentioned by Chen and Barnes (2007), high levels of trust and familiarity of the operations of making an online purchase are stimulating consumer purchase intentions. To build trust, e- retailers should have good intentions to buyers and that e-retailing web site is able provide positive customer experiences. Reliability refers to the extent of consistency the web site is providing in relation to the functions it is intended to perform (i.e. without broken links, pages or dead end links (Goode and Harris, 2007 as cited by Lee et al., (2011). This also means the ability of the e- retailing web site to correctly describe the products/services displayed including time deliveries as much promised by the company (Shergill and Chen, 2005). Tsai and Yeh (2010) stipulated that the construction of website platform should be in a way that it is able to provide awareness to consumers through a wide range of information to provide positive experiences online and also to assure security in the online shopping environment. Typically, a consumer faces immense difficulties in using web sites especially when it is his/her first time. An example is when he/she is exerting much effort in locating information desired including information relating to the specifics of the transaction he/she is about to take. Failure to respond to these discourages consumers to finish the current purchase or even the future purchases (Lee et al., 2011). This ability of the e-retailing web site to provide information in relation to the products, services and transaction guidelines or other purchase related information is termed functionality (Law and Bai, 2008 as cited by Lee et al., 2011). Chen and Barnes (2007) mentioned that providing full and detailed information as mentioned above builds initial trust and benevolence through the web interface experience. Handling consumers through the web site is just as important as how the web site looks and feels (Tsai and Yeh, 2010).

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Consumer Characteristics Aside from the web site features or characteristics offered by e-retailers to the consumers, specific characteristics of the consumer itself are also positing influence to their intentions to shop online or not. Besides, Hausman and Siekpe (2009) found out that both computer and human factors are indirect requisites for online shopping via the attitude to web site and its flow. One of these includes the demographic characteristics of the consumer such as age, gender, educational background and income. In a study conducted by Hui and Wan (2007), they found out that for apparel shops in the internet, gender differences posed an influence. Females show hesitation to shop online since they are not able to fulfil their shopping experience physically (Hui and Wan, 2007). In other words, females would much require physical touch or test the desired clothing apparel prior the purchase. Females were also found out to show lower cognitive and affective attitudes than males which reduce their intention to shop online than men (Hasan, 2010). In addition, Cowart and Goldsmith (2007) stated that the intention to engage in internet shopping is a matter of decision making styles of consumers. The authors further mentioned that the value conscious consumers less likely engage in online shopping than other with different decision making styles. Also, Balaji & Babu (2015) mentioned that consumer goals are main drivers that enable consumers to experience pleasure for the products or services bought. Nevertheless, interactivity, sufficient information and the friendly user interface of the web site can substitute the constraint (Hui and Wan, 2007). In fact, the initiative positively impacts men. As pointed out by Ganguly et al., (2010), masculine individuals are likely to be more assertive and quick in their purchase decision if the e-retailer is able to present information logically in the web design. However, Soopramanien and Robertson (2007) indicated that effects of gender and age are insignificant and that income is major influencing factor to increase the likelihood of purchasing products online. Hui and Wan (2007) also indicated that educational attainment of individuals also influences the decision to engage in internet shopping. The authors mentioned that highly educated individuals don’t have the sufficiency of time to do physical shopping since most of them are probably spending much of their time in workplaces and other activities. Other than the characteristics mentioned beforehand, the culture of an individual also plays a role. Like for instance, Cowart and Goldsmith (2007) found out that customers with high uncertainty avoidance significantly value the navigation design of the web site to generate trust. This necessitates e-retailers to provide or create e-retailing website that enables

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users to navigate easily with certain levels of interactivity and acquire needed information to support purchase decision. Other than that, collectivism is also found to exert negative moderation towards the relations of trust and purchase intention (Cowart and Goldsmith, 2007). The authors mentioned that western customers greatly place value on trust prior generating a purchase intention. As mentioned in the earlier discussions, web security is a major concern for most individuals engaging in internet shopping. Yet, the perception of how secure the web site is depends on one characteristic of an online shopper which is his/her literacy in using computers and previous ecommerce experience (Chen et al., 2010). Other consumer characteristics that influence internet shopping adoption and dis- adoption are discussed in the Chapters 2.1.2 (Basic Factors Affecting Consumer Online Buying Behaviour) and 5.1 (Online Buying Behaviour in Relation to Culture).

Website Product Characteristics Intentions to shop online also depend on the type of product being offered by the e- retailer in the web site. Moon, Chadee and Tikoo (2008) found out that search goods are more appropriate to be sold online than experience goods. They added that this scenario presents a huge challenge for marketers who are selling experience goods. The provision of options for experience goods is not an attractive strategy to drive consumers’ intentions to shop online (Moon, Chadee and Tikoo, 2008). Also, in a study conducted by Won Jeong et al., (2009), product presentation features offered by e-retailers in the internet can lead to successful participation of consumers in the online environment. The authors added that offering rich sensory information including lifestyle-oriented information of the product generates pleasure and arousal. In addition, Lian and Lin (2008) pointed out that products which require high involvement can positively impact attitudes towards online shopping. Meanwhile, offering well-known and respected products in the web site pose a strong influence on building consumer trust as this create positive outlook to the online vendor (Wakefield et al., 2004). Given the factors discussed above, the following hypotheses are established: H2: Security and Trust are the major factors that are highly valued (perceived) by students in both universities in making online purchase decisions

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2.5. Hofstede’s Cultural Dimension Scores: Philippines Vs Czech Republic

Culture comprises the set of customs, beliefs, arts of a particular society, group, place or time (Merriam-Webster Dictionary, 2015). It poses significant effect on the behaviour and value perceptions of consumers on products and services. Value perception as an antecedent of buying intention and behavior is not just about intrinsic dispositions, but it could be a result of internalized cultural values and norms and external contextual factors (Overby, Woodruff and Gardiall, 2005). Several studies were conducted to examine the influences of culture to consumer buying behaviour. However, because of its complexity, researchers made use of contemporary frameworks that facilitate them in synthezing, conceptualizing and operationalizing their cross-cultural research process. One comprehensive framework that has been used by researchers to understand the different layers of culture and how it affects an individual’s behaviour is called the Hofstede's framework. It takes into account the different dimensions of cultural variation: 1) individualism/collectivism, 2) power distance, 3) masculinity/femininity and 4) long-term orientation 5) and uncertainty avoidance. Comparing the Philippines and Czech Republic with respect to the Hofstede Model (Figure 1), scores have shown that there is a significant cultural variation between the two countries. These variations are discussed in the succeeding section which is largely based from the information provided by Hofstede Centre (2015).

Philippines Czech Republic 94

74 70 64 57 58 57 44 32 27

Power Individualism Masculinity Uncertainty Long Term Distance Avoidance Orientation

Figure 1. Hofstede's Model Score between Philippines and Czech Republic (Source: The Hofstede's Centre, 2015)

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Starting with power distance, the Philippines scored relatively higher than Czech Republic which means that that the country itself has a hierarchical society (e.g. reflecting inequalities, centralization, autocrat, subordinates follow) and that people accept hierarchical order. Moving to individualism, Czech Republic scored higher (58) as compared to the Philippines (32). This implies that Czech Republic is an individualist society, while, Philippines is a collectivist one. People in individualist societies are expected to take care of themselves and their immediate families only. Meanwhile, the Philippines exhibiting a collectivist culture emphasizes loyalty or long-term commitment to a group (e.g. family, extended family, extended relationships). Moreover, although Philippines scored slightly higher than Czech Republic, both countries exhibit masculine society. Having this, means that the society is driven by competition, achievement and success where people are decisive, assertive, emphasize equity, competition and live in order to work. On the other hand, with regards to uncertainty avoidance, it shows that Czech Republic stresses a relatively higher importance of avoiding uncertainty as compared to the Philippines. The country is highly intolerant of heretical behaviour and ideas thus maintain rigid rules, codes of belief and behaviour. Lastly, Czech Republic exhibits a pragmatic culture. People are characterized to have a strong tendency to save, invest, thrifty and the perseverance to achieve results. Moreover, people can also adapt traditions easily to different conditions or situations. Meanwhile, the Philippines accentuates the establishment of absolute truth in any situations. People respect traditions and focus more on achieving quick results. Given the cultural variations as discussed above, do these also reflect or influence the internet buying behaviour among consumers in both countries?

2.6. Online Buying Behaviour in Relation to Culture

Hofstede’s cultural dimensions are being predominantly discussed in the literature particularly in relation to cross-cultural comparison of consumer buying behavior include individualism/collectivism and uncertainty avoidance dimensions. The overview of other dimensions were described based on the definitions published by The Hofstede Centre (2015). Individualism/Collectivism. The Hofstede Centre (2015) defined individualism as a social pattern wherein individuals only look after themselves and their immidiate families. They tend to focus more on their individual actions, feelings, own preferences, needs and goals. Conversely, a tightly-knit form of social pattern is the collectivist culture wherein 21

individuals tend to be part of any associated groups (e.g. family) that are looking after them in exchange for loyalty (Hofstede Centre, 2015). People in collectivist societies, are motivated by norms and duties imposed by the group. They prioritize the group’s goal and expresses their feeling of connectedness to the group (Lee and Kacen, 2008). Kacen and Lee (2002) indicated that western people (e.g. Americans) are individualists, and that, they emphasize oneself, their individual needs and desires which consequently induce them to exhibit impulse buying behaviour. On the contrary, they specified that people from eastern parts of the world (e.g. China, Singapore, Malaysia) are collectivist consumers wherein people act coherently to the cultural norms of the society which can supress their impulsive trait. The degree of impulse buying, as a result, is substantially lesser than the individualist- westerners. Lee and Kancen (2008) found out that impulse purchase of collectivists consumers are more satisfying when they are with another important person at the time of purchase. Individualist consumers, on the other hand, showed no difference in satisfaction with or without the influence of another person. The two authors additionally specified that collectivists or individualists cultures doesn’t have an impact on satisfaction among planned purchase consumers. Furthermore, Park and Jun (2003) revealed that collectivism is primarily dominant in Korea than United States. In this regard, Koreans engage more time on internet but for online communities or communication related activities not for online shopping. Collectivism also plays an important role in the adoption and usage of mobile commerce. Harris, Rettie and Cheung (2005) indicated that though Hong Kong and United Kingdom have similar mobile telecommunications infrastructures, significant differences are attributed to the levels of collectivism, power distance in the cultures and to structural differences between the two markets. Fong and Burton (2008) also revealed that Chinese is highly engaged in higher levels of discussion to seek product information. This attitude is consistent with collectivist culture in Chinese society which involves information sharing and heavy reliance to other significant people. Conversely, Americans engaged in high information giving depicting individualist culture which is more vocal in terms of publishing opinions and recommendations. H3: As compared to Czech students, university students in the Philippines exhibiting collectivist culture are heavily influenced by any associated groups (e.g. family) in making online purchase decision

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Uncertainty Avoidance (UAI). According to Hofstede Centre (2015), this dimension expresses the level of an individual’s feeling of uncertainty and ambiguity including the degree to avoid it. They further described that societies with high uncertainly avoidance have well estalished rules, regulations or laws and intolerant to unorthodox behaviour and ideas. However, in low uncertainty avoidance societies, people tend to portray more relaxed attitude and believe that practice counts more than principles. In relation to consumer buying behaviour, Gong (2009) revealed that uncertainty avoidance has positive effect to internet shopping adoption and diffusion levels. Latin Americans have high uncertainty avoidance which explain their resistance to change and strong emphasis of reducing or avoiding risks. Likewise, the study of Park and Jun (2003) revealed that there were differences on perceived risk and internet usage on shopping online between Korea and United States. Koreans tend to have high uncertainty avoidance than the Americans, however, results suggests that they still tend to purchase online given the privacy and security risks that they are facing. This exist because of the fact that shopping sites in Korea are linked to trusted big shopping malls which reduce risk and uncertainty perception among consumers. Similar attitude is also exhibited by its neigboring Asian counties. Correspondingly, Sian et al., (2010) reported that in terms of uncertainty avoidance, Chinese have lower UAI than Malays which implies that Chinese are more tolerant to uncertainty and ambiguity and they are more willing to try new things. Teo and Liu (2007) found out that in China, Singapore and even United States, risk perception has the least negative relationships with attitude and with willingness to buy online. Gong (2009) specified that website innovativeness also played an important role and poses important managerial implications to shopping sites which include promotion of internet shopping than improve e-commerce security,strategic alliances with famous shopping malls to reduce perceived risk and convert internet users to buyers. Though internet shopping holds ambiguity and uncertainty, this can sooner be reduced in accordance with the advancement of information technology (Gong, 2009). H4: Czech students perceived high risks in online shopping and places strong emphasis of reducing these as compared to Filipino students

Power Distance (PD). As decribed by Hofstede Centre (2015), this dimension expresses the level of acceptance of members of the society that power is unequally distributed. They specified that in societies with high power distance index, a heirachical order exist; which means, people have a specific spot in the society which needs no justification. On the other hand, low power distance societies is characterized of having 23

equally distributed power and people tend to demand justification if power inequalities exist (The Hofstede Centre, 2015). Sian et al., (2010) found power distance as a factor of consumer behaviour between Malays and Chinese. Malays scored higher power distance index than Chinese. As Malays are more willing to accept their position in the family and in the society that is line on their religious point of view (Islamic – existence of Allah (God)). Malay families particularly the parents exert higher decision making rights than their Chinese counterparts. Meanwhile, Zhang, Winterich and Mittal (2010) also indicated that in societies with high PDB, consumers often display less impulsive buying behaviour. In chronically high PDBs, self-control is automatically enacted and restrained from temptations (Sian et al., 2010).

H5: Comparing Filipino and Czech students, Czechs students tend to be more influenced by their superiors’ ideas and opinions prior making a purchase decision

Masculinity/Feminity. According to the Hofstede Centre (2015), masculinity percieved society is more competitive as it values achievement, heroism, assertiveness and material rewards for success. They specified that men value quality and efficiency. Feminity, on the other hand, values cooperation, modesty, caring for the weak and quality of life. Thus, society in this case is more consensus-oriented (The Hofstede Centre, 2015). Bakshi (2012) revealed that that masculinity/feminity affected purchase behaviour in different manner. The author described feminity, as portrayed by most women, affect behaviour in a way that they are more subjective and intuitive and they acquire opinion first from other people prior to their purchase. They also value emotional connections and relations. H6: Filipino students are more subjective and intuitive in making online purchase as compared to the Czech students

Long-term Orientation (LTO).According to The Hofstede Center (2015), this dimension relates to the fact that societies bridge a link from the past to prepare itself to present and future challenges. They added that highly oriented societies favor pragmatic approach, wherein, members of the society are investing into something today (e.g. education) for it will be useful in the future. On the contrary, short term oriented societies maintain time- honoured traditions and norms while views change with suspicion. Yoon (2009) revealed that long term orientation plays a significant role in increasing the impact of trust to engage in

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online shopping. Bakshi (2012) also mentioned that women are long term oriented than men. This means that women tend to look at their purchases as long term decision while men took it as immediate needs. H7: The extent that Czech students look at their purchases online as long term decision is greater than Filipino students

Understanding how culture affects consumer buying behaviour is a complex process. In the literature, many cross cultural studies made use of Hoftede’s dimension of national culture to understand aspects of culture that may affect consumer behaviour. Results of studies proved that culture has a significant impact to consumer buying behaviour. These include: 1) an individualist consumer emphasize oneself, while, a collectivist tends to be influenced by cultural norms of the society in coming up of a decision to buy products online or not, 2) high uncertainty avoidance (UAI) cultures exhibit strong resistance to change and huge attention is placed on reducing or avoiding risks, 3) self-control is typically enacted in high PDB cultures as superiors posit strong influence to the decision making rights of the subordinates, 4) subjective and intuitive traits of females as compared to males affect behaviour in a way that they acquire opinion from people first prior making a final purchase online, and lastly, 5) long-term orientation plays in a way how a particular consumer look at the purchase as long term or for immediate needs. Basically, in one way or another, consumers behave differently due to culture differences. Understanding these provide significant implication to managerial decision makers to enable them to plan and develop effective and efficient managerial or marketing strategies to expand target markets and sustain competitive advantage.

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PART III

MARKETING RESEARCH CONCEPTS AND PRINCIPLES

3.1. Nature of Marketing Research

Businesses are the ones providing value to their respective customers. They offer the right goods and services to the right place, time, price through executing a mixture of marketing techniques and strategies (Hair, Bush, & Ortinau, 2006). Yet, because of the changing marketing environment, they need to upkeep their knowledge as well as their strategies to remain successful and sustain its competitive advantage. It is essential that they must fully understand the value they are offering to their respective customers. To do this, they must coherently acquire answers to the following questions in acquiring relevant information supporting their decision making process: 1) What do the company sell? 2) How do consumers view the company? What does the company/product mean to the customer? What do consumers desire? (Zikmund and Babin, 2006). The need for this kind of information continues to arise as each business decision has its own attached risk and uncertainty. Thus, conducting a research process called marketing research is becoming a core function that exerts strong influence in the success and survival of businesses nowadays. As defined by the American Marketing Association (2004), “Marketing research is the function that links the consumer, customer, and public to the marketer through information that is used to identify and define marketing opportunities and problems; generate, refine, and evaluate marketing actions; monitor marketing performance; and improve understanding of the marketing as a process.” They specified that it is a scientific process that systematically investigates a marketing phenomenon to acquire information that aids managers in making sound decisions. By this means, companies are able to understand much better the marketing problems and opportunities it faces which can be consequently form as the basis in the generation, refinement or evaluation of marketing strategies and performance. Marketing research is a very important means of gathering this information. Marketing research consists of systematic steps which include problem definition, crafting the research design, data collection, analysis and interpretation of results and communication of findings and implications to the users (Proctor, 2005). It involves the creation of hypotheses that are drawn from informal observations and have it tested through

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the marketing research process (Proctor, 2005). Subsequently, researchers are able to tell which of them will be accepted or rejected. Accepted hypotheses will become generalizations which form the basis of crafting marketing actions (Burnett, 2003). However, the validity of marketing research process is largely dependent on the objectivity and impartiality of researcher who is conducting it, thus, to acquire timely, accurate and relevant information, the researcher must be in full control of the research process (Proctor, 2005). That means, its research design must be accurately developed and be able to execute it according to plan.

3.2. Classification of Marketing Research

Marketing research can be classified based on the purpose it serves to the person or the organization who is conducting it. As pointed out by Malhotra (2010), there are two basic reasons why marketing research is conducted: 1) to identify marketing problems 2) to solve marketing problems. The author added that these form the foundations of marketing research classification, namely: problem identification research and problem solving research. Problem identification research is basically conducted to discover marketing problems that may influence the business in short run or in the long run (Malhotra, 2010). Some examples include analysis of market share, brand image, market characteristics including short and long range forecasting. On the other hand, problem solving research is performed to reach appropriate solutions to a particular marketing problem. Results of this particular research presents an enormous importance to marketing managers as these guide them in making sound decisions. Issues regarding the product, price, place and promotional activities are just some of the things that problem solving research is intended to elucidate, however, given the differences between the two researches, in the usual marketing research projects, they are conducted hand in hand and at the same time it follows the same marketing research process (Malhotra,2010). That is to say, it is likely to combine these two types of researches. The first stage may emphasize around the identification of the marketing problem and on the subsequent stages will focus on finding solutions to these problems. Furthermore, Parasuraman, Grewal, & Krishnan (2007) described another classification of marketing research based on its application. The authors mentioned that the first one is basic research which is conducted to generate knowledge, adding up new information in the field of marketing research, retailing, consumer behaviour, marketing and many others. Some examples could be consumer purchase intentions in online shopping 27

environment, assessment of customer satisfcation, price perception of customers and many others. Meanwhile, the other one is applied research, which conforms to the classification of Malhotra (2010) – the problem solving research. It is intended to solve marketing problems aiding marketers in the development and implementation of marketing strategies.

3.2.1. Quantitative VS Qualitative Marketing Research

There are two main approaches on how marketing research is conducted. It could either be conducted using quantitative or qualitative approaches or a mixture of both. Sheldon (2015) indicated that qualitative approach to marketing research is basically exploratory in nature, which means that findings are not statistically proven, but, a greater emphasis is placed on drawing indepth information that highlights marketing issues that cannot be captured in quantitative research. The author added that it focuses on collecting detailed amounts information from a small number of respondents through observation or face to face interviews. On the interviews, open-ended questons are posed to allow in-depth probing of the participants’ responses which consequently allows examination of the particpants’ behaviours (Hair, Bush, & Ortinau, 2006). Focus group discussions and other indepth interviews are the common methods qualitative research. It involves semi-structured discussion which allows respondents to express openly their respective opinions, attitudes, beliefs and intentions regarding an issue or topic being posed by a moderator (Riley, 2015). Hair, Bush, & Ortinau (2006) stated that subjective content, interpretation, or semiotic analysis procedures are employed to analyze the responses or the information gathered. However, qualitative research is also subjected to limitatons. One of its major limitation is its inability to generalize the data with respect to the whole paopulation (Hair, Bush, & Ortinau, 2006). It also lacks represetativeness of the target population which somehow inhibits decision makers in using qualitatively gathered information in the selection and implementation of marketing strategies (Hair, Bush, & Ortinau, 2006). Conversely, quantitative marketing research intends to acquire information that are measured with the aid of statistical analysis or other mathematical methods. Hair, Bush, & Ortinau (2006) have mentioned that in this kind of research, the research problem is specific and well defined allowing greater precision in acquiring the information needs. Furthermore, they specified that this research specifically aims at providing facts to decision makers with respect to the following: 1) predictions about the relationship between market factors and 28

behaviors, 2) insights into those relationshios, 3) validation of existing relationships and 4) hypotheses testing. Moreover, B2B International (2015) pointed out that quantitative marketing research offers critically measured hard data that presents usefulness in crafting recommendations that can also be used as controls in assesing the effectiveness of marketing actions. Some of the applications include determination of market size, market growth rates including the understanding of consumers behaviour and attitudes and many others (Riley, 2012). One typical feature of this approach is that inferences are taken from a sample of the entire population being studied. That is, of the entire population fitted to partake in the study, only a representative of them are actually included. Structured questionnaires are commonly used in this approach to capture respondents’ responses on the questions initally developed by the researcher. Since this approach is statistical in nature, Hair, Bush, & Ortinau (2006) suggested that researchers are required to take umost consideration in the selection of right sample and its size since accuracy and reliability of study findings are highly associated with it. They also mentioned that data realiability and validity are two serious concerns in any quantitative research undertaking. Thus, researches are urge to somehow accurately develop the research design to ensure the smooth sail of the entire research process.

3.3. The Marketing Research Process: A Brief Overview

Marketing research involves processes that are chronologically arranged and are interellated to each other (Figure 2). The arising interrelationship can be elucidated by the fact that each step presents an impact on the preceding or following steps.

Justify the Need for Marketing Research. According to Parasuraman, Grewal, & Krishnan (2007), marketing research process starts at a point where researchers are ask whether it is worthwhile conducting or not. The authors added that in this stage, the usefullness of the research especially the extent the results will reduce uncertainty and ambiguity of the decisions to be made by manager is primarily assessed and is followed by assessment of other criterias such as management attitudes towards research, available resources as well as the research cost and benefits. Findings must be fairly incorporated future decisions while taking into account the available resources (e.g. money, personnel, time) that the management has; otherwise, the results will be considered useless (Parasuraman, Grewal, & Krishnan , 2007). Thus, it is required that the research purpose must be fully established

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and clearly understood by all parties involved in the process. It should be neatly packaged, bearing the information requirements, scope and motives of conducting it.

Define the Research Objectives. One crucial part of any research project is the establishment of research objectives. Objectives are statements that describes what researchers are aiming to find out in entire research process. Basically, it serves as guide to researchers in obtaining only revelant information that satisfies the research purpose. According to Kumar, Aaker, & Day (2002), there are three crucial components of research objectives, namely: 1) research question (i.e. defines the information needs of researchers or decision maker) , 2) hypotheses (i.e. predefined answers to the research question that are tested at some point of the research process) and 3) scope of research (i.e. bounderies that narrow down the research findings such as include data, time, budget and other limitations that are out of control of the researcher. Moreover, Parasuraman, Grewal, & Krishnan (2007) mentioned that the key mechanism to determine whether to conduct the research or not is by accurately defining the research objectives. Thus, researchers are encourage to make specific and precise objectives.

Identify Data Needs. In this stage, the established research objectives are carefully examined in order to find out the specific data needs to satisfy it. However, identifying these data needs is largely dependent on how well or how clear the research purpose/objectives are made (Parasuraman, Grewal, & Krishnan, 2007). Thus, researchers are advised to pay careful attention in executing the earlier stages so as to obtain precise and valid outcomes.

Identify Data Sources. Parasuraman, Grewal, & Krishnan (2007) mentioned that after identifying the data required to satisfy the research objectives/purpose, the next thing to do is to locate the sources of these data. However, the authors noted that determining the source basically depends on the nature of the data desired. Some data are readily available and some are still needed to be gathered directly from research participants. Readily available data are called secondary data. These are already been collected by other people or institutions through previous research undertakings, experiences, opinions, etc. These are easily accessible internally in the company or externally such as in research publications, guides and indices, compilations, directories, databases, books, media and other communication material sources. On the other hand, primary data is the term for those data that are not readily available (Parasuraman, Grewal, & Krishnan, 2007). As a result, researches or users are needed to exert time and effort in order to gather these directly from the source (e.g. research participants, 30

experts, etc). It follows research gathering procedures such as surveys, discussions or direct observations.

Choose and Appropriate Research Design and Data Collection Method. Research design is a core requisite to complete a research project. It serves as a skeletal framework that specifies how the work should be conducted. Yet, this can only be made once the research objective and data needs are clearly defined. According to Parasuraman, Grewal, & Krishnan (2007), a research design can either be exploratory or conclusive. They explained that exploratory research aims to obtain initial insights to a particular research problem which can instigate further research undertakings. It also sketches possible decision alternatives and relevant variables that need to be considered (Kumar, Aaker, & Day, 2002). Kumar, Aaker, & Day (2002) stated that in this design, researchers doesn’t have strong preconceptions of what possible results he/she may obtain after coducting the entire research process. As a result, methods in this kind of research is highly flexible, unstructured and qualitative. Conclusive research, on the other hand, tend to verify previously gathered insights and helps researchers or decision makers to identify suitable course of action (Parasuraman, Grewal, & Krishnan, 2007). The authors mentioned that this kind of research design is catergorized into two: 1) descriptive research design and 2) experimental (causal) research design. As described by Parasuraman, Grewal, & Krishnan (2007), in descriptive research designs, research respondents are usually described in terms of socioeconomic and demographic characteristics. It stresses the importance of crafting clear problem statement, hypotheses to be tested and an outline of clearly defined data needs as well as the corresponding preplanned and structured procedures (e.g. obseration, case study or survey approaches). It specifies who, what, when, why as well as the procedures of doing it (Malhotra, Marketing Research: An Applied Orirentation 6th Edition, 2010). Experimental research or causal research design, on the other hand, involves investigation of the cause and effect relationship between dependent and independent variables (Parasuraman, Grewal, & Krishnan, 2007).

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Source: Parasuraman, Grewal, & Krishnan (2007)

Figure 2. Chronological Stages of Marketing Research Process

In inferring the causality, the researcher tend to manipulate the independent variables in a controlled environment and explain how it affects the dependent variables (Parasuraman,

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Grewal, & Krishnan, 2007). In other words, the design basically aims at understanding the cause (independent variables) and the efect (dependent variables) in a particular scenario.

Design the Research Instrument. As pointed out by Parasuraman, Grewal, & Krishnan (2007), the existence of research instrument is rooted to the fact that data collected should be recorded. They added that if the the research project requires primary data, it is necessary to produce a research intrument which aids the process of gathering and at the same time recording it. Primary data, as described by the preceding authors, originally comes directly from research respondents can be gathered in a number of ways, though, the most common example is by conducting surveys. Yet, prior the conduct the survey proper, an instrument like a questioannaire must be prepared beforehand. A questionnaire is an instrument used to generate the data necessary to provide answers to the research problems and satisfy the predefined objectives (Hair, Bush, & Ortinau, 2006). It should be noted that careful attention is required in creating the instrument as this affects the quality and the nature of data. As mentioned by Parasuraman, Grewal, & Krishnan (2007), there is a dual communication role in this kind of channel: 1) the questionnaire must communicate questions posed by the researchers, and 2) the questionnaire must communicate their responses back to the researchers. That is why, it is advised to conduct a pre-testing of the survey questionnaire before it will be applied to the real respondents. Traditionally, research instruments were developed in paper form and were distributed physically to the respondents. However, in these days, creation of research instruments exploited the opportunities offered in the Internet as lots of web sites are offering free online survey creation to users. Smith & Albaum (2010) stated that online surveys has become a dominant form of conducting structured/direct interviews . This is so since the internet provides rich support for the questionnaire allowing automatic recording of data (Furrer & Sudharshan, 2001). Employing this methods is typically fast and easy. It enables users to reach participants virtually anywhere around the globe, obtain information quickly and reduce significantly the cost involved in the administration of questionnaires. To assure the effectivity of the questionnaire to gather quality data or information, a pretesting activity is advised to be performed in order to check if there are any glitches in formatting, wording, length, sequencing, layout or anything else which bounds it capability to gather data in economical and systematic manner (Adolphus, 2015). As a matter of fact, Kumar, Aaker, & Day (2002) mentioned that in usual cases, initial drafts of the questionnaires lack important variables and contain ambiguous, ill-defined, loaded or double-barreled questions, which necessitates the process of pretesting. This is done 33

by administering the initial draft of the questionnaire to a few number of respondents (i.e. preferably the ones that will fully participate in the study) or other individuals that are capable of pointing out possible issues in its content as well as in its administration. The number of respondents vary depending on the researchers decision along with other factors such as manpower, time and money available (Kumar, Aaker, & Day, 2002). Once errors in the design are identified, correcting it requires researchers to revisit the previous steps in the questionnaire construction. And again, further examination and justification is required until the data collected meet the expectation of the researcher in terms of the data requirement. Only after that the questionnaires will be finalized and implemented.

Identify the Sample. In any research undertaking, it is essential to define who should provide the data. Apparently, a population exhibiting a common set of characteristics and parameters with respect to the research problem are the primary source for data or information (Parasuraman, Grewal, & Krishnan, 2007). However, as mentioned in the earlier discussions, a research project is subjected to various limitations which incapacitate researchers to involve all the population that are qualified to participate in the study. As a result, researchers opt to select only a sample or a subgroup to make inferences in relation to the characteristics of the whole population being studied. In the selection process, researchers employ sampling techniques which can either be probabilistic or non-probabilistic. As mentioned by Malhotra (2010), non-probability sampling heavily rely on judgement rather than relying on chance in the selection procedure. That is, it solely depends to the researchers’ consciousness in deciding which elements to include in the sample. Malhotra (2010) further indicated that commonly used techniques include convenience sampling, judgmental sampling, quota sampling and snowball sampling, yet, these techniques are subjected to limitations such as the lack of precision and don’t allow objective evaluation. On the other hand, random sampling, systematic sampling, stratified sampling and cluster sampling are just few probability sampling procedures that involve the selection of sampling units by chance allowing researchers to make inferences about the population from the sample drawn (Malhotra, 2010).

Collect the Data. Data collection is conducted only if the research instrument and design are already prepared accurately. In the process, it is essential to examine the completeness, consistency and adherence of respondent’s answers to the questions stipulated in the instrument (Parasuraman, Grewal, & Krishnan, 2007). Only after that the data approved for analysis. Taking the initiative to do this examination process ensures that the data gathered

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are of high quality and also keeps the researcher from experiencing difficulties in the data analysis and in making inaccurate conclusions (Parasuraman, Grewal, & Krishnan, 2007). Analysis and Interpretation of Data. Parasuraman, Grewal, & Krishnan (2007) mentioned that concrete findings and conclusions can only be created once the collected data are analysed and interpreted, yet, analysis and interpretation is highly interrelated to the previous steps. Recklessness in performing the previous research steps can completely make wrong inferences; discrediting the usefulness of the research project to wide range of users. In this stage, data obtained from respondents are edited, coded, and tabulated before performing formal analyses such as statistical tests (via SPSS, Statistica, MS Excel, other statistical software). Nevertheless, the type of analysis to implement is highly dependent on the sampling procedures, measurement instruments, and data collection techniques used (Smith & Albaum, 2010). Present Research Findings to Decision Makers. Parasuraman, Grewal, & Krishnan, 2007 indicated that marketing research is conducted in order to aid marketing managers in making sound decisions, which makes it a crucial last stage of the research process, wherein findings and inferences are presented to them orally or in written form. The authors added that accuracy and usefulness of the finds must be fully satisfied as future decisions and strategy formulation is highly dependent on the results of the research project.

3.4. Marketing Research in the Online Environment

The use of Internet in marketing research has grown significantly, driven by the desire to lower data collection cost and research cycle time (Grover & Vriens, 2006). It has become a remarkable tool to marketing researchers as it offers wide range of opportunities from cost reduction, enhanced interactivity on surveys, ease in administration, reduction/elimination of errors on data entry, coding and transcription (Smith & Albaum, 2010). Kent (2007) added that the Internet supports marketing research purposes which include the following: 1) access data on electronic database, 2) distribution of questionnaires via internet survey, 3) inclusion of samples through using e-mail addresses online, 4) design questionnaire via online questionnaire design software, and 5) data and analyses are readily available to clients. Given these benefits and opportunities, several difficulties also arise. To cite an example, maintaining respondents’ interest in marketing research surveys in the Internet is extremely difficult due to the fact that people’s span of internet attention are too short (Grover & Vriens, 35

2006). As a result, creating long surveys discourage people to finish the survey itself. Apparently, this presents a huge challenge to developers to make the survey interesting and stimulating. To do this, the researcher can improve the survey scale presentation (i.e. slide bars, drag and drop to better understand scales) or basically enhance its presentation, appeal and interactivity (e.g. rotating products, zoom in/out, movement of text graphic “piped”). Furthermore, as with the traditional survey methods, survey conducted in the Internet are still subjected to errors. These errors include coverage (sample frame does not represent the population as a whole), sampling (non-representative sample is drawn from the sample frame) as well as measurement errors (information generated and true value of information are not coherent) (Smith & Albaum, 2010).

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PART IV

METHODOLOGY

4.1. Site Selection

The study was conducted in Masaryk University in Czech Republic and Visayas State University in the Philippines since these schools precisely matched the major focus of the research undertaking that is to deal with the university students’ online buying behaviour in developed and developing countries. As reported by Cushman and Wakefield (2013), most developed countries in Europe such as United Kingdom, Germany, USA, France, Netherlands including Czech Republic participate significantly in the global online retail market and that these countries are also leading in terms of online infrastructure including market size and in exploiting market opportunities. Meanwhile, Philippines, ranking 48th in global online retail scale and potential, exhibit a continuously growing internet shopping market and which is also consistently adapting to the ever changing market environment (Cushman and Wakefield, 2013). Thus, given these information, it would be worthwhile to uncover similarities and differences of internet shopping behaviour among consumers in both countries. Aside from the things mentioned above, other factors such as accessibility and availability of resources were also considered by the researcher. As the researcher is currently connected in both schools, the process of data collection was considered more convenient without obstructing the quality and relevance of data obtained.

4.2. Research Model and Hypotheses

Being aware on every aspect of the targeted consumers (e.g. behaviour, culture, etc) is crucial in attaining business success. Thus, this study intended to examine the online buying behaviour between university students in the developed and developing countries via quantitative marketing research. Specifically, it intended to 1) provide an overview of the basic characteristics and magnitude of online shopping adoption between students in the specified countries, 2) identify the major drivers and barriers affecting their online shopping adoption and dis-adoption, 3) explain the impacts of national culture in relation to internet buying behaviour among students in the specified countries, and 4) develop recommendations

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as to how e-marketers should adapt the ever changing behaviour of the specified consumers in order to maximize profitability and sustain competitive advantage. A theoretical model was created to facilitate the understanding of online buying behaviour between university students in both countries (Figure 3). This model specifies that there are several factors (independent variables) that are affecting the consumer prior he/she elucidates a buying response (dependent variable). These factors include web site characteristics, web site product characteristics, consumer characteristics as well as culture. As soon as these factors interact in the buying process, various responses are created encompassing purchase frequency, e-retailer choice and product choice of the consumers. Marketers and researchers need to understand these foundation of buyers’ behaviour especially the factors that pose robust influence to buyers’ decision. In addition, it necessary for them to clearly spot what particular characteristics that the buyers’ possess (i.e. how buyers respond to stimuli) and how they make decisions given the factors mentioned above.

Figure 3. Theoretical Model Generated to Facilitate Understanding of Buying Behaviour of Consumers in the Online Environment

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Moreover, based on the review conducted on related past researches, the following hypotheses are established:

H1: The extent of online shopping adoption among university students in Czech Republic is greater than the Philippines

H2: Security and Trust are the major factors that are highly valued by students in both universities in making online purchase decisions

H3: As compared to Czech students, university students in the Philippines exhibiting collectivist culture are heavily influenced by any associated groups (e.g. family) in making online purchase decision

H4: Czech students perceived high risks in online shopping and places strong emphasis of reducing these as compared to Filipino students

H5: Comparing Filipino and Czech students, Czech students tend to be more influenced by their superiors ideas and opinions prior making a purchase decision

H6: Filipino students are more subjective and intuitive in making online purchase as compare to the Czech students

H7: The extent that Czech students look at their purchases online as long term decision is greater than Filipino students

4.3. Research Design

One of the core steps in the marketing research process is the selection of appropriate research design. A research design is a framework that specifies the processes, procedures and activities of how the research should be conducted in order to provide answers to the research questions that satisfy the research objectives and consequently provide information necessary for decision making (Malhotra, Marketing Research: An Applied Orientation 6th Edition, 2010). This study employed descriptive research design. This design is mainly concerned on the frequency of which an event occurs or in understanding relationship between two or more variables (Shukla, 2008). Specifically, survey methods were utilized in the gathering primary data. A structured quetionnaire was developed (see Appendix A1), composed of structured questions intended to generate the following data needs:

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 Demographic Profile of the Respondents - This include age, sex, economic status, level of education, income level, employment and other factors that may or may not pose an influence on consumers’ adoption and dis-adoption of internet shopping  Internet Experience and Frequency of Online Shopping among Respondents - This information pertains to how long respondents used the internet and the number of times they engage in online shopping in a specified period of time. Knowing this information enable the researcher to assess or measure the magnitude of online shopping adoption and discover its correlations with other factors influencing online buying behaviour.  Factors affecting Online Shopping - Aside from the demographic factors that may influence online buying behaviour, other factors such as website design, interfaces, security, reliability and website value-added services that may influence consumer buying intentions are also considered in the study. Examining Czech and Filipino students as entirely different provided insights as to how similar or different they perceived these factors influencing their online purchase adoption or behaviour.  Aspects of Culture (i.e. Hofstede’s Cultural Dimension) exhibited by Czech and Filipino students as influencing factors for online shopping adoption - Assessing the respective culture as an influencing factor of online buying behaviour between Czech and Filipino students is a core concern on this study. However, since culture is very broad concept, Hofstede’s cultural dimension was employed to explain aspects of culture influencing the online buying behaviour exhibited by the two culturally different groups. The cultural comparison dealt on individualism/collectivism, power distance, masculinity/femininity, long-term orientation and uncertainty avoidance among respondents from the Czech Republic and the Philippines. -

These questions were adopted from the questionnaires developed by Jha (2014), Yoldas (2011), Kim (2004) and Jeyashoke, Vongterapak, & Long (2014). As the studies of these authors dealt on consumer behaviour in the online shopping, some questions (e.g. factors affecting online shopping, internet use and online shopping frequency, demographics, 40

aspects of culture) presented on their respective questionnaires are relevant and suitable to gather data that satisfy the established objectives. Moreover, as the researcher has insufficient experience in developing questionnaires, the use of questions from a tested data gathering instruments enhances the accuracy of the survey questionnaire for this study.

Soon after the questions were collated, these were implemented in the Qualtrics Survey Platform. This survey platform enables users to freely customize a questionnaire and allow faster sharing through sending a web link to the respondents and let them answer the questions online. A pretest was administered after the questionnaire was completed to some study participants to look for biases and errors. Subsequently, the questionnaire was further checked and corrected in order to arrive the expected data needs. A non-probability sampling procedure called convenience sampling was used. In this sampling procedure, the selection of respondents was largely based on the accessibility or convenience on the part of the researcher (Ross, 2005). Sample units within a population that are easiest access are chosen. At the same time, due to the absence of a masterlist containing information of student online shoppers in both universities, it would be difficult for the researcher to operate probabilistic sampling techniques in the selection of respondents. Also, as this study aimed to explore initial insights regarding the online buying behaviour of culturally different students, the use of this sampling procedure can still generate informative results despite the fact that it is subjected to number of biases.

Full distribution of questionnaires was performed from January to March 2016 via sending a generated link to the respondents through emails and Facebook messages. Faculty of Economics and Administration Masaryk University (FEA-MU) - International office coordinator and thesis supervisor were contacted through email and asked to distribute the link to the Czech students. Around 2000 Czech and Slovak students from the FEA-MU were contacted to participate in the survey. However, only 371 students responded and completed the survey questionnaire. Meanwhile, in reaching Filipinos respondents, colleagues from Visayas State University were contacted through email for them to spread the questionnaires to the students in the entire university. No exact number as to how many students were encouraged to participate, yet, data showed that around 106 Filipino students participated. Around 100 respondents was initially targeted, however, all in all it reached 477 respondents. The profile of respondents is found in Part V: 5.1. Also, the study was initially intended to include Czech and Filipino nationalities only. Nevertheless, during the collection of data,

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results revealed that there were a significant number of Slovak nationalities who participated and completed the survey questionnaire. Thus, the researcher decided to include these respondents and the analysis is now dealt between three different nationalities, namely: Filipinos, Czechs and Slovaks.

Data that were obtained from the survey questionnaires were analysed using IBM’s Statistical Package for the Social Sciences (SPSS) Software. Specifically, the analysis involved descriptive statistics (e.g. frequencies and cross-tabulations) which aims at identifying the relative occurrence of different values of a particular variable and find patterns on the data obtained. Statistical tests were also performed, specifically, non-parametric test - Kruskal-Wallis H (H) that is highly suited for examining statistical differences on data (e.g. ordinal variables) was performed. Additionally, spearman’s correlation (rho) was used to determine the direction of association of two variables (i.e. at least one is an ordinal variable) (Lærd, 2016). Another test that is highly suited for analysis involving ordinal variables is the Mann-Whitney U test. This was conducted to compare differences between two independent groups (either ordinal or continuous) but not normally distributed (Lærd, 2016). Furthermore, the importance of various factors influencing online shopping adoption was assessed by the respondents. In the assessment process, a scale was established for ranking. For each factor, a respondent can choose a point in the scale reflecting owns perception how important the factor is in influencing online shopping adoption. At each point in the scale, scores were assigned: 1 = extremely unimportant, 2 = unimportant, 3 = neither important nor unimportant, 4 = important and 5 = extremely important. Total scores for each factor per nationality were calculated using the formula:

∑ 푓푎푐푡표푟 푖 = (푛1 푥 푆푐푎푙푒1) + (푛2 푥 푆푐푎푙푒2) + (푛3 푥 푆푐푎푙푒 3) + (푛4 푥 푆푐푎푙푒4) + (푛5 푥 푆푐푎푙푒5)

Where: n1 = number of respondents who indicated the factor as extremely unimportant (Scale 1) n2 = number of respondents who indicated the factor as important (Scale 2) n3= number of respondents who indicated the factor as neither important/ unimportant (Scale 3) n4= number of respondents who indicated the factor as important (Scale 4) n5= number of respondents who indicated the factor as extremely important (Scale 5)

Subsequently, maximum scores among all the factors per nationality were determined. In addition, the data were presented using tabular and graphical presentations. Both of these facilitated the interpretation since the data are systematically grouped and arranged, thus, making information easy to understand and compared.

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Part V

RESULTS AND DISCUSSION

5.1 Respondents Profile

There were 477 respondents who participated and completed the survey questionnaires. Out of these, 61.4% (293) were women and 38.6% (184) were men. The average age of the respondents was 22.68 years old with the youngest at 14 years old while the oldest was 54 years old. Around 45.1% (215) and 41.7% (199) of the respondents were full time and part time students, respectively. The remaining 13.2 % (63) were composed of the following: 6.5% working students, 4.2 full time workers, 0.6 self-employed, 0.2 unemployed and 1.7% self-employed students. Fifty percent (50.1% = 239 respondents) of the respondents were bachelor’s degree holder, while 38.4% (183), 11.3% (54)and 0.2% (1) of the respondents attained high school, masters and post-doctoral level, respectively. Czech respondents comprised the majority (61.4% = 293 respondents) of the respondents, followed by Filipinos (22.22% = 106 respondents) and Slovaks (16.4% = 78 respondents). The age, gender and educational level distribution by nationality are presented in Table 2.

Table 2. Profile of respondents Age Gender Educational Level

Nationality High Post- Min Mean Max Male Female Bachelors' Master's School Doc

Filipino 106 14 23.26 54 28 78 6 85 14 1 %within 22.22% 26.4% 73.6% 5.7% 80.2% 13.2% .9% Czech 293 19 22.63 45 119 174 140 119 34 0 %within 61.40% 40.6% 59.4% 47.8% 40.6% 11.6% 0.0% Slovak 78 18 22.05 26 37 41 37 35 6 0 %within 16.40% 47.4% 52.6% 47.4% 44.9% 7.7% 0.0%

5.1.1. Internet Use and Experience by Nationality

This study focused on online shopping hence it is also interesting to know the respondents’ internet experience. Results showed that majority (96% = 458 respondents) of the respondents have been using the internet for more than five years already with only 0.6% (3 respondents) who just started (i.e. with less than a year experience in internet use).

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Meanwhile, about 3.4% (16 respondents) were on the internet within the period of 1-5 years. Considering the time per week they spent on surfing the web, results indicated that 39.8% (190 respondents) of the respondents spent more than 20 hours in the Internet. Meanwhile, 46.2 % (220) were average users who consumed 6-20 hours per week in the web. Less frequent users (14% = 67 respondents) spent 0-5 hours in the internet per week. A comparison among nationalities was done to acquire insights on the extent of internet use. It was found out that majority of the Czechs (99.7% = 292 respondent) and Slovaks (98.7% = 77 respondents) were using the internet for more than 5 years already and the rest were on the internet for 3-5 years. Likewise, around 84.0% of the Filipinos were on the internet for more than 5 years; however, 13% (17 respondents) have just begun – existing in the internet world for around 1-5 years (Figure 4). This result implies that Czechs and Slovaks have used the internet for quite a while already as compared to Filipinos (H = 52.124, p=0.000) (See Appendix B1). On the other hand, in terms of the time spent per week in the internet, results showed that Filipinos surf the web less intensively than other nationalities, as indicated by the 36.8% (39 in count) of respondents spending time in the internet for 0-5 hours/ week (H = 42.943, p=0.000). Intensive users were the Slovaks and Czechs who spent more than 20 hours per week and 1-15 hours per week, respectively (See Appendix B2.). This leads to a conclusion that developing countries were not intensive users of the internet than nationalities from developed countries like the Czechs and Slovaks.

Figure 4. Time spent per week in surfing the web

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5.1.2. Internet Use and Experience by Gender Differences

Another interesting result was found when gender differences and time spent per week in surfing the web were cross tabulated. Values indicated that u = 22987.500, p = 0.005, which signifies that there is significant difference between the male and female users. Figure 5 showed that males used the internet longer than females.

50.00% 45.00% 40.00% 35.00% 30.00% 25.00% Male 20.00% 15.00% Female 10.00% 5.00% 0.00% 0 - 5 hours 6 - 10 hours 11 - 15 16 - 20 More than hours hours 20 hours

Figure 5. Gender and time spent per week in surfing the internet

5.2. Frequency of Online Shopping

Among the 477 respondents, 44.2% (211 respondents) indicated that “sometimes” they used the internet for shopping various products. Nevertheless, users in the extreme sides, such as those who shop very often and those who never experienced online shopping also appeared. Intensive users account 5.5% (26) of the total number of respondents while 3.8 % (18) accounts for users who never shop online. Looking more closely at the data (see Figure 6), it shows that between the three different nationalities, Czechs and Slovaks use the internet shopping more intensively, and that they absolutely have greater experience in online shopping compared to Filipinos (H = 27.704, p=0.000) (See Appendix B3). A significant 16.8% (18) of Filipino respondents never experienced online shopping yet. Accordingly, their reluctance to shop online is due to the following: 1) reliability of seller, 2) quality of the products offered online, 3) absence of credit/debit card, 4) insufficient knowledge of how online shopping works and 5) experience on shipping problems. Apparently, Filipinos are less active in online shopping environment as compared to other nationalities. Given these, the hypothesis previously established stating that “The extent of online shopping adoption among 45

university students in Czech Republic is greater than the Philippines” is proven to be true. Based on the data presented in the literature (see Part II: 1.1.), Czech Republic and Slovakia had established a good internet shopping infrastructures that led to the acquisition of a significant portion of the online market. Nevertheless, the Philippines as an emerging country is at its young stage in the online shopping environment. Its internet penetration rate is still very low at 45.6% according to Internet Live Stats (2016). Additionally, Gonzales (2015) reported that internet speed in the Philippines is lagging and is regarded as the 2nd slowest in Asia with a download speed of 3.64 megabit per second (mbps) which is way below the average broadband speed of 23.3 mbps. The author further added that it is also one of the most expensive, with an average value of $18.19 per mbps, triple times than the average global cost of $5.21 Nevertheless, various stakeholders (e.g. government) have started talking about this issue and with any luck alleviate this poor situation in the near future towards the realization of a better online retailing platform and stable customer base.

50.0%

40.0%

30.0% Filipino Czech 20.0% Slovak 10.0%

0.0% Never Rarely Sometimes Often Very Often

Figure 6. Frequency of using the internet for shopping

5.2.1. Internet Use/Experience and Frequency of Online Shopping

The relations between internet experience (i.e. length of time (in years) the respondents used the internet, time spent in surfing the web and frequency of online shopping were examined. As results revealed (see Figure 7), most non-internet shoppers are those who have been in the internet for less than a year. The number continues to decline as the years of existence in the internet rises. In other words, as users become more experienced in the internet and spent a significant amount of time surfing the web, there is a high likelihood that

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he/she will use internet for online shopping. Result of the correlation analysis revealed that there is a positive association between the two variables (rho = 0.177, p =0.000). Thus, signifies that the longer the person is using the internet, the more often he/she use internet for online shopping. Examining this relation by nationality, results revealed that for Czechs and Slovaks, the correlations are positive (rho = 0.011 and rho=0.033, respectively), though not statistically significant (p=0.855>0.05 and p=0.7777>0.05, respectively), signifying an inconclusive evidence about the significance of the association between the variables. However, the length (in years) of internet use and frequency of online shopping positive correlation is strong on Filipinos and is statistically proven to be significant (rho = 0.262, p=0.007). This result agrees to what Naseri and Elliott (2011) found that there was strong evidence that web experience is affecting online shopping. They specified that the probability of online shopping was significantly higher for consumers who frequently used the internet.

5.2.2. Products Bought Online

Results revealed that electronic goods (26.2%), clothing and accessories (19.2%) and theatre/cinema tickets (17.0%) were the commodities respondents usually bought online (Figure 8). These products still top when examined by nationality (Figure 9). Moon, Chadee and Tikoo (2008) indicated that search goods are more appropriate to be sold online than experience goods. The percentages enumerated above proved its appropriateness in the online market environment. Electronic goods and clothing and accessories as concrete examples of search goods exhibit a characteristic that they can be easily compared and evaluated before coming up with the final purchase decision. Meanwhile, Hansen and Moller Jensen (2009) reported that selection of clothing in the online market is a difficult pursuit for consumers and may prevent them to make a final purchase decision. Hasan (2010) also mentioned that females required much physical touch or test of the desired clothing apparel than males. Hence, prior to purchase they usually have lower cognitive and affective attitudes which reduce their intention to shop online than men. Additionally, Hansen and Moller Jensen (2009) indicated that there is a reduced possibility of obtaining personnel advice in purchasing clothing in the online market, thus, they suggested that online retailers has to provide personnel advice via chat rooms or other initiatives to provide guidance to consumers. Given these constraining factors, clothing apparels and accessories still tops among the products bought online by the respondents. 47

120.0%

100.0%

80.0% Never Rarely 60.0% Sometimes 40.0% Often

20.0% Very Often

0.0% Less than 1 year 1 - 3 years 3 -5 years More than 5 years

Figure 7. Relation between frequency of online shopping and time per week in surfing the web

26.2% 19.2% 17.0% 11.6% 7.8% 5.8% 5.2% 3.3% 4.0%

Figure 8. Products bought in the internet

35.0% 30.0% 25.0% 20.0% Filipino 15.0% Czech 10.0% Slovaks 5.0% 0.0% Clothing, Electronic Theatre, Holiday Perfume, Food and Household Accessories Goods Cinema Trips comsetics Drinks Goods, Ticket Furnture

Figure 9. Products bought online by nationality

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5.3. Respondents’ Perception towards the Factors Affecting Online Shopping Adoption

Based on the calculated result (Table 3), secure payment process is the factor that is greatly perceived by Filipinos, Czechs and Slovak respondents to highly influence their online shopping engagement. This result proves H2 specifying that security and trust are the major factors that are highly valued by the respondents. Also, the result agrees to the result found by Chen et al., (2010), wherein they found out that consumers often value security the most in purchasing goods and services online.

Moreover, ranking second among the factors vary in the three different nationalities. For Filipinos, they value clear product features after security. However, this factor is also a key feature of building trust. As Yang et al., (2009) indicated, trust can be seen as e-retailers describe products appropriately as well as keeping good ethical performance and stating privacy policies. Thus, implies the utmost relevance of security and trust features among Filipinos. On the other hand, for Czechs and Slovaks, saving money and previous experience ranked second, respectively. Through online shopping, consumers can save money through price discounted product offerings as well as they no longer visit physical stores. To purchase products online, few things are needed: credit/debit card, computer/mobile and internet connection. In few minutes, products will be purchased and in few days will arrive at the doorstep. The convenience, service reliability (e.g. on time delivery) plus the positive previous online experience provided by online shopping platforms enable Czech and Slovak respondents to be kept engaged in online shopping environment.

Table 3. Scores of Factors Influencing Online Shopping Adoption Factors Filipino Czech Slovak Secure Payment Process 509 (1st) 1365 (1st) 352 (1st) Clear Product Features 502 (2nd) 1105 (10th) 298 (8th) Privacy Protection 499 1194 (3rd) 309 (4th) Customer Service 497 1080 (12th) 278 (12th) Return Policy 492 1136 (7th) 280 (11th) Personal Internet Access 483 1020 (13th) 268 (13th) Convenience 482 1121 (9th) 293 (9th) Company Reputation 482 1162 (5th) 298 (7th) Save Money 481 1216 (2nd) 317 (3rd) Product Variety 479 1150 (6th) 305 (5th) Ease Of Use 474 1096 (11th) 290 (10th) Time Saving 470 1123 (8th) 302 (6th) Previous Experience 461 1186 (4th) 317 (2nd) See and Touch Before Buy 450 914 (15th) 229 (16th) Enjoyment 444 856 (16th) 245 (14th) Delivery Time and Fee 383 921 (14th) 236 (15th)

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5.3.1. Perception towards Previous/Current Online Shopping Experience

As respondents perceived the importance of factors towards online shopping adoption, they also provided their thoughts about their previous and current online shopping experience. These were evaluated and results are discussed in the following section.

Perception towards Web site Characteristics

Web site characteristics mainly comprise the features a particular web site exhibits. In one way or another, these characteristics affect online shopping intentions. These include: 1) perceived ease of use, 2) firm’s reputation, 3) trust, 4) reliability and 5) functionality. In this study, these characteristics were considered and examined particularly to its relation to online shopping intentions of Czechs, Slovaks and Filipinos. Different variables are used to assess the respondents’ perceived ease of use in the online shopping environment. These include a) how easy it is to navigate through the website, b) how convenient it is for the user, and c) how attractive it is to stimulate an online purchase. Data shows that a high proportion of respondents agreed that these features are already established in online shopping sites (Figure 10). Taking a look at ease of navigation, most Czech, Slovak and Filipino respondents perceived that e-shopping sites are easy to navigate in general. Those who agreed are largely dominated by those who have more experience in online shopping. This relationship is verified as Spearman’s correlation analysis revealed that frequency of online shopping and the perception towards ease of navigation is positively correlated (rho = 0.103, p = 0.024). Thus, the more intensive the user is in using online shopping, the more agreement he/she designates that online shopping platforms are easy to navigate (Figure 11). In between nationalities, results revealed no significant differences. Likewise, the same trend was observed with internet shopping convenience. Most respondents regardless of nationality still express conformity that online shopping is more convenient compared to the traditional brick and mortar store. Positive correlation between frequency of online shopping and perception towards online shopping convenience was found. Respondents who frequently shop online agreed that it is more convenient than going to physical stores (rho = 0.269, p = 0.000). On the other hand, for web site attractiveness, a significant difference on the perception of different nationalities exist at values H = 33.423, p=0.000. As indicated in Figure 12, Filipino respondents (24.5%) top in strongly agreeing that online shopping sites are attractive. Meanwhile, Czechs (43.0% or 126 in count) express neutrality or indifference on its perception to attractiveness (See Appendix B4).

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70.0 60.0 50.0 40.0 Convience 30.0 Attractiveness 20.0 10.0 Ease of Navigation 0.0 Disagree Strongly Neither Agree Strongly Disagree Agree nor Agree Disagree

Figure 10. Respondents’ thoughts about perceived ease of use in internet shopping

80.00% 70.00% 60.00% Very Often 50.00% Often 40.00% 30.00% Sometimes 20.00% Rarely 10.00% Never 0.00% Strongly Disagree Neither Agree Agree Strongly Agree Disagree nor Disagree

Figure 11. Ease of navigation and frequency of using the internet for online shopping

60.0% 50.0% 40.0% 30.0% Filipino 20.0% Czech 10.0% Slovak 0.0% Strongly Disagree Neither Agree Strongly Disagree Agree nor Agree Disagree

Figure 12. Respondents’ perception towards web site attractiveness

Firm’s Reputation is a product of taking actions that aims to protect the welfare of consumers. These actions included: 1) delivery of promises made to consumers (e.g. on time 51

delivery of products), 2) ensuring transactions are error free, 3) protection of consumers’ personal information and many others. The results revealed that most respondents (47.4% = 226 respondents) posed neutrality on shopping sites’ reputation. This means that they neither agree nor disagree that online shopping sites have strong reputation. About 32.9% (157 respondents) of them agreed that online shops have strong reputation. Likewise, respondents agreed that e-retailers are performing desirably in meeting customers’ expectations through their products and services. Meanwhile, based on nationality of respondents, data showed no significant difference (H = 0.072, p = 0.965 > 0.05). However, in terms of their perception on product delivery, Filipinos exhibit a slightly higher degree of disagreement that e-retailers deliver the products on time as compared to Czechs (Figure 13). This difference is found to be slightly significant: U = 13906.500, p=0.077 > 0.05. Furthermore, data also showed that there is strong relation between the perception of e-retailers’ reputation and frequency of online shopping. Correlation analysis revealed the value of rho = 0.185, p=0.000 signifying positive correlation between the variables. This suggests that respondents who often display disagreement or neutrality towards the previously mentioned factors are the less intensive shoppers (e.g. never, rare and sometimes shoppers).

70.0% 60.0% 50.0% 40.0% Filipino 30.0% Czech 20.0% 10.0% Slovak 0.0% Strongly Disagree Neither Agree Strongly Disagree Agree nor Agree Disagree

Figure 13. Perception towards on time delivery of products

Trust is built when there is a transparency of transaction made by the seller and the buyer. Martin and Camarero (2008) mentioned that online shopping trust is determined by web security, privacy policies and service quality provided by the e-retailers. When respondents were asked about the safety of online shopping, 41.1% (196 respondents) have agreed and 6.3% (30 respondents) strongly agreed that online shopping is safe (Figure 14). This means that these people perceived the risk of theft at low levels and positive online

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shopping was experienced previously via receiving the products on time with the right quality. Yet, 36.3% (175 in count) of respondents neither agree nor disagree on safety of online shopping. Disagreements among respondents also exist representing a total 15.9% (64 respondents) of the total number. On the other hand, the security of customers’ information is also a factor of trust. Data showed that 42.3% (202 respondents) of the respondents cannot really say that e-retailers secure the information they provided or not. However, 36.3% (173 respondents) have agreed that online shopping sites secured the privacy of information the customers provided. The perception of internet shopping safety between nationalities was found to be slightly significant (H = 5.804, p=0.055>0.05). Around 45.1% (132 respondents) of Czech respondents agreed that online shopping is safe. Slovaks express neutrality (44.9 %=35 respondents) compared to other nationalities. Filipinos (19.8% = 21 respondents), however, indicated a higher level of disagreement on the safety of online shopping. Positive correlation was found between frequency of online shopping and the respondents’ perception towards the safety of online shopping (rho = 0.105, p = 0.022). This result implies that the higher the perception of safety, the more frequent the respondent use internet for online shopping.

50.0% 45.0% 40.0% 35.0% 30.0% 25.0% Filipino 20.0% Czech 15.0% Slovak 10.0% 5.0% 0.0% Strongly Disagree Neither Agree Strongly Disagree Agree nor Agree Disagree

Figure 14. Safety Perception towards Online Shopping

Majority of the respondents regardless of nationality did not experienced online shopping scams and fraudulent activities (Figure 15). However, among those who are victims of scam and fraud, more Slovaks (28.2% = 20 respondents) and Czechs (25.3% = 77

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respondents) were victimized compared to Filipinos (14.2% = 15 respondents) as they patronized e-shopping (H = 6.634, p = 0.036) (See Appendix B5). Experiences of scammed victims include receipt of defective products. Victims find ways or initiatives to minimize losses by sending complaints to the seller. Some of them received feedback and even received full refund from the purchased item. There are cases when shoppers brought the problem to the police for filing a formal complaint. Nevertheless, others did not do anything to cope up with the scam.

120.0%

100.0%

80.0%

60.0% No Yes 40.0%

20.0%

0.0% Filipino Czech Slovak

Figure 15. Online Shopping Scams Experience

Reliability of online shopping sites can be measured by providing accurate description of their products/services online (Shergill and Chen, 2005). Around 39.6% (189 respondents) of the respondents indicated that perceived that online shopping sites correctly describe the products/services displayed online including the delivery time promised by the company. However, 32.9% (157 respondents) cannot really say if online shopping sites are really doing this or not. From the percentage indicated above, Slovaks and Czechs are into agreement than Filipinos (U= 3483.000, p = .055 > 0.05 and U = 13383.000, p = .026, respectively) (Figure 16) (See Appendix B6). Filipinos had stronger disagreement that products/services in the internet are accurately described and published as compared to Czechs and Slovaks (slightly significant at H = 5.607, p=0.061>0.05). This implies that online retailing infrastructure in the Philippines is not as established as that of the Czech Republic and Slovakia. Unreliable e- retailers deprived customers’ positive and contented online shopping experience. On the other 54

hand, a strong relation between the frequency and perception towards online shopping reliability was found. Correlation analysis result values indicated rho = 0.136, p=0.003, implying that intensive users exhibited strong sense of agreement, while, the less frequent shoppers poses neutrality or even disagreement towards online shopping reliability (Figure 17).

50.0%

40.0%

30.0% Filipino 20.0% Czech Slovak 10.0%

0.0% Strongly Disagree Neither Agree Agree Strongly Disagree nor Disagree Agree

Figure 16. Product description perception of respondents

60.0% 50.0% Strongly Disagree 40.0% Disagree 30.0% Neither Agree nor Disagree 20.0% Agree 10.0% Strongly Agree 0.0% Very Often Often Sometimes Rarely Never

Figure 17. Online Shopping Frequency and Perception towards product description perception

Functionality refers to the ability of the online shopping platform to provide information in relation to the products, services and transaction guidelines or other purchase related information (Law and Bai, 2008 as cited by Lee et al., 2011). The ease of finding information especially in comparing products online is a unit to measure functionality feature of the e-shopping platform. Based on the result, 48.8% (233 respondents) and 15.3% (73 respondents) express agreement and strong agreement, respectively; that product related information can be easily found in online shopping sites. However, this showed no difference

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in terms of perception by nationality. Meanwhile, 41.3% (197 respondents) agreed and another 40.3% (192 respondents) strongly agreed that products can be easily compared online. Nevertheless, different nationalities express varied perception. Both Czechs and Slovaks express much higher agreement (i.e. including those who strongly agree) that products can be easily compared online compared to Filipinos (H = 46.534, p = 0,000) (Figure 18) (See Appendix B7). This implies that Filipinos less perceived that the functionality features of the online shopping site in their country is well established. As the online shopping market in the Philippines is still emerging, e-retailers are still continuously developing the platform that it would offer a positive experience to existing and prospective customers. Flaws are still existing influencing the perception of customers. Czechs and Slovaks were already benefiting the advancement of online shopping platforms that offered positive experiences to wide range of online users. Furthermore, data also showed that intensive online shoppers had stronger agreement or justification that product information can be easily found in online shopping sites (Figure 19). Likewise, they also agreed that product comparison is relatively easier online.

60.0% 50.0% 40.0% 30.0% Filipino 20.0% Czech 10.0% Slovak 0.0% Strongly Disagree Neither Agree Strongly Disagree Agree nor Agree Disagree

Figure 18. Product Comparison Perception by Nationality

70.0% 60.0% 50.0% Very Often 40.0% Often 30.0% 20.0% Sometimes 10.0% Rarely 0.0% Never Strongly Disagree Neither Agree Strongly Disagree Agree nor Agree Disagree

Figure 19. Frequency of Online Shopping and Online Product Information

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In summary, it was found that frequency of online shopping and the perception towards ease of navigation is positively correlated, including perceived convenience and frequency of online shopping. Thus, the easier the online shopping platform is navigated and the more if offers convenience to consumers, the more the consumer engages in online shopping. Firm reputation as built by on time product delivery revealed that Filipino respondents exhibit a slightly higher degree of disagreement that e-retailers deliver the products on time as compared to Czechs and Slovaks. On the other hand, the perception of internet shopping safety as a factor of trust between nationalities was found to be slightly significant. A larger portion of Czech respondents agreed that online shopping is safe. Meanwhile, Slovaks exhibited neutrality compared to other nationalities. Most respondents haven’t experience online scams and fraudulent activities. However, among those who are victims of scam and fraud, there were more Slovaks and Czechs compared to Filipinos as they patronized e-shopping. Experiences of scammed victims include receipt of defective products. Establishing online shopping reliability can be done through accurately describing products presented online. Results revealed that Filipinos had stronger disagreement that products/services in the internet are accurately described and published as compared to Czechs and Slovaks. This implies that online retailing infrastructure in the Philippines is not as established as that of the Czech Republic and Slovakia. Unreliable e-retailers deprived customers’ positive and contented online shopping experience. In terms of online shopping web site functionality, both Czechs and Slovaks express much higher agreement (i.e. including those who strongly agree) that products can be easily compared online compared to Filipinos which implies that Filipinos less perceived that the functionality features of the online shopping site in their country is well established.

Consumer Characteristics Demographic characteristics of consumers may or may not pose influence towards online shopping adoption. Hui and Wan (2007) found that gender differences influenced apparel shops as females wished to physically see, touch or even wore before purchase. Educational attainment of individuals also affected online shopping adoption. Highly educated individuals have more responsibilities and that they limited time to do shopping in physical stores (Hui and Wan, 2007). In this study, the demographic characteristics of respondents and their level of engagement towards online shopping were examined. In terms

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of gender, men and women exhibit more or less the same frequency of shopping online (U=25212.500, p=0.207>0.05). On the other hand, women are largely buying perfumes, cosmetics, clothing & accessories, holiday trips and theatre/cinema tickets, whereas, products that were mostly bought by men comprises electric goods (Figure 20). See and touch factor is not crucial for Czechs and Slovaks suggesting that they can buy products even without touching or seeing. Filipinos extremely paid attention to this factor. They ranked see and touch factor as extremely important (44.3% = 47 respondents) and important (34.0% = 36 respondents). Educational attainment also influenced online shopping adoption. The higher educational level attained by the respondent, the more they engaged in shopping online (Figure 21). This conformed Hui and Wan (2007) that highly educated individuals are taking many responsibilities at work or any other aspect of their lives and that they have less time to go to physical stores. For them, it is much convenient to shop online as this saves time and effort and they also have the capacity to pay additional service (e.g. delivery). Spearman rho correlation analysis indicated the values: rho = -0.017, p=0.706, implying the negative relation between educational attainment and the frequency of shopping online. However, p- value suggests that the relationship is insignificant, thus, insufficient to refute the results of previous research findings. Furthermore, the best current occupation of the respondents were also considered and examined whether it influences their frequency to shop online. Results showed that occupation had a very slight relation to the frequency of online shopping (x2=35.765, p=0.058>0.05). This indicated that employed and unemployed individuals slightly exhibited differences on their online shopping frequency pattern. Nevertheless, as this study focused mostly students, the significance of occupation as well as income towards online shopping engagement is not clearly seen.

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100.0% 80.0% 60.0% 40.0% 20.0% Male 0.0% Female

Figure 20. Types of Products Bought by Gender

60.0%

50.0%

40.0% High School 30.0% Bachelors' Degree 20.0% Master's Degree

10.0%

0.0% Never Rarely Sometimes Often Very Often

Figure 21. Educational Attainment and Frequency of Online Shopping

5.4. Hofstede’s Cultural Dimension in the Online Buying Behaviour

Individualism/Collectivism. According to Jeyashoke, Vongterapak and Long (2014), individualism/collectivism cultural dimension affects consumer purchasing behaviour in such a way that it creates variation in crafting marketing strategies to accurately target the buyers with varied cultural context. Thus, focusing on Czech Republic, Slovakia and Philippines, statistics showed that Czechs (58) and Slovaks (52) scored more than 50 in individualism dimension, relatively higher than Filipinos (32) (The Hofstede Centre, 2016). Scores of more than 50 in this dimension implies that the country seem to exhibit an individualist culture while scores below 50 exhibit a collectivist culture. In the context shopping in general, a key attribute for individualistic consumers is that they are more into shopping alone rather in groups and do not rely on the opinion of friends, family and interpersonal communication in making a purchase decision (Shannon & Mandhachitara 2005 as cited by Jeyashoke, Vongterapak and Long, 2014). Looking at the result of the study, 87.2% or 416 respondents

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regardless of nationality agreed preference to unaccompanied shopping (Figure 22). However, looking at the intensity of their agreement (see Appendix B8), it shows that Czechs and Slovaks were displaying high preference to shop alone implying the dominance of individualism in their cultural context (50.2% and 48.7%, respectively). Despite these, many Filipino respondents still prefer unaccompanied shopping (59.4% or 63 in count), though, less intense as compared to Czechs and Slovaks which can be inferred as a slight indication of collectivistic culture. The differences in the intensity of agreement of respondents from different nationalities are proven to be significant (H = 29.611, p=0.000). This result implies that Czechs and Slovaks distinctly display their individualistic culture through their strong preference in unaccompanied online shopping and also the less reliance towards external reasons such as interpersonal communication and opinion of friends/relatives. Meanwhile, collectivistic culture suggesting high dependency towards external reasons such as interpersonal communication and opinions of peer groups or company on consumer purchases was true for Filipinos (Figure 23) (see Appendix B9). Among the nationalities, Filipinos express higher dependency on external influences in making a purchase decision (H = 51.849, p=0.000). This result provided much further evidence on how their collectivistic culture plays a role in making a purchase online. Therefore, H3 stating “As compared to Czech students, university students in the Philippines exhibiting collectivist culture are heavily influenced by any associated groups (e.g. family) in making online purchase decision” is proven true given the results mentioned above.

70.0% 60.0% 50.0% 40.0% Filipino 30.0% 20.0% Czech 10.0% Slovak .0% Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 22. Likelihood of Shopping Alone in the Online Purchase Behaviour

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50.0% 40.0% 30.0% Filipino 20.0% 10.0% Czech 0.0% Slovak Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 23. Reliance to External Reasons in Making Online Purchase

Uncertainty Avoidance (UAI). This cultural dimension implies peoples concern towards risk and security. Czech Republic and Slovakia scored more than 50 on this Hofstede’s cultural dimension (with 74 and 51 points respectively), higher compared to Philippines (44 points). Wursten & Fadrhonc (2012), as cited by Jeyashoke, Vongterapak and Long (2014) reported that scoring high in this dimension emphasizes security resulting to strong avoidance of failure. Strong attention to brand name serves as means of assuring consumers the reliability or quality of products. Products with reputable brand names reduce the consumers’ perceived risk of having undesirable and negative experience during or after purchase. As shown in Figure 24, high uncertainty avoidance nationalities such as Czechs show their agreement that they paid attention to brand name in online shopping (37.2% = 109 in count and 41.0% = 32 in count, respectively). However, a larger percentage was not mindful about brand names in purchasing products online as compared to Filipinos who have lower UAI (see Appendix B10). This difference is proven statistically significant: H = 28.411, p=0.000. In addition, Gong (2009) indicated that people with strong UAI have fewer acceptances towards new products and innovation. However, a contradiction is happening to what is done by respondents in the online shopping environment. Czechs and Slovaks with high UAI scores are supposed to exhibit strong avoidance to new products and innovation, however, showed relatively higher disagreement on the statement (35.2% and 32.1%, respectively) (Figure 24). Filipinos, on the other hand, with lower UAI express lower disagreement (16%), higher neutrality (45.3%) and a slightly higher agreement (28.3%) to the statement (See Appendix B11). The difference is still significant: H = 27.436, p=0.000). These results infer that UAI scores do not highly support what Czechs, Slovaks and Filipino respondents’ behaviour in their online purchases. In other words, consumers with high UAI score do not necessarily mean that they paid high attention to brand names and avoid newly 61

introduced products/innovations, or vice versa. Furthermore, these results disprove H4 indicating the high risk perception of Czechs in online shopping and their strong emphasis of reducing these risk (e.g. product brands/avoidance to new products and innovations). Recalling back the preceding result, most Czechs perceived online shopping as safe, implying less perceived risk. Czechs scoring high in UAI are supposed to express strong emphasis on risk and take initiatives of reducing online shopping risks. However, data showed that they are taking risk in making purchases online as indicated by the considerable percentage of Czechs respondents expressing less mindfulness towards reputable product brands. At the same time, it is also not true that most Czechs highly avoid newly introduced products and innovations.

60.0% 50.0% 40.0% 30.0% Filipino 20.0% Czech 10.0% Slovak .0% Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 24. Attention to Brand Name in Making Online Purchase

50.0% 40.0% 30.0% Filipino 20.0% Czech 10.0% Slovak 0.0% Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 25. Avoidance to Newly Introduced Products in Making an Online Purchase

Power Distance. Wursten & Fadrhonc (2012) as cited Jeyashoke, Vongterapak and Long (2014) indicated that high power distance cultures largely consider the opinions of more 62

powerful people in making purchasing decisions. Additionally, subordinates or less powerful people desire to buy products that embody their own status or the taste of referent groups so as to maintain social status (Jeyashoke, Vongterapak and Long, 2014). Based on The Hofstede Centre (2016) data, Czech Republics (94), Slovakia (100) and Philippines (57) scored more than 50 points in the power distance cultural dimension signifying a strong display of respect towards superiors and seniors. Respondents from the three nationalities reveal the same views with regards to the kind of products/services they bought online. As shown in Figure 26, respondents showed conformity of perception in terms of buying products that represent their own status or alike to the taste of referent groups (H = 0.592, p = 0.744>0.05) (See Appendix B12). Since majority of the respondents are young people, they look up to their superiors and paid high respect. They knew and accepted that they have a specific spot in the society. However, pertaining to the importance of ideas, opinions and experiences or suggestions of superior people in making purchase decision, high PD nationalities such as the Czechs and Slovaks indicated less importance to it (Figure 27). In fact, 14.6% and 12.2% of Czech and Slovaks respondents, respectively, express that it is not at all important for them in making a purchase decision (see Appendix B13). Filipinos having the least PD score, stress high importance (21.9%) to what the superiors impart or suggested. This difference is proven significant: H = 27.218, p=0.000. This result rejects H5 specifying the heavy influence of superiors’ opinions and ideas towards Czechs online purchase decision. The respondents’ perceived effect of superiors’ ideas or opinions on their purchasing decisions is proven more significant for Filipinos rather than Czechs and Slovaks.

Masculinity. Intuitiveness and subjectivity of people is a key feature of masculinity cultural dimension that affects consumer behaviour. Less masculine cultures, possessing low score on this dimension, are thought to be more subjective and intuitive in making a purchase. However, the result of the survey did not support H6 which proposes differences in the perception of Filipinos, Czechs and Slovaks towards the importance personal subjectivity and intuitiveness. Slovakia (100), Czech Republic (57) and Philippines (64), having scored more than 50 points on this dimension, are supposed to exhibit high masculine cultures. Yet, most of them still perceived that they are subjective and intuitive in making an online purchase. Furthermore, high masculine cultures greatly value product quality and efficiency (The Hofstede Centre, 2015). Result suggests that the three nationalities posed agreement that they value product quality and efficiency of online shopping, however, Czechs (16%) and Slovaks

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(16.7%) agree in a lesser extent as compared to Filipinos (42.5%) (Figure 28) (see Appendix 14). This difference was significant as indicated the following values: H = 29.982, p=0.000. This means that despite the high masculine cultures exhibited by the three nationalities, the attribute of masculine culture (i.e. perception to product quality and efficiency) is more pronounced among Filipinos than Czechs and Slovaks.

60.0% 50.0% 40.0% 30.0% Filipino 20.0% Czech 10.0% Slovak .0% Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 26. Preference to Purchase Products Representing Own Status or Referent Group

50.0% 40.0%

30.0% Filipino 20.0% Czech 10.0% Slovak 0.0% Not at all (1) 2 3 4 5 (Very Much)

Figure 27. Importance of Superiors' Ideas and Opinions in Making Purchase Decisions

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70.0% 60.0% 50.0% 40.0% Filipino 30.0% 20.0% Czech 10.0% Slovak .0% Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 28. Importance of Product Quality and Efficiency in Online Shopping

Long Term Orientation (LT). The personal time frame also poses significant effect in making a final purchase decision. Looking at the Hofstede’s cultural dimension score on the three centred countries for this study, data show that Slovakia (77) and Czech Republic (70) scored high on LT dimension. Meanwhile, Filipinos scored only 27 points. These numbers imply that countries with high LT cultures look at their purchase as long term decision, while low LT cultures look purchases as immediate needs. Substantiating this claim, Czechs and Slovaks are less likely to purchase based on immediate needs as compared to Filipinos (Figure 29). As indicated in the data, Czechs and Slovaks express higher disagreement (30% and 28.2%, respectively) on purchasing based on immediate needs as compared to Filipinos (10.4%). Likewise, in terms of their agreement, more Filipinos (48.1%) agreed that they purchase online based on immediate needs (see Appendix B15) (H = 29.572, p=0.000). These values signify that long term orientation scores of involved nationalities conform or pose an impact to their current purchase behaviour. This result support H7 that Czech and Slovaks look at their purchase as a long term decision in a larger extent compared to Filipinos. Moreover, as revealed by Bakshi (2012), women are long term oriented than men, which means that women tend to look at their purchases as long term decision while men took it as immediate needs. After examining the data, results revealed that for Filipinos, higher percentage of male respondents have agreed that they are purchasing based on immediate needs as compared to the female respondents (H=5.507, p=0.019) (Figure 30). This result conforms to what was found by Bakshi (2012). Meanwhile, for Czechs and Slovaks, the difference is not clearly seen (H=0.196, 0.196>0.05 and H = 0.311, p=0.577>0.05, respectively) (See Appendix B16).

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60.0% 50.0% 40.0% 30.0% Filipino 20.0% Czech 10.0% Slovak 0.0% Strongly Disagree Neither Agree Strongly Disagree Agree nor agree Disagree

Figure 29. Purchase based on Immediate Needs

70.0%

60.0% Strongly agree 50.0% Agree 40.0%

30.0% Neither Agree nor Disagree 20.0% Disagree 10.0% Strongly Disagree 0.0% Male Female Male Female Male Female Filipino Czech Slovak

Figure 30. Purchase based on immediate needs based on nationality and gender

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Part VI

CONCLUSIONS AND MANAGERIAL IMPLICATIONS

6.1. Conclusions

This study focused on examining the online buying behavior between university students in Czech Republic, Slovakia and the Philippines. Specifically, it was intended to 1) provide an overview of their basic characteristics and magnitude of students online shopping adoption; 2) identify the major drivers and barriers affecting their online shopping adoption and dis-adoption; and 3) explain the impacts of national culture in relation to their online buying behavior. Hypotheses were established to meet the above objectives. These were validated based on the data gathered and findings obtained from data analysis. Results revealed that Czechs and Slovaks use internet shopping more intensively, and they absolutely have longer experience in online shopping than Filipinos. Slovaks and Czechs spent more than 20 hours and 1-15 hours per week, respectively. As Filipinos surf the web less intensively, internet penetration rate in the Philippines is also twice lower than the Czech Republic and Slovakia. Only 44.5% of the Filipinos accessed the internet, while 88.4% of Czech and 82.5% of Slovak population (Internet Live Stats, 2016). This means that more Filipinos are not involved in the internet environment thus in online shopping. The online shopping and IT infrastructure in the Philippines is still far behind United States or in European countries like United Kingdom, France, Germany including Czech Republic and Slovakia (see Part II: 1.1.). Internet speeds are still very slow hurting e- commerce businesses (Lardizabal & Bonalos, 2015). Moreover, internet users were reluctant to shop online due to the following factors: 1) reliability of seller, 2) quality of the products offered online, 3) absence of credit/debit card, 4) insufficient/limited knowledge and 5) shipping problems. These led to a conclusion that Filipinos are less active in online shopping than the other nationalities which proved hypothesis H1 to be true. Among the factors influencing online shopping adoption, secured payment as a feature of building security and trust is greatly perceived by respondents to highly influence their online shopping engagement. This factor is considered both as a driver and also a barrier in shopping online. It becomes a driver when consumer’s fear of losing money and identity theft is greatly reduced. Meanwhile, it becomes a barrier when e-retailers or online shopping sites create undesirable experiences to customers which consequently hinder them to repurchase. This result verifies the validity of H2. The result conforms to the findings of Chen et al., 67

(2010) that consumers often valued security most in purchasing goods and services online. Nevertheless, safety and security perception of different nationalities propose varying results. Czechs agree that online shopping is safe while Slovaks were neutral. Filipinos, however, had a stronger disagreement on the safety of online shopping. This result confers ideas in online shopping platforms existing in the respective nations including the online shopping experiences of consumers. In Czech Republic, it is inferred that e-retailers or online shops have been providing positive shopping experiences by offering reliable and quality products and services. E-retailers and involved parties (e.g. banks, merchants) strongly assured security of transactions to keep e-commerce level high. Slovak’s, on the other hand, showed neutrality as their experiences in online shopping may not be consistently positive. Filipinos are apprehensive of the risk of e-commerce in their country as it is still in its infancy. Online transactions still pose a great security threat for Filipinos. Dispute-resolution facility and legislative frameworks are still deficient and obscure, thus, these needs to be strengthened to reinforce online security along with increasing information sharing and bilateral assistance (Olsen, Chua, Gergele, & Bartolucci, 2015). E-retailers’ emphasis on security of online transactions and effective communication between existing and prospective online shoppers offers paramount benefit. As results revealed that there is a positive correlation between the frequency of online shopping and the respondents’ perception towards the safety of online shopping, this implies that the higher the perception of safety, the more frequent the consumer use the internet for shopping. Hofstede’s cultural dimension explained the aspects of culture influencing online buying behavior. The cultural comparison dealt on individualism, power distance, masculinity, long-term orientation and uncertainty avoidance among Czechs, Slovaks and Filipinos. Czechs, Slovaks and Filipinos express preference to shop online alone rather than in groups. However, the intensity of preference differs from one nationality to another. Individualist culture among Czechs and Slovaks displayed supremacy in the online shopping behavior, by means of the strong preference of unaccompanied shopping. Also, influencing power of interpersonal communication and opinion of friends/relatives is less effective for Czechs and Slovaks in making an online purchase. Meanwhile, the less intense preference of Filipinos towards unaccompanied shopping and the profound effects of external reasons on their online shopping behavior showed an indication of its collectivistic culture. Thus, these findings prove H3 to be true.

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Furthermore, uncertainty avoidance (UAI) affects online shopping behaviour in a way that high UAI respondents emphasize security of online transactions including the means of avoiding failure (Wursten & Fadrhonc (2012), as cited by Jeyashoke, Vongterapak, 2014). However, results deviate from the preceding statement. It was found that UAI scores do not highly support what Czechs, Slovaks and Filipino behaviour in their online purchases. Consumers with high UAI (Czechs and Slovaks) did not necessarily mean that they paid high attention to brand names and avoid newly introduced products/innovations, or vice versa. Still, a larger percentage does not mind about brand names in purchasing products online than Filipinos who have lower UAI. Czechs and Slovaks take risk in making purchases online and they also preferred newly introduced/innovated products. In this technology-driven generation, where people heavily rely on technologies, new products and innovations enhancing the effectivity and efficiency of carrying out their activities is their prime consideration in the market. Consumers mostly bought electronic products online; seeking better or upgraded products is the trend, thus, rejecting the notion that having scored high in uncertainty avoidance index heavily avoids buying newly introduced products and innovations. Apple or Samsung of the mobile phone industry, year after year, introduced new products and features. Likewise, new clothing trends in the clothing industry, are spurring up, and consumers are keeping up with the trend. These are not overlooked by consumers. These results lead to the rejection of H4 as Czechs perceived lower risk in online shopping and place less emphasis of reducing these risks through avoidance to new products and innovations or considering product brands. The consideration of the opinions of more influential people or superiors is one role that power distance cultural dimension is playing in making a purchase decision (Wursten & Fadrhonc (2012) as cited Jeyashoke, Vongterapak and Long (2014). High PD nationalities are strongly relying on the influencing power of superiors. Nevertheless, results revealed the contrary. The ideas, opinions and experiences or suggestions of superiors in making purchase decision are perceived to be less important in high PD nationalities like Czechs and Slovaks. Meanwhile, Filipinos with the least PD, stress high importance to what the superiors impart or suggested. Thus, this result rejects H5 specifying the heavy influence of superiors’ opinions and ideas towards online purchase decision. The results did not support H6 which proposes differences in the perception of Filipinos, Czechs and Slovaks towards the importance personal subjectivity and intuitiveness. Personal subjectivity and intuitiveness in making a purchase is found to be a feature of less

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masculine cultures (Bakshi, 2012). The three nationalities exhibited high masculine cultures (scoring more than 50 in masculinity index), but they are more subjective and more intuitive in making their purchases. They value product quality and efficiency (The Hofstede Centre, 2015). Results showed that the role of masculinity plays in making an online purchase is more pronounced among Filipinos as compared to Czechs and Slovaks. Lastly, in terms of long term orientation, results supported H7 indicating that that Czech and Slovaks look at their purchase as a long term decision in a larger extent than Filipinos. In high LT culture, consumers often look at their purchase as long term decision, while low LT cultures look purchases as an immediate need. The high long term orientation index among Czechs and Slovaks is substantiated by the results that they are less likely to purchase based on immediate needs compared to Filipinos.

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6.2. Managerial Implications of the Study

Based on the results of the study, the following managerial implications are proposed:

1. Internet shopping in the Philippines still lags behind Czech Republic and Slovakia. The reasons behind rest on the inadequate technological infrastructure and issues such as 1) unreliable sellers, 2) poor quality of the products offered online, 3) absence of credit/debit card, 4) insufficient knowledge of how online shopping works and 5) shipping problems. These give an implication to e-retailers to counteract these problems and create positive online shopping experience to a wide range of customers. This could be achieved by describing products accurately, on time delivery of the products, offer other payment options (e.g. cash on delivery) and adopt an effective dispute-resolution facility. Moreover, despite the inadequate technological infrastructure and poor internet penetration rate in the country, there is still strong possibility that this will be resolved through effective government initiatives (e.g. technology and development programs, encouraging healthy competition among internet service providers, strengthening laws governing e-retailing for consumer protection regulations and enhancing computer literacy). 2. Conveying reliability, safety and security information of the e-retailing business or web assurance are needed so as to win the trust and confidence of the customers. Web assurance services alleviate consumers trust concerns. Companies or e-retailers investing into this kind of services obtain a seal indicating the business trustworthiness. According to Kim, Steinfield and Lai (2008), these assurance seal are offered by third-party certifying bodies which include banks, accountants, consumer unions, and computer companies that provide assurance that e-retailer's behaviour will be consistent with accepted standards in online commerce. However, further research is needed to acquire information whether the said initiative provide benefits that outweighs cost. 3. Exploit the influencing power of external reasons and superiors’ ideas and opinions which supports the effectiveness of e-retailers initiative to integrate social media sites in exposing customers’ feedbacks or shopping experiences online. Nowadays, most people are using social media such as Facebook, Twitter, LinkedIn, Instagram, Google Plus and many others to connect and network to other people. Integrating this functionality to an e-retailing site that allows customers or e-retailers itself to post

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purchases, feedbacks or experiences directly to their social media accounts is one way to entice their close peers, friends or relatives to engage in online shopping. Moreover, through sharing of positive online shopping experiences to customers, word of mouth marketing can be initiated. Customers get talking about their experiences with the e- retailing business itself to their peers placed an influencing power to shop online. Nevertheless, this initiative might not be effective for Czech and Slovak consumers. As they indicated less preference to unaccompanied shopping and less dependency towards external reasons. Clear product and service information allows informative product comparison. Consumers can easily match what they are looking for and the products or services being offered online, thus, increasing the probability of a successful purchase. 4. Results revealed that a Czechs and Slovaks do not mind brand names in purchasing products online as well as in the purchase of newly introduced/innovated products. This implies that product entry and penetration barriers can be less difficult and less damaging for e-retailers. This presents an opportunity for other businesses and innovators to come in. Results also revealed that Czech and Slovak perceived security of online transactions as a huge factor to influence online shopping. Placing great attention towards security of online transactions builds online trust, confidence and satisfaction among consumers to adopt the said online shop. 5. Masculine culture profoundly expressed by Filipinos in the online shopping environment placed a strong value towards product quality and efficiency of purchase which necessitates online businesses to offer quality products and services distinct from traditional stores. The online shopping benefits such as the delivery of damage- free products, on time delivery, security assurance of transactions, cost saving and the overall convenience provided hastens adoption of online shopping among Filipino consumers. 6. Czechs and Slovaks exhibited high long term orientation cultures look at their purchases as long term decision. Information is necessary to arrive at a final purchase decision. This implies that Czech and Slovak consumers carefully choose products to buy necessitating detailed information about the product and undergoing comprehensive product comparison. Inadequate product information may hinder the consumer choice in coming up with a decision to purchase. Thus, e-retailers are required to provide product variety and enough product information. When a

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consumer decides to buy a laptop, for instance, the e-retailer may provide wide variety of laptops and each with information about price, product specifications, warranty offerings, etc. Moreover, functionality can be integrated in the online shopping site for consumers to easily compare alternative products side by side and to facilitate the decision process.

6.3. Limitations and Recommendations for Future Study

This study has the following limitations:

 The ability to generalize results is restrained. Respondents do not entirely represent the population of interest. They only came from a single university (e.g. Masaryk University in Czech Republic and Visayas State University in the Philippines). Further study is recommended to take respondents from different universities in each country and take comparable or the same number of respondents. It is also recommended to include respondents other than university students.  This study only focused online shopping behavior in Czech Republic, Slovakia and Philippines. It is recommended that other developed and developing countries be included for future research.  The factors affecting consumers’ online shopping adoption and behaviour considered in this study do not include technological advancement, policies, technology literacy and others. Thus, suggested to include these in further research.  The study only used Hofstede’s cultural dimensions as a framework to explain how national culture affects online shopping behaviour. The descriptions how each dimension plays in online shopping environment were largely based on the literature found by the researcher. These are used to describe and measure the extent nationalities played in this role. Subsequently, results were used to make inferences as to how the chosen nationalities behaved in the online shopping environment. However, only few descriptions in the operationalization of each dimension were found. Thus, it is recommended that another study be conducted to gather features or attributes that the cultural dimensions play in the context of online shopping.  The managerial implications or recommendations above (e.g. web assurance service, social media advertisement, and addition of web site functionality) will provide basic 73

insights on how e-marketers should adapt the ever changing behaviour of consumers to maximize profitability and sustain competitive advantage. Its fulfilment is dependent upon the magnitude of benefits that e-retailers will acquire and cost it will incur. Thus, it is advised that e-retailers perform cost-benefit analysis and evaluate whether the given recommendation is appropriate or not to the business. The inclusion of such developments and initiatives entails costs, thus, might be harder to implement for start-up and small scale e-retailing businesses.

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APPENDICES

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Appendix A 1. Survey Questionnaire

Source: Jha, 2014

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Source: Jha, 2014

Source: Jha, 2014

Source: Yoldas, 2011

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Source: Kim, 2004

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Source: Jeyashoke, Vongterapak, & Long (2014)

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Appendix B. Statistical Analysis Results

Nationality * How long have you been using the Internet? Crosstabulation How long have you been using the Internet? More than 5 Less than 1 year 1 - 3 years 3 -5 years years Total Nationality Filipino % within Nationality 2.8% 6.6% 6.6% 84.0% 100.0% Adjusted Residual 3.3 5.0 4.0 -7.2 Czech % within Nationality 0.0% 0.0% 0.3% 99.7% 100.0%

Adjusted Residual -2.2 -3.4 -3.1 5.1 Slovak % within Nationality 0.0% 0.0% 1.3% 98.7% 100.0% Adjusted Residual -.8 -1.2 -.4 1.3 Total % within Nationality 0.6% 1.5% 1.9% 96.0% 100.0% Appendix B 1. Cross-tabulation result - Nationality and Length of Internet Use

Nationality * Time (per week) spent in surfing the Web Crosstabulation Time (per week) spent in surfing the Web More than 20 0 - 5 hours 6 - 10 hours 11 - 15 hours 16 - 20 hours hours Total

Nationality Filipino % within Nationality 36.8% 21.7% 8.5% 7.5% 25.5% 100.0% Adjusted Residual 7.6 1.7 -2.1 -2.4 -3.4 Czech % within Nationality 7.8% 15.0% 18.8% 17.4% 41.0% 100.0% Adjusted Residual -4.9 -1.0 3.0 2.0 .6 Slovak % within Nationality 6.4% 14.1% 9.0% 15.4% 55.1% 100.0% Adjusted Residual -2.1 -.6 -1.6 .1 3.0 Total % within Nationality 14.0% 16.4% 14.9% 14.9% 39.8% 100.0% Appendix B 2. Cross-tabulation result - Nationality and Time spent surfing the web

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Nationality * How often do you use Internet for Shopping? Crosstabulation How often do you use Internet for Shopping? Never Rarely Sometimes Often Very Often Total Nationality Filipino % within Nationality 17.0% 27.4% 38.7% 14.2% 2.8% 100.0% Adjusted Residual 8.1 1.3 -1.3 -2.6 -1.3 Czech % within Nationality 0.0% 22.2% 45.7% 25.9% 6.1% 100.0% Adjusted Residual -5.5 -.4 .8 1.5 .8 Slovak % within Nationality 0.0% 19.2% 46.2% 28.2% 6.4% 100.0% Adjusted Residual -1.9 -.8 .4 1.0 .4 Total % within Nationality 3.8% 22.9% 44.2% 23.7% 5.5% 100.0% Appendix B 3. Cross-tabulation result - Nationality and Often Use Internet for Shopping

Nationality * Online shopping site designs are attractive and stimulating Crosstabulation Online shopping site designs are attractive and stimulating Strongly Neither Agree Disagree Disagree nor Disagree Agree Strongly Agree Total Nationality Filipino Count 3 3 17 57 26 106 % within Nationality 2.8% 2.8% 16.0% 53.8% 24.5% 100.0% Adjusted Residual 3.3 -2.3 -4.8 2.5 4.4 Czech Count 0 29 126 114 24 293

% within Nationality 0.0% 9.9% 43.0% 38.9% 8.2% 100.0% Adjusted Residual -2.2 1.7 4.1 -2.4 -3.3 Slovak Count 0 7 28 35 8 78 % within Nationality 0.0% 9.0% 35.9% 44.9% 10.3% 100.0% Adjusted Residual -.8 .3 .0 .3 -.6 Total Count 3 39 171 206 58 477 % within Nationality 0.6% 8.2% 35.8% 43.2% 12.2% 100.0% Appendix B 4. Cross-tabulation result - nationality and web site attractiveness

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Nationality * Experienced online shopping scams and fraudulent activities? Crosstabulation

Experienced online shopping scams and fraudulent activities? Yes No Total Nationality Filipino Count 15 91 106 % within Nationality 14.2% 85.8% 100.0% Adjusted Residual -2.5 2.5 Czech Count 74 219 293 % within Nationality 25.3% 74.7% 100.0% Adjusted Residual 1.3 -1.3

Slovak Count 22 56 78 % within Nationality 28.2% 71.8% 100.0% Adjusted Residual 1.1 -1.1 Total Count 111 366 477 % within Nationality 23.3% 76.7% 100.0% Appendix B 5. Cross-tabulation result - Nationality and Shopping Scams

Nationality * Products in online shopping sites are accurately described Crosstabulation Products in online shopping sites are accurately described Strongly Neither Agree Disagree Disagree nor Disagree Agree Strongly Agree Total Nationality Filipino Count 5 23 39 28 11 106 % within Nationality 4.7% 21.7% 36.8% 26.4% 10.4% 100.0% Adjusted Residual 2.4 1.3 1.0 -3.2 .9 Czech Count 2 52 90 125 24 293 % within Nationality 0.7% 17.7% 30.7% 42.7% 8.2% 100.0% Adjusted Residual -2.4 .3 -1.3 1.7 .0 Slovak Count 2 8 28 36 4 78 % within Nationality 2.6% 10.3% 35.9% 46.2% 5.1% 100.0% Adjusted Residual .5 -1.8 .6 1.3 -1.1 Total Count 9 83 157 189 39 477 % within Nationality 1.9% 17.4% 32.9% 39.6% 8.2% 100.0% Appendix B 6. Cross-tabulation result - nationality and product description

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Nationality * It is easy to compare many products in online shops Crosstabulation It is easy to compare many products in online shops Strongly Neither Agree Disagree Disagree nor Disagree Agree Strongly Agree Total Nationality Filipino Count 2 17 25 41 21 106 % within Nationality 1.9% 16.0% 23.6% 38.7% 19.8% 100.0% Adjusted Residual 1.0 4.4 4.9 -.6 -4.9 Czech Count 2 11 17 123 140 293 % within Nationality 0.7% 3.8% 5.8% 42.0% 47.8% 100.0%

Adjusted Residual -1.0 -3.3 -4.4 .4 4.2 Slovak Count 1 4 9 33 31 78 % within Nationality 1.3% 5.1% 11.5% 42.3% 39.7% 100.0% Adjusted Residual .2 -.6 .3 .2 -.1 Total Count 5 32 51 197 192 477

% within Nationality 1.0% 6.7% 10.7% 41.3% 40.3% 100.0% Appendix B 7. Cross-tabulation result - nationality and product comparison

Nationality * I am more likely to shop alone or in a small group Crosstabulation I am more likely to shop alone or in a small group

Neither Agree Strongly Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 21 63 19 2 1 106 % within Nationality 19.8% 59.4% 17.9% 1.9% 0.9% 100.0% Adjusted Residual -5.5 3.6 3.4 -.6 .5 Czech Count 147 114 21 9 2 293 % within Nationality 50.2% 38.9% 7.2% 3.1% 0.7% 100.0% Adjusted Residual 3.9 -2.8 -2.1 .6 .2 Slovak Count 38 33 5 2 0 78 % within Nationality 48.7% 42.3% 6.4% 2.6% 0.0% 100.0%

Adjusted Residual 1.1 -.3 -1.0 -.1 -.8 Total Count 206 210 45 13 3 477 % within Nationality 43.2% 44.0% 9.4% 2.7% 0.6% 100.0% Appendix B 8. Cross-tabulation result - nationality and shopping alone

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Nationality * In my purchase decision, I rely more on external reasons such as interpersonal communication, friends or family's opinion, and their feelings and trust in the company Crosstabulation In my purchase decision, I rely more on external reasons such as interpersonal communication, friends or family's opinion, and their feelings and trust in the company Neither Strongly Agree nor Strongly agree Agree Disagree Disagree Disagree Total Nationalit Filipino Count 22 50 21 11 2 106 y % within 20.8% 47.2% 19.8% 10.4% 1.9% 100.0% Nationality Adjusted Residual 5.5 4.4 -3.3 -3.9 -1.3 Czech Count 14 73 109 85 12 293 % within 4.8% 24.9% 37.2% 29.0% 4.1% 100.0% Nationality Adjusted Residual -3.2 -3.0 2.4 2.7 -.1 Slovak Count 2 20 28 22 6 78 % within 2.6% 25.6% 35.9% 28.2% 7.7% 100.0% Nationality Adjusted Residual -1.9 -.9 .6 .8 1.7 Total Count 38 143 158 118 20 477

% within 8.0% 30.0% 33.1% 24.7% 4.2% 100.0% Nationality Appendix B 9. Cross-tabulation result - nationality and reliance to external reasons

I pay more attention to brand name to avoid risks in shopping online Strongly Neither Agree Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 23 53 23 6 1 106 % within Nationality 21.7% 50.0% 21.7% 5.7% 0.9% 100.0% Adjusted Residual 3.7 2.2 -1.6 -3.7 -1.2

Czech Count 27 109 84 63 10 293 % within Nationality 9.2% 37.2% 28.7% 21.5% 3.4% 100.0% Adjusted Residual -2.0 -1.9 .6 2.8 1.6 Slovak Count 5 32 25 15 1 78 % within Nationality 6.4% 41.0% 32.1% 19.2% 1.3% 100.0%

Adjusted Residual -1.5 .1 .9 .4 -.8 Total Count 55 194 132 84 12 477 % within Nationality 11.5% 40.7% 27.7% 17.6% 2.5% 100.0% Appendix B 10. Cross-tabulation result - nationality and attention to brand name 93

Nationality * I avoid buying newly introduced products, services, and technologies Crosstabulation I avoid buying newly introduced products, services, and technologies Strongly Neither Agree Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 11 30 48 17 0 106 % within Nationality 10.4% 28.3% 45.3% 16.0% 0.0% 100.0% Adjusted Residual 1.8 2.4 2.3 -3.6 -3.2 Czech Count 16 55 94 103 25 293 % within Nationality 5.5% 18.8% 32.1% 35.2% 8.5% 100.0% Adjusted Residual -1.2 -.9 -2.2 2.8 1.5

Slovak Count 4 11 29 25 9 78 % within Nationality 5.1% 14.1% 37.2% 32.1% 11.5% 100.0% Adjusted Residual -.5 -1.5 .3 .3 1.7 Total Count 31 96 171 145 34 477

% within Nationality 6.5% 20.1% 35.8% 30.4% 7.1% 100.0% Appendix B 11. Cross-tabulation result - nationality and avoidance to newly introduced products and innovation

I prefer purchasing products or services that represent my own status, and are similar to the taste of my referent group Strongly Neither Agree Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 18 56 25 6 1 106 % within 17.0% 52.8% 23.6% 5.7% 0.9% 100.0% Nationality Adjusted Residual .2 .6 -.3 -.7 -.5 Czech Count 48 144 73 22 6 293 % within 16.4% 49.1% 24.9% 7.5% 2.0% 100.0% Nationality Adjusted Residual .0 -.6 .1 .4 1.3 Slovak Count 12 40 20 6 0 78

% within 15.4% 51.3% 25.6% 7.7% 0.0% 100.0% Nationality Adjusted Residual -.3 .2 .2 .2 -1.2 Total Count 78 240 118 34 7 477 % within 16.4% 50.3% 24.7% 7.1% 1.5% 100.0% Nationality Appendix B 12. Cross-tabulation result - nationality and products of my own status and referent groups

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Nationality: * Ideas, opinions, experiences and suggestions of people superior than me (e.g. manager, boss, professors, family) Crosstabulation Ideas, opinions, experiences and suggestions of people superior than me (e.g. manager, boss, professors, family) Not at all (1) 2 3 4 5 (Very Much) Total Nationality: Filipino % within 7.8% 7.8% 23.4% 39.1% 21.9% 100.0% Nationality: Adjusted Residual -1.3 -3.2 -1.4 3.1 3.8 Czech % within 14.6% 24.0% 32.3% 22.9% 6.3% 100.0% Nationality:

Adjusted Residual 1.2 .7 .7 -.7 -2.5 Slovak % within 12.2% 36.7% 34.7% 10.2% 6.1% 100.0% Nationality: Adjusted Residual -.1 2.6 .6 -2.5 -.9 Total % within 12.8% 22.6% 30.8% 24.3% 9.5% 100.0% Nationality: Appendix B 13. Cross-tabulation result - nationality and ideas/opinions of superior people

Nationality * I value quality of products and efficiency in online shopping Crosstabulation I value quality of products and efficiency in online shopping Neither Agree Strongly Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 45 47 13 0 1 106 % within Nationality 42.5% 44.3% 12.3% 0.0% 0.9% 100.0% Adjusted Residual 5.8 -2.1 -2.4 -2.2 .5 Czech Count 47 168 65 11 2 293 % within Nationality 16.0% 57.3% 22.2% 3.8% 0.7% 100.0% Adjusted Residual -4.0 2.1 1.1 .6 .2 Slovak Count 13 40 20 5 0 78 % within Nationality 16.7% 51.3% 25.6% 6.4% 0.0% 100.0% Adjusted Residual -1.2 -.4 1.2 1.6 -.8 Total Count 105 255 98 16 3 477 % within Nationality 22.0% 53.5% 20.5% 3.4% 0.6% 100.0% Appendix B 14. Cross-tabulation result - nationality and the value of product quality and efficiency

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Nationality * I tend to make purchases based on the immediate needs rather than long term decision Crosstabulation I tend to make purchases based on the immediate needs rather than long term decision Strongly Neither Agree Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 10 51 31 11 3 106 % within 9.4% 48.1% 29.2% 10.4% 2.8% 100.0% Nationality Adjusted Residual 1.4 4.3 .1 -4.0 -2.2 Czech Count 14 76 88 88 27 293

% within 4.8% 25.9% 30.0% 30.0% 9.2% 100.0% Nationality Adjusted Residual -1.9 -3.2 .7 3.0 1.3 Slovak Count 7 22 19 22 8 78

% within 9.0% 28.2% 24.4% 28.2% 10.3% 100.0% Nationality Adjusted Residual 1.0 -.6 -1.0 .6 .8 Total Count 31 149 138 121 38 477 % within 6.5% 31.2% 28.9% 25.4% 8.0% 100.0% Nationality Appendix B 15. Cross-tabulation result - nationality and purchases based on immediate needs

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Nationality * I tend to make purchases based on the immediate needs rather than long term decision Crosstabulation I tend to make purchases based on the immediate needs rather than long term decision Strongly Neither Agree Strongly agree Agree nor Disagree Disagree Disagree Total Nationality Filipino Count 10 51 31 11 3 106 % within 9.4% 48.1% 29.2% 10.4% 2.8% 100.0% Nationality Adjusted Residual 1.4 4.3 .1 -4.0 -2.2 Czech Count 14 76 88 88 27 293

% within 4.8% 25.9% 30.0% 30.0% 9.2% 100.0% Nationality Adjusted Residual -1.9 -3.2 .7 3.0 1.3 Slovak Count 7 22 19 22 8 78

% within 9.0% 28.2% 24.4% 28.2% 10.3% 100.0% Nationality Adjusted Residual 1.0 -.6 -1.0 .6 .8 Total Count 31 149 138 121 38 477 % within 6.5% 31.2% 28.9% 25.4% 8.0% 100.0% Nationality Appendix B 16. Cross-tabulation result - nationality and purchase based on immediate needs

How often do How long have you use you been Internet for using the Shopping? Internet? Spearman's rho How often do you use Correlation Coefficient 1.000 .177** Internet for Shopping? Sig. (2-tailed) . .000 N 477 477 How long have you been Correlation Coefficient .177** 1.000 using the Internet? Sig. (2-tailed) .000 . N 477 477 **. Correlation is significant at the 0.01 level (2-tailed). Appendix B 17. Correlation analysis result between length of time of surfing the web (in years) and the frequency of online shopping

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Online How often do shopping is you use safe (i.e. risk Internet for of theft, receipt Shopping? of products) Spearman's rho How often do you use Correlation Coefficient 1.000 .105* Internet for Shopping? Sig. (2-tailed) . .022 N 477 477 Online shopping is safe Correlation Coefficient .105* 1.000 (i.e. risk of theft, receipt of Sig. (2-tailed) .022 . products) N 477 477 *. Correlation is significant at the 0.05 level (2-tailed). Appendix B 18. Correlation analysis results between frequency of online shopping and the respondents’ perception towards safety of shopping online

Value df Asymptotic Significance (2-sided)

Pearson Chi-Square 17.168a 8 .028 Likelihood Ratio 16.886 8 .031

Linear-by-Linear Association .001 1 .971

N of Valid Cases 477

a. 3 cells (20.0%) have expected count less than 5. The minimum expected count is 1.94. Appendix B 19. Chi-square test result on the perception of internet shopping safety between nationalities

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