M. ATİLLA ÖNER A. KEMAL TUĞCU
ANTICIPATION
CONCEPTUAL, THEORETICAL AND EMPIRICAL ISSUES Yeditepe Üniversitesi Yayınevi: 37
ANTICIPATION: Conceptual, Theoretical and Empirical Issues M. Atilla Öner and A. Kemal Tuğcu
@Yeditepe Üniversitesi Yayınevi, 2019 Bu kitabın her türlü yayın hakları Fikir ve Sanat Eserleri Yasası gereğince Yeditepe Üniversitesi Yayınevi’ne aittir. Tüm hakları saklıdır. Tanıtım amaçlı kısa alıntılar dışında yayıncının izni alınmadan hiçbir şekilde kopyalanamaz, çoğaltılamaz, yayımlanamaz ve dağıtılamaz.
ISBN: 978-975-307-103-1
1. Baskı, İstanbul, 2019
Sorumlu Editör: Didem Bayındır Kapak Tasarımı: Halil Ustaoğlu Sayfa Tasarımı: Savaş Yıldırım
Yeditepe Üniversitesi Yayınevi Yeditepe Üniversitesi İnönü Mah. Kayışdağı Cad. 26 Ağustos Yerleşimi 34755 Ataşehir İstanbul 0216 578 00 00 / 3716 Yayıncı sertifika no: 41307 M. ATİLLA ÖNER A. KEMAL TUĞCU
ANTICIPATION
CONCEPTUAL, THEORETICAL AND EMPIRICAL ISSUES
CONTENTS
Introduction – Özlem Kunday...... 7 Co-Editor’s Note – A. Kemal Tuğcu...... 9 Prof. Dr. Eng. M. Atilla Öner CV...... 13
PART I 1. Anticipation and Purpose – A. Kemal Tuğcu...... 19 2. Anticipation: Meaning and Usage - Çiğdem Kaya & M. Atilla Öner...... 43 3. Uncertainty and Anticipation – M. Atilla Öner, Senem Göl Beşer & Pınar Şenoğlu...... 65 4. Psychology and Physiology of Anticipation – Sara Saban...... 97
PART II 5. Anticipation and Entrepreneurship – Özlem Kunday, Deniz P. Alkan.....111 6. Anticipation in Economics – Ayse Sevencan...... 135 7. Anticipation in Financial Markets – M. Cihan Akın...... 161 8. Anticipation in Marketing – Y. Can Erdem & Nihat Tavşan...... 169 9. Anticipation in Strategic Decision-Making – A. Gönül Demirel...... 183 10. Anticipation in Artificial Intelligence – Özlem Şenvar...... 199 11. Anticipatory in Public Management – Hande Tek Turan...... 215 12. Anticipation in Architecture Utopias – Ece Ceylan Baba...... 239 13. Anticipation in Law – Hakan Üzeltürk...... 265 14. A Scenario Approach for Better Anticipating the Oil Market Shifts - Soufiane Naime, Christophe Bisson...... 285
About the Author’s...... 301
5
INTRODUCTION
Foresight & Futures Studies include all efforts to study the future by numerous methods and techniques to explain and predict how organizations and people will behave. These efforts in the field yielded the development and use of numerous scenario planning and foresight tools for social and life sciences with specific applications in public and business management areas. Practical applications involved strategic studies covering long range planning, policy development and technology assessment in several public and industrial sectors. Yeditepe University Management Applications and Research Center (MARC) has been a significant contributor in the field since 2009 and has organized several international conferences under the leadership of Prof. Dr. M. Atilla Öner [Yeditepe International Research Conferences on Foresight (YIRCoF’09 & YIRCoF’11)]. International research efforts during the past decade have evolved to a wider field calledthe Anticipation Science that encompasses natural, formal and social systems that intentionally or unintentionally use ideas of a future to act in the present, with a broad focus on humans, institutions and human-designed systems [R. Poli, Introduction to Anticipation Studies, Springer, 2017]. With recent developments in Artificial Intelligence and advances in Brain & Mind Research, the field has become a major interdisciplinary research topic and triggered a worldwide effort to understand, mathematically formulate and simulate the decision-making process of living organisms, humans, institutions and social-cultural entities. The field is also being referred as the Science of Decision-Making. UNESCO stresses on being Future Literate in understanding the nature of the future and the role it plays in what we humans see and do. The Institution has declared that developing this capacity to imagine the future can be a powerful tool for catalyzing change today and started
7 ANTICIPATION a World-wide Project on Futures Literacy. The Institution believes that becoming more skilled at designing the systems and processes used to imagine tomorrow is an essential part of empowering humans for crafting new approaches for more inclusive and sustainable development in the World [Transforming the Future – Anticipation in the 21st Century, UNESCO Publishing, 2018]. MARC has established partnerships with the University of Trento and UNESCO via Prof. Dr. Roberto Poli - a pioneer in the Anticipation Research field - who visited Yeditepe University in 2018 for an Anticipation Workshop. A well deserved and special thanks go to our Editor, Dr. Kemal Tuğcu, who has sincerely devoted himself to the completion of this book. His positive attitude and integrity has motivated all of us during this journey. Initially, Chapters of this book were designed by Prof. Dr. M Atilla Öner and completed by his colleagues after his untimely and unexpected loss. The book is dedicated to his memory. We miss him …
Assoc. Prof. Dr. Özlem Kunday MARC Director Yeditepe University
8 EDITOR’S NOTE
Anticipation science is a developing topic of research with an interdisciplinary character requiring joint effort of practitioners and academicians from almost all natural and social scientific fields. This book contains the results of a collection of joint research work initiated by Prof. Dr. M. Atilla Öner and represents a solid attempt to define what anticipation and anticipation research mean with contributors from a variety of Departments at Yeditepe University together with two contributors from Marmara and Arel Universities. Each chapter is written by a team member and represents the acquaintance phase of their specific academic fields with anticipation science and the science of decision-making. Future effort by the team is expected to result in a marriage that will mean a fruitful interdisciplinary research environment for advancements in the field of anticipation science. Chapter 1 primarily aims to set the stage by providing basic definitions of “anticipation” and related concepts within the context of Future Studies and emphasizes its essential relationship with a “purpose”. Formal definitions ofanticipation and purpose, based on published literature are given and generic behavioral aspects for a living organism acting as a decision-maker across an anticipated event are proposed. The secondary aim of Chapter 1 is to formulate some of the foundation pillars of theoretical decision-making mechanisms to define an “Anticipatory System” which will attempt to describe the behavior of a living organism within a given environment. Examples of anticipatory systems involving the behaviors of a human against the Nature and a company within a competitive business environment are described to demonstrate the fact that “deciding on a purpose” is of primary importance in the modeling of anticipatory systems. Chapter 2 aims to clarify the meaning and usage of the term “anticipation” to pave the way for the development of a good anticipation
9 ANTICIPATION theory. The defined meanings and synonyms of anticipation in dictionaries and usage of the term in recently published papers and books are examined. Chapter 3 introduces the “uncertainty notion” as a natural inherent characteristic of the anticipation process that should be well understood. The sole purpose of the Chapter is to review uncertainty in anticipation systems for conceptual clarity. The unknown character of the futures introduces the study of uncertainty, ambiguity and ignorance as a possible research theme in design-based foresight and anticipation systems. Chapter 4 establishes the connection between anticipation/decision- making and their underlying physiological brain and psychological processes. Old psychology schools of thought such as behaviorism, psychoanalysis are reviewed and a new proactive approach of psychology is suggested based on the anticipatory capacity of the human brain. Chapter 5 establishes the relation between anticipation and “entrepreneurship” that stands as an important human trait that obviously requires a significant anticipatory behavior. The authors summarize recent research work on entrepreneurship and ultimately aim to introduce a theoretical model to simulate entrepreneurial anticipation. Chapter 6 studies the links between the “economics” field and anticipation science. It is argued that economics as a social science is by nature aimed to be an anticipatory system. The first part of the Chapter presents a survey of the economic literature in terms of the role of forward-looking assumptions. The author concentrates on the rationality argument in economic decision-making and explains the importance of economic forecasting for all economic activities. The Chapter also outlines the economic theory from an anticipation perspective and attempts to demonstrate how multidisciplinary approaches to economics through anticipation can enrich economic thinking and decision-making. Chapter 7 focuses on the anticipatory aspects of “financial markets.” Economic theory of financial markets by purpose aims to be an anticipatory system. In financial markets many transactions require participating agents to forecast the future. To maximize their utility, agents estimate a difference between the present value and the future
10 EDITOR’S NOTE value of any financial security, and then make a decision based on this estimation. Anticipatory mechanisms in financial markets can be best understood and improved upon analyzing the determinants in decision- making process of these agents. The aim of this chapter is to study the existing economic theory of financial markets and demonstrate how a multidisciplinary approach to anticipatory behavior of the market participants can enrich the present economic thinking. Chapter 8 studies the field of “marketing” and starts with a presentation of a literature review from an anticipatory perspective. Topics such as customer behaviors, purchasing decision-making and the overall process of new product launch in industrial companies are discussed and future research issues are introduced. Chapter 9 enters the “management” area and attempts to define business organizations as anticipatory systems. A basic conceptual framework is proposed to define the anticipation capacity of a business organization for making better strategic decisions. The Chapter also presents the results of a survey that aims to evaluate a group of top executives’ understanding of strategic planning and anticipation science. Chapter 10 takes on the phenomenon of the 21st Century, namely the field of “artificial intelligence” and presents a conceptual overview of anticipation in this rapidly developing area of research. The challenges of machine learning (ML) and big data analytics (BDA) are discussed and new approaches are proposed within the context of anticipatory systems. It is highlighted that the knowledge about the anticipatory aspects of behavior and learning may influence our general comprehension of machine learning and increase the capabilities and capacities to enhance performances in the robotics field. Chapter 11 represents an introduction to expore anticipatory aspects of “law and lawmaking” practice. A normative approach is taken and anticipated problems in a specific law making area namely tax laws are presented along with suggested solutions to overcome the specific problem issues. Future research in this field is expected to cover and study anticipatory behaviors of lawmakers and legal characters such as lawyers, judges, plaintiff and defendant, etc.
11 ANTICIPATION
Chapter 12 covers an interesting topic of social sciences, namely the “public administration”, and takes on to evaluate the topic from an anticipatory viewpoint. It is streesed that public administration is a social science that assesses the past to create solutions to resolve issues in the present and the future. The Chapter argues that the rapid changes in the public sector are forcing the applications of anticipatory practices and explores the role of governments to employ anticipation science in providing public services to overcome individual, social, and global challenges, focusing in particular on the most recent developments in the world. Chapter 13 looks at “architecture” and attempts to reveal the antipatory aspects of the field by studying architectural utopias. Future research in this field is expected to explore anticipation science for enhancing creativity on behalf of architectures and understanding the decision- making mechanisms of architectural customers. Chapter 14 presents a real-world application of anticipation science to the oil industry. The oil market is highly volatile and exhibits high uncertainties due mainly to climate change and the new world energy geopolitics. Thus, it is vital for oil companies to anticipate future market shifts in order to remain competitive. The research work presented in this Chapter presents a new framework for developing future scenarios of future oil markets and demonstrates the use of these scenarios to help companies and governments to better prepare for facing such a volatile and strategic market.
Dr. A. Kemal Tuğcu Co-Editor
12 PROF. DR. M. ATİLLA ÖNER
Cogitate incognitum- Think the unthinkable Prof. Dr. M. Atilla Öner (1955-2018) Education: Ph.D.in Chemical Eng. Yale University (1984) MS in Chemical Eng. Yale University (1980) BS in Chemical Eng. Boğaziçi University (1978)
Academic Experience:
Oct 2000 – today: Dept. of Business Administration, Yeditepe University. 2016 Professor of Technology and Operations Management. 2011 Associate Prof. of Production and Operations Management 2001 Assistant Professor of Production and Operations Management
Jan 1998 – Dec 2001: Adjunct Faculty Member and Associate Researcher, - Engineering and Technology Management Programme (Graduate), Boğaziçi Univ. - Dept. of Chemical Engineering, Dept of Industrial Engineering and Dept of Business Administration, Boğaziçi Univ, - Engineering Management Programme (Graduate), Marmara Univ.
September 1986 - October 1988: Consultant and part-time instructor, Dept. of Chem. Engineering, Boğaziçi Univ.; organized the Organic Surface Coating Laboratory; initiated and formulated research projects in co-operation with industrial firms; supervised graduate research; taught undergraduate (Chemical Engineering Control, Chemistry and Technology in the Organic Surface Coatings Industry) and graduate courses (Special Topics in Polymer Chemistry).
February 1985 - March 1986: Alexander von Humboldt Foundation Fellow, Institute fuer thermische Stroemungsmaschinen, Univ. of Karlsruhe F. R. Germany; designed a shock tube system and conducted experiments to study the mechanism and kinetics of soot formation in high-pressure combustors, using optical methods.
13 ANTICIPATION
May 1984 - December 1984: Post-doctoral research fellow, Dept. of Chemical Engineering, Yale University; planned and conducted experiments to study the high-temperature oxidation kinetics of boron, utilizing a low-pressure fast-flow reactor and microwave-induced plasma emission spectroscopy.
Language Skills: English, German and French.
Prof. Dr. M. Atilla Öner thought courses on Systemic Business Thinking, Technology Management, R&D Management, New Product Development, Product Management, Goal-Directed Project Management, Production and Operations Management and supervised MS/MBA and PhD theses work in the fields of “systems engineering”, “engineering and technology management” and “business and technology strategies”, “foresight studies”.
His areas of research interests included public policy and strategies, Manufacturing and technology strategies, Business Planning and Improvement, Third Sector Management Development: Journal Papers (44), Conference Papers (28), Books (8), Administrative Tasks (12), Projects (8), Citations (646), Verified reviews (186).
This “Anticipation” book project was among his several innovative research projects which united academicians from different disciplines.
“My approach to Teaching: Learner centered learning substantially alters the role of a professor. A professor is no longer a dispenser of knowledge addressed to students as passive receptors. Instead, where small teams of students explore and work together and help one another, a “professor” becomes a colleague and participating learner. Professors set direction and introduce opportunities. Professors act as guides and resource persons, not as authoritarian figures dictating each step of the educational process. The relationship is more like being a thesis advisor than a lecturer.
14 PROF. DR. M. ATİLLA ÖNER
By making presentations themselves, by listening to presentations made by their class-mates, by discussing the course materials in class, and by working on a group project which combines all course material, the students get the benefits of the holistic approach in my classes...”
Prof. Dr. M. Atilla Öner Source: http://www.maoner.com
15
PART I
1 ANTICIPATION AND PURPOSE
A. Kemal Tuğcu
Introduction The primary aim of this Chapter is to defineAnticipation within the context of Futures Studies and emphasize its essential relationship with a Purpose. Formal definitions of Anticipation and Purpose, based on published literature will be given and preliminary models of generic exploratory and normative behavioral aspects for a living organism acting as a decision-maker across an anticipated event will be proposed. The second aim of the Chapter is to propose some theoretical decision- making mechanisms for formulating an Anticipatory System which will attempt to describe the conscious behavior of a living organism within a given environment. The behavior of a living organism encompasses a brain and mind functions which cannot be modeled by conventional (lineer, nonlineer, recursive, etc.) algorithms. Leaving aside the philosophical question whether these systems could be modeled (Keat & Urry 1975), such systems may violate the Principle of Causality and the current modeling effort may be seen as an attempt to explain the non- causal World. For the anticipation process defined in this study, however, it is important to realize that the driving force is not the future but the idea of the future as concieved by an organism, which is the approach that appropriately handles the question of causality. Examples of anticipatory systems involving the exploratory and normative behaviors of a human against the Nature and a company within a competitive business environment will be analyzed to demonstrate the fact that “deciding on a purpose” is the essence of anticipatory behavior and of primary importance in the modeling of anticipatory systems.
19 ANTICIPATION
Anticipation Anticipation is a mental phenomenon and a feature of living organisms. Only a living organism can forecast a future event, evaluate outcomes, make plans and actually take action to change the present; and hence, the future. Consider a real life event. You are sunbathing beside a swimming pool and see a 4-5 year old child riding his 3-wheeler on the rim of the pool. You somehow feel anxious and think that he may fall into the pool. You look around and observe that his parents are involved in a conversation with friends. You stand up and start to wander near the child. Suddenly the boy momentarily loses control of the bike and you see that the front wheel is heading toward the water. You jump and hold the steering wheel and slightly steer the bike away from the pool. You have anticipated an unfortunate future event, modified the present and hence, changed the future ! This example may be used to set our terms with the Principle of Causality. Causality is violated if a future event influences the present. In anticipation, it is important to realize that the driving force is not the future but the idea of the future as concieved by an organism. This fact is stated by Elkus (1919) as :
“The future as future can not conceivably affect a present, but the future as a present future or idea is a conception which we may entertain.”
A detailed and recent description of Anticipation within the context of Futures Studies has been made by R. Poli (2017) where a concise definition is given as :
“Anticipation occurs when the future is used in action.”
Poli describes the three levels of Futures Studies as : I. Forecasting II. Foresight III. Anticipation
20 ANTICIPATION AND PURPOSE
Forecasting is where a future event is described but no attempt is made by the observer (organism) to a) modify itself and/or its environment or b) change the event’s unfolding future. Foresight is where the mindset of an organism is employed as a decision-maker to explore possible alternative futures or define normative scenarios which may be pursued to be realized. Again, as in forecasting, there is no attempt on behalf of the decision-maker to modify the present or to change the future. Anticipation is where the organism acts as a decision-maker; uses outputs from both Forecasting and Foresight and aims at implementing them into decisions and purposeful actions to formally modify itself, its environment or to change the event’s foreseen future. Given the above definition ofAnticipation which will result in an action with a purpose, it is apparent that a criterion is needed for the decision-maker organism to base its decisions and perform a selection among a set of possible scenarios and corresponding actions. This need can only be satisfied if the organism adopts a suitablePurpose for the future. In the absence of such a temporary or permanent Purpose, the organism cannot function as a decision-maker.
Purpose There is a vast collection of literature published in the 1900’s in Philosophy and Psychology fields on the issue of Purpose. Avoiding papers with theological concerns, one can find many useful treatments, for e.g. (Warren, 1916). Another paper published in 1930 by Y. H. Krikorian provides us with general definitions of Purpose that suit best for our present study :
“The Purpose of an act or object” is defined by Krikorian (1930) as “the expected result of that class of act or object”. “Purposive Actions are set in a certain direction and they persist until they attain the result or are defeated.” “In Purposive Acticity, there are fundamentally two levels of action ;
21 ANTICIPATION
the Expected Result which is the end of the action and the Subordinate Acts which are the means for the attainment of the end.”
Every living organism has “the preservation of life” as its ultimate or highest level purpose. This is true whether the organism represents a living creature or a social group. The “immediate” purpose of the organism, however, varies according to the circumstances which are encountered during its lifetime. The term “immediate” may indicate a very short or a long temporal window depending on the situation. The organism, in order to achieve its ultimate purpose in life, must continuously and simultaneously decide on several immediate purposes and act upon them. From this point on in this Chapter, when we mention a purpose, we do mean these “immediate purposes” rather than the “ultimate purpose”.
Properties of Anticipation and Anticipation Models For the first property of Anticipation, we may consider the two cases where the Observer / Perceptor (System) or the decision-maker is aware or unaware that a future event is foreseen and consequently an action is being taken.
“The simplest distinction for Anticipation in Future Studies is between Explicit and Implicit Anticipations. Explicit Anticipations are those of which the system is aware of them. Implicit Anticipations, by contrast, work below the threshold of awareness” (Poli, 2017).
Next, the foreseen event can be evaluated as positive (desired) or negative (undesired). This distinction is described by R. Poli for explicit anticipation in an evolutionary context :
“If the system evaluates its own evolution as positive (according to its own criteria), it will maintain its own behavioral patterns; conversly, if the system evaluates its own evolution as negative, it may seek to change its behavioral patterns in order to prevent the occurrance of the anticipated negative result” (Poli, 2017).
22 ANTICIPATION AND PURPOSE
In our treatment, we may modify the first part of this statement and state if the system evaluates a future event as positive, it will not only maintain its own behavioral patterns but may also try to make arrangements for further magnifying the foreseen gains. An Anticipation Model or a System attempts to simulate the behavior of a living organism and contains a predictive model of the organism itself and its environment together with a model for modifications and/ or actions to be performed by the organism. Rosen (2012) gives a precise definition :
“An Anticipatory System is a system containing a predictive model of itself and/or its environment, which allows the system to change state at an instant in accord with the system’s predictions pertaining to a later instant.”
Poli (2017) classifies the Anticipatory Models also asExternal or Internal, according to the construction domain of the future. If the behavioral modification is done in accord with an objective future related to the Environment, the model is called an External Model. If the actions are taken on the basis of subjectively constructed psychological expectations, the model is called an Internal Model. Anticipatory Models attempt to simulate the decision making processes of a living organism and therefore involves the brain and mind functions. Louie (2010) describes the field as the“ technology of decision-making”. R. Poli introduces two mainstream competing positions in modeling the decision making phenomena, namely the “presentational” and the “representational” approaches (Poli, 2017). The “representational” modeling approach describes the decision making processes by focusing mainly on the brain functions. The “presentative” modeling approach, however, separates the brain and the mind (mental) processes and principally treat them as two separate layers (Poli, 2001). R. Poli further classifies all contemporary (lineer, non-lineer, recursive, etc) modeling approaches as “predicative” and introduces the major and revolutionary property of models attempting to simulate the behaviors
23 ANTICIPATION of living organisms (that seem to violate the principle of causality) as “impredicative” (Poli, 2017) where the primary source of impredicativity is explained as “self-reference” (Bartlett, 1987).
Anticipation and Purpose (Exploratory and Normative Cases) From the above definitions of Anticipation and Purpose together with the listed properties of Anticipation and Anticipation Models, we can immediately identify two distinct cases where a) an anticipation is made with a forward attitude from the present to the future and a purpose is selected accordingly, and b) a purpose is determined and an anticipation is made accordingly by working backward in time toward determining its necessary conditions. These two cases actually represent R. Poli’s (2017) definition ofExploratory and Normative Scenarios, respectively. For convenience, we will denote these two decision making / action taking cases Purpose for Anticipation [PforA] and Anticipation for Purpose [AforP], respectively. Note also that [PforA] may entail both positive [Pfor+A] or negative [Pfor-A] anticipations whereas [AforP] may logically entail only positive. Additionally, as R. Poli describes in (Poli, 2017),
in [PforA] one decides on an Action in [AforP] one decides on a Process
Purpose for Anticipation is the exploratory case which we may also describe by saying that “an Anticipation drives a Purpose” and the organism acts in a passive manner against a forecasted event. The organism initially forecasts a future event and foresights the expected outcome. The organism must then decide whether the expected outcome is positive or negative and adopt a suitable purpose to handle the expected outcome. Upon fixing the purpose in its mind, it must consequently decide on a way of action (strategy) by making a selection among alternative actions again by using its foresighting ability; create a Project Plan and advance with the deployment. Conversly, Anticipation for Purpose is the normative case where
24 ANTICIPATION AND PURPOSE
“a Purpose drives an Anticipation”. In this case the organism acts in a pro-active manner and envisions a (desired) future state in its mind. This means the adoption of apurpose which represents a future expected outcome in accord with its “ultimate purpose”. Although the organism’s “ultimate purpose” is single, the (immediate) purpose is multiple and variable. Behavioral characteristics and functional ability is determinative in this selection. If the anticipation is based on normative scenarios and therefore the purpose is by default positive, this purpose or desired outcome may be called a Vision. Having a set vision, the organism consequently anticipates on a process to attain this desired outcome. Foresight is employed since the expected outcome must be actually realizable. Otherwise self-motivation of the organism would be hampered. The organism must then foresight several alternative strategies and processes (subordinate actions) which would be successful to deliver the expected result. Then the organism has to make a selection and decide on the optimal strategy and process which will be deterministic on future actions to be performed. The organism, upon fixing the strategy and process in its mind, must consequently develop some sort of a Project Plan and implement this plan for actually realizing the anticipated process that will deliver the purpose what we called the Vision. We will now define the requirements for an organism to initiate a conscious decision-making process and try to develop generic algorithms using both of the above cases and attempt to apply them in real life situations.
Foundations for a Conscious Decision-Making Model in Living Organisms The following abilities must be considered for a living organism to be able to perform a Decision-Making Process :
1. The organism must be aware that ithas to make a decision. This requires that there should be a cost (penalty) associated for not making a decision.
25 ANTICIPATION
2. The organism must recognize the available alternatives and/or the alternative set from which it has to make a selection. The alternative set may present a simple Yes/No or a multi-selection structucture as well as a continuum of selections. Ideally, the organism may also be capable of creating additional alternatives within a given set. 3. The organism must be capable of anticipating the results and costs associated with each available selection. 4. The organism must perform an optimization process to maximize gains (utilities) and minimize losses (costs) simultaneously; or to minimize free energy which is recently arising as a critical quantity in brain theories and brain modeling research [Friston, 2010].
Generic Strategies for Purpose for Anticipation (Explorative Case) In the generic case of Purpose for Anticipation, an organism initially foresights a future event. After an event is foresighted by the organism, the initial decision for the organism is to assess whether the future event is positive or negative. This decision depends on its ultimate purpose of assuring the existence of its species and to extend its own lifetime. Upon making this assessment then the organism must then decide whether the foresighted event is inevitable, manipulatable or obstructable. If the forecasted event is assessed as positive, then the latter case naturally becomes an issue of protectability rather than obstruction. After this assessment is done, the organism will adopt a purpose which will be determinitive on the strategy and the following actions to be taken. The main criterion for this strategic decision will be the minimisation of potential losses for [Pfor-A] and the maximization of potential gains for [Pfor+A], where naturally the cost for each action will also be of additional concern. For [Pfor-A], the following generic categories of purposes may be proposed :
TO COPE : If we assume that a living organism forecasts an inevitable negative event and foresights that nothing can be done about the event’s unfolding, the only choise for the organism is to prepare
26 ANTICIPATION AND PURPOSE
itself by increasing the robustness of its own mindset and/or physical conditions. Hence the sole purpose becomes to cope with the event by modifying / changing its own behavioral dynamics and/or physical conditions. TO DECELERATE / STEER : Alternatively, the organism may foresight that the inevitable negative event’s temporal or physical characteristics may be manipulated. Hence the purpose of the organism becomes either to decelerate / slow down the process (retardation) and/or to conveniently alter the process or the outcome. TO HALT : In a third alternative, the organism may foresight that the forecasted negative event is not inevitable, which implies that the undesired outcome may be obstructed or cancelled. The purpose becomes to halt the event.
For [Pfor+A], we can identify the following generic cases for purpose selections :
TO WELCOME : If we assume that a living organism forecasts an inevitable positive event and foresights that nothing can be done about the event’s unfolding, the only choise for the organism is to welcome the event and its sole purpose becomes to prepare its own mindset / physical conditions in order to maximize potential gains from the event by modifying / changing its own behavioral dynamics and/or physical conditions accordingly. TO ACCELERATE / STEER : Alternatively, the organism may foresight that the inevitable positive event’s temporal or physical characteristics may be manipulated. Hence the purpose of the organism becomes either to speed up the event’s unfolding process or to somehow magnify the outcome. TO PROTECT : In the third alternative, the organism may foresight that the forecasted positive event is not inevitable, which implies that the outcome may be stopped / cancelled (by others). The adopted purpose then becomes to protect the outcome of the event.
27 ANTICIPATION
Note that if the selected purpose is in the TO ACCELERATE / STEER category, this does not mean that the organism will not also try to modify / change its own behavioral dynamics and/or physical conditions which represent the purpose of TO COPE category. This is also true for a purpose in TO HALT / PROTECT category where both TO COPE (or WELCOME) and TO ACCELERATE (or DECELERATE) / STEER categories. This means that a purpose belonging to a higher category will always encompass the purposes of the previous categories. It should also be noted that if the foreseen event is judged to be in one category, a natural lateral purpose may be adopted by the organism for promoting the event to a higher (manipulatable or obstructable) category. This will always be the case for an organism (such as a human or a company) which is capable of conducting research and developing measures for predominating the event.
STRATEGIC DECISION ON PURPOSE (Generic Case) Pfor+A Pfor-A Inevitable Event
PREPARE TO WELCOME PREPARE TO COPE
Manipulatable Event (Temporal & Spatial) TO ACCELERATE / STEER TO DECELERATE / STEER Obstructable Event
(Preventable Outcome) (Avoidable Outcome) TO PROTECT TO HALT
Table 1 Strategic Decision on Purpose
28 ANTICIPATION AND PURPOSE
Example Case (A): Purpose for Anticipation in Human versus Nature
In this Section we will treat Anticipation for Purpose with an example where the organism is a human and its environment is the Nature. We will begin to examine the alternatives and try to develop a basic decision making model. From the definition of Anticipation given in the previous sections, it should be obvious by now that if the Human (Observer/Perceptor) forecasts a future event related to the Nature and does nothing (in his awareness) in terms of changing any state related to itself or its environment, the forecasted data may just be called “information” and the underlying process is not Anticipation. The first thing a human should do against a forecasted event is to decide whether the event is positive or negative depending upon its ultimate purpose, which is to extend its own lifetime and (being aware or unaware) assure the future existence of Humanity. The human employs his/her foresighting ability to make this assessment. Upon making this decision, the following cases may be considered. If the foresighted event in the Human versus Nature case is judged negative (undesired) then the human adopts a [Pfor-A] purpose. The next decision is to judge whether the event is inevitable, manipulatable or obstructable. If the event is judged inevitable, a corresponding PREPARE TO COPE purpose must be adopted. The examples for the case where the future event is negative (undesired) and inevitable may be an earthquake, volcanic eruptions or an approaching meteor. The actions to be taken in this case may involve mental self-preparation, preparing emergency plans all the way to building durable buildings. The examples for the category where the event is negative and inevitable but manipulatable (where a TO DECELERATE / STEER purpose will be selected) may be global warming, animal species extinction or flooding. All these natural events are indeed inevitable but their underlying processes can either be slowed down or their outcomes may somehow be tempered. Global warming may be slowed down by
29 ANTICIPATION international treaties, extinction of animal species may be slowed down and floods may be tempered by building dams, canals and barriers. The examples for the category where a negative event may be totally or partiallly obstructed (where a TO HALT purpose will be selected) may be epidemies that can be halted by vaccines and soil erosion by planting trees. Alternatively, if the human judges the future event as positive, a [Pfor+A] purpose will be adopted. The examples for the Human versus Nature case where the event is positive (desired) and inevitable (where a PREPARE TO WELCOME purpose will be selected) may be seasonal rains, uninterrupted sunny weather or mild sea conditions depending on geography. The actions to be taken may involve mental self-preparation and preparing for enjoying sunny wheather, all the way to choosing the convenient crops for efficient agriculture. The examples for the manipulatable positive events category (where a TO ACCELERATE / STEER purpose will be selected) may involve seasonal rains or sea tides both of which represent a case which cannot be accelerated but the outcomes may be used for positive gains like generation of renewable energy and by building hydraulic and appropriate power plants. The examples for the obstructable positive events category (where a TO PROTECT purpose will be selected) may be strong winds which may be used in power plants and the resulting natural fertilization both of which may be protected by stopping urbanization by close-packed tall buildings and banning the excessive use of pesticides, respectively.
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STRATEGIC DECISION ON PURPOSE (HUMAN VERSUS NATURE EXAMPLE) Pfor+A Pfor-A Inevitable Event
Sunny Weather Earthquake PREPARE TO WELCOME PREPARE TO COPE (Prepare Beach Accessories) (Strong Buildings)
Manipulatable Event (Temporal & Spatial)
Excessive Rain Global Warming TO ACCELERATE / STEER TO DECELERATE / STEER
(Build Dams) (Reduction of Ozone/CO2) Obstructable Event (Preventable Outcome) (Avoidable Outcome) Strong Winds Epidemics TO PROTECT TO HALT (Stop Tall Buildings) (Develop Vaccine)
Table 2 Strategic Decision on Purpose - Example Case (A)
Example Case (B): Purpose for Anticipation in Company Management
The ultimate purpose of a company, similar to any living organism, is to subsist indefinitely (live forever). Accordingly, a company must operate profitably and continuously generate a positive return on investment. Some of the indicative measureable parameters of profitability are sales turnover together with other (financial and other) income, market share and operational (purchasing, manufacturing, logistics, sales, service, personnel, etc) expenses. In this example the company top management team foresights an event concerning the competitive market conditions and makes an assessment whether the event is positive or negative based on its effect on profitability and/or the indicative parameters. Then an
31 ANTICIPATION appropriate purpose must be selected which will be determinative on the actions to be taken by the company. The generic purpose selection categories of Table 1 may be employed : The examples for a negative and inevitable event (where a PREPARE TO COPE purpose will be selected) may be shrinking / diminishing markets or more generally an approaching economic crisis. The corresponding actions may involve conservative budgeting, reducing stock levels and/ or taking financial measures to evade or minimize possible loss of profits. The examples for a negative and inevitable but manipulatable event (where a TO DECELERATE / STEER purpose will be selected) may be an expected increase on corporate tax rates, the launch of an innovative new product by a competitor or development of new technology that may reshape the whole market conditions. The corresponding actions may be lobbying for less increase in corporate taxes or to fight for a complete abandonement of the increase which represents an effort for pushing a manipulatable event to the obstructable category. The actions for slowing down the negative effects of an expected innovative new product by a competitor may be to seek company buyouts or marriages if there is no time (or other sources) to invest for own new product development or conduct research for creating new technologies. The examples for a negative obstructable event (where a TO HALT purpose will be selected) may be a new competitor entering the market or a government plan for lifting import quotas. Both events may be obstructed by price reductions in the market and/or by conducting lobbying for abandonement of the lifting decision. The examples for a positive and inevitable event (where a PREPARE TO WELCOME purpose will be selected) may be an expected market expansion and/or economic growth. The corresponding actions may be increasing company stock levels and/or preparing for increased production. The examples for a positive and inevitable but manipulatable event (where a TO ACCELERATE / STEER purpose will be selected) may be a competitor in danger of going bankrupt where the process may be accelerated by starting price wars and further damaging the competitor’s
32 ANTICIPATION AND PURPOSE market position or a government plan for decreasing corporate tax rates where lobbying for the maximum decrease would be the corresponding action. The example for a positive obstructable event (where a TO PROTECT purpose will be selected) may be a government plan for establishing import quotas where to counter the lobbying against this plan would be the appropriate action to take.
STRATEGIC DECISION ON PURPOSE (COMPANY MANAGEMENT EXAMPLE) Pfor+A Pfor-A Inevitable Event Economic Growth Economic Crisis PREPARE TO WELCOME PREPARE TO COPE (Invest to Increase (Conservative Budgets) Production) Manipulatable Event (Temporal & Spatial) New Product / Technology Competitor Exit Market TO DECELERATE / STEER TO ACCELERATE / STEER (Company Marriage / (Price Wars) Takeover) Obstructable Event (Avoidable Outcome) (Preventable Outcome) New Competitor Entering Import Quotas Market TO PROTECT TO HALT (Lobbying)) (Price Reductions)
Table 3 Strategic Decision for Purpose – Example Case (B)
Generic Strategies for Anticipation for Purpose (Normative Case) In the generic case of Anticipation for Purpose, the living organism is expected to act in a pro-active manner and in accordance with its ultimate purpose in life, decide on a purpose related to a future state to be attained. Thisdesired future state may be called its Vision. For
33 ANTICIPATION this case, therefore, the first and foremostessential feature for a living organism is to be visionary, i.e. it must have a natural inner drive for (a) adopting a vision and (b) exert an effort for its realization. Both of these traits are important aspects of visionary behaviour. Not all living species embody such feature and among the organisms that have the trait, the capacity for demonstrating a visionary behavior for the organism varies with personal and environmental conditions. A certain section of the brain is recognized to be deterministic on visioning a future and the development of that section varies from person to person (Eagleman, 2015). Assuming that the organism do have the virtue of adopting a vision, the issue becomes the assignment of a degree of ambition while deciding on a vision. The degree of ambition while selecting a vision may be explained by two dimensions where one dimension reflects a measure of difficulty and the other dimension reflects a measure of riskiness. A vision may be difficult, requiring hard (but in some sense straightforward) work for success. On the other hand, a vision may exhibit risky features which may affect success no matter how hard one may work. The degree of ambition exhibited by an organism is determinative on the difficulty and riskiness levels of a vision to be adopted by that organism. Behavioral characteristics such as aggressiveness, self-confidence, tendency for risk acceptance (aversion) and/or accepting (avoiding) hard work, etc. play a role on the degree of ambition demontrated by an organism and hence, on the fundamental traits of the selected vision. Common personality tests on the market may be employed to provide good estimates of these behavioral characteristics for real persons. An example schema for a vision selection mechanism where a vision may be classified according to its difficulty and riskiness levels is given in Table 4. The exact relational mechanisms for these behavioral traits are beyond the know-how of the author and should be the concern of psychologists working in this field and neuroscientists dealing with modeling of brain functions.
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Vision Traits Selection CHALLENGING VISION RISKY VISION LIGHT VISION HARD VISION DIFFICULTY LEVEL
Table 4 Vision Traits Selection
The living organism’s trait for adopting a vision as in Table 4 actually defines the domain of achievable future states. The main drive for the organism to act normatively and adopt a vision stems from its ultimate purpose in life which may mathematically be formulated as an effort to resist an increase in (hence a minimization of) its body’s entropy. This complex problem may be accepted as the primary optimization problem that the organism must solve. For an organism to demonstrate a full visionary behaviour, it must also have an inner drive to exert an effort to realize an adopted vision. This drive of course originates from the above stated entropy minimization effort but this drive may be magnified by the organism’s understanding of its current state, the future state described by the vision and mainly by the difference (or distance) between these two states. The inner drive of the organism to achieve a visioned future state can be accepted as a secondary optimization effort to minimize this difference (distance). Both of the above mentioned primary and secondary optimization problems are highly complex and require an ability to solve difficult optimization problems. A useful approach in this respect is to consider Utility Theory (Fishburn, 1970) developed by economists and behavioral scientists. The organism’s optimization efforts for this minimization materializes in real life as the development and actual implementation of a strategic plan. The purpose or the vision statement to be adopted by the organism may be descriptive or numerical (qualitative or quantitative) but should always be measurable in some sense. An organism which fails to specify a measurable vision is actually not behaving in a pro-active manner and can be accepted as acting exploratively rather than normatively.
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Foresighting / decision-making ability and process knowledge of an organism play a significant role for determining the parameters or the description style of a desired and realizable vision statement. Upon fixing the vision in his mind, the organism has next to perform a strategy development process in order to attain the desired outcome. Several alternate strategies may exist that would be successful in delivering the expected result. Hence, the organism has to make a selection and decide on the optimal strategy and select the process which will be determinative on the future actions to be performed. Upon fixing the strategy and process in its mind, the organism must consequently develop some sort of a Project Plan and go on with the implementation for actually realizing the adopted purpose. The project plan consists of chosen milestones which represent the beginning and ending points of consequent and/or parallel subordinate actions of which the final output is the envisioned purpose, decision and monitoring points along with an estimated timing plan and cost budgets for each activity. Every subordinate activity should have deliverable goals with predetermined quality measures for accepting a goal as achieved and to evaluate the corresponding action as successfully completed. The next step would be the kick-off action to start the deployment process. The deployment process is to be monitored at predetermined control points which by default include the predetermined milestones and if evaluated as necessary, additional points within the subordinate activities. The process goes on until the project is completed which means that the desired future state (or the vision) is realized. The block diagram shown in Figure 1 shows the main features of this generic vision and strategy development process which may be seen as an optimization effort employed by the organism to minimize the difference between the current and the desired future state.
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Generic Vision & Strategy Development Case
Figure 1 The Generic Vision and Strategy Development Process
Example Case (C) : Anticipation for Purpose in Company Management In this example, we will focus on the normative purpose (vision) selection for a company taken as the living organism which operates in a competitive market environment. The overall behaviors and decision-making abilities exhibited by the company are represented by the behavioral characteristics and managerial / technical abilities of its top management team. For our present purpose in this Chapter, only the model for the vision selection / decision process in Table 4 will be considered. The completed case should involve a decision on fixing the future vision of a company, deciding on a strategy, developing a plan for
37 ANTICIPATION action and implementing / monitoring this plan in order to realize the adopted vision. Assuming that a normative drive for adopting a future vision is present, the first issue, as proposed in the generic case, is to decide on a vision statement. The decision process becomes complicated when the deciding actor(s) is a team of top managers where individual ambitions and leadership abilities exhibited by each team member arise as major factors in assessing a compounded degree of ambition for the team. The leadership and the degree of ambition displayed by the CEO as the leader of the top management team is highly indicative of the team behavior but individual team member’s personal degree of ambitions and leadership capabilities are also effective. Hence a measure of theassertiveness of the CEO may be considered to assess what portion of his/her degree of ambition will prevail against the other team members. Of course, it should not be forgotten that the degree of ambition displayed by the team may be higher than the CEO’s and if the assertiveness of the CEO is relatively low, a higher team degree of ambition than that of the CEO’s may also prevail. The dynamics of this team selection process can be modeled using the individual behavioral characteristics and a compounding algorithm which employs additional characteristic variables that reflects the assertiveness and communication skills of the team members. Measurability of the vision is straightforward if a quantitative parameter is accepted such as sales turnover (growth), market share or profits for a given time period. Alternatively, if a descriptive (qualitative) vision is adopted, appropriate surveys must be employed for representative evaluation. Profit is the most important parameter but may be variable over time and may even be negative for a period because of investment needs. The market may be growing, stationary or contracting and even safeguarding a present market share may be a challenging goal for a company in a competitive business environment. Since the adopted vision must act as an important motivator for the whole company, defining the vision by a parameter which the future value may be stationary or negative is not very desirable. Hence the sales turnover is generally a better parameter to choose for defining a future goal to be achieved.
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Assuming growing market conditions, the sales turnover of a company is normally expected to increase in parallel with the expected growth. A five year goal is generally appropriate. Inflation also positively effects the turnover to present a continuously increasing trend. Deciding on a numerical value for future sales turnover highly depends on the market conditions and the sector, but Table 5 may be helpful for providing a general guideline. With the adoption of such guiding information, the issue of vision selection becomes a process of evaluating the top management personalities data that comes from currently available personality tests and formulating a probabilistic method for assigning an appropriate point within the defined vision domain. Upon fixing the vision, the next step will be to decide on a strategy that will navigate the company from its current state to the future state defined by the vision statement. The required abilities for performing such a task should be defined and appropriate mechanisms for modeling each ability must be formulated. Several approaches for futures estimation methodologies suggested in recent research papers for e.g. Öner (2010), Tavory & Eliasoph (2013), Inayatullah (2007) may be combined and employed for this effort. This is by no means an easy task and should be the subject of future research. This normative example demonstrates the importance of purpose (vision) selection in anticipatory behavior exhibited by an executive team representing a company and establishes the role of anticipation in strategic planning. The developed simulation models may be used for educational as well as executive team members selection / appointment process purposes or for creating awareness to potential weaknesses that may be exhibited by a current executive top management team.
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Domain for Sales Turnover Vision CHALLENGING VISION RISKY VISION Well over expected market growth Significantly over expected % which include new products market growth % which include / technology developments with new product / technology additional manufacturing facilities developments and new manufacturing facilities as well as competitor buyouts LIGHT VISION HARD VISION Slightly over expected market Well over expected market growth % realizable with minor growth % and include new new product development product developments and employing current manufacturing extended manufacturing facilities facilities DIFFICULTY LEVEL
Table 5 Sales Turnover Vision Selection
Conclusions This Chapter attempts to review, understand and explain the developing field of anticipation research and explore its implications for a wide range of communication, strategic planning, decision-making and innovation related issues in company management. The relationship betweenanticipation and purpose within the context of future studies is firmly established and the necessity of a purpose in the anticipatory systems modeling of living organisms that exhibit intelligent behaviour is demonstrated. Preliminary generic algorithms for modeling the anticipatory purpose selection mechanism in decision-making processes of a living organism for both explorative and normative cases are presented. Example cases are developed for an individual (human) acting against the Nature and for a company top management team performing a vision selection operation as the first step of a strategic planning process. The Examples (A & B) developed for the explorative case clearly demonstrates the importance of purpose selection in anticipation. The company vision selection process in Example (C) developed for the normative
40 ANTICIPATION AND PURPOSE case presents ideas for future uses of anticipatory systems models and demonstrates the role of anticipation in strategic planning.
Acknowledgement Full credit is due to late Prof. Dr. M. Atilla Öner for introducing, encouraging and forcing me to start working on the subject. It is sad that we lost him too early.
References Dauten, M. Paul (1958), “Management Philosopy: The Time Dimension of Planning”, The Journal of Academy of Management, Vol. 1, No. 1, April, pp.23-33. Eagleman, D. (2015), “The Brain The Story of You”,Pantheon Books, October. Elkus, S. A. (1919), “Purpose as a Conscious Concept”, The Journal of Philosophy Psychology and Scientific Methods, May, pp. 290-296. Fishburn, P. C. (1970), “Utility Theory for Decision Making”, NY, John Wiley. Friston, Karl (2010). “The free-energy principle: a unified brain theory?” Nature Reviews Neuroscience / AOP, Published Online, January, doi:10.1038/nrn2787. Keat, Russell and Urry, John (1975), “Social Theory as Science”, Routledge Revivals (Taylor & Francis Group), London and Boston. Krikorian, Y. H. (1930). “The Meaning of Purpose”, The Journal of Philosophy, Vol. 27, No. 4, February, pp. 96-105. Louie, A. H. (2010), “Robert Rosen’s anticipatory systems”, Foresight, Vol. 12, No. 3, pp. 18-29. Öner, M. Atilla (2010), “On theory building in Foresight and Futures Studies: A discussion note”, Futures, 42, pp.1019-1030. Poli, Roberto (2001), “The basic problem of the theory of levels of reality”, Axiomathes, 12, pp. 261-283. Poli, Roberto (2017), “Introducing Anticipation Handbook of Anticipation, Theoretical and Applied Aspects of the Use of Future in Decision-Making”, pp. 1-14.
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Rosen, R. (2012), “Anticipatory Systems. Philosophical, Mathematical and Methodological Foundations (2nd Edition)”, Pergamon Press, Oxford. Tavory, Iddo and Eliasoph, Nina (2013), “Coordinating Futures; Toward a Theory of Anticipation”, American J. of Sociology, Vol. 118, No. 4, January, pp. 908-942. Warren, H. C. (1916), “A Study of Purpose I, Introduction: Teleology as a Scientific Problem”, The Journal of Philosopy, Vol. XIII, No. 1, pp. 5-26. Warren, H. C. (1916), “A Study of Purpose II, Purposive Activity in Organisms”, The Journal of Philosopy, Vol. XIII, No. 2, pp. 29-49. Warren, H. C. (1916), “A Study of Purpose III, A Study of Purpose”, The Journal of Philosopy, Vol. XIII, No. 1, pp. 57-72.
42 2 ANTICIPATION: MEANING AND USAGE
Çiğdem Kaya, M. Atilla Öner
Introduction Anticipation science has attracted attention of many scholars over the last decades and is continuing to arise as a field of research. It is very crucial to clarify the meaning of anticipation to be able to pave the way for anticipation to become a good theory. Yet anticipation has been used in place of words that are related to predicting the future in a considerable number of studies and has moved away from its original meaning. The aim of this chapter is to examine the meaning and usage of anticipation for clarifying this term that is very important in theory building. The meanings and synonyms of anticipation in dictionaries are examined. Then the concepts that are used for defining anticipation and synonyms of anticipation are compared and discussed based on the meaning of anticipation defined by Poli (2017). Afterwards, the usage of anticipation is scanned in published academic papers and books and its correct and incorrect uses are underlined. Finally, the importance of clarifying the meaning of anticipation in building anticipation theory is discussed and along with suggestions for future research.
1. Meaning of Anticipation Anticipation has various meanings and synonyms in dictionaries. In this part, we first present the meaning of anticipation as dictionaries include, and then go over the synonyms of anticipation and discuss them in detail. Lastly, we present anticipation-related concepts proposed by Poli (2017).
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a. Meaning of Anticipation in Dictionaries The Advanced Learner’s Dictionary of Current English (1971) gives the following entries for anticipation related verbs, adjectives and nouns. anticipate: v.t. (VP1, 11, 17A)1 1. do, make use of, before the right or natural time: Don’t anticipate your income, order goods, etc. before you receive your income. 2. do something before somebody else does it: It is said that Columbus discovered America, but he was probably anticipated by sailors from Norway who reached Labrador 500 years earlier. 3. see what needs doing, what is likely to happen, etc. and do what is necessary: He tries to anticipate all my needs, satisfy them before I mention them. A good general tries to anticipate the enemy’s movements. 4. look forward to, expect: I anticipate deriving much instruction from the lecture. She anticipates great pleasure from her visit to Italy. anticipatory: adj. anticipation: n. [U] action of anticipating: We bought an extra supply of coal in anticipation of a cold winter. Thanking you in anticipation, in advance and expecting you to do what I have asked. expect: v.t. 1. regard as likely; think or believe that something will happen or come, that somebody will come; wish for and feel confident, that one will receive: We expected you yesterday. We were expecting a letter from her. I expect to be (expect that I shall be) back on Sunday. You would expect there to be (that there would be) strong disagreement about this. You can’t learn a foreign language in a week; it is not to be expected. You are expecting too much of her. Based on these entries, anticipation related verbs, adjectives and nouns make us understand the concept as doing something before it is actually being necessary by foreseeing what will be happening in
1 Verbs marked VP 1 may be used with a simple direct object which is a noun or pronoun. Verbs marked VP 11 may be followed by a that-clause. Verbs marked VP 17 may be followed by a gerund. The pattern is subdivided. In Group A (including phrasel verbs such as keep on, go on, give up), in those cases where the gerund may be replaced by an infitive, a change of meaning results.
44 ANTICIPATION: MEANING AND USAGE the future. The concept also makes us think about taking an action to change the anticipated event before it occurs. As a verb “to anticipate” is used as both doing something before it actually occurs and expecting something to happen. Anticipation as a noun is used as acting now based on predictions about the future. The verb “to expect” is found in dictionaries as anticipated related verb. It means thinking or believing that something will happen or come without doing an action.
b. Synonyms of Anticipation Soule (1986) lists the following synonyms: anticipate: v.t. 1. Go before, get the start of. 2. Take up beforehand, consider in advance, meet or play in advance. 3. Foretaste, forestall, experience beforehand. 4. Expect, forecast, foresee, look forward to, count upon, calculate upon, prepare one’s self for. anticipation: n. 1. Expectation, expectance, contemplation, prospect, hope, trust. ABEYANCE 2. Foretaste, prelibation, antepast, presentiment, forestalling, foreseeing, foresight, presscience, prevision, forethought, forecast, preconception, experience beforehand, prior realization abeyance: n. 1. (Law) expectation, prospect, expectancy, waiting, anticipation, calculation, contemplation 2. Suspense, suspension, suspendedness, reservation, intermission, remission, dormancy, quiescence, suppression, sublation. expect: v.t. 1. Await, wait for. 2. Anticipate, look for, contemplate, look forward to, count upon, reckon upon, calculate upon, hope for, rely upon. expectancy: n. 1. Expectation, expectance 2. (Law) Abeyance, prospect. expectation: n
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1. Anticipation, prospect, expectance, expectancy. 2. Reliance, confidence, assurance, presumption. Roget’s Thesaurus of English Words and Phrases,Classic American Edition, Crown Publishers, Inc., USA, 1979. anticipate [false estimate of time] Anachronism. - N. ana-, post-, prochronism; prolepsis, misdate; anticipation, antichronism. V. mis-, ante-, post-, over-date; anticipate; take no note of time. Adj. misdated c. v.; undated; overdue; out of date; anachronous &c. n. [Prospective time.] Futurity. - N. Van de Ven (2007: 115) states that “there are two basic ways to define the meanings of terms at different levels of abstraction: semantic and constitutive definitions”. A term’s semantic definition indicates its similarities (positive semantic definitions) and differences (negative semantic definitons) with other terms (i.e. reference to synonyms and antonyms, metaphors and analogies for developing semantic definitions). Van de Ven (2007: 115) also states: “both positive and negative semantic definitions are required to clarify the meaning of the concept, positive definitions identify the properties of a term, negative definitions locate the boundaries of a term.” A term’s constitutive definition indicates its component parts required for descending the ladder of abstraction to make it possible to have theoretical and observable terms of the concept. “Semantic and constitutive definitions respectively classify the meaning of a concept by breadth and depth.” Therefore we present semantic definitions of anticipation in this section to make clear the concept of anticipation. Etymologically anticipation has its roots in “ante” that means “before” by referring to being aware of something coming at a future time. The words that are used as synonyms of anticipation are expectation, prospect, forestalling, foreseeing, foresight and so on as they are seen above entries. The synonyms of anticipation as noun mean expecting and looking forward. Expecting does not require any action. For example, a student expects high grade from her math exam because the exam was easy and she worked hard to get a high grade, but there is nothing
46 ANTICIPATION: MEANING AND USAGE that can be done to change this result after the exam. The verb forms of synonyms of anticipation, on the other hand, are used as “preparing for, forestalling”. As a result, anticipation means that something is expected and an action is taken in that expectation. This indicates that the verb forms of synonyms of anticipation as are used in the correct meaning of anticipation. In addition to its synonyms, antonyms of anticipation from Roget’s 21st Century Thesaurus (2013) are presented as ignorance, amazement, astonishment, doubt, fear, sensation, surprise, unreadiness, and wonder. Anticipation is used to overcome fear and doubt, not to give rise to astonishment, to foresee surprises for taking actions to be able to get ready for them. As a result, in this section we presented semantic definitions of anticipation. As we discussed in the subsection, Poli (2017) distinguishes among forecasting, foresight and anticipation and underlines that anticipation includes forecast and foresight studies. We also present anticipation-related concepts suggested by Poli (2017) and refer them as constitutive definitions (component parts) of anticipation.
c. Concepts in Anticipation Poli (2017, p. 1) defines anticipatory behavior as a“ behavior that ‘uses’ the future in its actual decision process” and states that anticipation has two components which are “a forward-looking attitude” and “the use of the formers’s result for action.” He then uses the example of a weather forecast to explain this situation further: A weather forecast in this sense is not an anticipatory behavior but watching a weather forecast and taking an umbrella before going out is an anticipatory behavior. Poli (2017) also states that his definition of anticipatory behavior with the above two components is consistent with Rosen’s definition of an anticipatory system (Rosen, 2012). Rosen’s definition states that An“ anticipatory system is a system containing a predictive model of itself and/ or its environment which allows the system to change state at one instant in accord with the model’s predictions pertaining to a later instant” (Rosen, 2012, originally published in 1985).
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Poli describes the three levels of Futures Studies as: I. Forecasting II. Foresight III. Anticipation
Forecasting is the predictive component of future study and ranges from a very short temporal window such as econometric models to very long such as climate change models while modelling its predictions. It is just about predicting the future by benefiting from mostly quantitative analysis by using past-based data. Future event is described in forecasting but no action is taken by decision maker to modify or change the future. Foresight is non-predictive, and qualitative and produces a variety of possible futures by using scenarios. Future events are described in foresight but no action is taken by decision-maker to modify or change the future as it is in forecasting. Anticipation is non-predictive and qualitative as it is in foresight. It uses the outcomes resulting from forecast and foresight models and implements them into decisions and actions to modify or change the future. Anticipation-related concepts that we refer them as constitutive definitons of anticipation in this context are presented below to understand the definition better.
i. Foreseen event There are two cases where the decision-maker isaware or unaware that a future event is foreseen and consequently an action is being taken (Tuğcu, 2019). Explicit anticipations are those of which the system is aware, by contrast, implicit anticipation works below the threshold of awareness (Poli, 2017). Foreseen event in anticipation can be positive (desired) or negative (undesired) in terms of explicit anticipation. Poli (2017) describes this distinction by stating that if the system evaluates a future event as positive, it will evolutionally maintain its own behavioral patterns. On the contrary, if the system evaluates a future event as negative, it will seek to change its behavioral patterns for avoding the anticipated negative results. Tuğcu (2019) modifies the statement for
48 ANTICIPATION: MEANING AND USAGE positive future event as if the system evaluates a future event as positive, it will not only maintain its own behavioral patterns but may also try to make arrangements for further magnifying the foreseen gains.
ii. Modification After positive or negative foreseen event is described, modifications and/or actions are performed to be able to maintain its own behavioral patterns and make arrangements for further expanding the foreseen advantages by external and internal models. External models are related to performing behavioral modifications by using information provided objectively from the environment; internal models are related to take actions based on subjectively constructed psychological expectations (Poli, 2017).
iii. Decision-Making Phenomena A living organism’s decision-making processes can be modeled under certain assumptions and simulated by anticipatory models (Tuğcu, 2019). These anticipatory models come from representational and presentational perspective points. Representational modeling approach is the modeling of a foreseen event based on brain processes whereas presentational modeling approach is the modeling of a foreseen event based on brain and mind processes by treating them as two separate layers (Poli, 2017). This is similar to Kahneman’s (2013) separation between fast and slow thinking for decision-making (for further detail, please see part 4b in this chapter). Representational modeling can be seen as related to fast thinking because fast thinking includes intuitive decisions. On the other hand, presentational modeling can be seen as related to slow thinking that requires optimization using both brain and mental functions to make decisions.
iv. Model Poli (2017) classifies modeling approaches as predicative and impredicative. Predicative models include modeling techniques such as linear, non-linear, etc. In other words, predicative models are modeling
49 ANTICIPATION the future based on using past knowledge and mathematical functions. Impredicative models’ primary source comes from self-reference and violates the principle of causality.
v. Scenarios Poli (2017) identify two distinct cases: exploratory and normative scenarios. The first one is making anticipation in a forward attitude from the present to the future. The other one is anticipating according to selected purpose by working backward in time toward determining its necessary conditions (Tuğcu, 2019).
2. Usage of Anticipation In this section, we first conducted a literature review in the academic papers and then examined a book in depth to indicate the usage of anticipation.
a. Usage of Anticipation in Academic Papers Anticipation has been used in variety of meanings in reviewed academic articles between the years 1981-2018 (all references and their usage of anticipation can be provided to the readers upon request). Early years of usage, it can be seen that anticipation is generally used as prediction and imagination as presented in Table 1. An example of the usage of anticipation as imagination is Clarke’s (1994) usage of anticipation: “A good military leader must dominate the events which encompass him’, so said Field-Marshal Montgomery. He has therefore got to anticipate enemy reactions to his own moves, and to take quick steps to prevent enemy interference with his own plans.” An example of the usage of anticipation as prediction is Clarke’s (1986) usage of anticipation: “The new thinking about the future is essentially an advance from general expectations to particular anticipations.” Publications in the late 1990s and after 2000 have used anticipation to mean different concepts such as foresight, forecast, guess, and expectation. Selected quotes for each respectively: “The added-value of Wild Card analysis in scenario development is about anticipating unexpected but probable major
50 ANTICIPATION: MEANING AND USAGE changes.” (Smith and Dubois 2010), “Both of these books anticipate how ‘science will change our lives in the 21st century.” (Slaughter, 2002), “The third is that futures studies has neglected to study the everyday futuring or anticipation of ordinary people” (Jarva, 2006), and “Anticipated (or expected) conflicting reactionsoccur when an individual possesses no, or only a few, manifest conflicting reactions and yetanticipates that there may exist conflicting information of which they are unaware” (Priester, Petty, and Park 2007). Anticipation, on the other hand, has been used similarly to Poli’s (2017) definition of anticipation, which is the adopted definition throughout this book, in the papers of Tognetti (1999), Reid and Zyglidopoulos (2004), De Haana et al. (2011), Rious, Perez, Glachant (2011), Dodonova and Khoroshilov (2012), Sanz, Hernandez and Sanchez-Escribano (2012), Rossel (2012), Fattouh, Kilian, and Mahadeva (2013), and Tavory and Eliasoph (2013). Two examples of usage are: “Anticipate implies planning, intent, or, in any case, actions or initiatives before the fact, as opposed to recover from, which entails recuperation or restoring to normal functioning after the fact.” (De Haana et al., 2011), “Sellers might feel that it is better to drop out of the English action (open-bid) because of the anticipation of the auction fever that might have strong negative effect on participation of bidders and the final price” (Dodonova and Khoroshilov, 2012).
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Meanings of Usage of Anticipation in References Academic Papers Bowers, Mitchell, and Webb (1980), Bowers, Prediction Mitchell, and Webb (1981), Godet (1983), Clarke (1986c), Clarke (1986a), Clarke (1986b) Clarke (1984), Clarke (1991), Clarke (1994), Razak Imagination (1996), Porta (1999). Textor (1995), Slaughter (2002), Van der Heijden (2004), Diaz (2009), Smith and Dubois (2010), Foresight Kuosa (2010), Sebillotte and Sebillotte (2010), Saritas, Smith (2011), Fidler (2011), Jissink (2017) Godet, Chapuy and Comyn (1994), Hearn and Stevenson (1998), Bainbridge (2003), Larson and Forecast Fowler (2009), Heidari and Wu (2010), Cristescu, Andreica (2011), Revet and Langumier (2015) Tognetti (1999), Reid and Zyglidopoulos (2004), De Haan et al. (2011), Rious, Perez, Glachant (2011), Dodonova and Khoroshilov (2012), Sanz, Anticipation Hernandez and Sanchez-Escribano (2012), Rossel (2012), Fattouh, Kilian, and Mahadeva (2013), Tavory and Eliasoph (2013) Guess Jarva (2006) Wilkins (2001), Schatzel and Calantone (2006), Priester, Petty, Park (2007), Murata (2008), Köszegi Expectation (2010), Dahlén, Thorbjørnsen, Sjödin (2011), Moore and Lee (2012), Kruschwitz et al. (2018) Table 1: Usage of Anticipation in Academic Papers
As it is seen in Table 1, anticipation has been used in a variety of meanings in academic articles. These are prediction, imagination, foresight, forecast, guess, and expectation. It is quite clear that the word of anticipation is used as prediction and imagination in the very early studies. This means that anticipation was simply seen to imagine the future and making prediction based on past knowledge and these imaginations. Studies after 2000 have used anticipation as nearly today’s usage except Jarva (2006) with the usage of the term as “guess”. However, anticipation is covering all the words including forecast, foresight, and expectation and those terms could not be used interchangibly.
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b. Usage of Anticipation in a Book In anticipation literature, there are few important books that make valuable contributions to the area. The most important books in this area are Rosen (2012), Poli (2017), Miller (2018), Nadin (2012) and Kahneman (2013). 2002 Economics Nobel laurate Daniel Kahneman discusses diffferent ways human beings make choices and decisions in his 2013 book Thinking, Fast and Slow. As choices and decisions involve “anticipations” on future results, we thought it useful to examine his usage of anticipation. In this chapter, therefore, we reviewed Kahneman’s book. Kahneman (2013) has discussed understanding of judgements and choices and underlined that anticipation of something is closely associated with coming with a judgement related to that thing and acting in accordance with the judgement. He has made distinctions between fast and slow thinking when making decisions by giving examples to explain each of them. We summarize his discussions below to understand the concept of anticipation in more detail: During the kitchen of a house was on fire, a commander of a team of firefighters shouted about getting out of there without knowing why he said this. After they escaped, the kitchen’s floor collapsed immediately. Later investigation showed that the fire that caused the collapse had been in the basement not in the kitchen. He called this situation as “the sixth sense of danger”. Another example comes from a chess master and a physician. The chess master makes a move without stopping. The physician makes a complex diagnosis after a single glance at a patient. Kahneman has called the sources of these judgements as expert intuition. He has added even our everyday intuitive abilities are similar to experts’ abilities in such situations as we detect anger in a phone call or rapidly react to indirect signs that the driver of the car in the next lane is dangerous. The accurate intuition contains no magic. Of course a chess master see the pieces on chessboard very differently from us because of thousands of hours of practice. This is explained by stating the
53 ANTICIPATION expert’s access to information stored in memory that provides answer. Therefore, intuition is related to recognition; learning to recognize the familiar and acting in a way that is appropriate to it. There is a difference between experts’ intuition and professionals’ intuition that professionals’ intuitions do not all arise from true expertise. They may make a decision to invest in an automaker’s stocks based on liking the models of the automobiles without knowing their prices. This is called as affect heuristics where judgments and decisions are guided directly by feelings of liking and disliking, with little deliberation or reasoning. If we have an expertise about a problem that we encountered, we can recognize this situation and an intuitive solution that comes to our mind will probably be correct. On the other hand, when the question is difficult and there is no intelligent solution, intuition provides the first answer that comes to the mind but may not help answer the original question. It is difficult to decide whether or not to invest in the stock, but the decision can be made immediately about liking or disliking the automobiles, and this can lead to the decision to make an investment. This is the fast thinking. Fast thinking includes both variants of intuitive thought—the expert and the heuristic— as well as the entirely automatic mental activities of perception and memory. Sometimes we may not find an intuitive solution spontaneously— neither an expert solution nor a heuristic answer comes to mind. In such cases we generally find themselves in thinking for a solution slowly, deliberately, and effortfully. This is the slow thinking and we allocate our attention to the effortful mental activities that demand it, including complex computations. The fast thinking is more influential in our decisions. Intuitive thinking is often underlined by unconscious processes. When we see a photo with an angry faced woman, we think that she is going to say us unkind words. This comes our mind automatically and effortlessly and it just happened to us.
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Due to fast thinking and slow thinking that can work simultaneously in our minds, we not only perceive the world we live in and the events around us, but also understand and interpret them. Moreover, we are guiding our lives by anticipating events that may or may not be possible through this capability. However, we must recognize the weaknesses and strengths of fast and slow thinking in order for us to use fast thinking and slow thinking correctly and effectively, that is, to interpret events correctly and make the right decisions. Kahneman discusses this subject in a very detailed and striking way. In this book, Kahneman used anticipation in diverse ways that are presented in Table 2. The reason that we present Kahneman’s anticipation uses is that he used anticipation in various ways by referring to its bases, such as intuitive based anticipation and psychology-based anticipation of regret.
Because of anticipating how friends and colleagues will evaluate our choices, our decisions and choices are based on our anticipated judgements Bias-based anticipation Intuitive-based anticipation Anticipation based on expert intuition Analysis and intuition based anticipation: Many judgements are based on anticipation and are influenced by a combination of analysis and intuition Anticipation failure on a catastrophic case Anticipation success based on luck Acting based on anticipation Anticipation based on expert intuition is successful for the short-term (what the patient will say next); but expert intuition is not useful for long-term forecasting (how well the patient will do next year) Extrapolating does not always help us successfully anticipate because of “unknown unknowns”. Therefore, sometimes information on hand is not enough to anticipate the whole because of being unknown of unknowns Being too improbable to be anticipated (“unknown unknowns”) Anticipation that is used as its synonym “prediction” Making decision based on anticipation of disappointment Making decision based on anticipated pain (anticipation is used as its synonym “expectancy” and for short-term oriented) Making decision based on anticipated emotions. Anticipation of faulty preferences
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Prefering conventional and risk-averse options based on the anticipation of regret: anticipated evaluation Avoiding from emotional pains by anticipating them Choices influenced by the anticipation of regret Overcoming to choose risk-averse options necessitates become open to the previous anticipations of regret by remembering them and their results that help you not experience bad things Psychology-based anticipation of regret. Anticipation that is used as its synonym “expectation” Anticipation under influence of something, short-term oriented Anticipation of regret based on remembering negative experiences Making decision based on anticipated outcomes Making decision based on anticipated actual experience Anticipation of faulty preferences Making decision based on anticipated emotions Psychology-based anticipation of regret Table 2. Usage of Anticipation in Kahneman’s Book “Thinking, Fast and Slow”
Based on Kahneman’s discussion and Table 2 that shows all the usages of anticipation in Kahneman’s book, it can be said that he used anticipation as a general term to understand and explain judgement and choices. It is seen that the word is mostly used for the near future since all the decisions should be made in a specified time period and the results of these decisions are mostly seen in a near future. On the other hand, anticipations of Montgolfier balloons and the landings on the Moon, and seeing the results of these anticipations required very long period of time. Kahneman (2013) used anticipation in his book in various ways by mostly reffering the meaning of anticipation as looking forward and taking action accordingly as defined by Poli (2017).
3. Discussion This chapter is based on understanding the meaning and usage of anticipation for clarifying the term for giving the way to anticipation to become a good theory. In this context, the meanings and synonyms of anticipation in dictionaries are examined and academic articles and
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Kahneman’s book are analyzed based on their usage of anticipation. According to dictionary entries, we understand anticipation as doing something before it is actually being necessary by seeing what will be necessary in the future. The concept also makes us think about taking an action to change the anticipated event before it occurs. The meaning of anticipation in dictionaries is the similar of the definition of Poli (2017) whose we adopted throughout this chapter. We also examined the semantic and constitutive definitions of anticipation that are needed to clarify the meaning of the concept on its way to become a good theory. Synonyms of anticipation indicate differences in terms of verb and noun uses. As we showed above sections, verb forms of synonyms of anticipation is quite similar the definition we adopted, whereas noun forms are more related to expecting and looking forward. After presenting dictionary forms of anticipation, we presented constitutive definitions anticipation, i.e. anticipation related concepts proposed by Poli (2017). Definitions related to terms used by explaining foreseen event, modification, decision-making phenomena, models and scenarios are constitutive definitions of anticipation. These definitons, however, need further attention to understand the concepts in detail because, as Van de Ven (2007) has underlined, these definitions indicate component parts of anticipation required for descending the ladder of abstraction to make it possible to have theoretical and observable terms. In academic papers published before 2000s, anticipation is used as making prediction based on past knowledge and imaginations about the future, on the other hand, papers published after 2000s used anticipation as both the current meaning we adopted, and the other meanings such as expectation, forecasting and foresight. In Kahneman’s book (2013), almost all the usage of anticipation has been in the sense of looking forward and taking action accordingly. This usage is similar to Poli’s definition of anticipation (2017). In Kahneman’s book, there are many types of anticipation according to its bases such as anticipation based on emotions and intuitive anticipation. Taken together, for paving the way for a good anticipation theory, it is crucial to clarify the anticipation and anticipation related concepts. Van
57 ANTICIPATION de Ven (1989:486) states that because a good theory moves the knowledge of scientific discipline forward, leads research to ask important questions, and advises management profession, it is quite practical. Bacharach (1989:498) underlines that definitions answer “what” questions but theory should answer “how, when, and why” questions, and a theory is a system of constructs and variables. In this context, propositions are formulated to indicate the relationships between constructs (Bacharach, 1989:498) and hypotheses are formulated to indicate the relationships between variables (Bacharach, 1989:498). Well-defined concepts help determine variables that are needed to gather data by descending abstraction level of the concept. According to Osigweh (1989), scientific knowledge, thus, necessitates systematically organized propositions formed by concepts that need to have good definitions. When the concepts are not defined well, they make propositions ambigious. For example, the certain aspects of anticipation may have poorly thought emphasis when it is ill defined. When the concepts are formed precisely, they become distinguishing and hence perfect for the purpose of data collection with their guidance and assistance in the efforts of researchers. Anticipation related concepts that are formed precisely are very important for continuing advancement of anticipation as a science. We have argued that the development of clear definitions for concepts is important to improving anticipation research and theory building. However, this is not well established in the literature. What is missing is the lack of knowledge about how to form precise concepts. Osigweh (1989:585) has underlined concept traveling and concept stretching for making good definitions. Concepts are the building block of science and therefore, they must be precisely defined to enable them “travel” to make the theory generalizable with its extensional coverage (i.e. breadth). On the other hand, concept stretching as broadening the concepts to extend their range of applications by being too comprehensive to be meaningful for empirical observation and professional practice can be problematic when the concept is stretched beyond reason because its depth should be protected. In terms of the usage of anticipation, there are many uses of anticipation and these uses make the concept stretched. With this
58 ANTICIPATION: MEANING AND USAGE chapter, we tried to classify meanings and usage of anticipation to be able to prevent its stretching beyond reason. This may lead to clarify the meaning of anticipation and anticipation related concepts in its way of becoming a good theory.
Conclusion We present what the current knowledge is about the concept of anticipation. There is a demand for explicit specification of meaning of the concept of anticipation and anticipation related concepts. The other demands for anticipation to become a good theory are to specify concepts, constructs and variables, to develop a theory and measure it. Thus, the value of this paper lies in its process recommendations for forming explicit concepts for anticipation. Future research can focus on meaning and usage of anticipation in different publications on different areas and in different books to help clarify the meaning of anticipation for further efforts in determining semantic and constitutive definitions, and in determining variables for measurement by descending abstraction level of anticipation. Further research can also go deeper in understanding all the processes, procedures, and ways to formulate a good theory. As we mentioned earlier, there are few important books that make valuable contributions to the area such as Rosen (2012), Poli (2017), Miller (2018), Nadin (2012), Kahneman (2013). In this chapter, we reviewed Kahneman’s book. Our aim is to review other mentioned books for future research. After focusing on current conceptualizations of anticipation and its various forms, an attempt is suggested for further research to develop an appropriate language about anticipation across various disciplines. There are some efforts made by the European Cooperation in Science and Technology (COST) to bridge the conceptualization of anticipatory processes across the different disciplinary domains, such as social sciences, life sciences and arts and humanities disciplines (COST, 2014). There should be a systematic and robust basis for theoretical development and empirical research into anticipatory practices across these disciplines. In this context, the overview of how the concept of anticipation is used
59 ANTICIPATION in different disciplinary domains such as law, physics, architecture, mathematics, management, music, sports and so on should be examined in further research. After discussing anticipation from those aspects, what addititonal works can be done for anticipation to become a good theory becomes clear.
References Bacharach, S. B. (1989), Organizational Theories: Some Criteria for Evaluation, The Academy of Management Review, October, 14 (4), pp. 496-515. Bainbridge, W.S. (2003), The future in the social sciences, Futures, 35, pp. 633–650. Bowers, D. A., Mitchell, C. R. and Webb, K. (1980), Modelling Bicommunal Conflict: 1. Posing the problem, Futures, December, pp. 473-488. Bowers, D. A., Mitchell, C. R. and Webb, K. (1981), Modelling Bicommunal Conflict: 2. Structuring the model, Futures, February, pp. 31-42. Clarke, I. F. (1984), Almanac of anticipations: Journeys through space and time-from the Santa Maria to the ‘last Columbus’, Futures, August, pp. 425- 434. Clarke, I. F. (1986a), The idea of the future: Une dkouverte France- Britannique?, Futures, April, pp. 325- 342. Clarke, I. F. (1986b), American Anticipations, War and peace- in the American Style, Futures, June, pp. 464-475. Clarke, I. F. (1986c), American anticipations Is the future what it used to be? American Views, 1945-1985, Futures, December, pp. 808-820. Clarke, I. F. (1991), From Space to Time, Factor three: science and fiction, Futures, August, pp. 637- 645. Clarke, I. F. (1994), 20th Century Future-Think: World War II, or, what did the future hold?, Futures, April, pp. 335-344. COST (2014), COST Action Application on “Towards a Discipline of Anticipation” to European Cooperation in Science and Technology. Cristescu, A. and Andreica, M. E. (2011), Estimation of Inflationary
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When Does it Enhance Innovation?, An Empirical Investigation of Firms and their Innovation Projects, Unpublished Dissertation, Aarhus University, Department of Management. Kahneman, D. (2013), Thinking Fast and Slow, Farrar, Straus and Giroux, New York. Köszegi, B. (2010), Utility from anticipation and personal equilibrium, Econ Theory (2010) 44, pp.415–444. Kruschwitz, J. D., Waller, L., List, D., Wisniewski, D., Ludwig, W. U., Korb, F., Wolfensteller, U., Goschke, T. and Walter, H. (2018), Anticipating the good and the bad: A study on the neural correlates of bivalent emotion anticipation and their malleability via attentional deployment Division of Mind and Brain Research, NeuroImage, 183: 553–564. Kuosa, T. (2010), Futures signals sense-making framework (FSSF): A start-up tool to analyse and categorise weak signals, wild cards, drivers, trends and other types of information, Futures, 42, pp. 42–48. Larson, Milan D. and Fowler, K. (2009), Anticipation is in the Eye of the Beholder: Top-Level Managers See Things Differently When It Comes to Crises Preparedness, Journal of Business and Management, 15 (2). pp. 129-141. Miller, R. (2018). Transforming the Future: Anticipation in the 21st Century, Routledge. Moore, D. J. and Lee, S. P. (2012), How Advertising Influences Consumption Impulses: The Role of Visualization, Anticipated Emotions, Taste Anticipation, and Hedonic Rationalization, Journal of Advertising, 41 (3), pp. 107–120. Murata, T. (2008), Constructing Future Higher Education Scenarios: Insights from Universiti Sains Malaysia. Compiled by Universiti Sains Malaysia, Penerbit (2007). 136 pp., ISBN: 987-983-861-328-6, Book reviews / Futures 40, pp. 689–697. Nadin, M. (2012). Anticipation across Disciplines, Springer. Osigweh, C. A. B. (1989), Concept Fallibility in Organizational Science, The Academy of Management Review, October, 14, 4, pp. 579- 594. Poli, R. (2017), Introduction to Anticipation Studies, Dordrecht:
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Springer. Porta, S. (1999), The community and public spaces: ecological thinking, mobility and social life in the open spaces of the city of the future, Futures, 31, pp. 437-456. Priester, Joseph R., Petty, Richard E. & Park, K. (2007), Whence Univalent Ambivalence? From The Anticipation of Conflicting Reactions, Journal Of Consumer Research, 34, June, pp. 11-21. Razak, Victoria M. (1996). From The Canvas to the Field: Envisioning the Future Of Culture, Futures, 28, 645-649. Reid, David M. and Zyglidopoulos, Stelios C. (2004), Causes and consequences of the lack of strategic foresight in the decisions of multinational enterprises to enter China, Futures, 36, pp. 237–252. Revet, S. and Langumier, J. (2015), “Introduction” in Governing disasters: beyond risk culture, Sandrine Revet and Julien Langumier (Eds.), pp. 1-20, Palgrave Macmillan: 1st Edition. Rious, V., Perez, Y. and Glachant, J. M. (2011), Power Transmission Network Investment as an Anticipation Problem, Review of Network Economics, 10 (4), pp. 1-21. Roget’s 21st Century Thesaurus, Third Edition, Copyright © (2013) by the Philip Lief Group. https://www.thesaurus.com/browse/anticipation (12.01.2019). Roget’s Thesaurus of English Words and Phrases (1979), Classic American Edition, Crown Publishers, Inc., USA. Rosen, R. (2012), Anticipatory Systems: Philosophical, Mathematical and Methodological Foundations, 2nd edition, NY: Springer. Rossel, P. (2012), Early detection, warnings, weak signals and seeds of change: A turbulent domain of futures studies, Futures, 44, pp. 229-239. Sanz, R., Hernandez, C. and Sanchez-Escribano, M. G. (2012), Consciousness, Action Selection, Meaning and Phenomenic Anticipation, International Journal of Machine Consciousness, 4 (2), pp. 383-399. Saritas, O. and Smith, J. E. (2011), The Big Picture – trends, drivers, wild cards, discontinuities and weak signals, Futures, 43, pp. 292-312. Schatzel, K. and Calantone, R. (2006). Creating Market Anticipation: An Exploratory Examination of the Effect of Preannouncement Behavior
63 ANTICIPATION on a New Product’s Launch Journal of the Academy of Marketing Science, 34 (3), pp. 357-366. Sebillotte, M. and Sebillotte, C. (2010), Foresight in mission-oriented research: The SYSPAHMM foresight method (SYStem, Processes, Clusters of Hypotheses, Micro- and Macroscenarios), Futures, 42, pp. 15-25. Slaughter, R.A. (2002), Beyond the mundane: reconciling breadth and depth in futures enquiry, Futures, 34, pp. 493–507. Smith, Christopher J. and Dubois, A. (2010), The ‘Wild Cards’ of European Futures: Planning for Discontinuities?, Futures, 42, pp. 846– 855. Soule, R. (1986) A Dictionary of English Synonyms, Omega Books, London. Tavory, I. and Eliasoph, N. (2013), Coordinating Futures: Toward a Theory of Anticipation, American Journal of Sociology, Vol. 118, No. 4, pp. 908-942. Textor, Robert B. (1995), The Ethnographic Futures Research Method: An Application to Thailand, Futures, 27 (4), pp. 461-471. The Advanced Learner’s Dictionary of Current English (2nd Edition) (1971), Oxford University Press, UK. Tognetti, Sylvia S. (1999), Science in a double-bind: Gregory Bateson and the origins of post-normal Science, Futures, 31, pp. 689–703. Tuğcu, A. K. (2019), Anticipation and Purpose (Chapter 1), Anticipation: Conceptual, Theoretical and Empirical Issues (Öner, M. A. and Tuğcu, A. K., Eds), Yeditepe University Press. Van de Ven, A. H. (1989), Nothing Is Quite so Practical as a Good Theory, The Academy of Management Review, October 14, 4, pp. 486- 489. Van der Heijden, K. (2004), Can internally generated futures accelerate organizational learning?, Futures, 36, pp. 145–159. Wilkins, W. (2001), The Art of Strategic Anticipation: Investing in Your Positive Futures, The Futurist, March-April, pp. 65-66.
64 3 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY
M. Atilla Öner, Senem Göl Beşer, Pınar Şenoğlu
“The only thing that makes life possible is permanent, intolerable uncertainty: not knowing what comes next.” – Ursula K. Le Guin, The Left Hand of Darkness
Abstract Anticipation science is arising as a new field of research and uncertainty is a natural inherent characteristic for the anticipation process. The purpose of this chapter is to review uncertainty for conceptual clarity. The inherently unknown character of the future leads us to study the unknown in three conceptual dimensions namely uncertainty, ambiguity and ignorance. A literature survey was conducted to clarify conceptual definitions of uncertainty. Results shown that there are discrepancies and overlaps between the definitions of these conceptual dimensions. Our study attempts to resolve the discrepancies and come up with a clear understanding of uncertainty which would be useful in anticipation systems studies.
Keywords – Uncertainty, anticipation, ambiguity, ignorance, design- based foresight, fuzziness, incompleteness
1. Introducing Uncertainty Anticipation- as a forward-looking attitude and the former’s result for action - has been widely studied in a number of different disciplines including futures studies which has been gaining momentum since it is
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“helping future practitioners to acquire a deeper understanding of social sciences and social scientists to better grasp the value of the experience accumulated by futurists” (Miller, Poli and Rossel, 2014). Tuomi (2013) distinguishes among forecasting, foresight and design-based foresight where the latter is grounded on the outcomes resulting from forecast and foresight models and aims at implementing them into decisions and actions, as well as being nonpredictive, qualitative and focus on discontinuity (Poli, 2017). Although research based on anticipation is undergoing development (Poli, 2014), it is crucial to understand the formal conceptual definitions of the abstract concept as well as the properties of the environment that is necessary for anticipatory action. The very abstract structure of anticipation imposes very severe constraints on the modelling of anticipation systems (Poli, 2010). Statistical analysis of causal characteristics and their measures cannot lead to a good measurement instrument, unless a concept is formally defined (Bollen, 1989). Not long ago, the dominant methods of how we think about and respond to ignorance (representing nonprobabilistic uncertainty) were to eliminate or absorb it, whilst the emerging frameworks now seem to have abandoned the assumption that ignorance is ultimately reducible, and the new style is “managerial” in the sense of attempting to understand, tolerate, even utilize certain kinds of ignorance (Smithson, 1988). Our attempt in this chapter is also in “understanding, tolerating and utilizing” the concept of uncertainty within anticipation systems where “anticipation is coupling between the system and its environment and anticipation as a cognitive projection (Poli, 2009). Cognitive projection in anticipation systems is also a representation of a paradigm shift in the concept of ignorance. This chapter also aims to contribute to the discussion on the theoretical and methodological background of uncertainty associated with futures studies – taking account of all major sectors in society along with socio-cultural, economic and technological trends – and will present a conceptual framework for communicating the process leading to decision-making under uncertainty - originating from ignorance - to the policy makers and corporations, as well as the third sector.
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For decades, researchers have sought an adequate definition of uncertainty and conceptualization of its development since it fills an important place as one of the most manageable kinds of ignorance. The study of uncertainty has not been confined to any single discipline but is being explored in fields as diverse as physics, economics, administrative science and management. The futurists are also the professionals who have challenged to deal with uncertainty. In an exhaustive review, which focused on this state of conceptual uncertainty in foresight, van Asselt (2005) commented: “... Foresight implies dealing with prognostic uncertainty, the notion ‘prognostic uncertainty’ refers to instances in which professional futurist have doubts about something in the future, partly or fully because (scientific) knowledge is perceived as absent, incomplete, irrelevant, insufficient, inaccurate, ambiguous, equivocal, inconsistent, fragmented, manipulated, complex or otherwise limited.” However, we need to construct an understanding of the future by examining the interactions between three notable human preoccupations that shape the future: imagination, anticipation and aspiration, where “we have not yet found ways to articulate how these three come together in the work of future making” (Appadurai, 2013). An anticipatory behavior is a behavior that uses the future in its actual decisional process (Rosen, 2012). Looking into the future is a complex and conflicting process of analyzing, experiencing, interpreting and absorbing uncertainties (Brown and Eisenhardt, 1997). All sources of uncertainty associated with the unfolding present and past must also be associated with futures studies. Facing up to the uncertainty environments, future studies aim to identify alternative futures and develop strategies to address these, to ensure the long-term survival of companies and societies. Distinguishing itself from utopia, foresight is taken to be a deliberate, critical, reflexive and creative forward-looking engagement with future, action-dependent states of affairs (Mendonça and Sapio, 2009). When futurists and foresight practitioners are asked to identify major challenges and trends ahead, the list tends to be long and complex including the dimensions of events, sectors, geographical
67 ANTICIPATION regions, eco-system breakdowns as well as power shifts (Öner, Kök, Başoğlu, 2007). Referring to technological futurism, in the early 1980’s ‘mighty micro’ had emerged from Silicon Valley whilst steering us towards enormous consequences of the information revolution; in the 90’s ‘information superhighway’, ‘cyberspace’ and ‘virtual reality’ became the decade’s popular themes along with “information labor’ cultivating education of the current epoch (Webster, 2000) – of which represents the 20 % of the workforce who are the organizers, coordinators, innovators, managers, plotters, designers and so forth in the ‘information age’ (Castels, 1996-97; cited in Webster, 2000). Referring to Marx and Engels’ (1848) statement of everlasting uncertainty, there is so much of complexity about how this environment represented is along with its consequences. Studies on the definitions of uncertainty have stated that the theoretical value of the research done is problematic. Perhaps the most alarming characteristic of the body of study of uncertainty is the abstractness of the concept or the instability that results from a lack of clarity on conceptual issue. Although there are several moderating factors that are so complex and uncertainty is prevailing in the minds of the people making them tend to behave “as though”, it is difficult to suggest a true or ideal set of states describing the future thoroughly. Thus, uncertainty could be defined as a “phenomenon that produces overlapping distributions of potential outcomes” (Alchian, 1950). This dilemma of uncertainty is particularly real for most of the contemporary environmental problems as well as issues within futures studies, because “…(1) the combination of circumstances may be so unique as to preclude formation of frequency estimates based on past (objective) observations; that is, only subjective probability statements can be made and (2) many of these… consequences [are produced] only after sufficient lags or cumulation of past discharges so that… knowing what state of nature has occurred or obtained is not a trivial exercise” (Conrad, 1973). On the other hand, the prediction of the outcomes of future events further away – whilst given the greater difficulty to develop images of
68 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY the future times as they are more distant from the present– should seem less probable and in general, personal events should be given higher probabilities of occurrence than external events (Milburn, 1978). Research also suggests that events with positive outcomes might be seen differently than events with negative outcomes, reflecting some wishful thinking. Another important area of future studies in the field of uncertainty (as well as anticipation systems) is the cone of uncertainty and possibilities elaborated by Hawking (1990) and Magnus (2012).
Figure 1. Cone of uncertainty and possibilities (Hawking, 1990; Magnus, 2012; Magruk, 2017)
According to Magnus (2012), the cone of uncertainty and possibilities is a model of all development roads in the future where it is conditioned by the resource of knowledge and information from the past and present. The model represents more probable future’s paths closer to the center where unrealistic paths are located on the outskirts of the cones. According to a completely deterministic system, if it would be known what was happening at a specific time at all points of the space area situated within the cone of the past, it could be a possibility to predict with a high probability what would happen in the future (Magruk, 2017). However, the events in the “elsewhere” cannot affect the future incident or the future incident cannot affect them. (Hawking, 1990).
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Knowing the fact that management has no choice but to anticipate the future under uncertainty and balance short- and long-range goals, we have structured the research on long-range planning considering a time span of 20 years and more; intermediate/medium range planning as 10 to 20 years, and finally short-range planning as 5 to 10 years (Kavrakoğlu, 1990). Attempting to clarify uncertainties is the most dominant issue in futures studies. In this chapter, we are apt to think about how we can use futures studies including the anticipation discipline and methodologies to help us make more informed choices and manage the process of change. By reference to an extensive literature review, the Chapter will first examine the nature and concept of uncertainty and then will outline a clear conceptual clarity for experiencing, interpreting and absorbing uncertainty in anticipation systems whilst building a platform for discussion on new forms of futures decision-making. After the introduction, the chapter is structured as examining, explaining and describing conceptual issues in uncertainty. Literature on the concept is given by looking at existing definitions and classifications of uncertainty along with the conflicting terms used with uncertainty. Section 3 looks at the importance of uncertainty in anticipation systems. Further research indicating possible contributory factors in the uncertainty context and emergence of new uncertainties are presented in section 4. Discussion and conclusion are presented in the final section.
2. Conceptual Issues in Uncertainty 2.1. Existing Definitions of Uncertainty A great deal centers on the definitional matters, otherwise it will be difficult for researches to develop the anticipation systems theory, define and test relationships between components of anticipation and develop a flow of research that builds on what has been done before. “Uncertain and ambiguous definitions of the same concept (in this particular example uncertainty in anticipation systems) can result in superficial differences but with potentially large consequences; and this is even more evident
70 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY when the concepts are frequently used as if the definitions were, in fact, unequivocal” (Strand, 1999). At least three strategies of definition are available (Smithson, 1988): 1. Positive or direct; 2. By reduction to some other concept(s); and 3. By negation or exclusion.
In our chapter, we have chosen to focus our attention on the reductionist strategy where it is usually “invoked when the framework to which probability is being reduced appears to have agreed-upon foundations.” As Osigweh (1989) states, “the more a conceptual definition excludes, the more precise it is and the more likely it will be unique”. The type of decisions people makes vary on how much knowledge or information they have about the issue and the environment. There are three decision-making environments; namely, decision making under uncertainty, under risk and under certainty depending on the assessment probabilities of each possible outcome/consequence (Heizer and Render, 2008). Rather than repeating comprehensive reviews of different approaches used to define uncertainty, we prefer to concentrate on interesting approaches for conceptual definitions in the study of uncertainty in decision-making. Definitions of uncertainty tend to rely on general explanations, using such terms, for example as “the absence of relevant information”, (Galbraith, 1977); “probability of outcome is unknown”, (Duncan, 1972); “the lack of information” and “the inability to predict the outcome of a specific decision made” (Tapinos, 2012). These definitions imply mentioning standard values about uncertainty, whereas a definition, especially, a conceptual definition should be clear, unique and useful for analytic purposes, and lead to inferences for determinants and impacts of any concept. Some of the literatures define uncertainty by explaining determinants and impacts of uncertainty. In the definition of uncertainty, Alchian (1950) says that uncertainty arises from at least two sources: imperfect
71 ANTICIPATION foresight and human inability to solve complex problems containing a host of variables even when an optimum is definable. In the light of Alchian’s view, we can evaluate imperfect foresight and human inability to solve complex problems as determinants of uncertainty. Under uncertainty, by definition, each action that may be chosen is identified with a distribution of potential outcomes, not with a unique outcome. As Newman (2006) stated, “we are faced with incredible uncertainty; not only are we unable to predict the consequences of events, we are unable to determine which events are the ones that will lead to future change.” Subjective risk on the other hand deals with the case in which there exists a probability distribution of anticipations which, however, is itself known with certainty (Tintner, 1941). Then again, subjective uncertainty assumes that there is an a priori probability of the probability distributions themselves (Tintner, 1941). Implicit in uncertainty is the consequence that these distributions of potential outcomes are overlapping (Alchian, 1950). Under uncertainty, selecting actions whose potential outcome distribution is preferable means choosing the action with the optimum distribution in decision-making. Although maximizing distribution is the main goal of decision-making, choosing the action under uncertainty with the optimum distribution is available. Choosing the action with the optimum distribution instead of maximizing distribution can be evaluated as the impact of uncertainty. During recent years, the quantum-like approach to modeling of cognition and decision-making under uncertainty has been progressively used in behavioral research which is rather surprising or problematic from classical perspectives (Bagarello et al., 2018). One of the main unique characteristics of this approach is to treat complementary decision-making problems inside the common model based on quantum probability (Bagarello et al., 2018). Quantum physics represents the ultimate measurement of uncertainty, in that the observer changes the object during the course of observation whilst predicting not a single consequence but rather a number of possible results all within a given range of predetermined levels of probability (Strand, 1999). Thus, it is impossible to interpret the state of a system without disturbing it.
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The complex systems defined in the 1990’s link uncertainty closely with complexity. Uncertainties are regarded as dangerous in chaos theory if disregarded and overlooked, “… thus, what we see is inevitably distorted, in some way and to some degree, in the process of seeing” (Thompson, 1995; cited in Strand, 1999). Erich Fromm (1947) went even further and declared that the quest for certainty not only restricts freedom1 but blocks the search for meaning; only uncertainty impels humanity to develop its full power.
2.1.1 Confusion between Terms Discussing theory building in foresight and futures studies, Öner (2010) stated that the unknown character of the futures introduces the study of uncertainty, ambiguity and ignorance as a possible research theme in foresight and anticipation in futures studies, possible with reference to different technologies. Risk and reliability studies have a long history of entailing two assumptions: uncertainty is either aleatoric or epistemic (Hacking, 1975). In order to examine uncertainty and establish a criterion for ignorance, absolute knowledge and epistemology is very crucial. Epistemic uncertainty is uncertainty associated with the knowledge of the state of a system and it includes uncertainty due to limitations of measurement devices, insufficient data, extrapolations and interpolations, and variability over temporal and spatial (Regan et al., 2002). The characterization and taxonomy of uncertainty is a pragmatic choice according to the purpose of a model, as well as the subjectivity in the selection of models. Der Kiureghian and Ditlevsen (2009) admit that from a linguistic point of view all uncertainties ‘are the same as lack of knowledge’ and they go on to state that the choice of model depends on context, application and convenience (Blockney, 2013). Linguistic uncertainty, on the other hand, arises because much of our natural language, including a great deal of our scientific vocabulary is under specific, ambiguous, vague, context dependent, or exhibits theoretical indeterminacies (Regan et al., 2002).
1 Freedom is a positively valued version of uncertainty in conventional terms (Smithson, 1988).
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As Corotis (2009) puts it ‘The world is less precise than our models, even our probability ones … advances … require bridging the gap … between theory and uncertainty measures’. Models may be based on diagrams, flow charts, mathematical representations, computer simulations however, in this study we use conceptual definitional tools to assist us in understanding the concept of uncertainty. Conceptual modeling is a mental model of the suspected relationships which may be evaluated by means of a framework (Meredith et al., 1989). This chapter will be analyzing only three conceptual models in depth with their attributes, definitions, as well as taxonomies and categorizations. It is essential to point out that in this chapter we neither claim that all uncertainty can be neatly and easily classified into three nor that the categories presented here are the only ones possible.
2.1.1.1 Conceptual Modeling I The complete taxonomy of ignorance in Figure 1 drawn by Smithson (1988) is taken as a viable framework to manifest uncertainty. Uncertainty occupies a special position as one of the most manageable kinds of ignorance where it is also one of the continuous parts of the human condition. In some fields, the term is employed as a synonym for ignorance. It should be clear by now, however, that uncertainty is not as broad a concept, even though it is the home of probability theory and several other newer normative approaches to ignorance (Smithson, 1988).
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Figure 2: Taxonomy of Ignorance (Smithson, 1988)
According to the taxonomy of ignorance displayed by Smithson (1988), ignorance is usually considered as “either the absence or the distortion of ‘true’ knowledge -- a loss of consensus concerning fundamental criteria of truth”, and as some form of incompleteness in information or knowledge. However, almost all Western culture lead us to reduce uncertainty or ignorance before making any decision or taking any action. As Smithson (1988) underlines it, if modern Western culture is undergoing a transformation of its methods for dealing with ignorance, then uncertainty and risk are the foci of that transformation. The last 60 years have witnessed a wind of new perspectives on uncertainty as well as ignorance, whose magnitude perhaps eclipses by the emergence of modern probability theory. Probability theory is normally interpreted in four main ways; as statistics of frequencies or tendencies, and as degrees of belief or measures of evidence (Blockley,
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2013). They are generated for the purposes of dealing with uncertainty or ignorance where uncertainty dominates a special position as one of the “most manageable kinds of ignorance “and in some fields is employed as a synonym for ignorance. Probability theory grips only certain special kinds of uncertainty while expelling vagueness, ambiguity, sheer absence of information, distortion, and irrelevance. However, the past 40 years alone have seen several nonprobabilistic formalisms proposed for dealing with uncertainty, surprise, doubt, fuzziness, vagueness and possibility (Smithson, 1988). On the other hand, modern probability theory has arisen in several fields but mostly in those concerned with the interactions between people and modern complex technologies as well as all people’s observed behavior2. Ignorance is used by many theoreticians (Hacking, 1975; Huber, 2010) to express the idea of unknown; unknown is unfortunate. In a practical context, it can imply negligence as a lack of learning, being uneducated or uninformed or not properly qualified and thus not exercising a proper duty or care (Blockley, 2013). As Smithson (1988) puts it “ignorance like knowledge, is socially constructed and negotiated” and has multiple/ distinct levels. However, in pointing out the differences between error and ignorance, Sokrates (in his dialog with Meno) uttered that “the person in error believes he knows that he doesn’t know while the ignoramus is conscious of his lack of knowledge.” Smithson (1985) prefers to rename “the error” defined by Socrates as conscious ignorance and the latter as meta-ignorance where it requires some person’s viewpoint to exist as a social construct. Incompleteness has received considerable attention from philosophers and scholars since it is more amendable than distortion. The taxonomy displays incompleteness in kind being termed as absence while incompleteness in degree be called as uncertainty. Uncertainty to be considered as modern accounts of ignorance includes concepts as probability, vagueness, ambiguity, fuzziness and nonspecificity.
2 Walley (1991) argues that it may never be possible to completely formalize real decision-making because intelligence, intuition, experience and judgement required cannot be captured.
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2.1.1.2. Conceptual Modeling II Our second model provides a schematic illustration of the relationship between formal definitions for the concepts of risk,uncertainty , ambiguity and ignorance where uncertainty applies to a condition under which there is confidence in the completeness of the defined set of outcomes, but where there is acknowledged to exist no valid theoretical or empirical basis confidently to assign probabilities to these outcomes.
KNOWLEDGE ABOUT OUTCOMES Knowledge About continuum of Set of discrete Outcomes Likelihods outcomes outcomes Poorly defined
INCERTITUDE
RISK
firm basis for apply: probabilities frequentist discrete AMBIGUITY distribution frequentist functions probabilities
Shaky Bayesian discrete apply: basis for distribution Bayesian probabilities functions Probabilities fuzzy logic sensitivity analysis
UNCERTAINTY IGNORANCE no basis for probabilities apply: scenario analysis apply: precaution
Figure 3: The formal definition of risk, uncertainty, ambiguity and ignorance (Stirling, 2001)
It is quite normal even in specialist discussions for the full breadth and depth of these issues to be condensed in the simple concepts of ‘risk’
77 ANTICIPATION or ‘uncertainty’; thus, seriously understating the difficulties involved. To avoid confusion between strict definitions of the terms risk and uncertainty, and looser non-literary usages, the term ‘incertitude’ can be used in a broad embracing sense to include all four subordinate conditions. Here ‘risk’ is, by definition, a condition under which it is possible both to define a comprehensive set of all possible outcomes and to resolve a discrete set of probabilities (or a density function) across this array of possibilities, illustrated in the top left-hand corner ofFigure 3. One of the problems in the scientific foundations of probability and rational choice theory is the ‘incommensurability’ (comparing apples and oranges) and ‘ignorance’ since “we do not know what we do not know”. Another fundamental problem underlying the social appraisal of technological risks concerns with incomplete information; however, risk is a domain under which the various techniques of risk assessment are applicable, permitting full characterization and ordering of the different options under appraisal. According to Stirling (2001), there are a host of details relating to this model such as those hinging on the distinction between ‘frequentist’ and ‘Bayesian’ understandings of probability, but none of these alter the fundamental definition of the concept of risk. Even were there to be complete certainty in the quantification of all the various classes and dimensions of risk, it is entirely reasonable that fundamentally different conclusions over environmental risk might be drawn under different but equally legitimate perspectives since different cultural groups, political constituencies or economic interests attach different degrees of importance to the different aspects of technological risk. The strict sense of the term uncertainty, by contrast, applies to a condition under which there is confidence in the completeness of the defined set of outcomes, but where there is no acknowledged and valid theoretical or empirical basis to confidently assign probabilities to the outcomes found in the lower left-hand corner ofFigure 3. Here, the analytical set is less well developed, with the various sorts of sensitivity and scenario analysis being the best that can usually be implemented
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(Funtowicz and Ravez, 1990). The different options under appraisal may still be broadly characterized but they cannot be ranked even in ordinal terms without some knowledge of the relative likelihoods of the different outcomes (Stirling, 2001). According to the model of Stirling (2001), both risk and uncertainty, in the strict senses of the terms, require that the different possible outcomes be clearly stable or measurable. This is often not the case, the complexity and scope of the different forms of environmental risk and the different ways of framing and prioritizing these, can all, too-easily render the definitive characterization of outcomes ambiguous (aka. poorly defined outcomes). Where these problems are combined with the difficulties in applying the concept of probability, we face a condition which is formally defined as ignorance. Ignorance applies in circumstances where there not only exists no basis for the assigning of probabilities (as under uncertainty), but where the definition of a complete set of outcomes is also problematic. Ignorance can operate as a factor dynamic to social change (Moore, Tumin, 1949). Therefore, recognition of the condition of ignorance is an acknowledgement of the possibility of surprise. Under such circumstances, not only is it impossible to rank the different options definitively, but even their full characterization is difficult. Under a state of ignorance, it is always possible that there are outcomes which have been entirely excluded from consideration. It is not difficult to see that it is the formal concepts of ignorance and strict uncertainty (rather than risk) which best describe the salient features of risk governance (and futures studies). Some of the main technologically induced ‘risks’ of our time are all cases where the problem lay not so much in the determination of likelihoods, but in the anticipation of the very possibilities themselves. In the energy sector, imponderables such as those associated with global climate change, geological diffusion models for high level radioactive waste repositories and even the long-term effects of major dependencies on renewables like biomass are all as much matters of ignorance and uncertainty as they are of risk in the strict sense. Even
79 ANTICIPATION where there is some confidence over the broad likelihood of an overall phenomenon like global climate change, there are still crucial questions over the implications for any specific region or human activity, invoking the formal condition of ‘ambiguity’ (in the top right corner of Figure 3). The curious thing is that these and other sources of intractable uncertainty and ignorance are routinely treated in the appraisal of technology by using the probabilistic techniques of risk-assessment. Given the inapplicability of probabilistic techniques under conditions of uncertainty and ignorance, this is a serious and remarkable error. For all the seductive elegance and facility of probabilistic calculus, it remains the case that judgements concerning the extent to which “we do not know what we do not know”, no matter how well informed, are ultimately and unavoidably qualitative and subjective. The treatment of uncertainty and ignorance as if they were mere risk effectively amounts to the “presence at knowledge3’’. Far from displaying a respect for science in technology appraisal, the effect of such scientific oversimplification is actually to ignore and undermine scientific principles. In a plural society, a unitary ‘sound scientific’ basis for the governance of technological risk is a fundamental contradiction in terms and considering the risk assessment and cost analysis benefit analysis, serious questions arise over whether the results of such risk-based methodologies are of much practical policy use at all.
2.1.1.3. Conceptual Modeling III Uncertainty was also classified using three conceptually distinctive and orthogonal separate attributes (Fig. 4): fuzziness, incompleteness and randomness (FIR) by Blockley and Godfrey (2000), contrasting definitions in natural languages with those of former languages. Other characteristics of uncertainty such as ambiguity, confusion, contingency, indeterminacy and conflict emerge from mixes and interactions between these basic tree attributes as they are interpreted in any real-world context.
3 von Hayek (1978).
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Figure 4: Some interpretations in the FIR space of uncertainty (Blockley, 2013)
Der Kiureghian and Ditlevsen (2009) remark that aleatoric uncertainty is intrinsic, irreducible and seen as objective since it does not depend on an observer whilst epistemic uncertainty is subjective, personal and can be reduced by using auxiliary non-physical variables. However, the aleatoric/epistemic classification is not rich enough for practical decision making (Blockley, 2013). Blockley (2013) has considered aleatory, random and stochastic processes as equivalent, since aleatoric means dependent on chance or accidental events or other contingencies. He goes on to state that it is insufficient for capturing the nuances in the meaning of uncertainty since all uncertainties are due to limitations in what we know or the conditions for acquiring or understanding, thus claiming all uncertainty is knowledge-based. In an age of complexity, understanding the complex interconnectedness and interdependence of natural and man-made systems requires the
81 ANTICIPATION acknowledgement of vagueness and imprecision in situations where we genuinely ’don’t know’ or are unsure Blockley, 2013). Figure 4 illustrates previous claims that other characteristics of uncertainty such as ambiguity, confusion, contingency, indeterminacy and conflict emerge from mixes and interactions between these basic three attributes as they are interpreted in any real-world context: thus, requiring clear definitions of fuzziness, incompleteness, randomness and their relationships with aleatoric and epistemic uncertainty (Blockley, 2013). Zadeh (1973) stated that “complex systems cannot be dealt with effectively by the use of conventional approaches largely because the description languages based on classical mathematics are not sufficiently expressive to serve as a means of characterization on input-output relations in an environment of imprecision, uncertainty, and incompleteness of information.” This statement highlights the difficulty of making precise and significant statements about a system’s behavior as the complexity of the system increases. Zadeh (1996) was also aware of the fact that complex systems cannot be dealt with effectively using conventional approaches due to the description languages based on classical mathematics as means of characterization on input-output relations in an environment of imprecision, uncertainty, and incompleteness of information. Therefore, fuzziness is not modelled mathematically as in the theory of fuzzy sets and fuzzy logic which are based on approximate reasoning. According to the classification of Blockley (2013), incompleteness was handled as the most neglected or denied characteristic of epistemic uncertainty since the probabilities of events or statement in the sample space must be known, identified and added to unity. As the third characteristics of uncertainty, randomness is interpreted as the “lack of a specific pattern or purpose in some data which is explicit in probability theory and its derivatives such as reliability theory.” Since those theories address only one aspect of uncertainty (randomness), it is difficult to include epistemic uncertainty in models of physical phenomena (Blockley, 2013). Ambiguity is defined as “a measure of the organization’s ignorance of whether a variable exists” (Zhang and Doll, 2001). It emerges from
82 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY interacting fuzziness and incompleteness that gives rise to a potential for more than one interpretation of the meaning of a statement whilst erratic uncertainty can happen when all three parameters of uncertainty occur simultaneously where the interpretations are deviating, wandering and not fixed (Blockley, 2013). In summary of the mapping from the FIR model of Blockney (2013), an expression or conceptual interpretation of a term within the interval probability measure of a region in the space of the model can be associated as uncertain within variously fuzzy, incomplete or random. Fig. 3 reveals one set of possible mixes of uncertainty in natural languages where the meaning of each word will depend on interpretation of the region of the fuzziness, incompleteness and randomness mix. While manifesting uncertainty, the assessment of futures’ decisions based on different courses of present actions and investments is the real deal. These actions/decisions may translate into possible, probable, preferred, and prospective futures (Saritas and Öner, 2004; Öner et al., 2013). Attention on the attitudes toward risk displayed by individuals, and upon the social evaluation of long-term, uncertain, and irreversible actions must be given, as the expected social value of proposed activities must also reflect the uncertainty of future effects and future tastes (Haveman, 1977). We need to study the characteristics of long-term plans/actions as they are more descriptive and qualitative than highly structured and quantitative (Jönsson, 1970).
3. The Importance of Uncertainty in Anticipation Systems Anticipation helps to develop more sophisticated courses of action and is required for understanding much individual and social behavior, as well as a feature characterizing the behavior of suitable-defined, complex systems (Poli, 2017). Whilst understanding anticipation, uncertainty is one of the most essential features of many areas of social and economic disciplines especially in future studies. Mainstream economics, particularly formal economic modelling, continues to neglect the significance of uncertainty for the understanding of economic systems, where many forms of uncertainty compete for attention in the literature
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(Lawson, 1994). On one hand, the degree of uncertainty is associated with the objective essence of randomness of a given phenomenon, and on the other, with subjective perspectives as the future orientation of human activities are burdened with an incomplete specificity, volatility and lack of continuity of the analyzed phenomena (Magruk, 2017). Regardless of whether we choose to view uncertainty as good or not, it is important to endeavor in answering the relationship between anticipation and the studies of uncertainty. Although in some cases, consideration of even a subset of the full spectrum of uncertainty has been weakening (Beissinger and Westphal, 1998), there has been no comprehensive evaluation of the importance of the full spectrum of uncertainties on decision- making processes (Regan et al., 2002). Strand (1999) for example, referred to the difficulty of having a model with substance by asking questions like: “Do decision makers decline certainty? Or when “muddling through” solutions good enough and best solutions in view of the costs involved in reducing uncertainties below a certain level?” Stirling (2001) has put this as a fundamental problem with a concern of incomplete information. Uncertainty is inherent in any decision since the essential feature of the decision-making process is the orientation towards the future, which is inherently uncertain (Dziel, 2011). Haveman (1977) also studied uncertainty as a factor in assessing future costs or benefits while reviewing its treatment in the economics literature since with an economic change dominated with technological developments, the decisions of both private sector households and companies and the public sector have consequences which extend into the distant future. Therefore, Haveman (1977) makes an adjustment for uncertainty in the anticipation of the results of an action which has long term effects. To isolate the issue of uncertainty and long-term effect, he noted that numerous circumstances exist requiring a premium be added to the expected value of future damages, as well as a discount subtracted from the expected value of future benefits in calculating the social value of proposed activities. Uncertainty adjustments are required under the following circumstances:
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1. the presence and degree of risk aversion4 among the population affected by a proposed activity; 2. the extent to which the effects of the activity are irreversible, in which case an option value5 is created; 3. the economic attributes of the expected effects, in terms of their public- or private-good character and, in the latter case, the number of people affected; 4. the extent to which the expected effects arecorrelated with other economic activities; 5. the extent to which information on the effect of activities is expected to improve over time because of learning from experience; and 6. the extent to which it is anticipated that tastes with regard to environmental questions will be altered over time (intergenerational taste change).
Haveman (1977) discusses the latter as the issue of uncertainty relating to the matter of intergenerational preferences in evaluating impacts which extend over several decades. As a summary, looking at Table 1, where the combinations are indicated, it is important to consider the major fundamental changes and discontinuities that carry irreversible negative effects. Haveman (1977) suggested that the cumulated adjustment for uncertainty in these cases implies a need for substantial caution in appraising requests for the commitment of additional social resources to these activities.
4 The attitudes toward risk and uncertainty are crucial and often considered in discussion of risk and uncertainty: risk neutrality (in which uncertainty attached to an event does not affect how an individual appraises the event) and risk aversion (in which uncertainty attached to an event leads an individual to appraise its worth at less than its mathematical expectation (Haveman, 1977). 5 When individuals are uncertain about their future used of a facility (or when the supply of the facility is uncertain), if an adverse impact on the facility is irreversible, and if the individuals are risk averse, and extra cost-called option value- must be added to the expected value of future damages (Haveman, 1977).
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Table 1. Evaluations of Benefits or Costs Requiring Uncertainty Adjustments
Lowenstain and colleagues (2001) have proposed a useful distinction between anticipatory emotions and anticipated emotions regarding decisions where anticipatory emotions are the immediate visceral responses (for example anxiety, fear and excitement) to uncertainties, whereas anticipated emotions (for example regret and rejoicing) are those expected to be experienced because of decisional outcomes. Accounts of how people perceive and respond to uncertainty may not be provided in many disciplines but psychology. As a part of the psychological question: “we do not think we are uncertain, we also feel uncertain” (Smithson, 2008) which is contradictory to Schumpeter (1954): “it has a much better claim to being called a logic of choice than a psychology of value.” Thus, the notion of uncertainty questions the optimizing assumption itself since the question is about how actors reduce uncertainty and stabilize highly dependent and interactive situations (Dequech, 2003).
4. Further Research 4.1 Possible Contributory Factors in an Uncertainty Context The high speed of change in the socio-cultural, economic, political and technological areas and high complexity of contemporary business world led to an increasing need to cope with these changes and the
86 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY accompanying uncertainty to enhance quality of life (Magruk 2017). Human strategies for managing under uncertainty are typically oriented towards the issues of how uncertainty can be (Smithson, 2008): i. Understood ii. Represented, quantified or estimated, and communicated; iii. Eliminated or reduced; iv. Accepted or tolerated; and v. Controlled, harnessed or exploited.
Several research efforts aim to contribute to advancement in this field. Factors contributing to ontologicaluncertainty are described under the headings of gender-based, personality-based, culture-based6 and experience-based differences (Fox, 2011). Göl (2008) studied the effects of femininity/masculinity, happiness, and space/time perspectives of individuals on assessment of mega-trends and corporate foresight projects. She defined some indices for describing bow a human’s decisions or anticipation behavior changes. Although these indices might bring different approaches, perspectives and priorities to foresight studies under uncertainty, further research needs to be carried on organizational and/or cultural orientation towards future. Even more importantly, the research results also supported that there was a relation- ship between the future orientation and happiness index of individuals. Milburn (1978) also suggested the optimism effect should also be considered as a contributing factor with groups of greater background differences since when one feels that things are bound to get better later, no urgent pressure is felt to plan for problems which might occur later.
4.2. Measurability Issues As we can see, the description of uncertainty is more difficult than its analysis. However, the most popular cultivating strategy is the quantification of uncertainty and imposition of a logical calculus for
6 The driving force of uncertainty might not be as powerful in countries where the tendency to avoid uncertainty is lower (e.g. Scandinavian countries, Minkov and Hofstede, 2014).
87 ANTICIPATION manipulating those quantities (Smithson, 1988) There is a strong impulse towards unification on establishing normative criteria and justification that prefer one measure over others; however, in terms of typology given in Model 1, the normative formal paradigms have moved not only into vagueness, nonspecificity, and ambiguity, but also unreliability, undecideability, distortion and conflict of opinion (Smithson, 1988). Uncertainty following the complexity of the studied phenomena creates a space, which one can determine the boundaries of computability (Magruk, 2017). Fuzzy set and possibility theory (as well as multi- attribute theory) have exhibited an ambivalence toward quantification; however, more qualitative approaches have come from three concepts concerning mundane reasoning under uncertainty: endorsements7, defaults8 and circumscription9 (Smithson, 1988). Moreover, there is the problem of future usage of theoretical terms that are not completely well defined and agreed upon by past usage. For example, some of our theoretical terms, although not uncertain now, have the potential for uncertainty. In summary, changes in the conception and quantification ofuncertainty have resulted in the emergence of new uncertainty management strategies to aid decision makers in the presence of high levels of uncertainty. Improved uncertainty assessment in turn would contribute to the improved decision making.
7 Cohen (1985) and Cohen and Grinberg (1983) propose that the strength of a belief and the adequacy of its evidence may be represented by the reasons for believing and disbelieving them, which they term endorsements. 8 Reiter (1980) advocates the use of defaults as a method for managing incompleteness where he claims default rules are akin to meta-rules insofar as they instruct us in how to extend an incomplete theory or knowledge base so that we may act. 9 Circumscription involves explicitly stating rules for eliminating possibilities on the basis of relevancy (McCarthy, 1980).
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5. Conclusion
“The only certainty for the future, we are assured, is that it will be very different from today.” Frank Webster, 2000
This chapter is an attempt at clarifying uncertainty in anticipation among with conceptual models and help users assess the risks and opportunities which they face while making futures’ decisions. Now we will state our final conceptual remarks based upon some areas of the social science discipline and their relationship with the issue of uncertainty: In the works of Marx and Engels (1848) – referring to the Marxist economic theory – accumulation and annihilation of wealth under capitalism has “undoubtedly exacerbated widespread feelings of apprehension and uncertainty” (Webster, 2000) in the society. Consumers - the single most powerful driving force in this economic system- who use information far more intensively to meet their economic needs are creating considerable uncertainty in the marketplace along with technological innovations, digitization, unfettered capital markets and globalization (Shaw, 2002). According to Smithson (1988), the modern impulse with regard to uncertainty (if not all other kinds of ignorance) is managerial rather than exclusionary where much of the contemporary debate over uncertainty concerns how far the managerial impulse should or can be extended and what other kinds of ignorance must still be excluded from normative theories. Depending on the level and nature of the uncertainty a company faces, shapers attempt to get ahead of uncertainty by driving industry change their way whilst adapters, take existing and future industry structure and conduct as given and attempt to win through speed and agility; i.e., some adapters manage uncertainty by building flexible organizations designed to respond to changing market needs (Shaw, 2002). Thus, companies must reinvent their strategic-planning processes to include such tools
89 ANTICIPATION as scenario planning and game theory if they wish to be successful shapers (Shaw, 2002). However, when it comes to managing and steering uncertainty, very interesting and important questions arise: i. Is there one method capable of dealing with all sources of uncertainty? i. How do we think about and respond to uncertainty during the decision-making process? ii. Is there any paradigmatic shift within the taxonomy of uncertainty? Since every paradigm includes and transcends the previous, how revolutionary are the new ones? iii. What are the developments in measurement of uncertainty in decision making within anticipation systems?
To realize the possible significance of uncertainty in terms of explaining social systems, Knight (1913b) states that “Human organisms are subjects as well as objects and the limits to their objectification are limits to their conformity to fixed laws. Whether an enormous complex and unstable organization of atoms which individually obey these laws … can theoretically account for the phenomenal uncertainty of organic and human behavior … must probably remain an open question (Knight 1913b: 50; cited in Nash 2003)”. Thus, a final emphasis on the concept of uncertainty must also be placed on multidisciplinary practice whilst considering the challenge of predicting human behavior and future society’s values. As Magruk (2017) puts it, “the logic of human behavior involves actual indefineteness, real change, and lack of continuity.” There is difference between intuitive judgements under uncertainty and the normative theory of subjective probability. As Tversky and Kahneman (1980) put it, “people have several different ways of thinking about probability, and their approach to the combination of probabilistic data depends on the manner in which those data are interpreted. This difference presents a major educational challenge: to help people achieve a synthesis between their natural modes of judgment and the logic of probability (Tversky and Kahneman 1980)”. Accepting uncertainty is not enough, we should also act on it. To conclude, uncertainties are dangerous only if they are overlooked,
90 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY because they are there, and always so: “thus, what we see is inevitably distorted, in some way and to some degree, in the process of seeing” (Cartwright, 1991; cited in Strand 1999). At present, we have several definitions of uncertainty where the greater and more complex areas of reality is inspected. According to the authors, the goal established in this chapter has been achieved by presenting the relationship between anticipation research and the uncertainty phenomenon.
References Alchian, A. A. (1950). Uncertainty, evolution, and economic theory. The Journal of Political Economy, 58 (3), 211-221. Appadurai, A. (2013). The future as cultural fact. London: Verso. Asselt, M. B. (2005). The complex significance of uncertainty in a risk era: logic, manner and strategies in use. International Journal of Risk Assessment and Management, 5 (2- 4), 125-158. Bagarello, F., Basieva, I., & Khrennikov, A. (2018). Quantum field inspired model of decision making: Asymptotic stabilization of belief state via interaction with surrounding mental environment. Journal of Mathematical Psychology, 82, 159-168. Beissinger, S. R., & Westphal, M. I. (1998). On the use of demographic models of population viability in endangered species management. The Journal of wildlife management, 821-841. Blockley, D. I., & Godfrey, P. (2000). Doing it differently: Systems for rethinking construction. Thomas Telford. Blockley, D. (2013). Analysing uncertainties: towards comparing bayesian and interval probabilities. Mechanical systems and signal processing, 37, 30-42. Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303-316. Brown, S. L., & Eisenhardt, K. M. (1997). The art of continuous change: linking complexity theory and time-paced evolution in relentlessly shifting organizations.Administrative Science Quarterly, 42 (1), 1-34. Cohen, P. R., & Grinberg, M. R. (1983, August). A Framework for Heuristic
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Reasoning About Uncertainty. In IJCAI (pp. 355-357). Cohen, S. (1985). Visions of social control: Crime, punishment and classification (pp. 127-143). Cambridge: Polity Press. Corotis, R. B. (2009). Risk communication with generalized uncertainty and linguistics. Structural Safety, 31(2), 113-117. Conrad, J., (1973). Uncertain Externality: The Case of Oil Pollution, unpublished PhD dissertation, University of Wisconsin-Madison. Dequech, D. (2003). Uncertainty and economic sociology: a preliminary discussion. American Journal of Economics and Sociology, 62(3), 509-532. Der Kiureghian, A., & Ditlevsen, O. (2009). Aleatory or epistemic? Does it matter? Structural Safety, 31(2), 105-112. Dziel, E. (2011). Niepewność i ryzyko w działalności gospodarczej. Periodyk Naukowy Akademii Polonijnej, 1(5), 135-144. Duncan, R. B. (1972). Characteristics of organizational environment and perceived environmental uncertainty. Administrative Science Quarterly, 17(3), 313-327. Fromm, E. (1947). Man for Himself: An Inquiry Into Psychology of Ethica. Holt, Rinehart and Winston. Fox, S. (2011). Factors in ontological uncertainty related to ICT innovations. International Journal of Managing Projects in Business, 4(1): 137-149. Funtowicz, S. O., & Ravetz, J. R. (1990). Uncertainty and quality in science for policy (Vol. 15). Springer Science & Business Media. Galbraith, J. (1977). Organization design. Reading: Addison Wesley. Göl, S. 2008. An Exploratory Study on the Effects of Femininity/ Masculinity, Happiness, Space/Time Perspectives of Individuals on Assessment of Megatrends and Corporate Foresight Project Results, unpublished PhD thesis, Yeditepe University, Graduate Institute of Social Sciences. Hacking, I. (1975), The emergence of probability, Cambridge University Press, Cambridge. Haveman, R. H., (1977). The economic evaluation of longrun uncertainties. Futures,9 (5), 365-374. Hawking, S. W. (1990). Krótka historia czasu. Od wielkiego wybuchu
92 UNCERTAINTY IN ANTICIPATION: TOWARD CONCEPTUAL CLARITY do czarnych dziur [A Brief Story of Time from the Big Bang to Black Holes]. Alfa, Warsaw. Heizer, J., & Render, B. (2008). Decision-making tools.. India: Pearson. Huber, W. A. (2010). Ignorance is not probability. Risk Analysis: An International Journal, 30(3), 371-376. John Nash, S. (2003). On pragmatic philosophy and Knightian uncertainty. Review of Social Economy, 61(2), 251-272. Jönsson, S. A., Lundin, R. A., & Sjöberg, L. (1977). Frustration in decision processes: a tentative frame of reference. International Studies of Management & Organization, 7(3/4), 6-19. Kavrakoğlu, İ. (1990). Dengeli gelişme için ekonomi politikaları. İstanbul: Boğaziçi Üniversitesi. Lawson, T. (1994). The nature of Post Keynesianism and its links to other traditions: A realist perspective. Journal of Post Keynesian Economics, 16, 503–538. Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, N. (2001). Risk as feelings. Psychological bulletin, 127(2), 267. Magruk, A. (2017). Concept of uncertainty in relation to the foresight research. Engineering Management in Production and Services, 9 (1), 46- 55. Magnus, S. (2012). The Adventure Future. Retrieved fromhttps:// adventurefuture.wordpress.com. Marx, K., & Engels, F. (1848). Manifesto ofthe Communist party. The Marx-Engels Reader, 469-500. McCarthy, J. (1980). Circumscription—a form of non-monotonic reasoning. Artificial intelligence, 13(1-2), 27-39. Mendonça, S., & Sapio, B. (2009). Managing foresight in changing organizational settings introducing new perspectives and practices. Technology Analysis and Strategic Management, 21 (3), 285-289. Meredith, J. R., Raturi, A., Amoako‐Gyampah, K., & Kaplan, B. (1989). Alternative research paradigms in operations. Journal of operations management, 8(4), 297-326. Milburn, M. A. (1978). Sources of bias in the prediction of future events.
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Organizational Behavior and Human Performance, 21(1), 17-26. Miller, R., Poli, R., & Rossel, P. (2014). 2 The Discipline of Anticipation. Transforming the Future, 51. Minkov, M., & Hofstede, G. (2014). Clustering of 316 European regions on measures of values: do Europe’s countries have national cultures?. Cross-Cultural Research, 48(2), 144-176. Moore, W. E., & Tumin, M. M. (1949). Some social functions of ignorance. American Sociological Review, 14(6), 787-795. Newman, L. (2006). Change, uncertainty, and futures of sustainable development. Futures, 38, 633-637. Oner, M. A., Basoglu, A. N., & Kok, M. S. (2007). Megatrends as perceived in Turkey in comparison to Austria and Germany. Technological Forecasting and Social Change, 74(4), 538-557. Öner. (2010). On theory building in foresight and futures studies: a discussion note. Futures, 42 (9), 1019-1030. Öner, M.A., Karaca, F., Göl Beşer, S., Yıldırmaz, H. 2013. Comparison of Nanotechnology Acceptance in Turkey and Switzerland, International Journal of Innovation and Technology Management, 10(2). Osigweh, C. A. (1989). Concept fallibility in organizational science. Academy of Management Review, 579-594. Poli, R. (2009). The complexity of anticipation.Balkan journal of philosophy, 1(1), 19-29. Poli, R. (2010). The many aspects of anticipation. Foresight, 12(3), 7-17. Poli, R. (2014). Anticipation: what about turning the human and social sciences upside down?. Futures, 64, 15-18. Poli, R. (2017). Introducing anticipation. Handbook of Anticipation: Theoretical and Applied Aspects of the Use of Future in Decision Making, 1-14. Regan, Colyvan, & Burgman. (2002). A taxonomy and treartment of uncertainty for ecology and conservation biology. ecoılogical applications, 12 (2), 618-628. Reiter, R. (1980). A logic for default reasoning. Artificial intelligence, 13(1-2), 81-132.
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Rosen, R. (2012). Anticipatory systems. In Anticipatory systems (pp. 313-370). Springer, New York, NY. Saritas, O., & Oner, M. A. (2004). Systemic analysis of UK foresight results: joint application of integrated management model and roadmapping. Technological Forecasting and Social Change, 71(1-2), 27- 65. Schumpeter, J. A. (1954). History of economic analysis, ed. EB Schumpeter. London. Shaw, F. (2002). Uncertainty and the new consumer. Foresight, 4(6), 4-13. Smithson, M. (1985). Toward a social theory of ignorance. Journal for the theory of social behaviour. Smithson, M. (1988). Ignorance and Uncertainty, New York: Springer- Verlag. Smithson, M. (2008). Uncertainty and risk: multidisciplinary perspectives London: Earthscan. Stirling, A. (2001). Science and precaution in the appraisal of electricity supply options. Journal of hazardous materials, 86(1), 55-75. Strand, S. (1999). Forecasting the future: pitfalls in controlling for uncertainty. Futures, 333-350. Tapinos, E. (2012). Perceived environmental uncertainty in scenario planning. Futures, 31, 338-345. Tintner, G. (1941). The Theory of Choice under Subjective Risk and Uncertainty.Economterica, 9 (3/4), 298-304. Tuomi, I. (2013). Next-generation foresight in anticipatory organizations. Paper presented at the European Forum on Forward-Looking Activities (EFFLA). European Commision. Tversky, A., & Kahneman, D. (1980). Causal schemas in judgments under uncertainty. Progress in social psychology, 1, 49-72. Van Asselt, M. B. (2005). The complex significance of uncertainty in a risk era: logics, manners and strategies in use. International Journal of Risk Assessment and Management, 5(2-4), 125-158.
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Von Hayek, F.A. (1978), “The presence of knowledge”, in von Hayek, F.A. (Ed.), New Studies in Philosophy, Politics, Economics and the History of Ideas, Routledge & Kegan Paul, London, pp. 23‐34. Walley, P. (1991). Statistical reasoning with imprecise probabilities. 1991. Webster, F. (2000). Information, capitalism and uncertainty. Information, Communication & Society, 3(1), 69-90. Zadeh, L. A. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on systems, Man, and Cybernetics, (1), 28-44. Zadeh, L. A., Klir, G. J., & Yuan, B. (1996). Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers (Vol. 6). World Scientific. Zhang, Q., & Doll, W. J. (2001). The fuzzy front end and success of new product development: a causal model. European Journal of Innovation Management, 4(2), 95-112.
96 4 PSYCHOLOGY AND PHYSIOLOGY OF ANTICIPATION
Sara Saban
Introduction This Chapter establishes the connection between anticipation/ decision-making, its underlying physiological brain and psychological processes. Old psychology schools of thought such as behaviorism, psychoanalysis will be reviewed and a new proactive approach of psychology will be suggested, considering all the physiological and psychological processes of the brain and the mind. Anticipation is the science of decision-making. All living creatures make decisions regarding their actions. We aim to understand anticipation and the consequent decision-making processes. Anticipation involves physiological brain processes in all creatures but also involves psychological processes in creatures that are developed enough to exibit mind functions. Anticipation definitions vary according different science.
Anticipation Definitions Anticipation definitions varied according to different sciences. For some sciences anticipation is a simple stimulus-response association, while for some other sciences anticipation has a mental goal representation, a mental schema.
In Biology: Anticipation can be considered as a stimulus based response (Reigler 2001). This definition suggests that anticipation occurs as a response to external stimuli in order to adjust to the future (stimulus- response association).
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In Cognitive Psychology: When human behavior is studied, the issue of anticipation (advancing, forecasting, expectation, prospection) is inevitably raised in psychological science. Anticipation can be considered as a goal directed behavior rather than a stimulus based response (Stock & Stock, 2004). According Poli (2010), Herbart in 1825 introduced the Ideo-Motor Principle (IMP), suggesting that anticipation is a determination in voluntary movements. Therefore behaviors are driven by goal representations rather than a stimulus. The subject controls his actions to reach the desired outcomes (Botvinick & Rosen, 2009). Therefore anticipation is a process that is triggered by real or mental representation of stimulus or goals. This point of view suggests that human anticipation is intentional, conscious and goal-directed Anticipation is central in organizing perception, cognition, affect, memory, motivation and action. Anticipatory processes, their resolution and efficiency is based on the analysis and synthesis of previous experience, continuous correlation with current events and on a selective information extraction from memory to realize an action. Future probabilities are considered, and evaluated with possible costs in effort, risk and gais and then an action is elected. After the action, its evaluation in terms of satisfaction or frustration will result in maintaining the action or revise the evaluative representation that will guide the next act. Past, present and future events are connected together in the concept of anticipation. Anticipation has a universal value for all aspects of person’s activity. Humans try to preserve the past, to reflect the present and to master actively the future prospect as well. These mental models would be in the form of conscious or unconscious representations (Akhmetzyanova, 2016). According Poli (2010), “When the brain must take a decision, it does not have time to consider all possible choices/ alternatives. The brain decides which options are more likely to be realized; it anticipates among formed “internal models” whose task is to guide the system in its decision- behavior”. The brain anticipates different alternatives for
98 PSYCHOLOGY AND PHYSIOLOGY OF ANTICIPATION making decisions (Berthoz, 2003). Schemata/construct anticipations of what to expect enable the organism to perceive the expected information (Riegler, 2003). The first schools of thoughts on psychology tried to explain human behavior, cognition and emotion by focusing the past, in a past- present- future continuum. Among them was behaviorism and psychoanalysis.
Behaviorism - Concepts of the Mind Behavior psychologists argued that behavior could be analyzed without any reference to the mind. They replaced the mind as a topic of study in psychology with the study of directly observable behavior. All behavior was seen as the classical conditioning of the organism, a passive stimulus – response association, subject to the forces in the environment (Pavlov, 1973). All future actions would be then explained in terms of already acquired stimulus-response associations. Watson, in “little Albert” experiment, used classical conditioning of a 9 month-old boy to demonstrate how the baby acquired phobia to a white mouse and how he generalized this phobia to all white fury animals and objects (Watson & Rayner, 1920). This way, the present and future behavior of an organism was only explained in terms of the past stimulus-response associations. Behavior psychologists also explained all behavior of the organism by operant conditioning, where the organism would passively increase all behavior that is rewarded and decrease all behavior that is punished. There was again this already acquired passive conditioning of the organism in the past to explain his present and future behaviors. Skinner, among behaviorists, was not interested in what was happening in the mind, but focused on determining how behavior was controlled by stimuli (Skinner, 1969). Behavior psychologists defined psychology only in terms of observable behavior and did not consider cognition and emotion.
Psychoanalysis – Concepts of the Mind Freud’s psychoanalysis was another school of thought focusing on the past in order to explain the future behavior, cognition and emotion
99 ANTICIPATION of the individual. According Freud, adult personality was formed completely by the age of 5. The unresolved conflicts of childhood such as Oedipus complex (sexual feelings of the boy to his mother), repressed conflicts, memories and thoughts into unconsciousness would lead into abnormal conduct and psychological problems in adulthood. Therefore human behavior was only determined by his past, all mental events were predetermined and nothing would occur by free will. According Freud the defense mechanisms e.g. identification (with another person); repression (of anxiety provoking impulses or thoughts); sublimation (substituting socially acceptable goals for ones that cannot be satisfied); projection (of anxiety source to someone else); reaction formation (replace hate with love); fixation (at a stage of development); regression (to an earlier developmental stage) formed by the unresolved repressed conflicts of the past and could only be treated by the patient having an insight of his past (Freud, 1933). These theories had a passive simplified past oriented view of the organism and could not explain the forward-looking intelligence needed for organisms to act and to survive. Hence, they could not explain how this proactive intelligence can be formed and how it can be developed.
Active, Goal – Oriented Anticipation The importance of anticipation in psychology, the short-term and long-term processing of anticipation, the unconscious (unaware, implicit) and the conscious (aware, explicit) processing of anticipation will be reviewed for its active, goal oriented definition in psychology. Anticipations may be explicit or implicit. Explicit anticipations are those of which the system is aware. Implicit anticipations are unconscious and they may activate the system without the system being aware of them. Anticipation exhibits different temporal patterns, from microantici- pations (i.e: in miliseconds) that are unconscious to longer forms of so- cial anticipation (i.e: in hours, days, months, years) that are conscious. Anticipation as a goal-directed, active process has 3 components (Rieger, 2001)
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- Cognitive (planning, imagining) - Affective (anticipated emotions) - Behavioral (current actions as preparation to a goal)
While anticipation is defined as long-term, conscious, active, goal- oriented process in many sciences, physiological studies, observing anticipation for immediate events/responses reported also short-term, unconscious, goal-oriented active processes during anticipation.
Short-Term Cognitive Processes and Unconscious Brain Dynamics During Anticipation A Slow Negative Cortical Potential (SCP) brainwave is formed in the cortex before all cognitive processes. This negative brainwave of anticipation might have the function to speed up, strengthen and activate the cognitive processes involved. Anticipation is a process that speeds- up cognitive operations before they actually take place and increases their efficiency. Anticipation brainwaves were observed during different cognitive processes such as before: visual attention tasks, muscle- movement coordination tasks, facial expressions recognicion tasks, face recognition tasks, reward expectations connected tasks, and during emotional anticipation (Van Boxtel & Böcker, 2004) Slow Negative Cortical Potentials have been related with motivation, attention, and arousal functions. Anticipation increases the efficiency of cognitive processes by an advance activation of brain areas involved in these processes Anticipation is thought to speed and facilitate the cognitive operations (Van Boxtel & Böcker, 2004) Anticipation is an active process, with increase in activity in specific brain areas before the stimulus onset, represented by slow cortical potentials SCPs. These SCPs are named differently according the cognitive processes and the brain locations involved. SCP is a slowly increasing negative brain potential shift of 5 to 20 microvolt registered, about 1 second before the response. This wave returnes to baseline level after the initial response. Motivation, attention, arousal and the intention to act are the central concepts in some SCPs.
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SCPs obtained during the anticipation of different tasks show different brain localizations. There is no unitary scalp topography for the SCP. Anticipation is characterized by the activation of the brain areas required for the specific upcoming cognitive operations, such as, perceptual input anticipation may activate posterior perceptual brain areas, anticipation of affective input may activate right frontal areas. Therefore, anticipation, is active, intentional, goal-directed, can be unconscious when exhibited in a very short period of time and can take place in miliseconds. The brain might be perceived as proactive rather than waiting to be activated by sensations, it is constantly generating predictions that help interpret the sensory environment in the most efficient manner. These predictions facilitate cognition. Repetitive experience will make the generation of predictions automatic and require less conscious effort (Kvegara & Bar, 2007).
Brain Localization of Short-Term Implicit Anticipation Different brain areas were activated during the anticipation of the following cognitive functions: - Thalamus, V1 and V4 visual areas for perception (Kvegara & Bar, 2007) - Hippocampus for memory (Bar. 2007) - Frontal Cortex for visual processing (Kvegara & Bar, 2007) - Right Hemisphere for emotional processing (Kvegara & Bar, 2007) - Amygdala and Hippocampus for fear (Kvegara & Bar, 2007)
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Fig: Limbic system activities during anticipation: Thalamus (perception); Hippocampus (memory); Amygdala & Hippocampus (fear anticipation)
Long-Term Cognitive Processes and Conscious Brain Dynamics During Anticipation Anticipation showed different brain processes during long-term decision-making: dopamine activity in the brain increased and memory centers of the brain were activated.
Dopamine Activity in Anticipation Dopamine effects were reported during anticipation and temporal processing in animal studies (Howe et al., 2013). Dopamine levels increased during: - Temporal processing of many tasks - Regulating anticipation in positive reward and negative reward conditions Dopamine activity increases in the striatum in rewarding conditions.
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In chained task experiments where the animals receive the reward in the end of all tasks, the dopamine level in the striatum increases steadily, peaking as the final goal is approached, as if an anticipation of a reward. The dopamine signal seems to reflect how far away is the final goal. The dopamine level is also related to the size of the expected reward. This internal guidance system, with increase in dopamine levels in every step of a goal, might explain the pleasure and motivation experienced as the goal is approaching. For example sometimes the pleasure of anticipating every step of a piece of art may be more pleasant than the end product itself, or planning step by step a pleasant event and its anticipation might be as pleasant as the expected event itself e.g. a travel for vacation.
Mental Time Travel People, when planning their actions, might rely on the memories of the previously executed various action sequences to help guide their present and future behavior. They can time travel relating the past, present and future into one another. The subjective personal history of the individual is implied during this mental time travel. Episodic memory refers to autobiographical memory for specific prior events, including information about who was present, what occurred and what was felt (Tulving 2002). Episodic memory is a constructive process. Each time an event is remembered, past episodes are reconstructered a little different than the ones before. Schacter (2007, 2008) argued that episodic memory provides details needed to construct prospective simulations of future events. Memory of the past provides the future anticipation. The ability to predict and imagine the future depends on the same brain areas and processes as that to remember the past knowledge. These findings have led to the concept of the prospective brain; an idea that a crucial function of the brain is to use stored information to imagine, simulate and predict possible future events. According Tulving & Szpunar (2012), studies of functional brain imaging on healthy adults revealed the activation of the same brain areas, frontal and medial temporal lobes when they mentally traveled back into
104 PSYCHOLOGY AND PHYSIOLOGY OF ANTICIPATION their personal past and forward into their personal future. Therefore similar mental processes may be used in both time travels. According Thakral et al. (2017), neuroimaging data indicate that in both during episodic memory and during episodic future simulation, the same brain regions are activated (the hippocampus, parahippocampal cortex, lateral and medial parietal cortex, lateral temporal cortex and medial prefrontal cortex). This network provides the reconstruction of past life episodes and the construction of future episodes. These findings were also supported by research done on brain damaged, neurological and psychiatric patients. Brain damaged people who have deficits in episodic memory are also unable to plan their futures, and form episodes of future mental time travel. Similarly patient populations like schizophrenia, Alzheimer’s disease who have difficulties to remember their personal past have deficits in mentally anticipating their personal future (Tulving & Szpunar, 2012). These findings may answer some of the questions e.g. where do the scenarios (where, what, who type) come from when people imagine their own future. Since they may relate their anticipated future scenarios to the episodic memories of their personal past, or the past of the people in their social world.
An Anticipatory Approach in Psychology The implicit/ unconscious inborn cognitive skills of prospective representations can be used and developed in psychology for a better education system, and better psychological interventions. Anticipatory theories, therapies and education can be used instead of the traditional psychology theories, therapy practices and education. A better understanding of biology, physiology and psychology of anticipation, and focus to the future will lead to better problem solving skills, therapy skills and education skills. Further research is needed to develop the knowledge of the physiology of anticipation and to develop new uses of anticipation findings. Schema-like expectation-based learning systems with consideration of future possibilities and flexible goal monitoring must be developed.
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Anticipation and forecast functions activate the organism, helping the organism to sensitize to the upcoming event. This activity both in humans and all the organisms point the importance of anticipation for organisms to survive. These important activities need to be understood more deeply in order to: - Develop measures /scales of anticipatory skills as part of intelligence, aptitude, ability tests. - Develop measures /scales of anticipatory skills as part of neuropsychological tests to study the brain damaged individuals - Incorporate into child development psychology, pedagogy fields, anticipatory tests and observations to see the effects of anticipatory skills for the child’s adaptation to social and physical environment. - Prepare education programs to teach from early childhood the skills of foresight and anticipation and the consideration of all the alternatives in order to learn to choose the best alternatives for decision-taking. - Teach anticipatory skills on individual, group and society levels of decision-making. - Schema like expectation-based learning systems related to conditions and environment may be encouraged in education rather than pure associative learning. This model could comprise the following steps: proactively seek information, allocate mental resources, evaluate alternatives and select action. Then evaluate failures and conflicts detected, to feed them to the goal-based system in order to improve the model. Teach who, where, what type of scenario constructions.
its physiology and brain processes were reviewed in the present chapter.
Conclusions The role of anticipation in psychology is anaysed with respect to old psychological school of thoughts such as psychoanalysis and behavior- ism that focused on the importance of the past experience in order to explain psychological processes and psychological disorders in the pres- ent and the future.
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Physiology of the brain and the related brain processes for the anticipation process was studied. Studies in physiological psychology and cognitive neurosciences have a proactive approach on the organism, reporting that the organism is active and goal oriented, during both short-term anticipation and longterm anticipation. During short-term anticipation, the organism’s anticipation starts about 1 second before the response, showing a 5 to 20 microvolt brain activation in the same brain areas which will later be activated to perform the action, this anticipation is implicit, unconscious and unaware to the person. During long-term explicit, conscious, aware anticipatory decisions, the same brain areas involved in autobiographic memory are activated. This finding shows that schemas used to plan the future are formed by using what, where, who type scenarios coming from the personal past experiences. Dopamine activity in the brain increases during anticipation, as the desired goal is approached. This finding explains the pleasure experienced during the goal-oriented activities, where the pleasure peaks in successful achievement. Therefore, a new approach integrating foresight and anticipation in psychology is suggested to replace the schools of thought of psychology focusing only on the past experiences.
References: Akhmetzyanova, A. (2016), The Theoretical Analysis of the Phenomenon of Anticipation in Psychology. International Journal of Environmental & Science Education, 11(7), pp. 1559-1570. Bar, M. (2007). The Proactive Brain: Using Analogies and Associations to Generate Predictions, Trends in Cognitive Sciences, 11(7), pp. 280-288. Berthoz, A (2003), La decision. Odile Jakob, Paris (Cited in Poli, 2010, The Many Aspects of Anticipation, Foresight, 12(3), pp. 7-17. Botvinick, M. M. & Rosen, Z. B. (2009), Anticipation of Cognitive Demand During Decision-Making, Psychological Research, 73(6), pp. 835-842. Freud, S. (1933), New Introductory Lectures on Psychoanalysis, In Standard Ed. (Vol. 22, pp. 3-182). London: Hogarth Press.
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Kveraga, K. & Bar, A. S. G., Top-down Predictions in the Cognitive Brain. (2007) Brain and Cognition, 65, pp. 145-168. Pavlov, J. P. (1973). Twenty Years of Experience in the Study of Higher Activity (Behavior) of Animals. Moscow: Science Poli, R. (2010). The Many Aspects of Anticipation, Foresight, 12(3), pp. 7-17. Poli, R. (2017), Introduction to Anticipation Studies, Springer Int. Publishing. Riegler, A. (2001), The Role of Anticipation in Cognition, In D.M.Dubois (Eds). Computing Anticipatory Systems, Proceedings of the American Institute of Physics. Riegler, A. (2003), Whose Anticipations? In M. V. Butz, O.Sigaud & P. Gerard (Eds), Anticipatory Behavior in Adaptive Learning Systems (pp.11-22). Springer. Schacter, D. L., Addis, D. R., Buckner, R. L. (2007), Remembering the Past to Imagine the future: the Prospective Brain. Nat. Rev. Neurosci. 8: pp. 657-661. Schacter, D. L. Benoit, R.G. & Szpunar, K.K (2017). Episodic Future Thinking: Mechanisms and Functions. Current Opinion in Behavioral Sciences, 17, pp. 41-50. Skinner, B. F. (1969), Contingencies of Reinforcement. NY: Appleton- Century-Crofts. Stock, A. & Stock, C. (2004), A Short History of Ideo-Motor Action. Physiological Research, 68(2-3), pp. 176-188. Thakral, P. P., Benoit, R. G. & Schacter, D. L. (2017), Imagining the Future: the Core Episodic Simulation Network Dissociates as a Function of Time- course and the Amount of Simulated Information. Cortex. 90: pp. 12-30. Tulving, E. & Szpunar, K. K. (2012), Does the Future Exist? In B. Levine & I. M. Craik (Eds). Mind and the Frontal Lobes: Cognition, Behavior & Brain Imaging. Oxford Univ. Press. Van Boxtel, G. J. M. & Böcker, K. B. E. (2004), Cortical Measures of Anticipation. Journal of Psychophysiology, 18(2-3), pp. 61-76. Watson, J. B. & Rayner, R. (1920). Conditioned Emotional Reactions, Journal of Experimental Psychology, 3, pp. 1-14.
108 PART II
5
12. ANTICIPATION AND ENTREPRENEURSHIP
Özlem Kunday, Deniz Palalar Alkan
Introduction Anticipation is a relatively new concept in social sciences. It refers to all forward-looking attitudes related to a single or a group of living organisms where a consequent decision and action is implied. In this respect, the concept is distinctly different from similar forward-looking processes such as expectation, prediction and/or estimation. Entrepreneurship on the other hand is a human trait that obviously requires a significant anticipatory behavior. This Chapter establishes the relation between anticipatory behavior and entrepreneurship and ultimately aims to introduce a theoretical model to simulate entrepreneurial anticipation.
Anticipation Anticipation is a term referring to describing all forward-looking attitude and activities (Poli; 2017). Robert Rosen (1934-1998) was a theoretical biologist who defined anticipation as related to human life and started the pioneering research on anticipatory systems. Rosen’s definition of an anticipatory system has two distinctive properties. He initially defined an anticipatory system as “a system containing a predictive model of itself and its environment” which can be referred to as a forward-looking attitude. The second portion of his definition is “allowing the system to change at an instant in accord with the prediction of the future” is referred as the use of former’s result for action (Rosen, 2012). Further theoretical conceptualization of the term by Poli (2017) indicates that the theory could be described within a three-level framework. According to Poli, an anticipatory system entails not only the forecast that’s aligned with Rosen’s definition but also encompasses
111 ANTICIPATION foresight as well. Hence an anticipatory system encompasses forecasting, foresighting and finally, anticipation at the third level. The anticipatory process from such a perspective indicates that the future becomes an action in the present due to external or internal circumstances. An anticipatory system that carefully examines external changes and alters the behavior accordingly is considered to be an external model. An internal model, on the other hand, is an anticipatory system where the system’s actions are decided according to subjective psychological expectations. Therefore, understanding internal anticipation is necessary in designing schemata on anticipatory behavior of people, groups, and organizations. In this Chapter, a model for entrepreneurial anticipation will be discussed. We aim to generate a model about how one decides to initiate a venture with given rapid and radical changes in the environment. Our conceptual framework will be grounded on Ajzen’s Planned Behavior Theory (Ajzen, 1988 and 1991) and we will try to simulate the process of entrepreneural behavior starting from an intention through the sequence of cognition up to start-up success.
Anticipatory System As stated above, an anticipatory system proposed by Poli defines the concept on three distinctive levels. The first level is called forecasting which describes the predictive component of an anticipatory model that tries to explain a quantitative portion. This component of the model tries to create a temporality for the system to determine further action to be taken on the bases of past events. Engaging in a forecasting event is, however, prediction towards the future from past data without a thorough comprehension (Reid, Zyglidopoulos, 2004; 239). Therefore the concept should be examined in further detail. The second level called foresight is the component related to the design and analysis of future scenarios. It is the notion of creating possible futures within the scope of bounded rationality of a decision maker. Foresight, for that reason, is qualitative. It tries to generate future predictions based on an understanding of underlying laws, factors, and structures apparent in observable phenomena (Reid, Zyglidopoulos,
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2004; 239). Scenarios can be defined as “hypothetical sequences of events constructed for attention on casual process and decision point” (Kahn, Wiener, 1967 as cited by Limon et al., 2009; 314). The scenario analysis is not a tool for the prediction of a future; it is instead a method to explore the future to guide current decision-making. The third level that Poli calls anticipation is the capacity to predict subsequent behavior of oneself/environment based on current behavior. This entails the utilization of outcomes from both forecast and foresight models. Especially with deviations happening at an unprecedented pace, construction of the future should be based on encoding the reasoning behind such behavioral patterns as well. Thus with rapid and radical changes taking place during an entrepreneurial activity, decisions based solely on forecast will not suffice. It is vital to understand all instinctive behaviors of an entrepreneur generated from encoded information of him/ herself, his/her surrounding environment and what triggers such initiative. The most straightforward distinction of anticipation stated in the current literature is the classification of explicit and implicit anticipation. Explicit anticipation occurs when the underlying system is aware. It can be explained as the behavioral aspect of anticipation where one behaves according to specific observable norms. Also known as the reflexive side of anticipation, explicit anticipation is the impact of anticipation on current behavior (Poli, 2017). On the contrary, implicit anticipation is intrinsic and related to the hidden traits of an individual. It is how one perceives the information and constructs its anticipation accordingly. On a different accord, anticipation can also be explorative or normative. The main difference between an explorative and normative anticipation is the attitude toward scenario building. Explorative anticipation focuses on the present toward the future, whereas normative anticipation focuses on the future back to the present. Exploratory method of scenario building can generate various scenarios. Contrarily, normative scenarios due to its nature select a specific scenario and work backward towards its required circumstances (Poli, 2017). Anticipative models can be created from representations or presentations of how one perceives the environment. Both representational
113 ANTICIPATION and presentational positions are related to one’s capacity to synthesize the gathered knowledge. From the representational perspective, an interpreter drives the meaning and the model solely by cognition. In other words, the meaning and the model are generated internally. On the other side, presentational perspective employs both the brain and mind functions (Poli, 2017). Paralleling these facts with enrepreneural behavior, research states that entrepreneurs are rational and well informed. Thus an entrepreneur, in order to identify opportunities, can continuously scan changing environmental conditions, calculate production costs and compare these costs related to different governance mechanisms (March & Simon, 1958; Weick, 1995; Wood & Bandura, 1989). This notion reflects the presentational perspective of how an entrepreneur creates a cognitive model in the decision-making process. Additionally, managerial decision-making is also rationally bounded and influenced by an entrepreneur’s prior experiences and cognitive biases and hence, exhibits a presentational perspective. One of the concerns addressed in entrepreneurship research is how one can identifies and consequently explores (or exploits) entrepreneurial opportunities. Behavioral research efforts have found out that human behavior is planned rather than spontaneous when envisioning a new venture as a career choice (Krueger, Reilly, Carsrud, 2000; 415). Entrepreneurial research suggests that a career-related decision is a cognitive process considering one’s prior experiences, beliefs, and accumulated knowledge (Davidsson 1991; Katz 1992). Surprisingly, the theory of anticipation also states that behavior is goal oriented rather than stimulus driven. Therefore, our aim to develop a theoretical model of how an entrepreneur recognizes an opportunity and bridges contingent factors coincides with exploring how a start-up is anticipated.
Entrepreneurship Entrepreneurship continues to be a popular topic of interest for many researchers throughout the last decades. Although a quite old field of research, efforts to contribute to its conceptual framework still continues. Scholars from a wide range of disciplines such as psychology,
114 12. ANTICIPATION AND ENTREPRENEURSHIP sociology, anthropology, management, history and economics show interest in this topic by including entrepreneurship into their research agendas (Hebert and Link, 1989). This interest is due to the vital role of entrepreneurship in fostering economic growth through innovation and increase employment levels through creation of new jobs. Early in the 1800’s, the economists Cantillon and Say introduced their original formulations of the entrepreneur as being a specialist on bearing risk. In the beginning of the 19th century, the concept of entrepreneurship had been rigorously studied by an Austrian economist, Joseph Schumpeter. According to Schumpeter, the entrepreneur is a vital element of the economic system and plays a fundamental role in revitalizing and growing economies, thus increasing employment levels. He furthermore discussed the importance of innovation and emphasized that the source of innovation is entrepreneurship. Later on, especially with the studies carried out by Kirzner and Baumol, different aspects and dimensions of entrepreneurship have been identified and adressed . Shane and Venkataraman (2000) propose that entrepreneurship is not limited with the creation of a new business, which was the dominant view of entrepreneurship since 1985. They argued that entrepreneurship can also emerge within an existing organization where opportunities may be sold / transferred to the organization or individuals. Along the same token, new concepts such as social entrepreneurship, ecopreneurship, technopreneurship as well as serial entrapreneurship are introduced. The types of motivation lying behind the choice of becoming a certain type of entrepreneur has also been in the main research agenda of several researchers (Ucbasaran et al. 2008; Simmons et al. 2014). Serial entrepreneurship is such a new dimension of entrepreneurship. Serial entrepreneurs can be defined as those entrepreneurs who launch businesses sequentially (Dujowich, 2010). They should be well distinguished from portfolio entrepreneurs, who run multiple businesses concurrently. There is an emerging literature on the theory of serial entrepreneurship. Serial entrepreneurs have a significant contribution to entrepreneurial activity (Dujowich, 2010). It is estimated that serial entrepreneurs
115 ANTICIPATION account for 18-30 percent of total entrepreneurial activity. The numbers for the US are a little bit lower, around 12 percent (Dujowich, 2010). Several studies (Holmes and Schmitz 1996; Headd, 2003; Dujowich, 2010) provide evidence that businesses initiated by serial entrepreneurs are more likely to survive as compared to those businesses founded by first time entrepreneurs. Prior research also shows that there exists a significant positive correlation between the human capital that results from the previous business experiences of the entrepreneur and serial entrepreneurship intentions (Fitzsimmon & Douglas, 2011). These studies also indicate that having prior experience in managing a business increases the chances for future opportunity recognition (Ucbasaran, Westhead, & Wright, 2009).
Entrepreneurial Anticipation We propose that entrepreneurial anticipation is the anticipation process that an entrepreneur faces especially from the aspect of the opportunity recognition process. The reasoning behind the discussion of the entrepreneurial anticipation concerning opportunity recognition is that it is the start point of any venture initiation. In this chapter, we propose that entrepreneurial anticipation occurs in temporality through a set of actions. In other words, in order to exploit or explore an idea and convert it to a viable action, an individual need to possess certain factors. To define entrepreneurial anticipation, we need to examine the effects of past and future expectations on the present decision making, especially in identifying or recognizing the opportunities. The absence of temporality perspective in the entrepreneurship research highlights the importance of this study. Temporality provides the individual with a context that combines the past and future to shape the actions of the present (Gill, 2013). Gill (2003) argues that temporality assumes the times as intertwined. Thus, the actions and decisions of the present are taken with the consideration of past experiences and future expectations. In this chapter the temporality perspective of entrepreneurial anticipation will be discussed from the aspects of (a) the past such as an entrepreneur’s prior knowledge, social
116 12. ANTICIPATION AND ENTREPRENEURSHIP capital, education, personal traits, and cognitive biases; (b) the present including environmental contextual conditions; (c) the future aspect of strategic vision and change. An individual’s prior knowledge becomes salient when achieving success in an entrepreneurial venture (Acs et al. 2009). Acs et al. indicated that knowledge spillovers allow entrepreneurs to identify and exploit an opportunity and is essential for achieving sustainable success. Since the knowledge that emerged from the previous experiences helps an entrepreneur to understand and identify the potential venues and take a required course of actions (Chiasson and Saunders, 2005). Various scholars identify the concept of social capital. Due to its multidimensional nature, there is a lack of consensus in regards to measuring and defining the concept (Eugelsdijk and van Schaik, 2005). Despite the variation among the conceptualization of the concept (Coleman, 1990; Onyx and Bullen, 2000; Adler and Kwon, 2002), many scholars agree on the positive effect of having a social capital towards achieving entrepreneurial success. Social capital is a network of structure and relationship exist among individuals. It is also a connected cohesiveness that links the actions of individuals and creates benefits and aims to facilitate mutual goal attainment. Thus, the bondage which created through the social network of an entrepreneur is one of the vital sources to recognize and achieve the opportunities (Aldrich and Cliff, 2003). Social capital becomes significant in accessing a wide array of relevant sources (Audretsch et al., 2011) and plays a mediating role between human capital and opportunity recognition (Bhagavatula et al., 2010). Entrepreneurship education also provides entrepreneurs for acquiring concept and skills are essential in opportunity recognition (Kourilsky& Esfandiari, 1997). The entrepreneurship education which allows an individual to equip with necessary knowledge and skills along with affecting one’s attitude, behavior, and values towards the career of entrepreneurship helps individuals to acquire knowledge such as opportunity recognition, new business formation, and managing skills becomes a vital source of entrepreneurial success. Cognitive frameworks and personal traits such as high self-efficacy (Tominc & Rebernik,
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2007), high level of intelligence and creativity (Ardichvili et al., 2003; Baron, 2006; Ramos-Rodriguez et al., 2010) are linked to identifying or recognizing entrepreneurial opportunities. According to the results of the empirical research (Gaglio & Katz, 2001), alert individuals are more prone to seeing the signals of market disequilibrium (Garcia-Cabrera & Garcia-Soto, 2009). In addition to aspects of the past, the present context such as environmental conditions has an impact on entrepreneurship. Entrepreneurial environment refers to a combination of circumstances that play a role in entrepreneurial activity. These factors that influence one’s willingness to start a new venture include economic, socio-cultural, technical and regulatory conditions (Webb et al. 2011) the availability of financial funding, public policy that is in favor of entrepreneurial activity such as providing tax incentives and venture capital funds creates a context in which facilitation of start-up process becomes attractive (Gnyawali and Fogel, 1994). The future point of view on entrepreneurial anticipation include strategic vision and how an individual interprets a change. Entrepreneurial success is also contingent upon an individual ability to think strategically. Entrepreneurs who possess strategic thinking can see an opportunity when others are incapable. Also, an entrepreneur who has an exquisite insight can manage others towards successful completion of shared long-term goal (Global Entrepreneurship Institute, 2014). Perspectives of past, present, and future within the opportunity recognition process are one of the fundamental a priori for a successful venture initiative. Prior research provides empirical and conceptual support from a particular facet that omits temporality. We believe temporality of the issue should be considered to gain a better holistic perspective in regards to how one individual can exploit or explore a feasible “window of an opportunity” in the creation or recognizing the signals within the market. Therefore, consideration of each time as intertwined is essential to conceptualize entrepreneurial anticipation. We propose that anticipatory entrepreneurial activity occurs cognitively in the minds of an individual that each facet intertwine.
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Opportunity Recognition Identifying the entrepreneurial opportunities is a significant focus in the entrepreneurship literature (Shane, 2000; Shane and Venkataraman, 2000; Gaglio and Katz, 2001; Hsieh et al., 2007; Shane et al. 2010; Murphy 2011). Discovering a feasible entrepreneurial opportunity, which can be described as a set of circumstances that are favorable and positive, plays a critical role in entrepreneurial success. For the past decade, we can conclude from the literature the concept is an essence to entrepreneurial research (Shane, 2000; Shane and Venkataraman 2000; Gaglio and Katz, 2001; Hsieh et al., 2007, Murphy 2011, Arentz et al., 2013). The concept, however, has a variety of perspectives in determining how an opportunity is recognized. Various models of opportunity recognition are contributed to the literature in recent years. These models have origins from various disciplines such as cognitive psychology and economics. The literature generates two perspectives for understanding the discovery of such opportunities from an entrepreneurial perspective. First, there is an emphasize on how internal knowledge such as past experiences and knowledge (Baron &Ensley, 2006; Dimov, 2010, Ucbasaran, Westhead &Wright, 2009), creativity (Gielnik, Frese, Graf, Kampschulte, 2012; Shane and Nicolaou, 2015), and cognitive process (De Carolis et. al., 2009; De Crolis and Saparito, 2006) play a pivotal role in recognition of an opportunity. The second perspective emphasizes more on how entrepreneurs utilize external sources and social networks in the creation of opportunity (Arenius, De Clercq, 2005; Bhagavatula et al., 2010; Davidsson, Honig, 2003; Ma, Huang, Shenkar, 2011; Ozgen and Baron, 2007); Arenius & De Clercq, 2005; Bhagavatula, Elfring, van Tilburg, & van de Bunt, 2010; Davidsson & Honig, 2003; Ma, Huang, & Shenkar, 2011; Ozgen & Baron, 2007). Research related to opportunity recognition has been influenced heavily by the works of Schumpeter or Kirzner. Schumpeter’s defines the entrepreneur as someone who is change-oriented and creates a disruption to the existing economic system that is in the state of “equilibrium” (Schumpeter, 1934). Kirzner defines an entrepreneur as an individual who is alert in identifying existing informational asymmetry
119 ANTICIPATION in the market and exploits such an opportunity. The author addresses the importance of market arbitrage in identifying an opportunity and was the first scholar who introduced the term of alertness. According to Kirzner, the concept of alertness related to an individuals’ awareness of existing overlooked possibilities that exist in in the market (Kirzner, I. M, 1997). An alert individual can take advantage of existing circumstances by buying resources where prices are low and selling the outputs where prices are too high (Shane, Venkataraman; 2000). As the definitions can drive it, there is a dichotomy that exists among the scholars in regards to the opportunity recognition process. Schumpeter’s (1934) view on opportunity recognition is not limited to the creation of products and services but also in the form of creation of new production methods and “restructuring” an existing market. Schumpeter (1973) characterizes an entrepreneurial activity with the notion of innovation that is related to the creation of new combinations. Thus, an entrepreneur is an individual who initiates a new opportunity. Kirzner (1979), on the other hand, emphasizes that the opportunities need to be invented rather than found in their final form. Kirzner argues that an opportunity can be found within market imperfections, and such circumstances can yield a potential to create an economic return. The author also emphasizes the importance of recognition rather than discovery. Aside from differentiation in the perspectives, both perspectives toward opportunity generation are compared to the notion of change (Shane, 2003). According to Schumpeter, the economic system in an equilibrium state until a change is created. The definition of change is the process generated by an entrepreneurial activity that threatens the existing incumbent’s profits and transforms the economic system into disequilibrium. Thus the state of disequilibrium creates vast opportunities for entrepreneurs in the economic system, and the entrepreneurs can seize the opportunity and act upon it. With that the system will gradually move back to its equilibrium state. On the contrary, Kirzner sees opportunities as a result of the equilibrating force, and tried to define the nature of the market conditions within the boundaries of disequilibrium. According to
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Kirzner, an economic system is in continuous disequilibrium. According to Kirzner, the growth of competitive activity exist in the market will eventually diminish the value of an opportunity and stabilize the market towards an equilibrium state (Kirzner, 1997). According to Shane (2003), one of the aspects that Schumpeter and Kirzner differ in the perspective on opportunity recognition is related to access to the valuable information required to initiate an action towards a venture. The question of whether an opportunity created through the production of new information source (Schumpeter) or arise from the access to the limited information (Kirzner) that already exist is one of the significant factors presents the diversity of perspective of both scholars (De Jong, 2011). According to Schumpeter, innovation is related to “re-combination of existing means “in terms of technological and socio-demographic, legal or regulatory changes that bring out new information that will eventually enhance the opportunity for the entrepreneur (Shane, 2003). Even though innovation is considered in the definition of both scholars’ perspectives, Schumpeterian opportunities can be considered as more of a “creation,” whereas Kirznerian is a “discovered.” Thus, the Kirznerian perspective sees an entrepreneurial activity from the standpoint of an individual’s ability to be alert to the unanticipated changes within the economic system. Shane (2003) also argues that Schumpeterian opportunities are “rare” than “common.” Due to its disruptive quality, Schumpeterian opportunities considered as unique and can be created less often than Kirznerian opportunities. Schumpeter puts much emphasis on the unique personality traits of entrepreneurs and intrinsic motivation that an individual possesses when creating such rare opportunity. Schumpeter comments on the fact that an entrepreneur is a “rare breed” that utilizes the benefits of technological and socio-demographic changes to create a reformist approach (Schumpeter, 1934). On the other hand, Kirznerian argues that an entrepreneur is an individual who acts upon the misfunctioning of the market, and opportunities are created through a response to price disparity (Dosi, 1988).
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Entrepreneurial Intent and The Theory of Planned Behavior Starting a business is an intentionally initiated process by the entrepreneur. It is therefore considered as a planned behavior which can be predicted by the person’s intentions ( Bird, 1988; Katz and Gartner, 1988). One of the fundamental characteristics of emerging organizations is intentionality. Therefore it is extremely important as well as interesting to excogigate the pre-organizational phenomena. This involves studying the decision of an entrepreneur to start up a business (Katz and Gartner, 1988). Intentions that an individual has towards a certain behavior are extremely determining in understanding further antecedents, moderators or consequences of a certain behavior (Kueger and Carsrud, 1993). By accepting that starting up a business is an intentional behavior, significant implications are also accepted for the relevant research. When studying intentional behaviors, stimulus-response models cannot be applied since processes are less well understood by considering past situations or events. Here, prospective studies should be applied. Theory- driven process models that are testable and focus on intentions as well as their emotional grounds are needed for entrepreneurial cognitions. At this stage, models of behavioral intentions from the field of social psychology that are used to provide predictive along with explanatory value for a several behavioral phenomena come into the arena (Kueger and Carsrud, 1993). Behaviors can be predicted best by intentions that are derived from attitudes (Kueger and Carsrud, 1993). Thus, attitudes are good predictors for intentions (Kueger and Carsrud, 1993). Especially in cases that are relatively rare, for which initiating a business is a good example, it is very useful to have an understanding of the intentions. Understanding these intentions will present important insights into the underlying processes as stated by Ajzen (1987, 1991). We can obtain significant insights into the initiation of the new venture without having actually observed it. Many researchers (Watters, 1989; Parker et al. 1990; Beale & Manstead 1991) have turn to the theory of planned behavior in trying to predict and get an understanding of individual’s intention to initiate several activities.
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The Theory of Planned Behavior (TPB) by Ajzen (1988) proposes that an individual’s attitudes to his/her behavior, his/her subjective norms along with his/her perceived behavioral control result in behavioral intent. A stated above, this theory postulates three independent constructs as determinants of intention. Attitude toward the behavior, the first construct, “refers to the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question” (Ajzen, 1991, p.188). Subjective norm, the second construct, “refers to the perceived social pressure to perform or not top reform a behavior” (Ajzen, 1991, p.188). Perceived behavioral control is the third construct that determines intention and defined as “the perceived ease or difficulty of performing the behavior and is assumed to reflect past experience as well as anticipated impediments and obstacles” (Ajzen, 1991, p.188). Consequently, intention is expected to be greatest when the individual show a favorable attitude along with subjective norm and has greater perceived behavioral control for a behavior. The theory of planned behavior is actually an extention of another theory, i.e. the theory of reasoned action, proposed by Ajzen and Fishbein in 1980 and Fishbein and Ajzen in 1975. These extensions were necessary due to the original model’s limitation to deal with behaviors over which individuals do not have complete volitional control. Just like as it is proposed in the original theory of reasoned action, the fundamental factor of the theory of planned behavior is the intention of an individual to perform a certain behavior (Ajzen, 1991). The main difference between the initial theory of reasoned behavior and the theory of planned behavior is the addition of perceived behavioral control construct to the model. It is obvious that perceived behavioral control plays a very important role in the theory of planned behavior. Several studies (Bandura, Adams, & Beyer, 1977; Bandura, Adams, Hardy, & Howells, 1980) have shown that an individuals’s behavior is strongly influenced by their perceived behavioral control or in other words, their self-efficacy, (i.e. confidence in their ability to perform it). The theory of planned behavior includes this construct into a general framework
123 ANTICIPATION of the relationships between beliefs, attitudes, intentions and behavior. Perceived behavioral control, along with behavioral intent, can be used in predicting behavioral achievement directly (Ajzen, 1991). Intentions are considered to capture the motivational factors that effect a certain behavior. Intentions are hints of how hard an individual is willing to keep on trying, of how much effort he or she is planning to put in to perform a certain behavior (Ajzen, 1991). It can be considered as a general rule that the stronger the intention to engage in a cretain behavior is, the more likely will be its performance. However, it should not be forgotten that an intention can result in a certain behavior only if that certain behavior is under the volitional control of the individual. This means that the individual is free to decide to whether perform or not to perform that specific bahevior. Some behaviors meet this requirement, but the performance of others depend to some degree on several non-motivational factors like the presence of resource and available opportunities such as money, cooperation of others and required skills, as stated for a dicussion in Ajzen, 1985. These mentioned factors together form an individual’s actual control over the behavior.
Attitude (behavioral beliefs x outcome evaluations)
Subjective norms Behavioral (normative beliefs x Behavioral intentions motivation to comply)
Perceived behavioral control (control beliefs x influence of control beliefs)
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In 2002, Ajzen has made a revision to TPB and theoretically proposed linkages between past behavior and future behavior intent.
Entrepreneurial Anticipation Conceptual Model The primary purpose of this chapter is to conceptualize a proposed model on entrepreneurial anticipation based on temporality perspective. Temporality is an important concept since any entrepreneurial activity is not a byproduct of a single circumstance. It is the combination of past experiences such as prior knowledge and entrepreneurial education and future expectation of strategic thinking that shapes today’s intentions and decisions. Thus, time is not something that we should regard as an “irreversible movement along a straight line,” it is intertwined. An individual need to have the ability of systematic foresight and forecast, which links the past and the future to the present.
Explore Prior knowledge Social capital Education Personal traits
Act Recognize Strategic Vision Scan the environment Interpretation of change Alertness
Intent personel attitude perceived societal norms personal control
Figure 1. Entrepreneurial Anticipation Conceptual Model
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The first dimension of the model will be referred to as “explore.” Prior knowledge, social capital entrepreneurial education, personal traits are one of the antecedents of successful entrepreneurship. Accumulation of such factors can contribute to a positive attitude to undertaking a risk that is associated with becoming an entrepreneur (Hisrich& Peters, 1992). We refer to explore dimension as the “past” since these factors are created through the years of experiences that shapes one’s decisions of the present. In other words, in order to recognize a viable opportunity and take advantage of the “window of opportunity,” we argue that combination of past factors is required and it is linked to the present decisions of today. The present dimension will be referred to as “recognition.” As mentioned, entrepreneurial anticipation requires the ability to actively scanning the external environment and contextual circumstances that exist in one’s surrounding. The process of recognition includes either capturing valuable information that will eventually create a profit due to information asymmetry or able to disrupt the existing market will attain success. Therefore, recognition includes the action of the present; however, it is still affected profoundly by one’s past experiences. The category of the present aspect will be referred to as “intention.” What distinguishes an entrepreneur from an “idea generator” is the intention towards taking necessary steps to start up a new business venture and assuming the risks associated with such actions. In other words, an entrepreneur is an individual who moves forward with the idea that generated cognitively and turned it into a viable business opportunity. As mentioned, we constructed the conceptual basis of intention process on the Theory of Planned Behavior that is contributed by Ajzen. The intention process of entrepreneurship starts with the implementation of an idea, which is the combination of certain aspects. These include personal attitude, perceived societal norms, and the control of one on his/her behavior. Barringer & Ireland (2016) indicate in their work that behavioral control of one’s action is one of the primary reasons why one becomes an entrepreneur. Thus, intention towards a belief that motivation of controlling ones’ actions is an essential part of becoming an entrepreneur. An entrepreneur personal attitude of
126 12. ANTICIPATION AND ENTREPRENEURSHIP possible future outcomes also motivates one to seek potential venture options. The subjective norm is defined as the pressure of societal norms on one’s behavioral intent. As supported by literature, entrepreneurs are known as the catalysts of economic expansion in both emerging and developed nations. They are accounted for various benefits to a nations’ economy along with society and community. Thus, in a country where regulatory landscape in addition to financial institutions affirms entrepreneurial initiative, then an individual will be more prone to become an entrepreneur. Accepted societal norms towards entrepreneurs can profoundly shape one’s intentions of becoming an entrepreneur if it is attributed to attaining a positive identity. Additionally, in the future aspect of the model, we argue that certain factors play a prominent role such as the ability to have a strategic vision and the interpretation of the change as a positive opportunity in one’s perception. This last category defined in the proposed model is called the “act.” The model occurs ina continuum since we interpreted entrepreneurial anticipation from the serial entrepreneurial standpoint. Serial entrepreneurs are individuals who continually seek new possibilities to combine the required resources in the pursuit of potential venture initiations. Therefore, we assume that a serial entrepreneur in his career will seek a variety of options to grasp and will continuously implement his ideas into a viable business. He/She will combine the aspects of past, present, and future in a continuum and initiate a variety of start- ups during their career. Temporality perspective of entrepreneurial anticipation refers to the convergence of all the aspects that is embedded in the definition of Shumpeter (1961) who characterizes an entrepreneur as an individual who has an initiative, responsibility or authority and capacity of forward-looking. As Adams (Adams et al., 2009) indicates, the anticipation is “a way of actively orienting oneself temporally.” Anticipatory actions start with the “will” and continue with courses of action in the “face of ongoing contingency and ambiguity.” Anticipation possesses a temporal form that tacking back and forth between the past, present, and future (Adams et al., 2009).
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Conclusion and Limitations Entrepreneurship is a popular concept as an area of interest for many scholars. Although a quite old phenomenon, the effort to add to its conceptual framework continues. Additionally, anticipation plays a crucial role in understanding the behavioral pattern of an entrepreneur. This chapter discusses the entrepreneurial activity based on the temporality of entrepreneurial anticipation. The proposed model guides a framework in understanding the entrepreneurial activity from a holistic view. The reason in developing such a model is that prior literature fails to link all the elements behind the explanation of a venture initiative. Thus, the attempt to discuss all venues that contribute to the activities performed by an entrepreneur analyzed based on the context of temporality. Temporality discussed within the scope of the chapter aims to combine all past, present, and future valances of anticipations. The conceptual model within the chapter helps to visualize the related aspects that concur simultaneously. There are certain limitations of the study since it provides a conceptual analysis without providing further empirical support. The conceptual framework guides a researcher with the logic behind the interconnected fundamentals of entrepreneurial anticipation process. The conceptual model can be further developed by applying quantitative and qualitative research methodology.
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6 ANTICIPATION IN ECONOMICS
Ayse Sevencan
Abstract Anticipation science, also known as the science of decision-making, is a new emerging field of research that aims to formulate a well-defined theoretical basis for the analysis of anticipatory systems. Anticipation as a term by itself is defined as all“ forward-looking attitudes and activities” and hence implies a present action based on a foresighted future (Poli, 2017). An anticipatory system is defined as a“ system containing a predictive model of itself and/or of its environment, which allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant” (Rosen 2012, pp.313). Economics as a social science is by nature aimed to be an anticipatory system and this Chapter aims to study the links between economics and anticipation science. The first part of the Chapter presents a survey of the economic literature in terms of the role of forward-looking assumptions. Economic literature uses expectation as a form of anticipation, in which economic agents act upon them, are either “rational” or anticipate according to animal spirits. An important aim of economic forecasting is to make ex ante decisions of the likely values for output, inflation, employment, spending and other economic activities. The Chapter also outlines the economic theory from an anticipation perspective and attempts to demonstrate how multidisciplinary approaches to economics through anticipation can enrich economic thinking and decision- making.
1. Introduction Anticipation plays a major role in economics. Economic thinking is by nature future oriented and this feature of temporal orientation is largely
135 ANTICIPATION absent in most of the other disciplines of social sciences (Beckert, 2016). Looking at the future under certain constant assumptions is inherent to economic thinking. Probably the most popular sayings of the economic research discipline are: “assume that” and “ceteris paribus”1. Most of the forward-looking theories of economics starts with the assumptions of an ideal world for analysis and keep all the other factors that might influence the result constant. The oxymoron of presuming “ceteris paribus” in an anticipating system and trying to predict the future are crucial shortcomings of the present economic theory. The foundation of orthodox economic literature is based on the rationality axiom. Taken to its logical extreme, the society is composed of economic men, who can make all the best decisions to maximize their utility while working - in such a way that their marginal productivity is just equal to their wage - in perfectly competitive profit maximizing firms. Unfortunately, such a world can only be seen in science fiction movies. The main reason of this way of abstraction in economic theory is that it enables the forming models and makes it possible to pose policy outcomes. Beckert (2013) criticizes the foundations of economic theories and rejects the rationality axiom and redefines it as frictional. In his own words:
Economic theories provide accounts of cause–effect relations, about the effects of decisions on future development, and about the behavior of economic systems. Given the openness of the future and hence the fundamental uncertainty confronting decision makers in the economy, economic theories can also only be interpreted as fictional depictions of causal relationships and future developments. Only under the conditions specified in economic theory (full information, rationality, and so on) can expectations anchored in calculation indeed be understood as anticipations of future states. This, however, is hardly ever the case. If rational expectations are assumed in situations with fundamental uncertainty, what is claimed to be “rational expectations” are indeed camouflaged “fictional
1 Latin: With other conditions remaining the same; other things being equal.
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expectations”. This camouflaging is important for the credibility of the theory (Beckert, 2013, pp 229).
Although we mostly agree with the Beckert’s criticism about the flows of the assumptions of the economic thinking we follow a fairly optimistic view of seeing how it can be changed and evolved. Economic actors (i.e. individuals, small groups, firms, organizations and institutions) engage in economic activities that are mainly referred as production, consumption, distribution and resource maintenance. Economics is about how these actors behave and interact as they engage in all economic activities. All of the economic agents are composed of humans; thus any economic behavior is entirely a reflection of human behavior. Hence, the decisions of organisations and institutions are also based on human decisions. For example, central banks do not operate by themselves and the announcement of interest rates are actually decided by humans who make specific predictions on the outcome. Throughout the history of economic theory development, the starting point for any theory has always been a statement made about the decision-making process of humans. Classical view of the economic theory is based on Adam Smith’s concept of the invisible hand that states people acting on their self- interest would through markets promote general welfare (Smith, 1790). Although used by later economists extensively, Smith originally defined the notion of “self-interest” in a different manner. InThe Theory of Moral Sentiments this concept is defined in detail as “people seek for self- respect and the respect of others (moral sentiments) which will balance the self-interest and in many cases self-interest can promote the public interest” (Smith, 1976). Following Smith, Ricardo and Mill shared the same view of complexity of human nature and motivations (Ricardo, 1817 and Mill, 1909). Marshall in 1890 brought together these ideas in Principles of Economics (Marshall 1890). Marshall indeed uses the Latin phrase “Natura non facit saltum” (nature makes no leap) in the preface of the first edition and as a motto throughout the text, widely accepted as influenced by Charles Darwin’sOrigin of Species. Although, Marshall’s
137 ANTICIPATION theory has been restricted to static models, the Darwinian intentions of Marshall can be seen in his own words:
“As civilization has progressed, man has always been developing new wants, and new and more expensive ways of gratifying them. The rate of progress has sometimes been slow, and occasionally there has even been a great retrograde movement; but now we are moving on at a rapid pace that grows quicker every year; and we cannot guess where it will stop. On every side further openings are sure to offer themselves, all of which will tend to change the character of our social and industrial life, and to enable us to turn to account vast stores of capital in providing new gratifications and new ways of economizing effort by expending it in anticipation of distant wants. There seems to be no good reason for believing that we are anywhere near a stationary state in which there will be no new important wants to be satisfied; in which there will be no more room for profitably investing present effort in providing for the future, and in which the accumulation of wealth will cease to have any reward. The whole history of man shows that his wants expand with the growth of his wealth and knowledge” (Marshall 1920, pp22).
By the twentieth century, the neoclassical approach started to dominate economic theory that accepted a narrower view on human motivations (Samuelson, 1937 and Fisher, 1930). In the neoclassical approach there are mainly two agents; firms and individuals, who both are motivated on maximizing their potential gains. Firms’ potential gain is profit and consumers’ potential gain is called utility. In its simplest form, utility is maximized through consumption of goods and services whereas profits are maximized through supplying goods and services at the optimum price and output level. These agents interact perfectly under some assumptions (perfect competition assumptions). In this ideal “value free” world, it is easy to model and analyze the economic outcome. Markets are always clear and if not, externalities are eliminated through interventions. The rationality axiom (rational economic man
138 ANTICIPATION IN ECONOMICS maxims his utility) is the other component of the neoclassical approach, along with the value-free assumption that makes economic theory purely deductive. The Chapter is organized to reveal the role of anticipation in different main subfields of economics. Section 2 surveys the role of anticipation in the published microeconomics literature. The two subsections are focused on the role of anticipation in individual decision-making (utility theory) and in public economics. In Section 3, the evolution of macro theories and their relevance are criticised from an anticipation perspective. Consequently, business cycles, financial markets and technological change are reviewed. Conclusions are presented in the last section.
2. Anticipation in Microeconomics The field of economics studies the behavior of the most important economic agent – the individual - through her decisions. How this agent decides to consume, produce and save are the critical questions to be dealt. Jevons (1905) described economics as a science mainly focused on people efforts to obtain ‘anticipal pleasure’, or similarly avoiding ‘anticipal pain’, through providing goods and services for the future consumption. The production and exchange dynamics in the economics, according to Jevons have the purpose of fulfilling these anticipatory feelings. Intertemporal choices - decisions involving tradeoffs among costs and benefits occurring at different points in time - not only determine individual’s health, wealth and overall happiness but also construct the dynamics of the economic system among the agents (such as firms, institutions and nations). Section 2.1 outlines how the individual decision is modelled in economics in an intertemporal dimension and stresses on the importance of anticipation in individual’s economic decision-making. Section 2.2 examines the role of anticipation in public economics.
2.1. Utility Theory- The Choice of Consumption The individual as an economic agent derives satisfaction (utility)
139 ANTICIPATION from consumption. How much to produce, amount of resources to use and how to distribute the products among individuals derives from this economic individual’s utility function. Based on Fisher’s theory (1930), Samuelson (1937) modelled a theory of utility function that has become a standard tool for economics analysis and teaching. 2 Discounted utility theory, refers to preference of early over later utility, is subject to both empirical and theoretical criticism. The literature on criticism of discounted utility theory is based on both empirical and theoretical perspectives (Shane et al, 2002). The most severe criticism in the literature is about the discount rates. In its general form, any satisfaction of consumption in future diminishes as time passes. We evaluate both past consumption and expected consumption less than current consumption. Both empirical and theoretical research results suggest that a positive discount rate is not the case (Köszegi, 2010). A typical example for comprehending a discount rate is to compare the happiness and excitement you feel when dreaming about buying a new house. Anticipation for buying a house starts much earlier than the actual purchase, most people start to buy decoration journals, imagine how they will decorate the house and even some start to buy new appliances. In this example, buying a house at time say t+1 years may even have greater
2 The ‘discounted utility’ function of Samuelson is as follows
(1)
Where U is utility, c is consumption, t is time (0,1,2…t…z) and ρ is the discount rate of time. According to this intertemporal utility function utility at time t is simply U(ct) and its independent of any consumption at any other time. In other words, neither future nor past consumption affects the utility at any given time. Consumption is determined by income, both accumulated and expected. According to the permanent income hypothesis consumption at time t is:
(2)
Where y is income and the series express expected income. Expected income affects current utility indirectly through its effect on current utility and hence anticipated future utility is a function of anticipated income and consumption.
140 ANTICIPATION IN ECONOMICS utility at time t than t+1. Once the house is bought the utility starts to diminish. In this case we obviously cannot talk about a positive discount rate. Another similar example may be about going to a dream vacation or reversely, negative utility of going through a surgical operation in a year might be greater than the discomfort of surgery itself. As Seneca puts it brilliantly “We suffer more in imagination than in reality” and this fact holds its relevance for many millennia (Seneca, Campbell, 1969). Lowenstein (1987) in his highly influential paper established a model of utility by incorporating Jevon’s anticipal pleasure and pain into the standard utility model. In Lowenstein’s model, anticipation itself is a source of utility along with consumption. When anticipation is a source of utility, the effect of delay on the value of an object can diverge from the prediction of existing theories. However, there are other aspects of decision-making under uncertainty that are impossible to be captured by expected utility models. Our anticipal pleasures and pains do not only depend on our own decision but also on behavior of others. A mother’s anticipated feeling of her daughter’s graduation not only depends on her devoted income to her daughter’s education but also on her daughter’s cognitive abilities and many other things gained throughout her daughter’s education. Savings or the amount unconsumed, is also derived from the discounted utility models in the economics literature. Permanent income hypothesis and life cycle theories of savings predict that individuals’ saving behavior depends on their levels of income and after retirement, a temporary period of dissaving occurs. After this brief period, however, retired individuals typically increase their rate of saving and continue to accumulate wealth until they die (Modigliani, 1986). Lowenstein explains the empirical failure of dissaving behavior after retirement and the general declining rate in saving assumption of permanent income hypothesis through the perspective of anticipation (Lowenstein, 1987). According to Lowenstein, “retirement for the young is a non-vivid event – perhaps partly because thinking about old age is aversive and tend to be avoided. Young middle aged couples and individuals, possibly for this reason, often ‘live like there’s no tomorrow’. As retirement approaches,
141 ANTICIPATION however, the prospect of having inadequate funds for retirement becomes increasingly vivid and causes anxiety that can be relieved in part by stepping up savings. The onset of retirement itself, and the sudden loss of wage income, of course, greatly increases this anxiety for the future. This anxiety raises the returns of saving in terms of anxiety reduction and counteracts the savings-discouraging effect of the loss of income upon retirement” (Modigliani, 1986, pp. 666-667). One other problem of the intertemporal choice functions is the assumption of steady state life span. According to this hedonic treadmill model, good or bad events’ effects on happiness (or in our case utility) is temporary so no matter what happens to them people will turn back to their “normal” level of happiness. In other words, when some kind of traumatic event happen in your life such as divorce or death of a loved one, this does not change your utility function in the long run. You come back to original point of wellbeing after adjustment. This is a controversial subject among economists and it does not even seem reliable from a psychological or social understanding. An illuminating example may come from the case of unemployment, where people do experience anticipatory bad feelings before they are being laid off and unemployment does not affect their consumption choices through income effect but through psychological process of anxiety, sadness and hopelessness. Anticipation of unemployment and pessimism about earning much less income in the future results in a shift in consumption habits long before unemployment and a continuing tendency to spend less in the future. In 1979, Kahneman and Tversky published a paper entitled “Prospect Theory” that offers a framework for how people frame economic outcomes as gains and losses and how this framing affects people’s economic decisions and choices. Prospect Theory, or the idea that people dislike losses more than they like equivalent gains, is consistent with many observed biases that traditional models of utility and risk aversion cannot explain (Kahneman and Tversky, 1979). Kahneman and Tversky showed that non-rational behaviors could be identified and predicted.
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2.2. Anticipation in Public Economics Almost every economic intervention occurs through government policy via price intervention and regulation. The governments seek to decide on the most effective and fair fiscal policies. However, these fiscal policy decisions are ex ante decisions. The resulting effect of any policy before it is implemented could only be estimated. Fiscal policies - whether expansionary or contractionary - change societies’ consumption and production levels, yet policy makers would want to implement the optimum policy to eliminate possible offsetting. For instance, announcement of a contractionary fiscal policy such as a tax increase creates the expectation of higher price levels and consequently increase the current consumption levels. Anticipation has a specific role in the existing Public Economics Literature. For example, in tax policy implementations, it is known and widely accepted that individuals will always choose to act in their own best interest. Along with their adaptation capability, if people have perfect anticipation skills, this in turn may result in a tax policy to become ineffective. Aronsson and Schöb (2012) analyzed the role of this anticipation bias in optimal income tax theory. In this sense when a tax is imposed, anticipation bias is assumed to lead the consumers to underestimate the extent to which they will adapt to changes in consumption in the future and therefore a tendency to overestimate the future marginal utility of consumption. In other words, if there exists an anticipation bias, any discretionary fiscal policy would not be much effective in terms of diminishing aggregate consumption. Their analysis suggests that to correct for this anticipation bias governments could use marginal labor income taxation and saving subsidies. In other words, to correct for the effects of anticipation bias, the optimal tax policy includes labor income taxes implemented for the young and the middle-aged yet at different marginal rates - in combination with a marginal savings subsidy implemented for the middle aged (Aronsson and Schöb, 2012). Any expansionary fiscal policy is also not always as effective as anticipated by the policymakers. Along with the other factors, one obvious reason is the anticipation of the taxpayers about the duration of
143 ANTICIPATION the crisis or recession. Policy makers, along with economists, oversee the physiological and social dynamics of the system during a crisis. Recent and widely popular example about the controversy over the effectiveness of fiscal policy could be a fiscal program of the United States during the president Barack Obama administration which is the economic stimulus package of American Reinvestment act in February 2009. Although it is still being argued whether these programs were effective in terms of overall effectiveness, the implemented tax-cut failed to increase consumer spending. Taylor (2011) empirically examine the direct effects of the three countercyclical stimulus packages of the 2000s and find that these packages did not have a positive effect on consumption and government purchases, and thus did not offset the decline in investment during the recessions. An expansionary fiscal policy such as a tax-cut is expected to increase disposable personal income and thereby stimulate consumption that will in turn increase GDP. One fundamental problem with this approach is the omission of economic agents’ level of confidence to the policy. During a recession, people do not change their consumption or saving behavior just because there is a temporary tax-cut. The problem is that, because people living in fast-growing economies expect their future income to be larger than their current income, and should therefore be borrowing to finance their current expenditures, people in slow-growing economies anticipate that they may need to save more if they wish to maintain their current standard of living in the future. During recession, there is always a tendency to save instead of consume. Carrol and Weil (1994) find that households with predictably higher income growth save more than households with predictably low growth. They argue that their finding is an evidence for consumption should be re-modelled with habit formation instead of using permanent income hypothesis. Mertens and Ravn (2012) study the impact of tax liability changes. For each piece of tax legislation they define an announcement date and an implementation date. When the difference between these two dates exceeds 90 days, they assume that the tax liability change is pre- announced. They find that the economy reacts in a different way to
144 ANTICIPATION IN ECONOMICS pre-announced and surprise tax cuts: a preannounced tax cut with an anticipation horizon of 6 quarters gives rise to pre-implementation declines in aggregate output, investment and hours worked. In contrast, aggregate consumption is hardly affected by the announcement. Malani and Reif (2015) also estimated anticipation effects in a public economics framework. According to their finding, interpreting pre- trends as evidence of anticipation increases the estimated effect of tort reforms by a factor of two compared to a model that ignores anticipation. In other words, physicians’ anticipation of a policy changes their behavior ex ante.
3. Anticipation and Macroeconomics In economics, whether they consume or invest, individuals are forward looking agents and their expectations about future affect their current behavior. In microeconomics, anticipation plays a role through consumption, individuals consume according to utility or what we may call their overall satisfaction along with their anticipated wealth and/ or income. In macroeconomics, on the other hand, anticipation plays a crucial role in determining the investment decision. Economic system needs investors to supply input for firms to use this input to produce output. Along with the detailed assumptions in different theories of macroeconomics, two distinctive issues of the theories stand a side. The first issue is about whether the processes should be intervened or not. Classical theory and its followers mainly do not suggest intervening the system. The second issue is about the rationality assumption. If all economic agents act “rationally”, markets will eventually clear and there is no need for government intervention. Throughout the history of economics and especially during the last two centuries, a reasonable doubt has accumulated about the economic rationality of individuals. Becker (2013) had clearly shown the ambiguity and irrelevance of the rationality assumption in the science of economics. Becker (2013) posits a competing assumption of “fictional expectations”. There are mainly two types of expectation theory used in the theory
145 ANTICIPATION of economics, which are namely adaptive expectations theory and the rational expectations theory. The adaptive expectations theory is based on the assumption that people make forecasts of future values of a variable using only the past values of that variable. In rational expectations theory, on the other hand, it is assumed that people make forecasts of future values of a variable using all available information. Hence the assumption formally states that people’s expectations equal optimal forecasts where all available information are used. Alan Greenspan (the former chair of the Federal Reserve Board) in his 1996 speech used the term “irrational exuberance” to describe the irrationality of stock market investors. The speech and the term had gained great popularity even decades after the speech. The term “irrational exuberance” is still used to describe the situation when markets have been bid up unusually high and unsustainable levels under the influence of market psychology. 60 years after Keynes (1936) the animal spirit had become popular again. In the General Theory of Keynes, the investment decisions of investors are derived with animal spirits - a spontaneous urge to action rather than inaction, and not as the outcome of a weighted average of quantitative benefits multiplied by quantitative probabilities. Further, Keynes in General Theory (1936) implies that if people act thoroughly rational, they would be paralyzed into inaction because they just don’t have the necessary information. People don’t know the kind of things that you would need to put into a decision-theory framework. However, they do act, and so there is something that drives people, and As Keynes puts it, is called animal spirits (Keynes, 1936).
3.1. The role of anticipation in business cycles Business cycle is defined as the periodic fluctuations in the general rate of economic activity, as measured by the levels of employment, prices, and production. It is the main interest of the most macroeconomists around the world. They, for example, want to explain why in some periods the output declines and unemployment rises. Likewise, they want to understand why these rates differ not only through time but also between the countries.
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The two obvious characteristics of business cycles are fluctuations in unemployment and output. Level of unemployment and output are affected from the societies’ view on the magnitude of these fluctuations. In other words, economic agents’ anticipation to changes in economic environment does affect the actual change. The idea of business cycles driven by expectations can be traced back to old publications such as that of Pigou (1927). According to Pigou, the very source of fluctuations is the wave-like swings in the mind of the business world between errors of optimism and errors of pessimism. This view is also closely related to Keynes’ (1936) notion of animal spirits as it relates to these waves of optimism and pessimism as important driving forces behind economic fluctuations. The literature in business cycles is divided in terms of how do the expectations are formed. On one side, following the neoclassical approach assumptions, Real Business Cycle models are based on the rationality axiom. On the other side the opponents claim that economic agents do not act rationally during these fluctuations and some form of intervention is needed. This section of the paper examines how agents’ expectations, whether rational or irrational, change the economic outcome in terms of unemployment and output. The neoclassical version of the business cycle models can be summarized underneath Real Business Cycle (RBC) Models. The RBC theory of business cycles has two main principles. First, following the classical theory on neutrality of money, money has a very limited effect in business cycles. Second, business cycles are created by rational agents who respond to fluctuations in productivity, government purchases, import prices and preferences in an optimal manner. The most well known paper in the Real Business Cycles (RBC) literature is Kydland and Prescott (1982). Real Business Cycle models unlike Keynesian approach, advocates that the government shouldn’t do anything about the business cycle. If people aren’t working because there is a recession, this is an efficient response to present low productivity. In other words, they will not get paid as much as they work. People take time off when productivity is low
147 ANTICIPATION and work harder when productivity is high (Akerlof and Shiller, 2009). The literature against the relevance of the real business cycle models would be outlined in this section. One of the alternatives of real business cycle models is the news view of business cycles. News business cycle models stress the importance of the society’s ability to anticipate to future economic outcomes. These models suggest that recurring boom periods that are higher than average growth in investment, consumption and employment are followed by an opposite period of depression and are mainly the result of agents having incentives to continuously anticipate the economy’s future demands. In other words, booms arise mainly as the result of speculation; that is, booms are not initially driven by simultaneous changes in technology or preferences but instead are driven by agents’ anticipation of the economy’s future developments. If agents get news regarding potential technological change in some sector of the economy, then they may want to take advantage of such news in at least two ways. First, they may want to directly invest in the sector being affected by the change, or, alternatively, they may want to invest in complementary sectors that will benefit only indirectly from the change (Beaudry and Portier, 2007). News driven business cycle models distinguish anticipation from rationality. Economic agents form their optimistic or pessimistic expectations based on the information they gather in social surroundings, but they cannot always perform on anticipating. A boom driven by a wave of optimism arises when agents have gathered information suggesting that future fundamentals favor high investment demand today. If their information is valid and expectations are realized, then the boom may not be followed by a crash. In contrast, if agents have made an error and have been overly optimistic, then there will almost certainly be a crash. This type of recurrent boom and occasional bust phenomena, driven by information and possible errors, is the defining property of news-driven business cycles (Beaudry and Portier, 2014). Bruckner and Papa (2013) provide an interesting example of speculative cycles. They examine the macroeconomic effects of bidding for the Olympics using panel data for 188 countries during the1950 - 2009
148 ANTICIPATION IN ECONOMICS period. News about the Olympics makes output and investment increase even at the time of the bidding. In unsuccessful bidding countries, the agents’ optimism turns out to be unfounded and, as a result, the economy returns to its original trend, while hosting economies enjoy quantitatively large and significant positive effects from hosting (Bruckner and Pappa, 2013). Another outstanding example of a speculation driven cycle could be the IT boom of 1990s. The dotcom bubble occurred in the late 1990s, and was characterized by a rapid rise in equity markets driven by investments in Internet-based companies. During the dotcom bubble, the value of equity markets grew exponentially, with the technology-dominated NASDAQ index rising from under 1,000 to more than 5,000 between 1995 and 2000. The dotcom bubble grew out of a combination of the presence of speculative or fad-based investing, the abundance of venture capital funding for startups and the failure of dotcoms to turn a profit. Investors poured money into Internet startups during the 1990s in the hope that those companies would one day become profitable and many investors and venture capitalists abandoned a cautious approach for fear of not being able to cash in on the growing use of the Internet. Housing price dynamics are examples of news driven business cycles, in which agents not always act rationally. The U.S. mortgage crisis of 2007– 10 stemmed from an earlier expansion of mortgage credit, including to borrowers who previously would have had difficulty getting mortgages, which both contributed to and was facilitated by rapidly rising home prices. New financial products were used to apportion these risks, with private-label mortgage-backed securities (PMBS) providing most of the funding of subprime mortgages. The less vulnerable of these securities were viewed as having low risk either because they were insured with new financial instruments or because other securities would first absorb any losses on the underlying mortgages (DiMartino and Duca 2007). This enabled more first-time homebuyers to obtain mortgages (Duca, Muellbauer, and Murphy 2011), and homeownership rose. This induced expectation of still more house price gains, further increasing housing demand and prices (Case, Shiller, and Thompson 2012).
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Optimistic news raises economic agents’ expected future net worth, expands their borrowing capacity, and allows them to purchase more housing and consumption goods. Higher housing demand raises housing prices and creates a housing boom. Soo (2013) develop a measure of sentiment across local housing markets by quantifying the positive and negative tone of housing news in local newspaper articles. She finds that this housing sentiment index forecasts the boom and bust pattern of house prices at a two year lead, and can predict over 70 percent of the variation in aggregate house price growth. Exploring further the interaction between anticipation and social learning will likely give new insights about how dispersed information regarding the future evolution of the economy may affect anticipated response of economic agents and thereby cause macroeconomic fluctuations.
3.2. The role of Anticipation in Financial Markets Expectations also play a crucial role in financial markets because many transactions require participants to forecast the future. For an individual considering taking out a mortgage loan in which she agrees to pay a fixed interest rate for many years, she needs to forecast such things as: the future income, the future inflation rate and even she needs to estimate the future of the neighborhood the house is in. How people construct their expectations in financial markets can be explained by two distinct theories. Between the two main expectations theory, the rational expectations theory is the widely accepted tool in financial markets. Adaptive expectations theory is not so accepted since it assumes that people ignore information that would be useful in making forecasts. Muth (1961) proposed the theory of rational expectations and argued that someone who did not use all available information would not be acting rationally. For instance, in forecasting the price of a firm’s stock, investors should use not just the past prices of the stock but also any other information that would affect the future profitability of the firm, such as the quality of the firm’s management, new products the firm might be developing, and so on. In other words, if enough
150 ANTICIPATION IN ECONOMICS investors and traders in the stock market have rational expectations, the market price of a stock should equal the best guess of the present value of expected future dividends, which is the stock’s fundamental value. Years after, however, Muth came up with a “revised” form of rational expectations theory. Muth (1985) examines the forecast performance of different expectation approaches on a firm’s production outcomes and he concludes as: “The results of this analysis do not support the hypotheses of the naïve, exponential, extrapolative, aggressive or rational models. Only the expectations revision model used by Meiselman is consistently supported by the statistical results” (Muth, 1985, p 200). What Muth calls expectations revision model, is however, the equivalent of adaptive expectations theory that is believed by many economists today that it is not a better measure than rational expectations. The application of rational expectations is known as the efficient market hypothesis (EMH) - that the equilibrium price of a security is equal to its fundamental value. With respect to the stock market, the efficient market hypothesis states that when investors and traders use all available information in forming expectations of future dividend payments, the equilibrium price of a stock equals the market’s optimal forecast of the stock’s fundamental value. Although the efficient market hypothesis indicates that the price of a share of stock is based on available information, any random observation of a price of a stock in the market will show that the prices of stock will change day-to-day, hour-to-hour, and minute-to-minute. Anything that affects the willingness of investors to hold a stock or other financial asset affect’s the stock’s fundamental value. A rather naïve assumption of efficient market hypothesis is that all information is publicly available. A key implication of efficient market hypothesis is that stock prices are not predictable. Since any stock’s optimal forecasted price would be equal to its present price, the future price of the stock should not change. Rather than being predictable, stock prices follow a random walk, which means that on any given day, they are as likely to rise as to fall. Probably the most straightforward and yet striking argument against the efficient market hypothesis is stated by Malkiel (2012) who said: “On Wall Street,
151 ANTICIPATION the term ‘random walk’ is an obscenity. It is an epithet coined by the academic world and hurled insultingly at the professional soothsayers. Taken to its logical extreme the theory means that a blind folded monkey throwing darts at newspaper’s financial pages could select a portfolio that would do just well as one carefully selected by the experts”. Further, Nobel Prize winner Robert J. Shiller has also criticized the EMH for being “the most remarkable error in the history of economic thought” (Shiller, 1989,pp 8).
3.3. Economic Growth, Technological Change and Anticipation Technology is a determinant of the production function in economic growth theory models. In the general Solow model, total production is formulated to be a function of physical human capital and technology (Solow, 1957). In its simplest form, the model is as follows:
Yt = AF (Kt , Lt)
where Yt is total output/income produced at time t, A is exogenous technology, Kt is the physical capital at time t and Lt is the labor force at time t. However, the interaction between the technology and labor productivity in this general model is not established. This traditional view of technology in economic theory (gradual continuous and homogenous technical progress) fails to explain key aspects of economic growth. This is perhaps because Solow did not anticipate the tremendous technological breakthrough in the last half-century. As clearly demonstrated by Aures (2005), there are two different modes of technical progress: Normal Mode - a gradual improvement when technological improvements occur incrementally as a result of accumulated experience and learning, and Technological breakthrough - the radical improvement mode when a radically new innovation is capable of displacing all older competing technologies. The radical innovations are necessary for continued long term economic growth. The steam engine, electricity, computers are examples of such dramatic technology shifts. The IT revolution is also accepted as a breakthrough (Martinez et al., 2010).
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Greenwwod and Yorukoglu (1997) while explaining the US productivity slowdown in the mid-1970s, mentioned an unanticipated permanent increase in the technological change rate in 1974 and concluded that, the technological advances unexpectedly caused the productivity slowdown mainly because of the costs of learning and adoption of recent technologies. Martinez et al. also list economic evidence of substantial short-run negative effects until new IT equipment is completely adopted by the industry (Martinez et al., 2010). Hritonenko and Yatsenko (2010) analyzed the optimal capital replace of vintage capital during technological shocks. Their analysis shows that the optimal investment is zero immediately before and after a technological breakthrough - a direct anticipatory effect. In other words, there is a sharp decline in investment, output and employment right before and after a technological shock because agents anticipate higher returns in the future and prefer to take no action during a technological breakthrough. Their results indicate the existence of certain fundamental anticipatory property in economic systems. Chow (2012) after decades of work on expectation based theories concluded expectation dilemma in his own words as follows3:
“For the purpose of finding good proxies for psychological expectations as required in the study of economic behavior, adaptive expectations should be used whenever the economist believes that the economic agents in question form psychological expectations by taking a mean of past values with geometrically declining weights. He should use rational expectations if he believes that his econometric model can generate mathematical expectations that are closer to the psychological expectations of the economic agents than the adaptive expectations can.” (Chow, 2011, pp. 5)
For expectations to reflect reality as in anticipation, expectation- based studies should use both forecast and foresight (Poli, 2017). From
3 See Chow 1957,1989,1997,2007 for example
153 ANTICIPATION this perspective, adaptive expectations fit the economic agents’ behavior better than the rational expectations. However, foresight of the agents is a topic that should be elaborated in further studies. Although the effects of anticipation are clearly important in the field of economics, there is considerable conflict and ambiguity in economic theory of how the anticipation of future events are formed and in what ways they affect economic outcomes. Here we can clearly argue that the formation of expectation and modelling must be handled with a multidisciplinary approach and a new way of economics should be based on this path. Ehrig and Jost (2012) argue that the formation of expectation can be examined as a game-like situation of mutual anticipation of economic agents if there is uncertainty about the actions of other economic agents. Uncertainty about the actions of the other agents arises because markets are complex, and agents mutually anticipate each other. Under this uncertainty the price changes can be caused by the changes in standard variations of demand and supply as well as by the changes in the expectations of other agents. Separation and evaluating these two independent effects are necessary to express these two phenomena in a mathematical formulation is needed.
3.4. Estimation of Anticipation There are two main difficulties in estimating models with anticipation effects. The first is the period selection for anticipation effect is assumed to take part in. In microeconomics literature, commonly used method is to use a “quasi myopic” model that includes anticipation terms for a finite number of periods. In this method, anticipation effects are estimated in a non-parametric manner. An alternative way of selecting the period needed for anticipation to effect is to posit outcomes as a function of exponentially discounted expectations about future output. This method is mainly called exponential smoothing and is commonly referred in finance and macroeconomics literature. Exponential discounting use differencing which makes it possible to estimate but also eliminates nearly all anticipation terms. Examples include, but not limited to, R&D
154 ANTICIPATION IN ECONOMICS decisions, present value asset pricing models (Chow, 1989), investment in human capital (Ryoo and Rosen, 2004) and pricing of durable goods (Kahn, 1986). Second difficulty of estimation of anticipation effect is that “anticipation” is mostly unobservable and heterogeneous. As in the example of saving decisions, elderly have different anticipation of wealth than younger adults. The heterogeneity of how economic agents anticipate makes it difficult to construct a model. Criticism against behavioral economics in economic literature arises from the same problem. Economics deal with millions of participating agents and aggregation is crucial for the analysis of the system. A multidisciplinary approach with sociology to aggregation could open new avenues for anticipation modelling.
4. Conclusion Anticipation plays a crucial role in both micro and macro perspectives of economic actions. This Chapter outlined the different branches of economics focused on the future motivation of the economic agent’s behavior. The rationality assumption in mainstream economics permits the application of maximizing methods from mathematics and provides an eligible framework for empirical validation. Throughout this Chapter we outlined the alternative sets of orthodox economic theory assumptions that apply to both macro and microeconomics issues. We tried to show in which ways the assumptions fail. Our analysis demonstrates that these failures are mostly due to the nature of these assumptions. Policy makers should anticipate all economic agents’ ex ante behavior to policy implication, which are mostly the root cause of failure. As the development of economic theory during the past 200 years has demonstrated, economists mostly fail to anticipate how the economic agents would respond in different scenarios. In an evolving world along with the society and institutions, the starting point for economists and policy makers would be to start from the beginning and questioning all the assumptions. Models are crucial for economic analysis and some form abstraction is necessary, but failing to include fundamental forces of the system such as anticipation leaves the economist to forecast a
155 ANTICIPATION hypothetical future that does not exist. This study outlays the need for the forward-looking economic studies to develop an understanding and motivation for anticipation analysis with the other fields of social sciences like psychology, sociology and mathematics. Mathematical computation of the models and estimation techniques requires the similar co-operative studies with the scholars of the sociologists, psychologists and futurists. Further studies could focus on the specific areas such as modelling and estimation of anticipation and incorporating anticipation as an input factor to business cycle models.
References: Aggarwal, R., (2014), “Animal spirits in financial economics: A review of deviations from economic rationality”, International Review of Financial Analysis, Vol. 32, pp. 179-187. Akerlof, G. A. (2007), “The Missing Motivation in Macroeconomics”, American Economic Review, 97(1): 5-36.DOI: 10.1257/aer.97.1.5. Aronsson, T. & Schöb, R. (2012), “Adaptation, anticipation-bias and optimal income taxation”, Discussion Papers 2012/13, Free University Berlin, School of Business & Economics. Autor, D., Donohue, J. and Schwab, S. (2006), “The costs of wrongful- discharge laws”, Review of Economics and Statistics, Vol. 88(2), (May), pp. 211–31. Beckert, J. (2013), Imagined futures: fictional expectations in the economy, in “Theory and Society”, 42 (3), pp. 219-240. Beckert, J. (2014), “Capitalist Dynamics: Fictional Expectations and the Openness of the Future”, Working Paper, MPIfG Discussion Paper 14/7. Beaudry, P., & Portier, F. (2007), “When Can Changes in Expectations Cause Business Cycle Fluctuations in Neo-Classical Settings?”, Journal of Economic Theory, Vol. 135, pp. 458-477. Beaudry, Paul, & Portier, F. (2004), “News-Driven Business Cycles: Insights and Challenges”, Journal of Economic Literature, 52, No. 4, pp: 993-1074, http://www.jstor.org/stable/24434169. Burton, G. Malkiel (1973), “A Random Walk Down Wall Street”, W. W.
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7
ANTICIPATION IN FINANCIAL MARKETS
M. Cihan Akın
Abstract Anticipation science, also known as the science of decision-making, is a new emerging field of research that aims to formulate a well-defined theoretical basis for the analysis of anticipatory systems. Anticipation as a term by itself is defined as all“ forward-looking attitudes and activities” and hence implies a present action based on a foresighted future (Poli, 2017). An anticipatory system is defined as a“ system containing a predictive model of itself and/or of its environment, which allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant” (Rosen 2012, pp.313). Economic theory of financial markets by purpose aims to be an anticipatory system. In financial markets many transactions require participating agents to forecast the future. To maximize their utility, agents estimate a difference between the present value and the future value of any financial security, and then make a decision based on this estimation. Anticipatory mechanisms in financial markets can be best understood and improved upon analyzing the determinants in decision- making process of these agents. The aim of this chapter is to study the existing economic theory of financial markets and demonstrate how a multidisciplinary approach to anticipatory behavior of the market participants can enrich the present economic thinking.
I. Introduction Analysis methodology for forecasting the direction of prices varies greatly by their fundamental assumptions. Technical analysis methods form optimal decisions by an estimate of a future price. Mean-variance Analysis suggests an asset’s value should not be assessed by itself but
161 ANTICIPATION can be assessed by how it contributes to a portfolio’s overall risk and return. Efficient-market Hypothesis on the other hand dictates prices already reflect all available price altering information, hence an investor cannot raise their utility by making timely decisions. Wide variety of beliefs and contradicting methodology used in price estimation has created many controversies covering some of the most fundamental questions regarding how financial markets operate. Such as: what causes fluctuations in the price of assets? The lack of solid theoretic foundation in this area becomes further apparent with the inconsistent approximation accuracy of these diverging methods. While “the market has already been “human- factors-engineered” to function remarkably well” (Shiller, 2013), the lack of understanding of the financial market events such as price bubbles, price volatility etc. further demonstrates the necessity for better refined theoretical framework and improved prediction models.
II. Rationality Axiom and Efficient-market Hypothesis Most of the forward-looking theory in economic research inherits assumptions of an ideal world for analysis and keep all the other factors that might influence the result constant. One of the majorly accepted financial models which is fundamentally built on the rationality axiom is the Efficient-market Hypothesis. Efficient-market hypothesis maintains that prices have a rational basis in terms of fundamentals like the optimal forecast of earnings, or assessments of the standard deviation of risk factors facing corporations. The initial assumption is that the agents have perfect knowledge of market regarding any information that may have an effect on future prices. Then the following main implication is that these Agents act in perfect efficiency within the market. In this ideal world, markets always clear and assets prices fluctuate around their real value. Because prices are rationally determined, they are changed from day to day primarily by genuine news, which is by its very nature essentially unforecastable. This assumption suggests that because all the markets efficiently incorporate all public information, every asset in the market is at its fair value at
162 ANTICIPATION IN FINANCIAL MARKETS any given time. There are no opportunities for investors to purchase undervalued stocks or sell stocks for inflated prices, hence it is impossible to “beat the market” by outperforming the overall market through any means of stock selection or market timing. Efficient-market hypothesis has been, both empirically and theoretically, disputed by investors and researchers. Imperfections in financial markets are attributed to a combination of cognitive biases such as overreaction, overconfidence, representative bias, information bias, and various other predictable human errors in reasoning and information processing. These issues have been researhed by psychologists such as Daniel Kahneman, Amos Tversky, Richard Thaler and Paul Slovic. The errors caused by these issues in reasoning lead most investors to avoid value stocks and buy growth stocks at expensive prices, or sold stocks at bottom values in overreactions. These observations form the basis of arguments against the rationality axiom and efficient-markets hypothesis.
III. Role of Psychology in Financial Markets & Behavioral Finance While widespread acceptance of the behavioral finance and the notion that markets are also substantially psychology driven came into attention only in recent decades, there are examples of implementing behavioral psychology into economic thinking. One of these observations is Adam Smith in his book “The Theory of Moral Sentiments” where he reflects morality issues a person may face in the chase of personal interest and he questions because of this conflict, whether individuals actually act solely upon personal interest and utility, or if there are moral sentiments involved in their behavior? Role of the irrationality in a financial market manifests most obviously during events of financial manias, such as bubbles. Nobel Prize winner Robert J. Shiller has defined financial bubbles as such:
“A situation in which news of price increases spurs investor enthusiasm which spreads by psychological contagion from person to person, in the process amplifying stories that might justify the price
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increase and bringing in a larger and larger class of investors, who, despite doubts about the real value of the investment, are drawn to it partly through envy of others’ successes and partly through a gambler’s excitement.”
This definition suggests an epidemic nature of irrational behavior, emotional involvement in decision-making and spread of imperfect information through media. While there is no easy method for measuring the extend of this behavior, during manias this kind of behavior in agents can be observed. There are models of behavior that replace the assumption of rational expected-utility-maximizing agents with alternative models, such as Prospect Theory. Prospect Theory developed by Daniel Kahneman and Amos Tversky in 1979, which later on formed the founding theory of behavioral economics and of behavioral finance, suggested that an agent’s anticipations on financial markets work not just by future expectations, but also work on biases built upon previous experiences and perceptions. Extend of the effects of these biases depend on the accumulated severity of the experiences it was built on. For example, an investor who has been successfully through a small scale volatile fluctuations of the market may develop a false sense of personal skill. Sense of security caused by such belief may inhibit rational judgement and lead to irrational actions. In another case, a series of unsuccessful anticipations may result in extreme pessimism towards the future trends. Psychologists have documented “A tendency for people to anchor their opinions in ambiguous situations on arbitrary signals that are psychologically salient even if they are obviously irrelevant” (Shiller 2013). Another example research on the subject (Ulrike Malmendier, University of California, Berkeley, and Stefan Nagel of Stanford University Graduate School of Business) indicates that investors’ willingness to participate in the stock market is affected by the margin of returns they have acquired from their participation in market. They found that even decades after a long downtrend, investors whom remained invested in the market through that period and suffered losses were more
164 ANTICIPATION IN FINANCIAL MARKETS reluctant to invest in the present stock market than first time entries. Similarly, investors who were in during an uptrend market and made significant profits were willing to make investments of larger scale in the same market. All these examples suggest that psychological pressure on anticipatory mechanisms create distance from the rationale norm of financial markets. The discipline of psychology offers many other principles of human behavior that have been shown to be relevant for evaluating the financial markets.
IV. Conclusion Anticipation plays a crucial role in decision making of individuals in a financial market and it is best studied from a multidisciplinary approach. Most of the forward-looking theory in economic research inherits assumptions of an ideal world for analysis and keep all the other factors that might influence the result in ways that are hard to predict or measure, such as psychological factors. While the rationality assumption in mainstream economics permits the application of maximizing methods from mathematics and provides an eligible framework for empirical validation, the oxymoron of presuming “ceteris paribus” in an anticipating system and trying to predict the future from a narrowed perspective are crucial shortcomings of the present economic theory, evident by its inability to explain events such as financial bubbles and crises.
References Aggarwal, R. (2014) Animal spirits in financial economics: A review of deviations from economic rationality, International Review of Financial Analysis, Vol 32 pp. 179-187. Adam Smith, The Theory of Moral Sentiments (1759). Akerlof, G. A. 2007, “The Missing Motivation in Macroeconomics.” American Economic Review, 97(1): 5-36.DOI: 10.1257/aer.97.1.5. A. Kurov, R. Stan/ Journal of Banking and Finance 86 (2018), Monetary Policy uncertainty and the market reaction to macroeconomic news. Aronsson, T. & Schöb, R. (2012), “Adaptation, Anticipation-bias and
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optimal income taxation”, Discussion Papers 2012/13, Free University Berlin, School of Business & Economics. Autor, D., Donohue, J. and Schwab, S. (2006), “The costs of wrongful- discharge laws”, Review of Economics and Statistics, vol. 88(2), (May), pp. 211–31. Beckert, J. (2013), Imagined futures: fictional expectations in the economy, in “Theory and Society”, 42 (3), pp. 219-240. Beckert, J. (2014), Capitalist Dynamics: Fictional Expectations and the Openness of the Future, Working Paper, MPIfG Discussion Paper 14/7. Beaudry, P., Portier, F., (2007), When Can Changes in Expectations Cause Business Cycle Fluctuations in Neo-Classical Settings? Journal of Economic Theory, Vol.135, pp 458-477. Burton, G. Malkiel, A Random Walk Down Wall Street, W. W. Norton & Company, New York (2012) (First Edition, 1973). Browning, E.S. (July 31, 2007), “Reading market tea leaves”. The Wall Street Journal Europe, Dow Jones, pp. 17–18. Retrieved from: Technical Analysis, In Wikipedia. https://en.wikipedia.org/wiki/ Technical_analysis#Empirical_evidence Caplin, A., & Leahy, J. (2001), Psychological expected utility theory and anticipatory feelings, Quarterly Journal of Economics, 116(1), pp. 55- 79. DOI: 10.1162/003355301556347. Carroll, C.D., and D. N. Weil (1994), “Saving and Growth: A Reinterpretation,” NBER Working Paper No. 4470, September 1993, and Carnegie-Rochester Conference Series on Public Policy, 40: pp. 133-92, June 1994. C.G., Chow. 2011. “Usefulness of Adaptive and Rational Expectations in Economics”, CEPS Working Paper Series 5. Coglianese, J., D., L. W., K., L., and Stock, J. H. (2017), Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand, Journal of Applied Econometrics, Vol 32: 1–15. doi: 10.1002/jae.2500. Fisher, I., 1930, The Theory of Interest, As Determined by Impatience to Spend Income and Opportunity to Invest It, The Macmillan Company, New York. Gasteiger, E., Zhang, S. (2013), Anticipation, learning and welfare: The
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case of distortionary taxation. Journal of Economic Dynamics and Control. 39. . 10.1016/j.jedc.2013.11.012. Gunn, C., M., (2015), Animal Spirits as and engine of boom busts and throttle of productivity growth, Journal of Economic Dynamics and Control, Vol 57 pp 24-53. Gupta, Prashant & Mishra, Tapas & O’Leary, Nigel & Parhi, Mamata, 2015, “The distributional effects of adaption and anticipation to ill health on subjective wellbeing,” Economics Letters, vol. 136(C), pp. 99-102. Jevons, W.S.(1905), The Principles of Economics Macmillan and Co. New York. Kahneman, D. and Tversky, A., (1979), “Prospect Theory: An Analysis of Decision under Risk”, Econometrica, 47, issue 2, pp. 263-291. Köszegi, B. (2010), Utility from anticipation and personal equilibrium, Economic Theory, Vol 44 No 3, pp. 415-444.https://doi.org/10.1007/ s00199-009-0465-x Loewenstein G. (1987), Anticipation and the valuation of delayed consumption, The Economic Journal, Vol. 97, pp. 666–684. Modigliani, F. (1986), “Life Cycle, Individual Thrift, and the Wealth of Nations,” American Economic Review, American Economic Association, vol. 76(3), pp. 297-313.
Robin M. (1998), Psychology and Economics, Journal of Economic Literature, Vol.36, No.1, pp. 11-46. Samuelson, P.A. (1937), Some aspects of the pure theory of capital, The Quarterly Journal of Economics 51 (3), pp. 469-496. Shane, F., Loewenstein, G. and O’Donoghue T. (2002), “Time Discounting and Time Preference: A Critical Review”, Journal of Economic Literature, 40(2): pp. 351-401. Schwarts H. (2010), Does Akerlof and Shiller’s Animal Spirits provide a helpful new approach for macroeconomics? The Journal of Socio Economics, Vol. 39, pp.150-54. Taylor, J.B. (2011), “An Empirical Analysis of the Revival of Fiscal Activism in the 2000s”, Journal of Economic Literature, 49:3, pp. 686–702.
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Malani, A., Reif. J. (2015), Interpreting pre-trends as anticipation: Impact on estimated treatment effects from tort reform, Journal of Public Economics. Vol 124, pp. 1-17. Mertens K. & Ravn, M. O. (2013), The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States, The American Economic Review, 103 (4), pp. 1212-1247. Muth, J. (1985), Properties of Some Short-Run Business Forecasts, Eastern Economic Journal, 11(3), pp. 200-210. Retrieved from http://www.jstor.org/stable/40324984 Poli, R. (2014, Anticipation: What About Turning the Human and Social Sciences Upside Down? Futures, 64, pp.15-18. Rabin, Matthew (2013), “An Approach to Incorporating Psychology into Economics”, American Economic Review, Vol. 103(3), pp. 617-22. Ricardo, David (1817), On the Principles of Political Economy and Taxation, Piero Sraffa (Ed.),Works and Correspondence of David Ricardo, Vol. I., Cambridge University Press (1951). Rosen, R. (2012), Anticipatory systems: philosophical, mathematical and methodological foundations, 2nd Edition, Springer, New York, ISBN 978-1-4614-1268-7 Shiller, R. J. (1989), Market Volatility, The MIT Press, London, England, ISBN 0-262-19290-X Smith, A. (1904), An Inquiry into the Nature and Causes of the Wealth of Nations. Edwin Cannan, ed., Library of Economics and Liberty. Retrieved from the: http://www.econlib.org/library/Smith/smWN.html Smith, A. (1790), The Theory of Moral Sentiments, Library of Economics and Liberty. Retrieved from the: http://www.econlib.org/library/ Smith/smMS.html Solow, R.M. (1957), “Technical Change and the Aggregate Production Function”, Review of Economics and Statistics, Vol. 39, pp. 312-320. Von Scheve, C., Esche, F. & Schupp (2017), “The Emotional Timeline of Unemployment: Anticipation”, Reaction, and Adaptation Journal of Happiness Studies, Vol. 18, Issue 4, pp. 1231–1254.
168 8 ANTICIPATION IN MARKETING
Y. Can Erdem, Nihat Tavşan
Anticipation: A Marketing Perspective The overall objective of this chapter is to provide a general view of literature about the impact of anticipation on different marketing applications and to stimulate new thought about it. Due to its multidisciplinary nature, the phenomenon of anticipation has been explained by many different definitions done by academicians and practitioners from different fields such as natural and life sciences (Biology, Physics, Medicine, etc.), social sciences (Sociology, Psychology, Law, etc.), management disciplines (Management, Marketing, Finance, etc.) and arts/humanities (Architecture, Philosophy, etc.). In marketing literature, anticipation has always been one of the popular concepts studied for the analysis of consumer behavior, new product launch, sales and many other marketing applications. A conceptual definition of anticipation will help marketing academics and practitioners in further analysis of how to induce and enhance the anticipation of consumer behaviors. One definition of anticipation within the context of marketing is given as: “A consumer’s future-oriented behaviors aiming at securing desired outcomes which can take forms of cognitions, affections, and preparatory actions and are driven by uncertainty and importance of future events with the consequence of an increase of the valuation of consumption” (Vichiengior, T. & Ackermann, 2017). On the way to differentiate anticipation from other forward-looking constructs, what may be essential is to understand what it is not. Rosen and Kineman (2005) emphasized that anticipation occurs only if the future event is relevant to the subjects since they need to be involved in decoding external and internal related information in order to encode
169 ANTICIPATION the future and recent events. This, for example, is the major difference between anticipation and forecasting. From a marketing viewpoint, anticipation may be either passive or active (normative). In order to both identify and differentiate it from passive anticipation, Vichiengior & Ackermann (2017) both made a definition of normative anticipation and listed the characteristics of it: Relevancy - A high level of involvement (Rosen & Kineman), the need for stimulated cognitions for the important and relevant outcomes, the need for action to control and to secure the future. According to this normative definition, anticipation should be referred to as an active strategy both to avoid surprises and to increase the notion of security in achieving desired goals. Passive anticipation refers to the future states that “could be seen coming” with an effect on people so that they prepare and get ready for the approaching events. Izard (1977) asserted that surprise resulted when “a stimulus does not conform to expectations” (cited in Hutter & Hoffmann, 2014) and that one “could not have seen it coming” (Stanley, 2009). This notion makes “surprise” to be a natural component of passive anticipation. In the following sections anticipation in the marketing field will be analyzed with respect to a) consumer behavior, b) purchase decisions and emotions, c) new product launch process.
Consumer Behavior The contemporary marketing concepts like Customer Relationship Management (CRM) and Customer Experience Management (CXM) underline the fact that customers are considered as the strategic intangible assets of a firm and it is essential for institutions to develop the competency to anticipate customer value. The notion of Customer Value Anticipation (CVA), introduced by Flint et al. (2011) refers to a ability of a supplier to look forward at what specific customers will value from supplier relationships including their product / service offerings and the benefits they create given the monetary and non-monetary sacrifices to be made to obtain the benefits of the offering (p.219). Here
170 ANTICIPATION IN MARKETING what is important is to investigate the notion from the perspective of customers which is based on the perception of the customers regarding the suppliers’ ability to anticipate the needs of them if possible before they do. Zhang, Liang, & Wang (2016) investigated the relationships among customer value anticipation, customer lifetime value and product innovativeness from customers’ point of view. They found that customers’ perception of customer value anticipation can significantly impact product innovativeness and this association is partly mediated by product innovativeness. Besides, both practical and emotional advertising messages were found to have a moderating role in the association between product innovativeness and customer lifetime value (2016). Anticipation of future consumption is also a very relevant phenomenon that has been used by institutions to explain some key economic decisions like retirement planning and financial portfolio planning. The fact that consumers delay their pleasurable consumptions has been searched by many scholars but Lowenstein (1987) was the first one who, in his pioneering article, discussed a model that modified the Discounted Utility Theory by recognizing that anticipation, like consumption itself, was a source of utility (1987). He claimed that “waiting for consumption to occur can often be pleasurable or painful - indeed, that much of our feeling of well-being and despair arise from emotions associated with anticipation - seems self-evident” (p.678). Bilgin & Le Boeuf (2010) found that losses seem more forthcoming than gains, maybe because consumers often perceive themselves in an unhappy position of not only mourning an imminent damage but also perceiving it as happening rather soon (p.529). Caplin & Leahy, (2001) introduced the psychological expected utility model, and used it to analyze the impact of anticipatory feelings on decision-making. Chan et al. (2010) demonstrated that anticipation was short lived with evaluations following an inverted U-shaped curve. They showed that making a choice leads to anticipation if the delay is short. However,
171 ANTICIPATION when the delay is long, the positive impact of the choice does not last. Therefore, these findings of consumer behaviors are consistent with the Loewenstein’s anticipation model. In addition they illustrate both the perceived control in driving down the evaluation of long- delayed consumption and the moderating function of self-sufficiency of consumers. The final contribution of the study to the anticipation literature is that fundamental consumption motivation had a mediating impact on the observed impact. Kőszegi (2010) provided a framework for modeling and studying the consequences of utility from anticipation when it interacts with utility from physical outcomes. Kuznitz, Kandel, & Fos (2008) investigated the portfolio choice decisions of investors who enjoy not only current but also in consideration of future consumptions with a finding that deriving utility from anticipation of future consumption has an incredible impact on portfolio choice. Schubert (2012), in his popular article, stated that anticipating a prospect event or outcome that is expected to be enjoyable tends to create instant hedonic welfare. Furthermore, the anticipation is often even more pleasurable than the actual realization of the occurrence. This acknowledgement of “pleasures of expectation” dates back as early as 1789 when the founder of Utilitarianism, Jeremy Bentham included it as one of the fourteen pleasures that humans keep seeking since they precipitate happiness. Additional aged comments regarding the anticipation of future outcomes are what Tibor Scitovsky wrote in his remarkable books in 1976 and 1981: ‘being on the way to [our] goals and struggling to achieve them are more satisfying than is the actual attainment of the goals’ (Scitovsky, 1976, p. 62), for it is the struggle that may provide valuable stimulation and, if set under conditions of uncertainty, even ‘excitement’ (Scitovsky, 1981). Another major consumer issue associated with anticipation is “negative discounting” which states that consumers evaluate pleasurable delayed consumption better than immediate consumption because of
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“anticipation”. Le Bel and Dubé (1998) proposed that, “beyond the actual experience, consumers derive pleasure from anticipating and reminiscing about pleasant events”. In other words, the pleasure derived from the actual experience may be less than the total pleasure resulted from actual experience, its anticipation, and its memory since anticipation before consumption is considered as a major source of pleasure (Le Bel and Dubé, 1998). As the findings have shown, the anticipation and reminiscing phases of hedonic experiences are just as equally important as the consumption phase itself. Planning and supervising hedonic experiences calls for attention to each stage individually and to their connectivity (Le Bel and Dubé, 1998). The smart marketing and sales strategies built upon the consumer data regarding what consumers anticipate and take it into the experience, as well as for the process by which they build memories of their experiences can be extremely effective against competition. Recently, Chan and Mukhopadhyay (2010) have contributed to the knowledge of anticipation on consumer evaluation. They demonstrated that the value of both hedonic consumption and of the delayed consumption increased when the respondent consumers made their own purchasing decisions.
Purchase Decision and Emotions Purchase decisions are driven by both utilitarian and hedonic considerations. Consumers choosing among alternative brand/products care about utilitarian features (e.g., payment terms, price) as well as the hedonic attributes (e.g., color and design). Research suggests that these different considerations taken into account during the process of attitude formation and product evaluation enable customers to distinguish between goods/services according to their relative hedonic or utilitarian nature (Mano and Oliver 1993; Batra and Ahtola 1990). Being major constructs of hedonic decisions, emotions, in particular, deserve a special attention within the anticipation concept. Research in well-being and happiness demonstrates that anticipation of desirable goals creates a sense of current welfare through anticipatory emotions
173 ANTICIPATION and anticipated emotions (Schubert, 2012; Macleod & Conway, 2005; Gilbert & Abdullah, 2002; Loewenstein, 1987). There are attempts to separate anticipated emotions from anticipatory emotions. For example, Baumgartner, Pieters, and Bagozzi (2008) used certainty and uncertainty in future events to distinguish between anticipated and anticipatory emotions and their behavioral effects. According to the authors (2008), thinking about future events generates two kinds of emotions. Anticipatory emotions are affective reactions felt currently (Ortony, Clore, & Collins, 1990) because of the uncertainty of future events (Baumgartner, Pieters, and Bagozzi 2008; Lee and Qiu 2009; Moore & Lee, 2012). On the other hand, certainty of future events of imagined experiences results in anticipated emotions (Baumgartner et al., 2008). The findings of the research showed that both anticipatory and anticipated emotions motivated goal -directed behavior while motivational effects of anticipated emotions were stronger than those of anticipatory emotions. What is also interesting was the finding that the negative emotions were more powerful determinants of behavioral intention relative to positive emotions which is consistent with the finding that negative info often has more influential impact on information processing, persuasion and behavior than positive information (Tversky and Kahneman, 1981) For example, Gilbert and Abdullah (2002) conducted a research with two groups of respondents and found that participants who were waiting for their holidays (holiday-taking group) were happier with their life as a whole than those of non-holiday-taking ones although there was no significant change in their current economic situation. Simply put, the anticipation of a pleasurable event, the holiday trip/leisure travel in this case, had affected the hedonic level of the holiday-taking group. Moore and Lee (2011) investigated the influence of some specific features in determining the impact of some hedonic advertising messages on consumption instincts and found that the two fundamental reactions of the respondents were the AEs and taste anticipation. These responses are of major importance for advertising practitioners since each of them verified to be dominant mediators of the influence of hedonic advertising appeals on consumption. Taste anticipation in particular is
174 ANTICIPATION IN MARKETING a very definite symbol of the anticipated consumption experience and is based on the belief that people will be attracted to the alternative with the greatest personal anticipated enjoyment (O’Doherty et al, 2002; Rolls, 2005; Mellers, Schwarz & Ritov, 1999). Taste anticipation may be enriched by various inputs like multisensory bases such as the smell or color combination of a extremely preferred food (Elder and Krishna, 2010).
Purchase Intention The Research on emotions shows that consumers anticipate a range of combinations of emotions and this anticipation stage of emotional consequences impact the decisions (Patrick et al., 2009; Kahneman & Tversky, 1979). Termed the theory of anticipated emotions (AEs), it was found through an integration of studies that four AEs can function in decision-making; the findings herein largely confirm this. Bagozzi et al., (2016) made contributes to deepening how AEs function by reinterpreting the different theoretical approaches underlying AEs and by investigating their formation and participation in the purchase decision process in a commercial setting. Behaving in an anticipatory way means adjusting present behavior in order to address future problems. In other words, an anticipatory entity takes its decisions in the present according to forecasts about something that may eventually happen. The best-known definition of anticipation is Rosen’s: “An anticipatory system is a system containing a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant” (Rosen, 1985, p. 341).
New Product Launch The marketing practitioners would agree with the general proposal that the launch stage of new product development (NPD) process would be the most risky one because of unexpected reactions of the competitors and also of the financial risk involved. One of the leading scholars in the NPD research is Kim Schatzel. Her findings in 2003 indicated that the interest
175 ANTICIPATION and support of both existing and potential supply chain members like wholesalers, distributors and retailers are very crucial for the success of the process. The authors have studied the effects of Strategic Channel Activities Preannouncements (SCAP) in particularly at NPD stages in particularly B2B markets. The definition of SCAP in their writing state: “any formal communication by a firm that provides a direct or indirect indication of its motives, future intentions, goals, or internal situation concerning strategic channel activities” (Schatzel, Droge & Calantone, 2003). In 2006, Schatzel, and Calantone (2006) developed and tested a preannouncement behavior model with an impact on the performance of a new product launch through market anticipation, competitive equity, and new product development resources. The conclusions indicated that preannouncement behavior stimulates the success of new product through its encouraging influence on market anticipation and emphasizes the use of preannouncements as B2B marketing communications focused at manipulating existing and potential supply chain partners in the organization’s favor.
Discussion and Future Research On the previous sections the current research regarding the concept of anticipation in marketing has been listed in detail. Further research can examine whether the anticipation of emotions is related to other emotional clues in decision-making and/or purchase decision-making (Baumeister et al., 2007). Previous research shows that anticipated emotions (AE) are different from current emotions (e.g. fear and disgust) but it may be wise to search if AEs are connected with other types of future-oriented emotions, like anticipatory emotions (e.g., feeling anxiety experienced due to an anticipated upcoming issue (Baumgartner et al., 2008). Further research should address the relationship between AEs and consumer goals (e.g., social, cultural, environmental) since consumers prefer to focus on those that are more relevant for their future affective states (Baumgartner, 2008; Xie et al., 2013; Hetts et al., 2000; Zeelenberg et al., 1996).
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Anticipated Emotions and their function in behavioral decision practices arise as a very comprehensive field of research with many alternative ways for additional exploration such as customer experience management, advertising, experiential marketing etc. A more detailed attention should be paid to marketing strategies inspiring AEs motivating purchase decisions and reducing AEs demotivating non-purchase. Further research on the influence of AEs on the after purchase feelings are studied by Klaaren, Hodges, & Wilson, 1994 and the level of brand attachment by Proksch, Orth, & Cornwell, 2015. Tsai & Bagozzi found that attitudes and some other social variables like social identity, group dynamics and subjective standards have provided independent impact on purposes along with AEs (2015) and desires of customers have been shown to accomplish this function. A further research could investigate how these numerous sources of influence become integrated and transformed into decisions. (e.g., Bagozzi et al., 2006; Tsai & Bagozzi, 2015), Finally, it would be interesting to search for the techniques to improve the anticipation skills necessary in the world of marketing in general and the new product development in particular.
Conclusion Research on anticipated emotions imply that they do influence the individual decisions. The research by various scholars contributed to the knowledge that anticipations affect consumer behavior on the assumption that personal characteristics and other socio-economic variables may have an effect on this relationship. What is already certain is the fact that companies ought to not only be better than their competitors in creating what customers value but also need to be good at anticipating how those values will change in time. Developing an expertise in anticipating changes customers’ desired value may be a very unique competitive advantage. In global markets where expectations, preferences and even value systems of customers keep changing, this competitive advantage of anticipation skill is considered to be a great competency.
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Research in psychology confirms that anticipation skills can be learned /developed and are usually based on deeper learning of details related to the activity in question (Smeeton et al., 2005; Wofford & Goodwin, 1990). Therefore, it can be said that anticipation skills can and should be developed since the future of marketing is to be built upon the ability to understand and anticipate the consumer behavior.
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182 9 ANTICIPATION AND STRATEGIC DECISION-MAKING An Anticipatory Thinking Perspective
A. Gönül Demirel
1. Introduction In this chapter, Business Organisations are defined as Anticipatory Systems and a basic conceptual framework is proposed to define the Anticipation Capacity of a business organization seeking to make better strategic decisions. A survey was designed and conducted. The survey consisted of questions for assessing the understanding and perspectives of Top Executives related to the proposed conceptual framework. The received answers are evaluated and the findings are presented.
1.1. Business Organization as an Anticipatory System The concept of anticipation as a technical term has two meanings (Poli, 2017). One refer to “the distinct aspect of futures studies that goes beyond forecast and foresight modeling“ and the second meaning refers to “the qualifier “anticipatory” as in the expression “anticipatory systems”. In this study, the latter is employed. According to Poli, “Anticipation occurs when the future is used in action”. Hence, “A system behaving in an anticipatory way – an anticipatory system – makes decisions in the present according to ‘anticipations’ about something that may eventually happen in the future” (Poli, 2017). From the philosophical perspective, anticipation occurs in the spacious present (Husserl, 1991 as cited in Poli, 2009). Here the tendency is towards focusing in the present as the major time orientation. Today’s business organisations must monitor and foresight global market developments and act swiftly. This puts an extra burden on
183 ANTICIPATION business managers to anticipate their competitors’ future strategies and decide on their own counter strategies as fast as possible. Hence, anticipation capability is becoming more and more important for strategic decision-making processes. We may define a business organization as an “anticipatory system”. Strategic decision-making in business organizations is a subsystem process that requires anticipatory thinking within this system in the spacious present. Anticipation capability of an organisation requires a highly developed anticipation capacity. Anticipation capacity of an organization includes both the anticipatory thinking capacity of the management team that reflects intuitive and qualitative knowledge levels of the decision-makers plus the use of supporting system specific IT systems (e.g. MIS) for quantitative data. Therefore the level of analysis for such a perspective is meso-level. Anticipatory thinking is action oriented and hence, different from simple prediction of the future. It requires “active attention management, i.e. focusing attention which entails on likely sources of critical information” (Kline, Snowden, 2011). Action orientedness in present requires managers to have access to fast information processing within the organization as well as having highly developed intuitive and cognitive skills. We can say that anticipation is by nature embedded in the strategic decision-making process. In times of war, anticipating the moves of the enemy and in times of competition, anticipating the moves of the competitors are pivotal. Business and competitor intelligence stored on highly developed Management Information Systems (MIS) are the system specific requirements that are used by organizations for fast information processing capacity. Both system specific requirements and human cognitive elements should be considered for deciding on the right strategies through anticipatory thinking. Strategic anticipations also come from intuition that involves past experiences, inspirations, gut feelings etc. System specific requirements on the other hand requires access to necessary information to overcome (reduce) the inherent uncertainty during the
184 ANTICIPATION AND STRATEGIC DECISION-MAKING strategic decision making process. Here the sources of information such as the major stakeholders e.g. competitors, customers and suppliers are very critical. In such an approach to strategic decision making; stakeholder relationship management, analysis, rational decision- making and information processing approaches are important factors. On the other hand, we are in the information age heading towards a digital revolution. Rapidity characterizes our age and all relations of causality together with our perception of time and space has changed. Everything seems more complex and the information age has created a whole new kind of individual. People are exposed to every kind of information through the Internet and communication patterns have changed all over the globe. A reflection of this global change to business organizations is the pragmatic change in vertical and horizontal linkage systems in formal organisational structures. The definitions of formalization and specialisation are changing. Specialization today may be defined as the division of labor based on expertise and talent but it is also becoming more and more related with the capability and extent of the managers and other employees’ use of current technologies and data processing capacities. Decision-making role of the manager is getting more complex than ever. Making the best out of the present can only prepare people and organizations for the future but does not allow them to create it in a normative way. Manager needs to anticipate future and create visions by thinking more comprehensively in present. Overcoming uncertainty in such an age which is characterized by the speed of change especially in technology requires some very special human cognitive capacities like intuition capacity and much more complex human attitude like the capability of reorganizing and managing the changing time and space relationships. Among all these, the new decision-maker must also have a highly developed capacity of perception. Although in our proposed framework the strategic decision-making process in a business organization is an “anticipatory system” that involves both internal (cognitive) elements and external (critical stakeholders as
185 ANTICIPATION major sources of information) constituencies, how managers actually anticipate strategies is the major concern of this particular study. In order to explore how managers actually anticipate and decide on strategies in today’s rapidly changing business environment, the related literature is reviewed and an interview is performed with top managers (primarily CEOs) of several companies in varying sectors to have a prior understanding of how managers are actually anticipating strategies in the Turkish context.
1.2. Literature survey on how managers anticipate strategies The surveyed literature concentrates on the place of intuition versus rationality while top managers decide on their companies’ strategies. Omahe (1985) treats rationality and intuition as complementary and defines strategical decision-making as being intuitive and analytical at the same time. Numerous references, however, stress on the importance of intuition. A famous quote by G.Steiner (Mintzberg, 1994) states that “If an organization is managed by intuitive geniuses there is no need for formal strategic planning” (quote by G. Steiner in Mintzberg, 1994). Considering that geniouses are not too common, this quote can actually be seen to parallel Omahe’s (1985) proposition. Later example views of well-known top managers support these assumptions by indicating the place of intuition in anticipating strategies (Davidson, 2009): “Instinct can be just as important as data when it comes to making a truly innovative decision or taking a business risk” (Stelios Haji-Ioannou, CEO Easygroup; as cited in Davidson, 2009). “I can smell good and bad decisions. It is in my blood and I feel it in my stomach. When you make decisions every day you can’t always draw up a business plan” (Adidas CEO Herbert Hainer; as cited in Davidson, 2009). “You have to ask a lot of questions and listen to people, but eventually, you have to go by your own instincts” (Kerkor Kerkorian; as cited in Davidson, 2009). Mintzberg (1989) also undermined the rationality in strategic planning concept when he defined strategy as “a process of learning by
186 ANTICIPATION AND STRATEGIC DECISION-MAKING doing instead of a process of rational conceiving before doing” in his article “Rise and fall of strategic planning”. Thus Mintzberg introduced a kind of “action orientedness” to the literature that we discuss today within the framework of anticipatory thinking. On the individual level, anticipatory thinking is both intuitive and analytical or both subjective and rational. Three major approaches that managers can possess while making decisions are pure rationality, bounded rationality and intuition. Management Science approach is purely rational and is only applicable when problems can be fully analyzed where all the variables in question are clearly defined and measurable. Intuitive decision-making on the other hand is based on feelings and judgements. Pure rationality, however, has always been questioned by social scientists. Simon (1982) introduced the concept of bounded rationality for the decision-making process within organizations (Scott, 2015). Simon emphasizes that the human mind necessarily restricts itself, or, is bounded by “cognitive limits”. He states that people look for things that are good enough. He applied the idea to organizations as well as to individuals (Scott,2015). The Carnegie Model Research done by Cyert and March (1992) concentrates on who has the active role in strategic decision-making. The results indicate that on the organizational level decision-making, several managers are included into the process and the final decision is based on a coalition among those managers (Cyert, March, 1992). Organizational decision-making process is affected by several factors like the internal formal structure of the organization and the degree of uncertainty of the environment (Daft, 2001). Drucker (1994) emphasizes the need for increasing the firm’s capacity for strategic anticipation by preparing for difficult challenges in order to anticipate the changing environment. In Carnegie Model, for example, uncertainities that arise from limited information and the managers’ personal constraints are seen to force the organization towards a kind of cooperation for a satisficing solution (Cyert, March, 1992). Another approach developed by the same scholars (Cohen, et al. 1972) in order to help managers cope with uncertainty,
187 ANTICIPATION complexity and change while making decisions is the Garbage Can Model. The Model stresses the chaotic nature of decision-making and call the organizations where uncertainty is experienced at a very high level as “organized anarchies”. This typology represents a highly organic organization structure. In such a structure goals and problems are not clearly defined; cause and effect relationships are undefinable and there is no open data access for the related decision. When compared to these models anticipatory thinking as a decision making mechanism on the organizational level can be said to be more preventive of the problems in future by being more action oriented in present to foresee the future. In the next section a general conceptual framework is proposed and in Section 3 the opinions of some top managers within the Turkish business environment are sought for setting the preliminary stage of a qualitative and interview based theory for anticipation and strategic decision-making.
2. A Conceptual Framework of Anticipation Capacity The conceptual framework shown in Fig. 1 can be drawn to explain the anticipation capacity of an organization.
Anticipatory Thinking Capacity of the Organization (intuition + cognitive skills of managers)
Anticipation Capacity of Organizations
Organization System Specific Requirements (e.g. IT Systems, Data Access, Information Processing)
Figure 1. A Proposed Framework of Anticipation Capacity
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3. Interviews with Top Managers The interview sample consists of 13 multinational Companies from different sectors operating in Turkey. Semi structured interviews are done with 13 CEOs, CFOs and COOs whom are conveniently reachable by a group of PhD students. Interviews are interpreted through descrip- tive analysis.
3. 1. Interview Questions To explore the anticipation capacity of sample organizations, respon- dents were directed to answer questions under the following headings :
3.1.1. Who has the active role in the strategic decision making process The question aims to understand the decision-making process in the company and find out who or which committee has the last word for finalizing strategic decisions.
3.1.2. Importance of MIS (Data analysis) for making strategic decisions The aim of this question is to assess the undertanding of top managers on data analysis for and the use of MIS in strategic planning
3.1.3. Distribution of formality/informality while anticipating strategies The question aims to find out whether anticipation and strategical planning activities within the company involves a formal or an informal process.
3.1.4. Place of intuition during top manager’s decision process The aim of this question is to understand the place of intuition as stat- ed by the top managers themselves.
3.1.5. Perceptions of “rationality” of the top managers during decision making
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These two questions aims to determine how the respondents see the place of rationality versus intuition in strategic planning and tries to assess the weighting they assign for strategic decision-making.
3.1.6. Perceptions of time The question aims to reveal how top managers describe the time spans of short, medium ang long term strategies related to their business in Turkey.
3.1.7. Perceptions on “anticipation as being action orientedness in present rather than just making predictions for future” This is actually the major question for assessing the top managers’ understanding of the importance of anticipation and future based (visionary) strategic planning in company management.
3. 2. Respondents’ Answers and Evaluations 3.2.1. Who has the active role in the strategic decision-making process “GM and managers” “The proposals come from the bottom up in the process, the Board of Directors makes the final decision” “Board and the senior management” “Strategic decisions are evaluated by the Board of Directors and they have an active role in the decision-making process but a definite impact of the Company Partners can be felt on the Board of Directors.” “Active roles belong to the Chairman of the Board of Directors, the Regional Director and the Country Manager.” “GM takes an active role. BOD has no active role. But in accordance with the (financial) size of the strategic decision, BOD also becomes ac t ive.” “A plan, time line and an implementation plan is prepared and submitted to BOD for approval. After approval, the professional managers take the leadership for the implementation process. This leadership starts at the CEO level, and shared by VP, COO, CFO, interchangeably.”
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“Our boss, CEO, C Level Managers and General Managers in charge of the Region.”
“Ideas actually originate from the Chairman and the BOD. Then the Sectoral Groups work on these ideas by working on data from internal and external markets and develop plans and feasibility reports. These plans and feasibility reports establish the basic information for the Chairman and BOD. Decisions are finalized after these reports are discussed in the BOD Meetings.” Evaluation : The respondents’ answers reveal that mostly the BOD and than the top managers (GM or CEO) have the active role in strategic decision-making process. Large investment decisions are made by the BOD and the company executives are allowed to decide on relatively smaller investment decisions by themselves. In most companies alternative plans and feasibility studies are prepared by line management and presented to higher management for approval.
3.2.2. Importance of MIS (Data analysis) for making strategic decisions “MIS (data analysis) is an important tool for reaching the targets. It is also important for the corporate memory as accurate company information is stored in a reachable form. This information is important for conducting accurate analysis. The data is important for resolving daily problems and it can also be used for strategic decision-making.” “In our company, know-how, experiences and opinions of Partners (Owners) are used as primary source of information. This information supplies the basic data both for rational and intuitive based strategic decisions in our sector.” “How the MIS is designed is critical. It can be useful during strategic decision-making if it can respond to the current needs of management. In our company, MIS support strategic decisions to be taken in the fields of revenue optimization and sales force effectiveness.” “Financial reports, non-financial reports, KPIs, CRM data including market information are used for data. In addition, “sensations” from the market are also taken into account.”
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“Every system should be viewed as a tool. Each tool is used to assist our work. If development and use of the tool, however, is elevated to the position of the main goal, then the results will always be failure. Perhaps a few successes can happen by chance, but it can not be sustained.” “It’s a very important issue for building institutional memory because MIS helps us store accurate information in a reachable form. Versatile control of incoming information is critical for accurate analysis. For this reason, our company continues to invest in most advanced technology and systems, including Navis N4 in the operational field and SAP in the ERP side.” Evaluation : The answers show that most of the interviewed managers are fully aware that MIS is important. However, it appears that these managers’ data expectations are mainly limited to revenues, expenses and sales figures. Only one of the respondents mentioned about the use of non-financial reports and other critical performance data for analysis. One other respondent mentioned about their company’s “ongoing” investment in MIS software, signalling that it may not currently be fully operational. Most managers imply that MIS data is mostly used for daily management (monitoring) purposes rather than strategic planning for the future.
3.2.3. Distribution of formality/informality while anticipating strategies “We start by informal discussions and we get official approval on the Board of Directors meetings.” “Generally, strategic decisions are taken at Board meetings. The Board meets according to a pre-set calendar. Besides, many strategic plans may also get approved at informal meetings as well.” “Corporate culture is not very formal, it can be considered semi- informal.” “A timing and development plan along with a budget is prepared for BOD’s approval. After approval, implementation is the duty of the professional manager. It starts at the CEO level, is applied by the VP, COO, CFO interchangeably.”
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“Analysis and assessment reports are prepared and presented to the upper management. Official signatures are necessary in cases where a legal formality is required. Then the decisions made by the senior executives are communicated to the related departments.” Evaluation : The answers reveal with the exception of one company that anticipation and strategical planning is an informal or at best a semi- informal process, mostly dealt at the BOD level and communicated to the rest of the organization for implementation. It can also be observed that the interviewed top level executives’ idea of formalism is limited to the calender scheduling of meetings and signature requirements when legal issues are of concern.
3.2.4. Place of intuition during top manager’s decision process: “For growth and investment related decisions it can be said that intuition has a primary place in anticipation. Data and analysis becomes important for decisions especially in product development and sales. For marketing decisions at the tactical level intuition regains importance. For marketing, we can say data comes first, then comes market trends and finally intuition takes effect.” “If you are a 100% public international company there is absolutely no place for intuition. Everything has to be connected to a plan. As a very recent example, even for Tesla, a work plan, development plan and its financial application must be approved by the BOD. Besides, it is meaningless to discuss intuition when engineering is concerned. Often, the stock exchange organizations enforce strict rules and prohibite the use of intuitive approaches.” “Especially for growth and investment decisions there is some place for intuition in anticipation. Usually our board chairman - our boss is using more initiative at this point. “ “Advanced Analytics, such as Big Data Analytics, is on the agenda of our Company. We are working on it. We are trying to place intuition behind strategic decisions as little as possible.” “If data exists, we perform data analysis and detailed reviews. We use intuition when there is no data.”
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One reason for this is that our management team is very experienced. In any case, we work on a complete business plan before we make our final decision.” “Besides data and trends, it is always intuitive.” “Intuitive decision-making is valid once you establish confidence in the intuitions of those who have a proven track record.” Evaluation : Intuition is generally accepted to be of primary importance for growth and investment related decisions and when trusted data is not available. The executives stress the importance of rational analysis but somehow hint that bottom line final decisions must pass on intuitiveness. Public companies’ executives stress on the fact that rationality is enforced by law and the Stock Exchange authorities strongly emphasize on rationality for their auditions. The tone of answers imply that these executives actually desire that their intuitions should be of primal importance. Hence they seek rationality for legal necessities and actually use them for the endorsement of their intuitive decisions.
3.2.5. Perceptions of “rationality” of the top managers during decision-making “The process is 80% rational and 20% intuitive.” “Rational thinking is more important, but intuition can never be ignored.” “Intuitive approach is important. But we believe taking action with sole intuition without a rational approach increases the chances of making mistakes.” “Intuition naturally becomes important in every environment where there is no data and hence no data management. Intuitive decisions should be minimized.” “I think half-and half. Strategic decisions are always future oriented and future is uncertain by nature. It is not possible to be 100% rational.” “The strategic decision process must be rational. It should be interpreted intuitively in the direction of rationality and findings. Intuitive thoughts are limited to personal ideas if rationality is not the base.” “Current efforts of our partners to institutionalize the organization continuously pushes everybody to place more emphasis on rationality.
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Intuitiveness in strategic management, however, is not something that may be ignored. In this respect, our Company partners always seek rationality to endorse their intuitions.” “To sum extent engineers are using their intuitions while developing a new product. When strategy is concerned, however, intuition was the main source of information for decision-making at the beginning of the 20th century. But in today’s business environment public company actions are very strictly and thoroughly controlled by the stock market and their audition methods require total rationality.” “When evaluating strategic decisions, we primarily trust our intuition. If we do not have enough positive predictions on the issue we prefer not to continue with it.” Evaluation: The respondents’ answers reveal that both intuition and rationality are viewed necessary for best business results. They are fully aware that rationality should be given a primal importance when trusted data exists and intuition may only be relevant for future related decisions where uncertainies tend to arise. Engineering is generally viewed to be %100 rational but on the other hand, it is also stated that the product development process does also involve intuition as well. It is frequently stressed that rationality is a must for public companies.
3.2.6. Perceptions of time “In Turkey, long term is usually accepted as 3 years but temporal definitions has recently changed. Nowadays, we concentrate only on the year ahead.” “Strategic plans are made separately for 3 and 5 years ahead. But, often, short term decisions are in effect, regardless of their time frame.” “Short-term plans are tactical and are most beneficial if they also support long term strategies. The business environment changes rapidly. We need to make long term plans but continuously monitor and revise them frequently.” “The sense of time has changed because everything changes much faster. Long term plans are still in effect but they need to be revised more often.”
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“It’s very important to take quick action. It’s very important to be fast in order to make a difference in the market and be successful.” “Everything is so fast now, the expectation of response is very short.” “Globalization, internet, logistics, and such subjects influenced our perception of time. I believe that short, medium and long term plans are indispensable but short term is now shorter than it used to be, medium term is nearer than before and long term is definitely not too long”. Evaluation: It is obvious from the answers that the volatility of the Turkish business environment and the necessity of swift actions in today’s rapidly changing global markets force the company executives to place more emphasis on short term planning which they quantify as one year ahead. The answers also hint that they work more on a short term basis because the requirement of frequent revisions overburdens the work on longer term planning.
3.2.7. Perceptions on “anticipation as being action orientedness in present rather than just making predictions for future” “Strategic decisions are made by using of a combination of many hints. While past performance, present performance and current trends make up the rational part, issues such as how they will affect your business and how the market will change in the future require more intuition.” “The first step is to read the data correctly. The second step is to analyze the short-term, medium-term and long-term opportunities and risks by interpreting the data. The third step is the creation of the action plan.” “In fact, we can see that the main reason for the increase in the importance of strategic decision making is the action orientedness. The fact that time perception is changing and the necessity of very effective evaluation of resources is causing faster processes to operate especially in strategic decision making about product and market. At this point, the intuition of decision makers outweighs.” “In multinational companies action orientedness is constrained and not fast enough because of their dependence on overseas technologies and strategic actions.” “Long term strategic plans are meant to be discussed at 3 and 5 year strategic decision meetings, but often these meetings turn out to be short
196 ANTICIPATION AND STRATEGIC DECISION-MAKING term and action oriented due to the intuition based management style of the Chairman of the BOD.” Evaluation : This is actually the major question related to assessing the executives’ understanding of the meaning and importance of anticipation and future based (visionary) strategic planning in management. The answers unfortunately reveal that these executives view anticipation as an approach for strategical planning for the short term and neither have much idea about normative anticipation nor pro-active management to create the future for their companies.
4. Some Implications Anticipatory thinking requires managers today to ask more questions. Only then anticipation capacity of the organization can develop. They ask questions in present so that they will get the appropriate answers, but not the right answers, because the meaning of right and wrong are also becoming vague and relative because when the manager makes a decision in present he needs to see and evaluate the end results after some time before he can actually decide if it has really been a right or wrong decision. There is a time lapse in between. However, anticipatory thinking while making strategic decisions is action oriented in present and present involves the subjective perceptions of the individuals and their attitudes and behaviour to the observed reality. Deciding strategies by Anticipatory thinking is different from making decisions through strategic thinking. What we mean is making strategic decisions through anticipatory thinking is kind of enlargement in the present moment, in other words, kind of investing more into the present. Strategy is usually associated with long term planning so in general it is future oriented. However the future is hypothetical since it exists in our anticipations (Mead, 1929). Instead of strategic decisions based on future visions, technology oriented foresight can be offered to the decision makers to improve their strategic anticipation capacity. Capacity of the decision makers to adapt themselves to the new technologies, thus individual flexibility, technical digital knowledge, catching up with the present technological developments, learning organizations via digitalization are the growing trends in decision-making process today.
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References Cohen, M., March, J. and Olsen J. (March 1972), A Garbage Can Model of Organizational Choice, Administrative Science Quarterly, Vol.17. No 1, pp.1-25 Cyert, M., March, J. (1992), A Behavioral Theory of the Firm, Wiley- Blackwell; 2. Edition.
Daft, R. (2001), Organization Theory and Design, South-Western College Publishing. Davidson, A. (2009), 1000 CEOs, Proven Strategies for Success, Dorling Kindersley. Drucker, P.F. (1994), The Age of Social Transformation, The Atlantic Monthly, 274(5). Husserl (1991as cited in Poli, 2009), The Many Aspects of Anticipation, Foresight. Klein, G., Snowden, D. (2011). Anticipatory Thinking. Informed by Knowledge Expert Performance in Complex Situations. 10.4324/9780203847985. Mead, G. H. (ca1929). “The Self, the I, and the Me.” G. 224-229 in Social Theory: The Multicultural Readings (2010) edited by C. Lemert. Philadelphia: Westview Press. Mintzberg, H. (1989). Mintzberg on Management, Inside Our Strange World of Organizations, New York and London: Free Press/Collier Macmillan. Mintzberg, H. (1994), The Rise and Fall of Strategic Planning, Harvard Business Review. Omahe. K. (1982), The Mind of the Strategist,McGRaw-Hill. Poli, R. (2009), The Many Aspects of Anticipation, Foresight. Poli, R. (2017), Introduction to Anticipation Studies. Dordrecht: Springer. Scott, R. (2015), Organızatıons and Organizing Rational, Natural, and Open System Perspectives. Routledge-Taylor & Francis Group. Simon, H. (1982b), Models of Bounded Rationality. Vol. 2: Behavioral Economics and Business Organization. Cambridge, MA: The MIT Press.
198 10 ANTICIPATION IN ARTIFICIAL INTELLIGENCE
Özlem Şenvar
Abstract Many disciplines have realized the importance of anticipation and artificial intelligence (AI) over the last decades. This study seeks to present a conceptual overview to anticipation in artificial intelligence. This study provides a classification of quantitative and qualitative techniques of anticipation based on artificial intelligence. Since we are living in data deluge era, the challenges of machine learning (ML) and big data analytics (BDA) are incorporated for anticipatory systems in this chapter.
Keywords: Artificial Intelligence, Machine Learning, Big Data Analytics, Anticipation, Foresight, Forecasting.
1. Introduction Many disciplines have realized the importance of anticipations and AI over the last decades. As a matter of fact, the root of all intelligence (natural or artificial) is the learning. The sense of the paradigm is sequenced as data, knowledge, information and wisdom, respectively. Artificial intelligence (AI) emphasizes the creation of intelligent systems that work and react like humans. Generally, AI refers to computational tools that are able to substitute for human intelligence in the performance of certain tasks. AI is the development of computer systems that are able to perform tasks that would require human intelligence. These tasks are visual perception, speech recognition, decision-making, and translation between languages. Also, AI is commonly used to establish mechanisms for systems via inclusion of characteristic intellectual processes of humans such as the ability of learning from past experience, reasoning, discover
199 ANTICIPATION meaning, generalizing, pattern recognizing, data mining, planning, and problem solving, and etc. Machine learning (ML) is the application of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed by the help of humans. ML is learning, understanding and analyzing from the past experience to predict or classify new objects or stuffs. ML develops computer programs that can access data and use the data to learn for themselves. A machine with strong AI can think and act just like a human and learn from experiences along with predict or forecast future outcomes based on the data gathered in the past. Notably, predictions or forecasts, desires or intentions strongly influence behaviors, adaptations, and learning. Anticipation gives the possibility to prematurely intervene a process to enable the desired results. This chapter handles anticipation in AI. This chapter addresses the following research questions:
1. What is Artificial Intelligence? 2. What is Anticipation? 3. How anticipation mechanisms are incorporated in AI ?
From this standpoint, the rest of the chapter is organized as follows: In section 2, general overview to AI and Anticipation is given. In section 3, Challenges of machine learning and big data analytics are provided for anticipatory systems. Section 4 includes discussion. In section 5, conclusions along with recommendations for further directions are presented.
2. General Overview to Artificial Intelligence (AI) and Anticipation 2.1 Artificial Intelligence (AI) Artificial intelligence (AI) is a science associated with intelligent software programs, machines or systems that can make inferences and
200 ANTICIPATION IN ARTIFICIAL INTELLIGENCE solve problems in much the same way as humans do (Minsky, 1968). AI pursues creating the computers or machines or systems as intelligent as human beings. AI relates to the part of computer science that focuses on designing intelligent computer systems that are similar to what is recognised as intelligence in human behaviour (Barr and Feigenbaum, 1981). A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving. AI is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think. AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes as a basis of developing intelligent software and systems. According to Barr and Feigenbaum (1981), AI is an intelligent computer with the capabilities to behave like a human would. This includes characteristics like the imitation of human behavior and reactions, reasoning, learning and problem solving. AI aims to study mental faculties through the use of computational models (Charniak and McDermott, 1985). AI attempts to make machines or systems smarter (more intelligent) and understand what intelligent is and make machines more useful. In simple terms, AI is about the study of the thought process of humans and representing them via machines. In some ways they advance over natural intelligence: their ability to sustain operation; ease of duplication and dissemination, and consistency (Khosrowshahi and Howes, 2005). In these aspects, AI has two fundamental goals, which are listed as follows: i. To Create Expert Systems − The systems which exhibit intelligent behavior, learn, demonstrate, explain, and advice its users. ii. To Implement Human Intelligence in Machines − Creating systems that understand, think, learn, and behave like humans.
Many problems in AI (in reasoning, planning, learning, perception and robotics) require the agent to operate with incomplete or uncertain
201 ANTICIPATION information. Intelligent robots perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memories to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment. The main advantage of AI techniques is their ability to deal with non- deterministic situations where a given problem is likely to have several possible outcomes. Moreover, AI is capable of doing this without the need for the expert. These characteristics make AI highly relevant to management decision making, particularly at the strategic level, where the decisions are extremely uncertain and far from being deterministic: in the absence of the expert, management decisions could be replicated, hence offering cost effective and time saving solutions. They have the ability to deal with problems where an algorithm or procedural problem solving approach cannot be adopted. Furthermore, AI is capable of exploiting the range of knowledge needed to emulate intelligent behavior and exercise a problem solving process. These characteristics make AI highly relevant to management decision making, particularly at the strategic level, where the processing primarily involves reasoning and intelligence rather than computing and algorithm; the input components are often incomplete and made of knowledge rather than just data; the search methods are usually heuristic; and the outcome is probabilistic and incomplete.
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Table 1 gives the some known advantages and disadvantages of AI.
Advantages Disadvantages Overall cost of implementing an AI Reduction in error is enhanced within machine is huge, only a few can make decisions taken by machine(s). use of it Ability to take right decisions, which Dependency of humans on machines are based on a set of algorithms, in a is ever increasing short span of time Situations where the safety of a human With efficient AI and automation, is unsure. AI machine is fitted with human jobs will soon be replaced by predefined algorithms can be used machines Since a machine does not get tired, it Machines cannot think creatively or can work continuously without taking out of the box and will not perform any breaks such kind of tasks. Table 1 Some advantages and disadvantages of AI
In practice, the knowledge has some properties coming from raw data, which are huge, not well organized or well formatted, incomplete, vague. AI techniques can organize data and transform into knowledge and extract useful information efficiently in perceivable, flexible formats.
Khosrowshahi and Howes (2005) emphasized that the concepts surrounding AI emerged in the 1950’s, resulting in the development of many techniques, which are ranged from human logic reasoning to replication of humans’ neural system and genetic inheritance. The streams of AI, which are shown in Figure 1, include neural networks; natural language processing and semantic modelling; robotics planning and knowledge; intelligent computer aided instruction; cognitive system; perception; and ML consisting of neural computing, genetic algorithm, case based reasoning, inductive learning, and explanation based learning. It should be considered that the AI techniques have complementary characteristics with their individual strengths and weaknesses. For example, complex relationships can be captured between the input and output variables by exposing instances to learning abilities of the neural networks (Senvar et al., 2016).
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Figure 1 Streams of AI
2.2 Anticipation Anticipation is defined as the process of predicting future actions or behaviors based on any kind of information from the current or past. Anticipation cover all the initiatives to know the future. Future can be considered as anticipation with the all phenomena, conscious or unconscious, physical or ideational. Anticipation is an important tool since it provides to experience within experiment in a safe virtual setting, without facing real world consequences of trial-and-error. Anticipation takes attention to the potentially unforgiving nature of reality and the costs arising from what may turn out to be wrong decisions. It facilitates
204 ANTICIPATION IN ARTIFICIAL INTELLIGENCE decision-making by giving an outlook of what the future will look like. Davidsson et al. (1994) defined anticipation as a mental activity that humans and the other living organisms, are capable of and one which is frequently practiced via utilization of the knowledge of future states to guide the current behaviors. Anticipation discipline develops, sorts, and diffuses definitions of the processes/systems of anticipation or how the later-than-now enters into reality. Anticipation discipline improves the conscious use of the future in the present. Anticipation discipline takes novelty into account as the perceptions of the present. Anticipation discipline provides ideas and tools that can alter and expand the role of anticipation in shaping what humans perceive, including capability and capacity to make the sense of novelty. Anticipation discipline can improve anticipatory capacities in a wide range of circumstances by enlarging and enhancing the analytical and operational approaches. An anticipatory system is a system which involves a model of itself and/or of its environment in view of computing its present state as a function of the prediction of the model. Rosen (1985) defined the anticipatory system as a system containing a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant. Anticipatory systems have to predict the consequences accurately and precisely. Anticipatory discrete systems can be modelled, simulated and controlled with the concepts of incursion and hyper incursion (Dubois, 1998). In fact, many anticipatory systems cannot in themselves act meaningfully or represent intentionally. This stems largely from the derivative nature of their functionality. All current artificial control systems, and many living systems such as organs and cellular parts of organisms derive any intentionality they might have from their designers or possessors. Derivative functionality requires reference to some external autonomously functional system, and derivative intentionality similarly requires reference to an external autonomous intentional system. The importance of autonomy can be summarized as “No meaning without intention; no intention without function; no function
205 ANTICIPATION without autonomy”. Collier (1999) developed the role of autonomy to show how learning new tasks is facilitated by autonomy, and further by representational capacities that are functional for autonomy. There are different types of anticipation such as biological, psychological and social types of anticipation having own distinguished properties and inherent patterns. When different types of anticipation are simultaneously active, they may work harmoniously together or they may interfere with each other (Miller and Poli, 2010). Butz, Sigaud, and Gérard (2003) highlight the importance of an interdisciplinary approach to anticipatory behavior and learning. According to them, anticipations mediate behavior; purposes direct attention; predictions influence learning; expectations predispose the mind and body; desires bias or cause motivations; intentions initiate behavior execution. All these influences express a certain anticipatory behavior – behavior, or some cognitive process, that does not only depend on current sensory input but also on predicted, desired, or intended future states or future properties. Anticipatory behavior aspects can be combined in a general framework. There are distinctive aspects which are required to be examined between different anticipatory mechanisms, within their applicative time frames, their influences, and their possible benefits. The interdisciplinary approaches to anticipatory behaviors are vital gathering and analysing of different anticipatory phenomena from psychology, linguistics, or neuroscience, and etc.. The gathered data allows conclusions on structure and general purpose of anticipatory behaviors (Butz, 2004). Methodology of anticipation is mainly based on qualitative approaches that can be supported by quantitative inputs in various stages and settings. Table 2 summarizes qualitative and quantitative techniques. Since everything cannot be quantified, qualitative methods should be combined with projections for a turn-key analysis. Combining quantitative and qualitative methods is desirable in anticipation. Notably, quantitative projections can be a cornerstone in developing systematic approaches. Limitations in data or models can be overcome by using qualitative methods.
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Qualitative Techniques for Quantative Techniques for Anticipation Anticipation • presenting behavioural • Surveys of employers or other information. groups, • interviews with key participants, • Formal,national-level,model- including employers based projections • scenario development, • Time Series • roundtable debates In the presence of time series, • focus groups, more complex examination is • delphi method required to find patterns that can be • comprehensive case studies used to foresee future tracks. (particularly of specific areas) Such methods are extensively used in the financial and business Advantages world, even though they are more • holistic accurate in forecasting (short-term • direct ‘user/customer’ involvement. alterations than longer-term forms). • Extrapolation of historical trends Disadvantages Extrapolative methods are for various sectors and research used when time series data are areas, non-systematic methods can unavailable. be inconsistent and very subjective Table 2 Qualitative and Quantitative Anticipation Techniques
3. Challenges of Machine Learning (ML) and Big Data Analytics (BDA) Behavior decision making is certainly affected by many factors and includes the whole field of decision making. Anticipatory planning and decision making must be handled via computational approaches. Since incorrect expectations may lead to incorrect biases and inappropriate behavior decisions, statistical decision making along with machine learning within big data era are inevitable. This is necessary for the anticipatory component, that is, anticapatory behavior is influenced not only by the current sensory stimuli but also by the desired future stimuli. In this regard, computer science and especially ML suggests the need for an internal model to improve adaptive behavior and learning (Sutton & Barto, 1998; Sutton, Precup, & Singh, 1999; Butz & Hoffmann, 2002).
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ML is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions relying on patterns and inference instead. Depending on the nature of the task and types of data available, the best algorithm may vary. The vast majority of ML algorithms are classified into one of the four categories as supervised learning, unsupervised learning, semi supervised learning and reinforcement learning. Figure 2 shows an overview to ML, which is known as the representation of the input data and generalization of the learnt patterns for use on future unseen data. Big data analytics (BDA) is where advanced analytic techniques operate on big data sets. Hence, big data analytics is really about two things, which are big data and analytics, plus how the two have teamed up to create one of the most profound trends in business intelligence (BI). Notice that, BDA is the application of advanced analytic techniques to very big data sets including diverse data types and streaming data (Russom, 2011). Figure 3 shows AI, ML, Deep Learning, BDA and data mining and data science interrelationships. Data science deals with the two topics that are known as BDA and Deep Learning (DL). Big Data has become vital for both public and private organizations that have been collecting massive amounts of domain specific information, in which useful information must be extracted to reveal problems such as national intelligence, cyber security, fraud detection, marketing, and medical informatics, and etc. Companies such as Google and Microsoft are analyzing large volumes of data for business analyses and decisions, impacting existing and future technologies. DL algorithms extract high-level, complex abstractions as data representations through a hierarchical learning process. Complex abstractions are learnt at a given level based on relatively simpler abstractions formulated in the preceding level in the hierarchy. Main advantage of DL is the analysis and learning of massive amounts of unsupervised data, making it a valuable tool for BDA where raw data is largely unlabeled and uncategorized. DL can be utilized for addressing some important problems in BDA, including extraction of the complex patterns from massive volumes of data, semantics, data labelling, fast
208 ANTICIPATION IN ARTIFICIAL INTELLIGENCE information retrieval, and simplifying discriminative tasks (Najafabadi et al, 2015).
Machine Learning Overview
Advertising Popularity Prediction Meaningful Structure Compression Discovery Population Growth Market Prediction Forecasting Dimensionality Regression Reduction Big Data Feature Estimating life Weather Visualization Elicitation expectancy Forecasting
Identity Fraud Recommender Detection Systems Unsupervised Supervised Customer Learning Learning Retention Clustering Classification
Targetted Machine Diagnostics Image Marketing Customer Classification Segmentation Learning
Real-time Learning decisions Tasks
Reinforcement Learning Robot Skill Navigation Acquisition
Game Al
Figure 2 ML Overview
The goodness of the data representation has a large impact on the performance of machine learners on the data. In contrast, a poor data representation is likely to reduce the performance of even an advanced, complex machine learner. Domingos (2012) mentioned that feature engineering focuses on constructing features and data representations from raw data. As an important element of ML, feature engineering consumes a large portion of the effort in a ML task, and is typically quite domain specific and involves considerable human input.
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Figure 3 AI, ML, BDA and data mining and data science interrelationships
In contrast to more conventional ML and feature engineering algorithms, DL has an advantage of potentially providing a solution to address the data analysis and learning problems found in massive volumes of input data. More specifically, DL aids in automatically extracting complex data representations from large volumes of unsupervised data. This makes it a valuable tool for BDA, which involves data analysis from very large collections of raw data that is generally unsupervised and uncategorized. The hierarchical learning and extraction of different levels of complex, data abstractions in DL provides a certain degree of simplification for BDA tasks, especially for analyzing massive volumes of data, semantic, data labelling, information retrieval, and discriminative tasks such as classification and prediction.
4. Discussion In the literature, researches regarding futures have employed varieties of approaches and techniques, ranging from forecasting to simulation,
210 ANTICIPATION IN ARTIFICIAL INTELLIGENCE from planning to trend extrapolation to scenarios, technology foresight. In addition to all these, highly diverse conceptualisations and formalisations have been proposed. These remarkable varieties can be simplified to some extent by stating the two fundamental assumptions, which are given below: i. future is at least partly governed by the past, ii. future can be better confronted by opening the minds and learning to consider different perspectives including the possible, probable, and preferred future scenarios.
Predictions, desires, or intentions strongly influence behavior, adaptation, and learning. These anticipations influence behavior mediating decision making and action execution as well as attention. Although it is not the future itself that influences the present but the anticipated future states or future properties stimulate driven behavior and learning. Environmental properties along with anticipatory mechanisms are required to be examined for enhanced improvements in behaviors. Anticipatory mechanisms along with the environmental properties are considered to be bias, and thus future learning capabilities are immediately influenced by current anticipations. In order to understand or create effective behavioral or cognitive learning mechanisms, it is necessary to understand the underlying structures or principles of the dynamic environments in which the behaviors are executed. For anticipatory behaviors, several principles can be proposed and the effective corresponding anticipatory mechanisms can be characterized and evaluated accordingly. In fact, cognitive processes have explicit anticipatory components, which are structured and evolved not only interactions with the dynamic environments and but also interactions with itself. The anticipatory behaviors are goal- oriented behaviors mediated by attention, action, and decision-making processes.
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5. Conclusion ML along with AI helps to validate the emerging theories using facet- wise analyses. The knowledge about the anticipatory aspects of behavior and learning may influence our general comprehension of learning. These concepts can be handled within the researches regarding futures with the inclusion of power of AI techniques to increase the capabilities and capacities and enhance performance. Successful anticipation depends on identification of clear and realistic goals. Anticipation should be embedded into an institutional framework, which includes identification and engagement of key stakeholders along with the dissemination of results across various channels, in order to broaden the utilization and the usefulness of anticipation in AI within the multidisciplinary perspectives. The perspectives of expectation and purpose as part of the cause in the dynamic environments can be considered and further investigations can be conducted through anticipation in AI. Anticipation approaches are important for making decisions. Anticipation approaches should be undertaken within a broader foresight approach with other elements of technology and economic developments, where the investment in education/training and the changes in structure and quality of jobs are viewed as part of the holistic process. Holistic approaches along with inventive solutions in analysis and research can better accommodate the time gap between the real change in demand and the implementation response and policy. Extensive further researches regarding DL field would be conducted. In particular, more examination is required on how we can adapt DL algorithms for problems associated with BDA, including high dimensionality, streaming data analysis, scalability of DL models, improved formulation of data abstractions, distributed computing, semantic indexing, data tagging, information retrieval, criteria for extracting good data representations, and domain adaptation in terms of anticipation in AI. From these perspectives, anticipatory systems can be more handled via AI, ML and BDA since intelligent robots can anticipate the future,
212 ANTICIPATION IN ARTIFICIAL INTELLIGENCE by outlining two broad approaches: the first approach shows how robots can use anticipation to learn how to control their own bodies; the second approach shows how robots can use anticipation to predict the behavior of themselves interacting with others, and hence demonstrate improved safety, or simple ‘ethical’ behaviors. Autonomous systems with the ability to anticipate would exhibit novel, interesting and possibly unexpected properties that might enhance the capacity of autonomous and intelligent systems. For further directions, having more practical realizable embedded artificial intelligence mechanisms, robots can indeed predict the future. Inclusion of the ability to anticipate the behavior of the robots has the potential to make the behavior of the robots more efficient. Notably, this is highly dependent on the complexity of the environment and the accuracy along with the precision of the control of the robots. Anticipated and intelligent systems are inevitable with significant potentials for enhancing safety and compatible human-robot interactions.
References Barr and Feigenbaum (1981), “The Handbook of Artificial Intelligence”, Vol. 1, Morgan Kaufmann, Los Altos, CA. Minsky (1968), “Semantic Information Processing”, Cambridge, MA, MIT Press. Charniak and McDermott (1985), “Introduction to artificial intelligence”, Reading, MA, Addison-Wesley. Khosrowshahi, F., & Howes, R. (2005), A framework for strategic decision-making based on a hybrid decision support tools. Journal of Information Technology in Construction, 10, 111-124. Rosen, R. (1985), Anticipatory Systems: Philosophical, Mathematical & Methodological Foundations, Pergamon Press, Oxford. Senvar, O., Yalaoui, F., Dugardin, F. & Lara, A. F. B. (2016), Data mining approaches for the methods to minimize total tardiness in parallel machine scheduling problem. IFAC-PapersOnLine, 49(12), 431-436. Davidsson, P., Astor, E. & Ekdahl, B. (1994), A framework for autonomous agents based on the concept of anticipatory systems. Cybernetics and
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Systems, 94, 1427-1434. Dubois, D. M. (1998, July), Computing anticipatory systems with incursion and hyperincursion, In AIP Conference Proceedings (Vol. 437, No. 1, pp. 3-30). AIP. Collier, J. D. (1999, March), Autonomy in anticipatory systems: significance for functionality, intentionality and meaning. In AIP Conference Proceedings (Vol. 465, No. 1, pp. 75-82). AIP. Miller, R., & Poli, R. (2010), The many aspects of anticipation. foresight. Butz, M. V., Sigaud, O. & Gérard, P. (2003), Anticipatory behavior: Exploiting knowledge about the future to improve current behavior. In Butz, M. V., Sigaud, O., & Gérard, P. (Eds.), Anticipatory Behavior in Adaptive Learning Systems: Foundations, Theories, and Systems (pp. 01-10). Butz, M. V. (2004), Anticipation for learning, cognition and education. On the Horizon, 12(3), 111-116. Sutton, R. S., & Barto, A. G. (1998), Reinforcement learning: An introduction. Cambridge, MA: MIT Press Sutton, R., Precup, D. & Singh, S. (1999), Between MDPs and semi- MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 112, 181-211. Butz, M. V., & Hoffmann, J. (2002), Anticipations control behavior: Animal behavior in an anticipatory learning classifier system. Adaptive Behavior, 10, 75-96. Russom, P. (2011), Big data analytics, TDWI best practices report, fourth quarter, 19(4), 1-34. Najafabadi, M. M., Villanustre, F., Khoshgoftaar, T. M., Seliya, N., Wald, R., & Muharemagic, E. (2015), Deep learning applications and challenges in big data analytics. Journal of Big Data, 2(1), 1. Domingos P (2012), A few useful things to know about machine learning, Commun ACM 55(10).
214 11 ANTICIPATORY PUBLIC MANAGEMENT
Hande Tek Turan1
Introduction public administration is a social science that assesses the past to create solutions to resolve issues in the present and the future. As we are experiencing an increasingly interconnected environment and everything around us is changing, the field of public administration cannot be apart from the constant need to innovate and change. We are living in an era of rapid change, unpredictable and anticipatory practices are coming to the forefront of political, organizational, and citizens’ society. Public administrations have to explore how to improve the capacity of society to innovate, prosper and especially adapt to emerging issues, unforeseen events and changing circumstances. As a result, the public sector in many developed countries feels the need to move beyond the static and machine bureaucratic paradigm of Weber’s traditional (bureaucratic) system (Stanley H., 1959) (Pfiffner P., 2004) to the New Public Management system. This chapter argues that in the future of public administration, there is a flexible public sector rather than machine bureaucracies. Regarding anticipatory practices, this chapter also seeks to identify how anticipation is defined and understood in the literature and to explore the role of the governments in the anticipatory practices to provide public services to overcome individual, social, and global challenges, focusing in particular on the most recent developments in the world.
1 Asst.Prof.Dr.; Dept. of Public Administration, Yeditepe University, Istanbul, Turkey.
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Defining “Anticipation” Anticipation is increasingly central to urgent contemporary debates, from climate change to the global economic instabilities and it has been widely studied within numerous different fields, and under diverse names, in fields including biology, psychology (Louie 2009; Louie and Poli 2011; Poli 2009, 2010, 2011), resilience (Almedom et al. 2007; Almedom 2009; Martin-Breen and Anderies 2011; Zolli and Healy 2012), futures studies (Miller 2006, 2007, 2011, 2012), and governance (Fuerth 2009, 2011; Kar- inen and Guston 2010; Fuerth and Faber 2012). (Boyd, et al., 2015) The concepts of anticipation, foresight, vision, prediction, and expec- tation are not products of the same cognitive process, that means they are different procedures in charge of processing all the information received from the environment. In general, all attempts to understand, imagine, and benefit from the future can be seen as modes of anticipation, a con- stant feature of human behaviour (Poli, 2011). The clearest difference between them is that the anticipation occurs when the future is used in action. So, it includes assumptions, however, expectations, for example, constitute the “passive” side of the mental process. Likewise, foresight is the capacity to anticipate alternative futures, based on sensitivity to weak signals, and an ability to visualize their consequences, in the form of multiple possible outcomes, while vision tends to be a fixed image of the future, tends to be inflexible (Fuerth, 2009). Voros’s contribution to the anticipation literature is much more about its cognitive process; he argues that studying the future means studying the cognitive construc- tion of the future within the present (Voros, 2007). While acknowledging that little is understood about anticipation, Poli (2009) shares the following conclusions:
1. Anticipation comes in different forms, e.g., explicit and implicit, and different types of anticipation may work simultaneously. 2. Anticipation has been a major evolutionary breakthrough. If Rosen’s theory (Rosen, 1985) holds true, anticipation may be deeply embed- ded in the organisms’ functional structure. 3. Anticipation’s abstract nature depends on hierarchical or self-referen- tial loops, imposing severe constraints on the modelling of anticipa- tion systems.
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THEMES FİELDS DEFINITION SOURCES ADDRESSED According to Husserl, antici- Anticipation Husserl pation is the way in which the as a compo- (1991), merely co-presented is present nent of con- Bloch (1995), in perceptual experience. Heide- sciousness; Heidegger Philoso- gger’s “Philosophy of Death” humans’ ex- (1962, p. phy describes anticipation as “the pectations 260) possibility of understanding one’s own most and uttermost potenti- ality-for-Being-that is to say, the possibility of authentic existence.” Rosen’s Theory of Anticipatory Theory of Rosen (1985, Systems states that: “An anticipa- Anticipatory p. 341), Lou- tory system is a system containing Systems ie (2009), a predictive model of itself and/ Louie and or its environment, which allows Poli (2011), it to change state at an instant in Poli (2009, Biology accord with the model’s predic- 2010, 2011) tions about a later instant.” His theory showed that anticipation is not limited to living systems. Poli (2010, p. 8) states, “non-living or non-biological systems can be anticipatory.” The psychology of imagining the Cognitive Fukukura et Psychol- consequences of hedonic future studies al. (2013) ogy events and future orientation of cognitive studies In relation to climate change, Anticipation Bennett Nuttall (2010, p. 23) states, to orient hu- (1976), Nut- “While adaptation is largely about man action; tall (2010) responses to climate change, how people anticipation is about intention- make choices ality, action, agency, imagina- and decisions Anthro- tion, possibility, and choice; but based on pre- pology it is also about being doubtful, dictions, ex- unsure, uncertain, fearful, and pectations or apprehensive.” Nuttall finds that beliefs about anticipation may be a prerequisite the future for thinking about CCA (Climate Change Adaptation)
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Anticipatory adaptation acts on Anticipation Alme- the best models of climate change is an import- dom et al. impacts. They “are effective in ant feature of (2007), Mar- creating systems that can main- resilience. Re- tin-Breen tain their state in response to the silience litera- and Ander- unexpected crises arising from ture mentions ies (2011), Resilience climate change” (Martin-Breen anticipation Berkes et al. and Anderies 2011, p. 48) but does not (2003) seem to draw extensively upon antici- pation theory According to Fuerth (2009, p. Anticipatory Quay (2010), 29), anticipatory governance is “a governance; Fuerth system of institutions, rules, and forecasting, (2009), norms that provide a way to use simulation, Karinen Futures, foresight to reduce risk, and to trend extrap- and Gus- planning increase capacity to respond to olation, sce- ton (2010), events at early rather than later narios. Antic- Miller (2006, stages of their development.” ipation is well 2007, 2011, developed in 2012) this field
Rossel (Rossel, 2010) stresses that the anticipatory systems concept is another way of framing reality, so even with highly sophisticated modelling tools, we cannot escape our inability to be outside ourselves. The same is true for public administration as the governments could not be indifferent to the contemporary public and global issues. Beyond the definitions above, the essential problem is thatthere is a common feeling that man’s needs for understanding and controlling themselves and their societies may, in the next thirty years, be different from their current needs. It is difficult to deny the validity of these feelings (Emery, 1997).
Public Administration Today Public administration is the implementation of government policies and an academic discipline that studies this implementation and prepares civil servants for working in the public service. Today public administration is often regarded as including also some responsibility
218 ANTICIPATORY PUBLIC MANAGEMENT for determining the policies and programs of governments. Specifically, it is the planning, organizing, directing, coordinating, and controlling of government operations. Within the framework of the phases in the evolution of public administration, traditional public administration has taken the course of being regimented; rule and procedure based and centred on top-down, not bottom-up planning, decision-making, implementation, and public personnel administration. Since the 1980s, with the new public management, the practice in public sector moved into a focus on reducing the size and scope of government; the goal was more on market-driven approaches to government and non- governmental action which includes subcontracting works and projects. By the late 1980s and the early 1990s, as their role became more complex and demanding, governments needed more flexibility. As a result, many of the reforms that they introduced during this period were aimed at making public service organizations more productive, efficient and effective. Many of the realized reforms have also involved a focus on improving governance (Bourgon, 2009). The public sector has moved today into a system of networked governance. In network governance, the role of the government is less central or much smaller in steering and dictating the terms of societal policy governance. In fact, the role of government vis-à-vis other actors (non-governmental actors) has shifted significantly in the past two decades, and it is likely that these relationships will continue to be refined or even redefined. Both the tools and how governments interact with citizens and other actors (non-governmental organizations) have changed, most notably with the rise of e-government initiatives and civil society, and this raises new questions of accountability, transparency, and trustworthiness of government and public administration (Curry, 2014). Networked governance has as a result of this rise in prominence as a way to address the lessening of hierarchy within and between many public- sector bodies, and between governmental (state-actors, governmental institutions, bureaucracies) and nongovernmental (non-state) actors including civil society, charitable and/or environmental organizations, transnational corporations (TNCs), etc.
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All these developments nevertheless will not be enough to prepare governments to serve citizens in the 21st Century. Because the future that has become a common theme in the governance of contemporary societies, particularly in the context of technological developments, is presented as open and uncertain. According to Bourgon (Bourgon, 2009), future reforms regarding public administration and services must also explore the role of governments in a world that is characterized by unpredictability, discontinuity, disruptions, unforeseen risks, and unprecedented breakthroughs. Within this framework, “anticipatory governance” appears as the other concept related to the governance; it is a new concept that has significant relevance for developing strategies under uncertain environmental futures. Its anticipatory dimension plays an important role in public administration since anticipatory governance involves changing short-term decision making to a longer- term policy vision, including the notion of foresight. Multiple strategies are anticipated, which are appropriate in the short and long term, given the range of possible futures. Changing conditions are monitored over time (Boyd, et al., 2015). The other definition of the anticipatory governance emphasizes its contribution to building capacities in foresight. So, according to the detailed definition of the anticipatory governance, it is “a broad- based capacity extended through society that can act on a variety of inputs to manage emerging knowledge-based technologies while such management is still possible.” It motivates activities designed to build capacities in foresight, engagement, and integration – as well as through their production ensemble (Guston, 2014). The analysis of the paradigm shift from government to governance, from public administration to public management will help to understand better how anticipation could be only possible, realizable within the public management and governance approach.
Shifts in paradigms: Administration versus Management According to above briefly summarized transformations of public administration, the public sector in many developed countries feels the
220 ANTICIPATORY PUBLIC MANAGEMENT need to move beyond the static and machine bureaucratic paradigm of Weber’s traditional (bureaucratic) system to the New Public Management system. Furthermore, several alternatives to New Public Management, such as the New Governance and Public Values paradigms have also gained prominence in recent years. Paradigm is one of the most important words for public administration because the easiest way to see the development of the field by classifying theories of public administration into eras like the first paradigm “Politics-Administration Dichotomy” includes the period 1900-1926, while the second “Principle of Administration” embraces the period 1927-1936. Several frameworks have been developed to classify and analyze different approaches to public administration and public sector reforms in advanced industrialized countries. Most of these focus on the transition from the Old/Traditional Public Administration to the New Public Management that occurred in the 1980s and 1990s as shown in detail in the table below:
Phase Indicative Period Traditional / Classical Public Administration 1800s to 1950s Modern Public Administration 1950 to the present Development Administration (the 1950s to 1960s) New Public Administration (the 1970s) New Public Management (the 1980s to 1990s) Reinventing Government (the 1990s) PA as Governance (the 1990s to the present)
From 2000 there was a discernible trend towards an emerging model variously termed the “new public service,” the “new public governance” or the “post-New Public Management”? (Denhardt & Denhardt, 2000) (Dunleavy & Hood, 1994) (Osborne, 2006). The “Classic Model” was appropriate to the industrial age but is quite overcome by the contemporary conditions of globalization, social networking, information technology, climate warming, and pandemics. The Classic Model saw“ government as primarily a provider of professional services”, whereas the public interest today “can best be described as a
221 ANTICIPATION collective enterprise that involves government and many other actors and citizens as value creators and co-producers of public results, an idea that is turning public administration on its head” (Bourgon, 2012). Regarding New Public Management as a term coined in the late 1980s to denote new stress on the importance of management and ‘production engineering’ in public service delivery, it is often linked to doctrines of economic rationalism (Hood, 1989) (Pollitt, 1993). So, the New Public Management system has been the dominant paradigm in public administration theory and practice since the last 30 years determining its affinity with markets and private sector management. Anglo Saxon states such as USA, UK, New Zealand, Australia, etc. adopted vivid reform discourses to transform the paradigm of public administration from Weber’s traditional bureaucratic system to the New Public Management system. Reform efforts were mostly the principles of downsizing and entrepreneurship, decentralization, performance management, planning, and control cycle (Rahman, et al., 2013). NPM shifts the emphasis from traditional public administration to public management and also pushes the state toward managerialism. The traditional model of organization and delivery of public services, based on the principles of bureaucratic hierarchy, planning, centralization, direct control, and self-sufficiency, is being replaced by market-based public service management, or enterprise culture (Walsh, 1995). B.G. Peters (Peters, 2002) interpret this paradigm shift between “the classic model” and NPM differently; he suggests two extreme models for governing: the traditional hierarchy model and the market alternative, which provides some important benefits in the provision of public services but also may have some weighty disadvantages as well. He argues that the process of moving away from the traditional concept of governing and toward alternative modes of governance is far from complete. What has been occurring is a process of reform of the public sector that introduces some features of the governance model while at the same time retaining many aspects of traditional governing (Vigoda, 2002). The challenges of today certainly have a huge influence on the paradigm shift in theory. Some authors as Caldwell (Caldwell, 2002) addresses the
222 ANTICIPATORY PUBLIC MANAGEMENT problems of public administration in a highly informed society, dealing with ethics, law, human rights, and scientific information. Caldwell argues that with the onset of the 21st century, the expansion of technology has profoundly altered the processes of communication and the treatment of information. The impact of this increasing technologic capability has been experienced notably in the more ‘‘developed’’ societies with higher levels of public information and organized participation in public affairs (Vigoda, 2002). New opportunities and hazards undeniably challenge governments and their public administration. As the consequences of the unprecedented developments are realized, doubt has arisen among many as to our ability to responsibly manage the new information and communication capabilities. As a result, the public sector in many developed countries feels the need to move beyond the static and machine bureaucratic paradigm of Weber’s traditional (bureaucratic) system to the New Public Management system. In sum, since the early 1980s, there have been significant changes like the state and its governance worldwide. These unprecedented changes or reforms are largely guided by the assumptions of state failure and market superiority, the objective of replacing the role of the state by non-state actors, and the agenda of transforming public governance based on market-oriented principles, policies, and standards (Clarke & Newman, 1997). The existing literature tends to characterize these paradigmatic changes often regarding neoliberal ideology, new economic policy, and New Public Management. Within this section, our focus is confined to the broader shift in approach set out by Osborne (Osborne, 2006) who outlines three modes of public administration and management and, by association, their principal characteristics as follows: Public Administration (PA-statist and bureaucratic), New Public Management (NPM-competitive and minimalist) and New Public Governance (NPG- plural and pluralist) (Robinson, 2015). Besides analysing the changes and transformations in public administration literature, understanding what public administration is today depends on understanding its social and political-economic
223 ANTICIPATION context as well. According to Eikenberry (Eikenberry, 2009), society today is increasingly characterized by the dissolution of traditional authority, parameters, and support systems. This change has been described as a shift from the traditional to the post-traditional. Within this post-traditional period, anticipation in public management becomes crucial / comes into prominence as Catlaw (Catlaw, 2006) said, “what has been” no longer provides the moral and normative content for “what should be done” in any general way. The traditional public administration is considered predictable. So, this approach is based on the idea that “uncertainty must be eliminated” while new public management approach appears more flexible, participant, transparent, accountable, responsiveness that could overcome the uncertainty.
Shifts in context: Need for change and innovation Both the theory and the practice of public administration have been extraordinarily dynamic. As everything around us is changing in an increasingly interconnected environment, with simultaneous changes – shocks, crises, failures, surprising breakthroughs, in several fields such as society, politics, business and economics, the field of public administration cannot be away from the need to innovate and change. There are four transformations that indicate why we need to change and innovate: first, the nature of our concerns, priorities, and issues has grown in complexity and scope; secondly, the shift away from short term solutions and towards transformative, enduring change; and then finally the expansion of values from solely effectiveness and efficiency to equity and ethics. According to Farazmand, four major challenges exist facing public administration: predatory globalization, institutional failure, poverty of the field, and success of the field, with technology introduced as a fifth challenge (Farazmand, 2012). The last but not the least, advances in technology, the rapid spread of information along with the use of technology and social media as well have been affected and accompanied the shift in paradigm regarding public administration field that we
224 ANTICIPATORY PUBLIC MANAGEMENT have mentioned below. The context where public officials serve is also changing; it is now an expanded public space that is being reshaped by the rise of social networking and modern information and communication technologies. So, in this era we are going through, several features could be observed such as connectivity, volatility, ambiguity and the rise of the curious class (people who ask questions). These characteristics influence all parts of life, and they also have a significant influence on the public sector as well. The changes regarding public sector have two sides. First, for the developed countries, public administrations have to find ways to save money, cut down on costs, and generate more returns for their investments. On the other hand, many governments / public administrations in developing countries must contend with radical changes because of the red-tape bureaucracy and corrupt bureaucrats. In consequence of the use of the technology by masses and their protest, the public sector faced pressure and has to make the bureaucrats more accountable. Within this context, emerging trends and future directions on public management could be identified like governance, stakeholder-based analysis, network analysis, self-organizing, evidence-based policy and management, organizational learning and innovation, user and community co-production. While essential public services are not likely to disappear any time soon, the way their administrative functions are carried out and evaluated is likely to change considerably. In a globalized world characterized by increasing uncertainty and growing expectations of the demanding citizenry, the politics of budgetary austerity is pressing on public administrators at every level of government. They must think in radically different ways about what it means to govern in the 21st century. The future of public administration predicts a future with new sets of challenges for the nation-state and its public administration systems (Theodoulou & Roy, 2016). There are several ways in which the public sector can innovate. Most of them are using technology more proactively, collaborating and communicating within and with the external world, adopting a more humane approach to administration and attending to the grievances of
225 ANTICIPATION the citizenry, and most importantly “walking the talk” which meant that they had not only to declare their intent but also have to act accordingly. As for using technology and social media, the public sector and the public managers are gradually taking to Information Technologies to communicate and collaborate among them as well as with the external world. As it has been observed, a rapid change characterizes the world we live in. Globalization and information technologies are both causes and effects of change, and as a result, public administration has had to respond and adapt to these driving forces (Zulean, et al., 2017). Globalization and Information Technology are not the only strongest driving forces for change, but also the KPMG report named “Future State 2030” (KPMG, 2014)2 identifies nine global megatrends3 that are most salient to the future of governments, public administrations, and citizens. The report also discusses a set of characteristics, which it suggests will be typical of “leading practice” governments in the future (KPMG, 2014). These characteristics, which include more evidence-based policy making, more long-term thinking, and more market testing of providers, are contrasted with “characteristics of typical constraints facing some governments today” (KPMG, 2014). As a result, if the traditional public administration is considered as predictable, so preparedness comes out as one of the features within the New Public Management and governance approach. Following same order, the retrospective thinking replaces the anticipatory proactive thinking in the New Public Management. Within the New Public Management, anticipatory proactive thinking arises as more important than retrospective thinking, as the future is multiple and uncertain. There is not one, but multiple possible futures are foreseen in the transition from past to present, and from present to future. The question, hence,
2 https://assets.kpmg.com/content/dam/kpmg/pdf/2014/02/future-state- 2030-v3.pdf (accessed 5 May 2018) 3 Demographics, Rise of the individual, Enabling technology, Public debt, Economic power shift, Climate change, Resource stress, Urbanization
226 ANTICIPATORY PUBLIC MANAGEMENT becomes how will the public administration deal with the multiplicity of possible and uncertain futures.
Where Now? Future Trends in Public Administration As mentioned previously of this chapter, there have recently been considerable changes like state governance and public administration based on certain market-oriented principles, structures, and standards. Considering factors that influence this paradigm shift in the public administration, the article also presents the trends affecting the future of the public administration, public sector exploring some examples from several countries which adopted a long-term vision. As a major consequence of the advances in technology, the way we access and share information has changed, and all these have a significant influence on foresight system of governments that means the ability to anticipate, intervene, innovate and adapt concerning many public issues and contemporary debates from climate change to global economic crises. Thus, anticipatory practices are coming to the forefront of political, organizational, and citizens’ society. Therefore, public administrations/ governments have to explore how to improve the capacity of a given society to innovate, prosper and especially adapt to emerging issues, unforeseen events and changing circumstances. As a result, foresight activities and anticipatory practices would contribute to good governance; in other words, collective power in the 21st century could give us the idea on several trends affecting the future of the public sector.
Serving beyond the predictable? Some More Recent Future Trends in Public Administration Although the field of public administration has always been dynamic and ever evolving; it’s experiencing unstoppable and rapid changes today than ever before. A mix of technological and social trends has markedly impacted the public administration, especially the way of policy development and its implementation on every level from local to central or even global.
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Technology has been a deciding factor in everything from local elections to the entire nation’s popular revolution. It changes the way the news is reported, the way law enforcement works, and the way leaders communicate with their constituents. (access on http://patimes.org/ significant-issues-public-administration) In an age characterized by increasing use of the internet and the communication technologies, public administrators are facing the challenge of reorganizing the public services to become fully electronically accessible. Some biggest trends are affecting public administration which can be listed as technology boom, democratization, global thinking, sustainable systems, and these trends are likely to expand in the future years. Global thinking aided by information and communication technologies increased awareness of world-spanning issues and meant more people are becoming globally minded. Topics like environmental sustainability, equal rights for girls and women, and international trade, climate change, etc. are discussed on social media by growing numbers of people every day. The other trend, (the first trend mentioned as global thinking) sustainable systems includes some features of the transition of public administration from 20th to the 21st century. Applying simple market principles related to perpetual growth and prosperity has led to boom and bust patterns in every aspect of society. With global economic crises now a fact of life, public policy is joining many other systems in the promotion of sustainability. This situation will mean a reduction in waste, corruption, and inefficiency for the sake of realistic long-term planning. Public administration professionals must continuously keep an eye on the future to ensure that today’s policies remain functional for tomorrow’s problems. A dramatic change in the 21st century is undergoing in public administration. This change is especially visual in advanced economies. But can also be felt in many parts of the developing world. Globalization and the pluralization of service provision are the driving forces behind these changes (Robinson, UNDP, 2015). The era of E-Government, which can be defined as the use of IT within government to achieve
228 ANTICIPATORY PUBLIC MANAGEMENT more efficient operations, better quality of service and easy public access to government information and services, is now underway (Kraemer & King, 2005). Gibson and Hammer (1985) claim that “today’s applications of information technology can dramatically change the way individuals, functional units, and whole organizations carry out their tasks.” Today’s ideal public administration professional should be tech-savvy, communicative, globally minded, and efficiency driven. This requires continuous learning and a strong will to stay informed (California, 2015). In that case, the public administration of the future must be flexible, anticipatory, interconnected and human-centered.
The government of the Future The aim of the public decision-making process within the legislative, the executive and the judiciary, is to organize society and to lead its future developments. Indisputably then anticipation will be one of the most fundamental activities of future public decision makers (Petit Jean & Brunet, 2017). According to Poli (Poli, 2009), behaving in an anticipatory way means adjusting present behaviour to address future problems. In other words, an anticipatory entity (system or whatever) makes its decisions in the present according to forecasts about something that may eventually happen. In this section, the anticipative capacity of governments will be discussed with some country examples. The future holds complex problems and challenges. Policy makers use foresight techniques to explore alternatives for a better future in a structured way. Additionality to the trends affecting the future of the public sector mentioned below, this section explores some examples from several countries which adopted a long-term vision and strategy such as Singapore’s Risk Assessment and Horizon Scanning Program, Finnish Parliament’s Committee for the Future, or Project on Forward Engagement in the United States. The European Union (EU) in particular –as a supranational organization, underlines the foresight and prepares reports on its importance for its member and candidate countries.4 According to the EU, the foresight helps first to evaluate
4 Please go to the web page below for the European Union’s foresight definition:
229 ANTICIPATION current policy priorities as well as potential new policy directions. Then see how the impact of possible policy decisions may combine with other developments; following inform, support and link policy-making in and across a range of sectors; identify future directions, emerging technologies, new societal demands, and challenges. Finally anticipate future developments, disruptive events, risks, and opportunities. Authors van der Steen and van Twist ( (van der Steen & van Twist, 2013) and Nelson (Nelson, et al., 2008) state that anticipatory practices are practices that produce anticipatory knowledge. Such knowledge provides information and insight about the future, and this information must be transformed into real actions plans. This epistemological characteristic of anticipatory knowledge supports its performative aspect related to the action. According to Anderson (Anderson, 2010), anticipatory practices are practices that give content to futures and make them present through specific materialities. These practices range from calculation techniques, forms of imagining futures such as scenarios, to forms of performing futures such as gaming, role-playing, etc.; these are collective practices that involve the circulation of collective expectations (Konrad, 2006). The first example is the “Finnish Parliament’s Committee for the Future”; the Constitution underpins a Standing Permanent Committee of 17 parliamentarians representing all political parties. They deliberate about matters affecting future development, research and the impacts of technological development, acting in effect to guard against short- sightedness by the government. They are not involved in legislative proposals or scrutiny; rather its role is on the Future such as to prepare parliamentary documents such as Parliament’s response to the Government’s Report on the Future, to discuss future trends and related issues, to serve as the parliamentary body responsible for assessing technological development and societal consequences. They have the power to decide on their agenda and take initiatives, preparing studies on futures, in a sense serving as Parliament’s think tank. They call this “the power of vision.” They also provide information to support the Parliament’s decision-making processes by assessing the long-term
http://ec.europa.eu/research/foresight/index.cfm
230 ANTICIPATORY PUBLIC MANAGEMENT effects of current decisions.5 The Singapore’s Risk Assessment and Horizon Scanning Program (RSHS) was launched in 2004, as part of the National Security Coordination Secretariat. The RAHS program explores methods and tools that complement scenario planning in anticipating strategic issues with a significant possible impact on Singapore.6 Projects carried out by the Program generally explore emerging issues with the aim of enhancing strategic anticipation capabilities for the agencies. Other examples are from Sweden and the Netherlands which were founded in the early 1970s. It was the dramatic political, social and technological changes in the 1960s and 1970s that significantly increased interest in future studies. One of them was the Swedish Secretariat for Futures Studies7, established in 1973, the predecessor to the Institute for Futures Studies. Sven Tägil (Tägil, 1981) summarizes in his article some studies of Sweden in the long-term international context, undertaken by the Secretariat. Four scenarios/perspectives are presented; they contain international and domestic issues. According to the article, Sweden is often characterized as a highly developed, wealthy and stable small state. The Swedish Secretariat for Futures Studies has played a central role in this context. The following wishes were already expressed in the directives for the government study which preceded the foundation of the Secretariat (Tägil, 1981):
An important and necessary means to this end is that we ourselves study the future, for us and the world around us, and base these studies on democratic objectives and articulated demands for international solidarity. In that way, the small state can mobilize opinion in favour of other possible alternatives as to how the future world should be constituted.
5 Please go to the web page below for more details: http://www.fdsd.org/ideas/the-committee-for-the-future-finnish-parliament 6 Please go to the web page below for more details: https://www.nscs.gov.sg/public/content.aspx?sid=191 7 Please go to the web page for more details: https://www.iffs.se/en/research/
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As for the Dutch case, there is The Netherlands Scientific Council for Government Policy8, established in 1972, tasked with identifying and advising on future trends and developments. This was a period in which advisory councils were used mainly in specific policy domains and to increase the public voice in policy decisions. In this context, The Netherlands Scientific Council for Government Policy was a new kind of institute with a new kind of task. In their article, John Schoonenboom and Frank Veeneklaas analyse the efforts of the Council to survey the future of Dutch society as a whole (Schoonenboom & Veeneklaas, 1985). The article describes the Council’s future survey and its use of various normative perceptions discernible in the political system. According to Michio Kaku (professor of theoretical physicist, futurist, and popularizer of science - science communicator), “it is impossible to predict the future with great accuracy.” So, the future is unpredictable; it is only designed and experienced. As explained at defining anticipation section, foresight starts by gathering information about possibilities, abilities, and intentions. This information is then processed via “strategic intelligence” and “sense-making” to provide policymakers with information that will support their present-day decisions and help them shape the future. Public administrations/governments of different countries should then adopt, for predicting the future, a system called “innovative governance” that enables to adapt first to the particular situation of each country and secondly, to every kind of problems, events, and challenges while protecting the basic features of the governance simultaneously. In the future, the anticipative capacity of governments will be an important component for the whole public management system. The examples mentioned above show the importance to prepare government for the challenge “serving beyond the predictable.” It’s possible to indicate that the Western outlook on life is prospective rather than retrospective. Its mood is one of anticipation rather than of reflection. (Mennell & Rundell, 1998)
8 Please go to the web page for more details: https://english.wrr.nl/about-us
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The question appears “How to improve the anticipative, innovative and adaptative capacities of government and society.” Countries with the capability to anticipate and the ability to use these insights to make better decisions and intervene ahead of time will have an important advantage.
Conclusion the ability to anticipate in an ever-changing world and complex environments may improve the resilience of governments under global threats and insecurities. The first part of the article explained the limitations of hierarchy and rigidity associated with the traditional Public Administration approach and on the other hand, the paradigm shift to New Public Management perspective and governance system (networked governance and anticipative governance) that emerged in the 1980s. Public administration does not exist in a vacuum and is largely shaped by the political and social context in which it operates. At the same time, public administration responses can in turn shape external factors, population and demographic change, energy and the environment, food issues, public debt and information technology (Curry, 2014). Fountain (Fountain, 2002) says, “Technology is a catalyst for social, economic and political change at the levels of the individual, group, organization, and institution. And he is initially assumed that the Internet “…would overwhelm organizational forms and individual resistance and…would lead to rapid organizational change” (Batalli, 2016). So, technology will surely have a significant impact on how governments interact with their citizens and develop appropriate legislation to meet their demand. Therefore, it obliges both foresight activities for public administrations and facilitates them at the same time. Hence, public administration will have to adapt accordingly. Some authors (Robertson & Choi, 2010) foresee public administration reforms as adapting to large trends in society, moving from a mechanistic view of the world to a more ecological approach (Curry, 2014). This ecological approach will emphasize interconnectedness, self-organizational capacity and co- evolutionary dynamics of public administration systems, over a more
233 ANTICIPATION mechanistic approach of reductionism, competition and prediction, and control. This shift will have an impact on the purpose, design, process, and relationships underpinning public administration. (Robertson & Choi, 2010) Briefly, the first item for the government of the future would be to remove the opaqueness and the secrecy surrounding its activities and instead embrace accountability and transparency as the principal motto. For instance, the government of the future is one where the citizenry is made aware of the decisions taken by it rather than hiding under laws and regulations in the name of confidentiality. Apart from this, the government of the future is one that is proactive instead of reactive where it anticipates the changing trends and responds accordingly to events and incidents. As the good governance also requires, this means that the public servants have to be responsive to all the stakeholders including their superiors, the elected representatives, and most importantly the citizenry instead of favouring a privileged group over the other. So, in the high-tech high-touch era, the public sector can provide services and innovate using technology and should adopt a more humane approach to administration and consequently, the future belongs to the flexible sector rather than machine bureaucracies.
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Social Studies of Science (SAGE), Cilt 44(2), pp. 218-242. Hood, C., 1989. Public Administration and Public Policy: Intellectual Challenges for the 1990s. Australian Journal of Public Administration , Cilt 48, pp. 346-358. KPMG, 2014. Future State 2030: The Global Megatrends Shaping Governments, s.l.: s.n. Mennell, S. & Rundell, J. F., 1998. Classical Readings in Culture and Civilization. s.l.:Psychology Press. Nelson, N., Geltzer, A. & Hilgartner, S., 2008. Introduction: the anticipatory state: making policy-relevant knowledge about the future. Science and Public Policy, 35(8), pp. 546-550. Osborne, S., 2006. The New Public Governance?.Public Management Review, 8(3), pp. 377-388. Peters, B., 2002. Governing in a Market Era: Alternative Models of Governing. %1 içindeE. Vigoda, dü. Public Administration: An Interdisciplinary Critical Analysis. New York: Marcel Dekker, INC.. Petit Jean, M. & Brunet, S., 2017. Does anticipation matter for public administration? The case of the Walloon Region (Belgium).Foresight , 19(3), pp. 280-290. Pfiffner P., J., 2004. Traditional Public Administration versus The New Public Management: Accountability versus Efficiency. %1 içindeA. Benz, H. Siedentopf & K. Sommermann P., düz. Institutionenbildung in Regierung und Verwaltung: Festschrift fur Klaus Konig. Berlin: Duncker&Humbolt, pp. 443-454. Poli, R., 2009. The Many Aspects of Anticipation.Foresight. Poli, R., 2011. Steps toward an explicit ontology of the future. Journal of Future Studies, Cilt 16, pp. 67-78. Pollitt, C., 1993. Modernizing the Management of the Public Services Sector: Between Crusade and Catastrophe?. Helsinki, s.n. Rahman, M., Liberman, L. S., Rolandas, V. & Akhter, T., 2013. The Paradigm from Traditional Public Administration to New Public Management System in Bangladesh: What Do Reform Initiatives Stand for?. pp. 297-303. Robertson, P. & Choi, T., 2010. Ecological Governance: Organizing
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Principles for an Emerging Era. Public Administration Review, Issue Special Issue, pp. 89-99. Robinson, M., 2015. From Old Public Administration to the New Public Service: Implications for Public SectorReform in Developing Countries, Singapore: UNDP / Global Centre for Public Service Excellence . Rosen, R., 1985. Anticipatory systems. Philosophical, mathematical and methodological foundations. 2nd edn, 2012 dü. s.l.:Pergamon Press. Rossel, P., 2010. Making anticipatory systems more robust. Foresight, 12(3), pp. 72-85. Schoonenboom, J. & Veeneklaas, F., 1985. Political Images of the Future: The Dutch Case. Futures, pp. 360-374. Stanley H., U., 1959. Bureaucracy and Rationality in Weber’s Organization Theory: An Empirical Study.American Sociology Review, 24(6), pp. 791-795. Tägil, S., 1981. Sweden in the World: Some alternatives for a small state. Futures, pp. 2-12. Theodoulou , S. Z. & Roy, R. K., 2016.Very short introductions. [Çevrimiçi] [%1 tarihinde erişilmiştir2017]. van der Steen, M. & van Twist, M., 2013. Foresight and long-term policy-making: an analysis of anticipatory boundary work in policy organizations in the Netherlands. Futures, Cilt 54, pp. 33-42. Vigoda, E., 2002. Public Administration: An Interdisciplinary Critical Analysis. New York: Marcel Dekker, INC.. Voros, J., 2007. On the philosophical foundation of futures research . %1 içindeP. v. d. Duin, dü. Knowing Tomorrow? How Science Deals with the Future. Delft: Eburon Academic Publishers, pp. 69-90. Walsh, K., 1995. Public Services and Market Mechanisms: Competition, Contracting and the New Public Management. London, UK: Macmillan. Zulean, M. et al., 2017. Romanian public administration 2.0: using innovative foresight methodologies to engage stakeholders and the public. Foresight, 19(3), pp. 261-279.
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12 ANTICIPATION IN ARCHITECTURAL UTOPIAS: An Analyze of Le Corbusier’s Urbanisme
Ece Ceylan Baba
Introduction The concept of anticipation is a complex entity that serves to handle decisions with addressing future problems that may happen. Architecture is also a complex field where anticipation may be critical. Architectural utopias analyze and criticize humankind’s present problems according to futuristic forecasts. Moreover, both anticipation and architectural utopias consist of present acts that use future predictions. This similarity between anticipation and architectural utopias establishes the basis for this paper. “Anticipation” in referring to architectural utopia studies is also a central premise. In this study, anticipation and anticipatory points are related to utopian architectural approaches. Anticipatory thoughts (systems) may cause some side effects that cannot be predicted during progress. In utopias, the final result may be dramatically different than which is foreseen. The conduct of architectural utopia, which is itself an enlightened approach, is based on the complete demolition of existing structures through human intervention and their replacement with artificial but new and rational-functional structures. The method for transformation is not evolutionary. It’s revolutionary. Past experience proves that utopias that look perfect on paper may bring highly imperfect results in practice. The fact that utopias squeeze present systems into ‘good on paper’ models and attempt to alter them strictly on the basis of these models leads to a number of unwanted side effects. These cannot always be foreseen for various reasons that may emerge during the design
239 ANTICIPATION process or due to the limitations of science. Such side effects may hinder adaptation of the system to the model and transform the model, which was initially designed as a utopia, into a dystopia. Side effects manifest as structural consequences of a system’s configuration based on specific models (Poli, 2010, p.4). A model cannot represent all the key features of a system (apart from the most basic system) and its entire interaction with other systems. Even anticipatory systems that are considered able to anticipate their own evolution (Poli, 2009, p.19) may contain immensely vague and obscure elements (Poli, 2010b, p.15). The effectors that have impact on a system almost always bring other or different impacts than projected, which means architectural utopian modelling can only predict transformations which will take place in the future of a system with inevitable margins of error. The more dramatic the increase in the margins of error and the greater and more complex the undesired side effects generated by the model in terms of representation of the system’s future become the more complex the modelling and system. Accordingly, models of an immensely complex system tend to generate immense side effects. Although architectural utopias are generated via anticipatory approaches for the shaping of the future, they are also the cause of a number of unwanted, unexpected, unpredictable and uncalculated side effects. These are mostly very hard or impossible to foresee, but the harmful side effects are directly proportional to the size of human interventions in the environment. In this article, utopia is considered as an example of “anticipation in architecture” as a normative anticipation model. In other words, normative anticipation leads to a vision, this vision is related with utopia. This study examines the possible relationships between anticipation and architectural utopias with different approaches in a conceptual manner, and analyzes the subject on an architectural utopic example.
Anticipation in Conceptual Context Anticipation is a relatively new concept that has multi dimensional meanings. The term has two different meanings. Firstly, it refers to a
240 ANTICIPATION IN ARCHITECTURAL UTOPIAS distinct aspect of futures studies that goes beyond forecast and foresight modeling. Secondly, it acts as the qualifier anticipatory in the expression of anticipatory systems. (Poli, 2017) In this study, the framework of anticipation is mainly considered as an aspect of future studies that has a distinctive “act” in its process.
There are several dictionary meanings of anticipation. Selected two are listed below.
The Advanced Learner’s Dictionary of Current English, 2nd edition, Oxford University Press, UK, 1971 anticipate: 1. do, make use of, before the right or natural time 2. do something before somebody else does it 3. see what needs doing, what is likely to happen, etc. and do what is necessary 4. look forward to, expect anticipation : action of anticipating.
R. Soule, Dictionary of English Synonyms, Omega Books, London, 1986 anticipate : 1. go before, get the start of. 2. take up beforehand, consider in advance, meet or play in advance. 3. foretaste, forestall, experience beforehand. 4. expect, forecast, foresee, look forward to, count upon, calculate upon, and prepare one’s self for. anticipation: 1. expectation, expectance, contemplation, prospect, hope, trust. 2. foretaste, prelibation, antepast, presentiment, forestalling, foreseeing, foresight, prescience, prevision, forethought, forecast, preconception, experience beforehand, prior realization
Anticipation is discussed in this paper with its feature of decicion- making while addressing the future. Likewise, architectural utopias always
241 ANTICIPATION refer to the future in an unknown place and time. Anticipation is a bunch of decisions taken in the present according to forecasts. Anticipation sometimes refers to foresight, however anticipation is an active and action-oriented concept, whereas foresight is passive. This important difference establishes the principle common point of anticipation and design, which also is an active and action oriented concept.
Architectural Utopias Utopia is a place imagined but not realized (Noble, 2009, p. 12). It is yet nowhere but it is already there (Havemann, 1990, p. 61). It is a modeled design of perfection and a contender to replace the existing and defective system. It is an abstract design, but its very purpose is to embody by preserving all its features. Utopia can be defined briefly by two main concepts: first it is stagnant, second progressive. Utopias aspire to change the existing structure altogether. For this reason, they are radical and revolutionary. However, if they reach the new urban architecture and social structure they intend, they would no longer accept any changes (Kurt, 2007, p. 160). Because any change that will take place after that, would mean a deviation from the ideal society that has been reached or created, and an impairment from the perfect structure. For this reason, utopias aim for an indeterminate conservatism from the moment they actualize themselves. Nevertheless, since no utopia in history has been actualized to build itself in such a way that the design on paper is perfected, if this indeterminate conservatism can actually be carried out or not has not been tested. But the utopia, which is revolutionary in the theoretical sense cannot build itself, it disperses into conservatism in theoretical perception, and places itself in this stagnancy forever. Equality, prosperity, and order that are dreamed of in utopias have never achieved that perfect structure as the utopias aim. However, although criticized for a variety of reasons, utopian initiatives have always provided new and progressive solutions for the city and urban space, and they have also succeeded in actualizing some of them (Kahya, 2007, p. 21, 22).
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Distinctive features of utopia are the rational order, the authoritarian and totalitarian attitude, the absolutism, and the hindrance to alternative choices by getting its strength from its perfection (Mumford, 1996, p.362, 363). They have almost always emerged in periods when societies have suffered from depression and decay (Usta, 2015, p.18). Utopia has appeared as a literary genre of the theory of state. Although types of utopias differ in the following years, they have always continued to be hand in hand with the theory of the state, even when they have converted into architectural utopias. In this sense, utopias, even in their most architecturally weighted versions, are within the tradition of political philosophy and in search for the ideal order (Davis, 1983, p.57). Each of the utopias, within the framework of theory of state, intended to produce a city state and by claiming that these city states should dominate over the whole world; although they seem to be making a single model, but in fact they have been contenders to transform the whole world (Usta, 2015, p.18,19). Utopia has achieved ultimate and eternal perfection of the already existing world, which it has abolished, and surpassed (Havemann, 2005, p. 20). Utopianism aims to build an ideal universe in which all conflicts of conscience and interest in society ended, everything that is obstructive to a prestigious life is removed with the help of modern technology, and to create an environment where peace, prosperity and virtue are eternal and universal (Kateb, 1975, p.17). Each one of the utopias is an ideal and even the tiniest drop in the ideal in this sense will disrupt its supreme position and abolish the utopia. For this reason, although many utopian ideals has been tried to be actualized in history, these ideals have never been realized without loss, because of the many different factors that have not been accounted for on paper or in theory. But utopias have never been ineffective just because they have not been actualized in their ideal states. On the contrary, the most important influences of utopias in history have been their ability to transform the past and the society. Although utopian ideals have not succeeded in direct actualization of utopias, they have been successful in transforming the world with radical changes each time. Utopias have become the most
243 ANTICIPATION important leverage of the movement, in the sense that history, in the face of current circumstances, being intercepted by the free-formed thoughts developed by the human mind and facilitate significant leaps. The image below is an example of a utopia which is designed for an ideal future life. This ideal life is consisted of transformation of the past and the society.
An anonymous image of an utopia from 20th century. (https://warosu.org/sci/thread/9510383 - date: 4.5.2019)
Utopia is a design that is primarily tailored to a location, a space and fundamentally to a city and it has an urban form (Harvey, 2008, p. 192). In fact, according to Mumford, the first utopia is the city itself (Kumar, 2005, p. 25). Utopia is a form of the space that has been liberated from its present state and structured from the very beginning somewhat into a dream. For this reason, utopias identify and describe almost all spatial organizations. From the houses to the buildings, from the workplaces to the fields, from the avenues to the streets, from the city centers to its borders, directly constructs how the whole architecture of the city will be built on the utopian frame. Thus, cities acquire the feature of being the projections that create the ideal society. Every city is a bit utopic in its essence, and every utopia is mostly a city (Yüksel, 2012, p. 11). The utopian thought that emerges from the notion that the form determines the content as well as the content determines the form, finds the architecture of its utopia, which it has determined in the city scale,
244 ANTICIPATION IN ARCHITECTURAL UTOPIAS as necessary. The architectural form, according to them, determines the material, spiritual content, destinies of the city and everyone living in it. According to this idea, a good society is be built in a systematic manner in the light of principles of mathematics, geometry, in short, rationally. Ideal city wants to capture and control all kinds of possibilities within its walls (Kumar, 2005, p. 35). Utopians do not think it is right to consider the human first and create an architecture that is appropriate for them. First, they design the appropriate architecture in the footsteps of rational principles, and then advocate that society be defined and created by this rational architecture. All utopian architecture, in this sense, is a social engineering practice. Utopia is, hence, an ideally designed urban layout proposal (Alver, 2009, p. 143).
Anticipation - Utopia Associations In this study, the association between anticipation and utopia is linked with Rosen’s anticipation definition. According to Rosen: “An anticipatory system is a system containing a predictive model of itself and/or its environment, which allows the system to change state at an instant in accord with the model’s predictions pertaining to a later instant” (Rosen, 2012, p.8). This definition has dramatic similarities with architectural utopia design process. Concepts of anticipation and utopia are related at different intersections. Both concepts include progressive proposals for the future, often departed from the past. Below, some of the subtleties about the intersection of urban utopias with the concept of anticipation are presented. The process boxes below summarizes similarity and associations of anticipation and utopias.
• In Normative Anticipation:
Forecast and/or Act (planned) in Anticipation Foresight Future
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• In Architectural Utopias:
Forecast and/or Future Planning Architectural Foresight (with action) Utopias
As defined above, the associations of utopias and anticipation is explaned briefly. The conceptual links between two concepts are defined and explained below are from the points of architectural utopias. • Anticipation of Defying the Current Order Utopia is the rejection of identifying with the circumstance encompassing the existence. In this sense, utopias are those designs that assert a claim of declaration of intent to overcome reality and not sufficing, that demonstrate actions aimed at breaking up the ‘existing order’ partly or entirely (Mannheim, 1979, p. 173). The utopian thought attempts to break the obliqueness of ideological stability that legitimates the present state. It is a radical attitude towards the operating system of the minds, in other words, a possible alternative and search for the perfect world. Every utopia is a radical critique and a rebellion against unfairness, injustice, discrimination, inefficient use of resources and especially irrationality created by the political, economic, cultural and social conditions in which the designer is included (Eurich, 1967, p.vii). Often, with the emergence of a new means of production, utopia originates from a conflict of the upcoming world with the present world. As well as transforming society, it aims to abolish and transform the shortcomings of social production order (Abensour, 2009, p.66). Severing all ties with the past is among the basic features of the utopia (Coşkun, 2004, p.22). By cutting off all ties, utopic criticism reveals that it sides with the total rejection of the past. The criticism is not related to certain persons or some aspects but to the whole system. • Anticipation of Unadulterated Rationalism “In utopia, mind has become the sole criterion of everything” (Davis,
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1983, p. 14). In Cioran’s words, “the most striking thing about utopian narrative is the lack of psychological sense of smell and intuition” (Cioran, 1999, p. 85). This is because everything is connected to the unadulterated rationalism. Its value is the mind and its symbol is the plan (Kumar, 2005, p. 35).
• Anticipation of Modelling Utopia is the modeling of a society ideal, with a view that has its own unique history and character (Kumar, 2005, p.13). Rather than the transformation of the existing, it prescribes it to be produced from the very beginning and almost completely from scratch. In this sense, it is created on a fundamental rejection of the old. In a very harmonious manner with the identity of modernism, utopia is based on the principle of designing first and consequently, actualizing later. Everything is a subset of the mind, as well as an unadulterated mind is able to design what people would need. What has not yet happened, what does not exist but seems to be realized, would be not yet happened events and unexisting yet realizable structures are first created in the human mind (Usta, 2014, p.32). And then an application that corresponds one-for-one to this creation would be pursued. Moreover, this modeling will apply not only for a location but apply to everywhere, complying with the logic of this modeling.
• Anticipation of Universality Utopia, since it is a new structure built on a fundamental rejection of the old, is not a structure which is designed for a single place and does not carry organic bonds with the old. For this reason, in accordance with the definition of the model, it claims to be universal rather than one. Utopia modeling is done once, and then the whole world is required and expected to be renewed accordingly. Utopias do not accept that they are historical and they claim to have general universal validity. It is not for a single place, but for every place. In this sense, the utopias separate “place” and “space” and they make a reference to a defined space, rather than a defined place. Thomas More,
247 ANTICIPATION who is the inventor of the word utopia, derives this word, which was the title of his text, from ancient Greek, by combining “ou” meaning “nonexistent” and topos meaning “place”. This derived word, which plainly meaning a nonexistent place, semantically supports that the utopian space does not belong to a certain place (Köksal, 2014, p. II, III). Utopias are not for a certain place. They are for everywhere.
• Anticipation of Presentation of an Alternative Order Utopia aims for the construction of a certain way of life, free from imperfections of the existing order; an alternative paradigm arising from the criticism of the present situation (Goodwin, 1980, p.384,385). Utopians think that every kind of contradiction ends in a perfect society (Cioran, 1999, p.87). The alternative order offered by the utopias is, without exception, a society without conflict. Here, conflicts of interest have been overcome, and all classes and all members of society are defined and positioned so that they act as a whole gear for the common good of the community. “We” has taken the place of “I” (Ağaoğulları, 1986, p.34). Utopians depart from the thought that the order they live in is troubled and create a positive vision for the future (Erdem, 2005, p.78). Problems such as class struggles, inequalities, unfairness and injustices, wars and miseries that exist in the present world are overcome in this vision.
• Anticipation of Perfection “There is the establishment of an ideal life in which everything goes well, every detail is considered, all human actions are calculated, identified, designed; that is, almost all problems are resolved” (Alver, 2009, p.141). Utopia is Platonic, in other words, a perfect ideal. In the Platonist sense, the “reality” which has subsided by transforming from the “ideal” to the material universe, composed of impaired representations, is tried to be converted into the ideal world through the designed utopia. The fall from perfection will turn the utopia to the contrary. At least the utopian’s belief is in this direction that human paradise will be built on earth.
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Utopia has no dynamism because claims perfection and any change that may occur in this structure may only be in the direction of deterioration. In other words, utopia is so flawless that progress is not possible in a positive direction. For this reason, utopian designs are completely closed to all kinds of changes and developments. “Monotony of perfection” reigns in utopias. However, this sharp stability imprisons the individual, for the sake of “happiness” (Ağaoğulları, 1986, p.33). The ultimate goal of the utopia is to build social integrity, order and perfection and volunteers to make it happen at any cost (Davis, 1983, p. 8). In this sense, one can state that utopias anticipate perfection.
• Anticipation of Community Engineering Utopias do not agree with the idea that human beings have a nature and that all life must be compatible with and built around this nature. On the contrary, utopists believe that by altering environmental conditions, people and society can also be altered (Kurt, 2007, p.160). These beliefs are in a methodical context. They think that they can predict what changes made in environmental conditions would bring what social changes. For this reason, utopias have an unlimited confidence that they can construct the physical conditions of the city in such a way as to create the society they want to achieve. They assume that the ideal form of the city will also shape the society and social structure ideally (Yüksel, 2012, p.11). Thereby, every utopia is actually an architectural utopia. Transformation of the physical conditions of the city will shape the society in the desired direction. Utopians view the key to the flawless ideal of society is the architecture of the city and they fully believe that they can anticipate and redesign society from top to bottom.
• Anticipation of Anti-Libertarianism Utopia, in the name of order, restrains freedoms. This is an order in which free will is put aside and no steps that are not rational are tolerated. In the name of maximum rational functioning of the society, it lifts free will from the center and excludes, forbids unequivocally everything that are irrational for the society. In this sense, utopia is oppressive and anti-libertarian which
249 ANTICIPATION does not trust the individual and therefore does not recognize its right to choose. The utopia designer alone has defined what is “the best” for everyone, and the freedom to get out of this definition is taken from the very beginning. The individual’s personality is dissolved within the society and they are reduced to a homogenous, analogous version of any individual living in the community. In utopia, private life is often interfered with, and in many utopian designs, even the right of private ownership is taken away including the right to acquire a home, and the person is forced to live a public life in the name of efficient use of resources (it is highly doubtful that these designs can achieve such efficiency). Individual freedoms, and the right to choose are sacrificed for the ideal design of society. The individual is transformed into a fiction, a symbol. People do not live there, only perform the functions defined for them. Human no longer has any personality (İzzetbegoviç, 1987, p.244, 246). In the utopias, duties, statutes of all citizens are definite and these qualities determined by the center cannot be changed (Kurt, 2007, p.160). There is no societal transitivity. In the name of an absolute equality, the freedom of individuals to be different has been effaced. The equality in the utopia is the most restrictive equality that social consensus can achieve. An equality is provided not in the sense of freedoms but in the sense of anti-libertarianism. In utopias, there is a material prosperity for all of the citizens. There is no room for poverty in these ideal designs (Meyerson, 1996, p.119). However, just as it is for equality, in the name of financial securities, the price paid by citizens is the transferal of freedoms to the central system. In utopias, individual freedom is sacrificed for material assurance. While the utopia takes away the right to choose and behavioral rights of the individual for the sake of creating a perfect society, it leans on bureaucracy and technology. In order to keep people under constant control and pressure, it invests in the bureaucracy, and to produce the means and tools necessary for the bureaucracy to fulfill this function properly, in technology. Utopian dreams often tend to result in totalitarian nightmares (Kolakowski, 1982, p.247). The authoritarian vessels of the utopias always stand as a threat for ideological abuse.
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Analyzes in the Context of Anticipation through an Urban Utopia: Le Corbusier’s “Urbanisme” One of the most important names in the modern city planning discipline is Le Corbusier, author of the book Urbanisme. Le Corbusier played a pivotal role in defining the design principles of modern architecture and in enabling the International Architecture style to spread rapidly and earned World Wide acknowledgement (Merzi, 2017, p.10, 11).
A Model of Le Corbusier’s Utopia in Paris (http://projets-architecte-urbanisme.fr/architectes/le-corbusier/, date: 2.3.2019)
Le Corbusier thinks that a rational design, in accordance with modernism, has universal validity. Paris was always in his mind when writing Urbanisme; he has started from the deficiencies of Paris and the anger he felt toward the city. However, he thought that the city he had designed in Urbanisme had to be a model for all cities of the world. This
251 ANTICIPATION is one of the main arguments of his book: according to Le Corbusier, there is only one common truth for humanity and the human mind is able to find it. Le Corbusier, in Urbanisme, claims that he found the only common truth in the modern city planning. In 1925, Le Corbusier elaborated on this design of his textually and compiled his proposals into a book, creating a corner stone, a cult study that reflected many influences today. Urbanisme is his utopia and one of the most important texts of utopian history (Köksal, 2014, p. i). For Le Corbusier, a design must always be derived from the rationality of the human mind. The world is inordinate in its natural state, and man must circumvent this disorderliness with the categories of his own mind and regulate the world (Corbusier, 2014, p.15). Rationality, according to him, is the order itself. “Han has to put work in an order” (Corbusier, 2014, p.22). For Le Corbusier, a city that has not been organized in a rational way will hinder people. The peace of man depends on the perfection of the order. What will save us from the chaos of nature is a rational city design, designed with right angles. And its tool in architecture is geometry. However, today’s city has not been realized with a “geometric minds” (Corbusier, 2014, p.24). In the urban life, Le Corbusier advocates the transition from entropy of romanticism to rational prescriptivism of modernism that sets standards. According to Le Corbusier, a single mind must construct an order by designing an entire city with a rational plan. Where there is no plan there is irregularity and arbitrariness. Modern life demands and expects a new plan for the dwelling and the city (Corbusier, 2017, p.34). He designs a “modern city” for the “modern life” and forms it with a very “modernist” approach. He describes the method of architecture as “art above all others which achieves a state of platonic grandeur, mathematical order, speculation, the perception of the harmony which lies in emotional relationships”. According to Le Corbusier, “geometry is the foundation” (Corbusier, 2014, p.ix). Thus, Le Corbusier identifies the instruments of architecture that will resurrect the city as mathematics and geometry.
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Instrument of the Order: Geometry According to Le Corbusier, engineers and businessmen who use mathematics and geometry have pioneered new forms of production. Now the architect has to design mass-produced houses and radiant cities that would benefit everyone who came to the “fundamental pleasures” of the new age. A whole new environment had to be created where industrialization techniques facilitated the daily lives of the citizens. On this count, the chaos would disappear. In Le Corbusier, the harmony of society was becoming a “problem of building” (Fishman, 2016, p. 180). This was the motivation that led Le Corbusier to design a utopian city in Urbanisme. He wanted to produce a machine that would work impeccably: a city machine.
Rules of Modernism : Standardization and Homogenization Le Corbusier did not lend credence to contingency or historicity; thought that logical and rational solutions for similar situations would be the same and one. In other words, he has completely accepted the principle of modernism which states “great minds think alike”. So, the city Le Corbusier designed is standardized and homogenized. It is focused on mass production. He has been influenced by the industrial production models and new material choices and argued that cities and houses should now be produced in this way in serial and standard form. Le Corbusier designed a standard and homogeneity among cities as well as the standard and homogeneity of the city itself. He claims that he created a model connected to the norms and reproduced this model worldwide by producing a universal city plan. Therefore, the settlement that is planned for three million people is designed for any place, not for a specific space. There is nothing local in the design. It has been developed with an unadulterated rationality.
Creative Destruction Modernity always believes that there must be a fundamental disengagement with the past. It always tends to see the world as a tabula rasa, a blank page that can be written from scratch without reference
253 ANTICIPATION to the past or ignoring it altogether. That is why modernity, whether democratic, revolutionary or authoritarian, is always associated with “creative destruction” (Harvey, Paris, Modernitenin Başkenti, 2013, s. 7). The treatment Le Corbusier suggests for the recovery of cities is as modernist as the diagnosis he recognizes for them. He suggests that the old city, which is not produced rationally at all, should be completely destroyed and replaced entirely by a rational city. He advices that the irrationalist old city plan produced from traditions, beliefs, habit, and the avenues, streets, buildings, monuments, graves, all other things that carry out this plan should be bulldozed through. Le Corbusier tries to build how the ideal city of the twentieth century should be. He believes that the community he has been in needed first and foremost new cities. He thinks the format would reformulate the content. According to him, physical possibilities will create the commu- nal living again and in a most positive way. He rejects the possibility of progressive improvement. He aims not to improve the old cities but to transform the urban landscape as a whole. Le Corbusier’s design is an “urban revolution manifest”. The ideal city of Le Corbusier is perhaps the most ambitious and complex expression of the belief that the entire life of society can be radically changed by reshaping the physical environment. In harmony with modernism, he has imagined that he could rebuild society together with the city, and he was optimistic in this dream. He was engaged in a sort of community engineering. Le Corbusier’s action plan, which is acticipated by him, is extremely radical. According to him, the classical cities, which concealed themselves in city walls for military reasons, have already overflew out of the city walls in the twentieth century, and since it does not have a rational design to be able to function, now the inner city must be completely demolished and rebuilt in the frame of rational principles (Corbusier, 2014, p.88). By rejecting conservative evolutionist conception of urbanism, takes up a position toward a radical-rational revolutionary urbanism attitude. In order to build the functional, he expunges in an instant all the past and its accumulations, the traditional life forms they point to and the identities they produce, without hesitation.
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A Contemporary City: Le Corbusier’s Utopia: Utopian city planning of Le Corbusier, who advocates the complete destruction of old city centers and construction of centers in their place, begins at this stage. With A Contemporary City, Le Corbusier tells the bases and principles of his utopia. There is a train station in the center of the utopic city of Le Corbusier. This station is integrated into the metro, buses, and other transport facilities as well as also to the airport via a helicopter. The station is surrounded with 60 floors high skyscrapers, each of which is arranged symmetrically at wide intervals. These large complexes will serve to fulfill the trade needs of the community. In parks surrounding them, there are luxury restaurants, theaters and shops. The majority of the population lives in spacious, high-rise apartments with elevators and with a special hanging garden for each apartment, while others live in colonies of detached houses. The streets are of three storeys that go at different speeds to provide different types of vehicles to flow at different velocities. Raising the density to such a high level allows people to be comfortably placed in a small space, thus liberating large areas to be enjoy as agricultural, recreational and natural spaces. Geometrically, such a wide range of urban development allows for the provision of cultural services or other kinds of services required by an intensive consumer population and an adequate transportation system. The fact that Le Corbusier envisions the city as a complex machine, a machine necessary for everyday life, also enables its inhabitants to live in privacy and beauty in a radiant, green, spacious, and serene environment at the same time (Meyerson, 1996, p.120). In Le Corbusier’s urban design approach, everything that is not functional is excluded. Everything that appears irrational, such as traditions, habits, aesthetics, public memory, historicity, is an enemy of his urban design. Since he wants to build a city that was entirely rational and profitable, he paid attention for everything to be very close and compact. As the basic principles of the plan of its utopic city he has determined: 1) Eliminating the congestion of the city center; 2) Increasing the density; 3) Increasing traffic vehicles; 4) Increasing green areas.
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According to him, the solution of the first two is possible by the settlement of the traffic issue and the replacement of existing buildings with very high-rise buildings. For Le Corbusier, the reason for the dense traffic in the city is that the spaces are as far apart as well as the fact that curved roads from the Middle Ages are unfit for motor vehicles. Le Corbusier tries to solve this problem by increasing the density of the city center and therefore by reducing the number of streets and street intersections. According to Le Corbusier, the number of street and street intersections of existing cities should be reduced by two-thirds. In the existing plans, streets intersect in every 50, 20 or 10 meters. For Le Corbusier, street intersections are the enemy of traffic. Le Corbusier argues that the distance between two metro or bus stops is optimal distance for street intersection. This corresponds to a distance of 400 meters (Corbusier, 2014, p. 162). By increasing the density of the city, Le Corbusier aims to reduce the traffic and to facilitate intra-central access. He has dreamed of increasing this density through skyscrapers. Accordingly, the existing floors of the low-rise buildings will be reduced, but 60-storey skyscrapers will be erected on this narrowed floor areas. In Paris, if the number of floors in a building is assumed to be 6, Le Corbusier desires a 10-fold vertical rise. Thus, he uses skyscrapers as “street in the air” with his own words. As a result of vertical conglomeration instead of horizontal expansion, the distances are shortened; places are made possible to be reached sometimes by walking and sometimes only with the help of elevators. This is an important solution to the city’s traffic problem. Another advantage of retracting from the horizontal expansion is; as a result of lowering floor areas that buildings occupy, the land on which the building is planted previously will be transformed into green areas. According to Le Corbusier, modern work requires tranquility and healthy air quality. However, these are not possible in the environment where green areas are not found and everywhere is covered by buildings. Le Corbusier, as well as vertical growth, increases city density and reduces traffic, thus cleansing the city’s air and creating a more serene landscape
256 ANTICIPATION IN ARCHITECTURAL UTOPIAS that people will be more comfortable with (Corbusier, 2014, p.160). In plans of the utopic city of Le Corbusier, on the grounds of skyscrapers that will accommodate 6,000 population per hectare, there will be 95% green area, where squares, restaurants and theaters will be constructed. On the grounds of luxury houses situated in recessed parcels that will accommodate 300 population per hectare, there will be 85% green area, where there will be gardens and sports fields located. In the closed parcels that will house 305 population per hectare, there will be 48% green area where again gardens and sports fields can be found (Corbusier, 2014, p. 165).
Three Dimensional Drawing of Residential Settlements in Le Corbusier’s Utopic Design for an Urban Area. (Corbusier, L., 2014. Urbanisme, p.180.)
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In the city of Le Corbusier, boulevards are drawn between skyscrapers over 200 meters high and in the middle of empty spaces; there are luxury shops with elegant window displays, which will be reached by consecutive stairs that are cramped in between one-two-or three-storey structures, where pleasure-oriented shopping can be done; similarly, there are restaurants, coffee houses, terraces that open to tree clusters of five or overlooking to the openings of the English gardens. The street, first of all, has been re-established with elements in the human scale. Le Corbusier anticipated an utopian city with rationally described rules. These rules are explained in previous parts. Also as an architect, he proposed a financial management proposal to realize his utopia.
Anticipation of Rationalism in “Urbanisme”: A Radical Financial Management Proposal for an Utopian City In order to demonstrate the feasibility of the city plan he has designed, Le Corbusier tries to prove the financial profitability of completely demolishing the city and rebuilding another one on its place. By doing so, Le Corbusier aims to announce to necessary authorities that it is a project that can be actually realized rather than a model that only works on paper. While preparing the said economic modeling, he chooses Paris as his model and produces his calculations within the framework of this city. For Le Corbusier, if the city is destroyed and rebuilt according to his suggestions, it will have a much more substantial value, relative to its former value. Le Corbusier turns this into a formula: he presumes the value of existing buildings in the city together with their land as (A). Then, he says, let’s think of demolishing these suffocating, outmoded streets, environment, and parks, neighborhoods that are not suitable for living, and let’s imagine replacing them with new and splendid neighborhoods that are placed keeping the same number of flats. In this new case, according to Le Corbusier, the value of each unit will increase with the total value increase of the neighborhood. Le Corbusier estimates this increase as (A5). Le Corbusier does not suffice with that; because in his plan both the neighborhoods will be rebuilt optimally
258 ANTICIPATION IN ARCHITECTURAL UTOPIAS within their own planning framework, and all the number of building floors will be increased. During this increase of number of floors, since the floor area of the buildings are slightly narrowed, although the total number of building units does not increase as much as the floor area of the buildings, the population of neighborhoods will increase to 3,300 from 800 people per hectare; in other words, a full fourfold unit increase will occur. For this reason, Le Corbusier multiplies the land value which is transformed to (A5) by 4 to reach to the 4(A5) formulation. In this method, perhaps the public administration will allocate a significant budget for demolishing and rebuilding, but at the end of the operation it will make a huge profit because it will be creating an enormous value increase. To these new buildings, both locals and foreign investors from around the world, such as the US, Germany, UK and Japan, will invest. Thus, the city of Le Corbusier will become a world city and since it is transformed into a city receiving investments all around the world, in the event of a possible war, as no nation would afford to bomb the city they have invested, it will not carry the risk of being demolished during any war (Corbusier, 2014, p.284-286). At the same time, a much larger economic return will be obtained compared to the budget spent on building the new city.
Conclusion As explained, the concept of anticipation may be for future oriented actions like utopias, for both, there is no guarantee of success. Also Poli explains that anticipation is not always correct. In parallel to anticipation, utopias are not always correct too, their main mission is to create a future oriented vision. In this study Le Corbusier’s utopia has been chosen to visualize an anticipated architectural philosophy, the ideal city concept is the pursuit of excellence, clarity, certainty and non-contradictoriness. Its design, for the sake of being able to provide justice and equality and being able create social order, has the claim to be void of esthetics and be totally functional. Instead of livable cities, it inclines to build zones based on their functions. He assesses the level of creativity of an architect and the
259 ANTICIPATION aesthetic value of the building according to the benefits that they provide to human beings and to the community. For Le Corbusier, cities should be designed according to an ideal model; this is a city utopia. The homogenous city he planned to go into circulation all around the world and produced with the same standards in every point of the earth, is a giant machine. It is possible to feel this feeling in every corner of the city, even on its plan. Everything that is nonfunctional is excluded from this city and expelled. For the sake of optimization of productivity, all the texture belonging to the past has been discarded. This radical disengagement in the design of the city is not just about its design, it is all about the past at the same time as well. Le Corbusier’s suggestion is an uprooting operation. And he hopes that the lines created by a single mind to dominate the whole world. What lies behind externalizing everything that is unique to the human beings such houses, streets and the city from all living areas, is the monopolistic radical rationality and the unconditional glorification of the bureaucratic power? (Harvey, 1999, p.51) The design of Le Corbusier is, over time - ironically- the projection of political authoritativeness in the scale of urbanism of modernism which initially emerged as a liberating paradigm. However, humans are not only made up of the mind and the function individually; on the contrary they are cultural and social entities. In an unadulterated rational city design produced by a single mind in which no intervention of its inhabitants is accepted, it is not easy to anticipate masses to be satisfied, to establish identity, and to develop belonging with the city they live in. The city is, as Lévi-Strauss says, “a work of social art.” Its densely intertwined structure is the product of thousands of intellects and thousands of individual decisions. Its diversity is derived from unexpected intersections and unpredictable interactions. As Fishman said, “Even if a genius, how can a single individual hope to understand this structure? And how can he produce a new plan possessing the same satisfying complexities? How can an individual alone hope to impose his own idea to the history?” (Fishman, 2016, p.25, 26). It is as if the architect is given the opportunity, he will instantaneously solve all our problems with rational professional understanding and planning skills. For the
260 ANTICIPATION IN ARCHITECTURAL UTOPIAS architect, the society is as if one of his professional instruments, as well as the object of his actions (Tanyeli, 2017, p.11). Determining what is right and necessary for the man and the society by simply reducing it to numerical values, based on a simple equation, focusing on parameters such as square meterage, topography, economy and producing plans founded solely on basic human biological functions, may come out from minds who assume, such as the city, man is also consisted of a machine. As much as the city is not just made up of a “work machine”, nor is human being consisted of a biological machine. An architecture invented with these assumptions is oppressive since it considers physical environment and society as a tool to be disciplined. The architectural power of the architect, defended by Le Corbusier, points to an authoritarian ruling, a dictate aimed at building on sociality. However, the success of Le Corbusier’s utopia could not be tested, it is only anticipated. Like most of the utopias, Urbanisme has only be a uncertain vision which has lots of future oriented acts to idealize the world. Beckert explains this uncertainity with following explanation: “under conditions of fundamental uncertainty, expectations cannot be understood is being determined through calculation of optimal choices taking into account all available information, but rather are based on contingent interpretations of the situation in the context of prevailing institutional structures, cultural templates and social networks” (Beckert, 2013, p.325). With these words, Beckert explains the expectation by referring to “present imaginaries of future situations that provide orientation in decision making despite the incalculability of outcomes”. (Beckert, 2013, p.325). The common aim for both anticipation and utopias may be to create a group of uncertain visions for future, the following process may be the hidden evolution in utopia design process.
Normative Architectural Vision for Future Anticipation Utopia
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References: Abensour, M. (2009). Utopia, from Thomas Mora to Walter Benjamin. Ütopya, Thomas More›dan Walter Benjamin›e (in Turkish). (A. U. Kılıç, Translation) İstanbul: Versus. Ağaoğulları, M. A. (1986). Classic Utopias: from Freedom to Despotism. Klasik Ütopyalar: Özgürlükten Despotizme (in Turkish). Ankara University. Department of Journalism, Yearbook, 1983-1985 Number VIII’den Special Print. Alver, K. (2009). Utopia: Space and Ideal Form of City. Ütopya: Mekan ve Kentin İdeal Formu (in Turkish). Journal of Sociology, Sosyoloji Dergisi (in Turkish), 3 (18). Beckert, J. (2013). Capitalism as a System of Expectations: Toward a Sociological Microfoundation of Political Economy. Politics and Society, 41(3), 323-350. Cioran, E. M. (1999). History and Utopia. Tarih ve Ütopya (in Turkish). (H. Bayrı, Translation) İstanbul: Metis. Coşkun, İ. (2004). Criticism of Present: Thomas More and Utopias as an Facilitation/ a Proposal. Şimdinin Eleştirisi: Thomas More ve Bir İmkan/Öneri Olarak Ütopyalar (in Turkish). Hece (90-91-92). Corbusier, L. (2017). Towards an Architecture. Bir Mimarlığa Doğru (in Turkish). (S. Merzi, Translation). İstanbul: Yapı Kredi Publications. Corbusier, L. (2014). Urbanisme. Şehircilik (in Turkish). İstanbul: Daimon. Davis, J. C. (1983). Utopia & The İdeal Society”. Cambridge: Cambridge University Press. Erdem, E. (2005). Utopia and Architecture Relationship in History. Tarihte Ütopya ve Mimarlık İlişkisi (in Turkish).. Mimar-İst (18). Eurich, N. (1967). Science in Utopia: A Mighty Design. Cambridge: Mass. Fishman, R. (2016). Urban Utopias in 20th Century. Yirminci Yüzyılda Kent Ütopyaları (in Turkish). İstanbul: Daimon. Goodwin, B. (1980). Utopia Defended Against the Liberal. Political Studies , 28 (3). Harvey, D. (1999). Status of Postmodernity. Postmodernliğin Durumu (in Turkish). (S. Sarvan, Translation) İstanbul: Metis.
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Harvey, D. (2008). Spaces of Expectancy. Umut Mekanları (in Turkish). (Z. Gambetti, Translation.) İstanbul: Metis. Harvey, D. (2013). Paris, Capital City of Modernity. Paris, Modernitenin Başkenti. (in Turkish). (B. Kılınçer, Translation) İstanbul: Sel. Havemann, R. (2005). Utopia and Prospect, (in Turkish), Ütopya ve Umut. in R. Havemann, Tomorrow Yarın, (in Turkish), İstanbul: Kaynak. Havemann, R. (1990). Tomorrow (in Turkish), Yarın. İstanbul: Ayrıntı. İzzetbegoviç, A. (1987).Islam, in between East and West. Doğu ve Batı Arasında İslam (in Turkish). (S. Şaban, Translation) İstanbul: Nehir. Kahya, G. Y. (2007). Future Predictions in the Context of Urban Develeopment: Cybercities. Kentsel Gelişme Olgusu Bağlamında Gelecek Öngörüleri: Siberşehirler (in Turkish). İstanbul: İstanbul Technical University, MSc. Thesis. Kateb, G. (1975). Utopia and Its Enemies. London: Collier-MacMillan. Kolakowski, L. (1982). The Death of Utopia Reconsidered. The Tanner Lectures on Human Values. içinde Utah: University of Utah Press. Köksal, A. (2014). “Urbanism” As a Distinct Text. Açık Bir Metin Olarak “Şehircilik”(in Turkish). in Urbanisme, L. Corbusier İstanbul: Daimon. Kumar, K. (2005). Utopianism. Ütopyacılık (in Turkish). (A. Somel, Translation) Ankara: İmge. Kurt, H. (2007). Utopists’ Heritage of Urban and Environmental Problems. Kentsel ve Çevresel Sorunların Çözümünde Ütopyacıların Mirası (in Turkish). in, Kent ve Politika. Ankara: İmge. Mannheim, K. (1979). Ideology and Utopias. (L. Wirth, & E. Shils, Çev.) London: Routledge & Kegan Paul. Merzi, S. (2017). Translator’s Foreword. in L. Corbusier Towards an Architecture. Bir Mimarlığa Doğru (in Turkish). İstanbul: Yapı Kredi Publishings. Meyerson, M. (1996). Traditions of Utopia and City Planning. Ütopya Gelenekleri ve Kentlerin Planlanması (in Turkish). Cogito (8). Mumford, L. (1996). Legend of Machine. Makine Efsanesi (in Turkish). (F. Oruç, Translation) İstanbul: İnsan.
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Noble, R. (2009). The Utopian Impulse in Contemporary Art. Utopias. içinde Cambridge: Whitechapel Gallery. Poli, R. (2009). The complexity of anticipation. Balkan Journal of Philosophy, 1 (1), 19-29. Poli, R. (2010a). An introduction to the ontology of anticipation. Futures, 42 (7), 769-776. Poli, R. (2010b). The many aspects of anticipation. Foresight, 12 (3), 7-17. Poli, R. (2017). Introduction to Anticipation Studies. Dordrecht: Springer. Rosen, R. (2012). Anticipatory Systems. Philosophical, Mathematical and Methodological Foundations. New York: Springer. R. Soule, Dictionary of English Synonyms, Omega Books, London, 1986. Tanyeli, U. 2017. Build by Demolishing. Yıkarak Yapmak (in Turkish). Metis Publishings. The Advanced Learner’s Dictionary of Current English, 2nd edition, Oxford University Press, UK, 1971 Usta, S. (2014). Turkish Utopias. Türk Ütopyaları (in Turkish). İstanbul: Kaynak. Usta, S. (2015). Antique Utopias. İlkçağ Ütopyaları (in Turkish). İstanbul: Kaynak. Yüksel, Ü. D. (2012). Urban Utopias from Antiquity to Today. Antikçağdan Günümüze Kent Ütopyaları (in Turkish). İdeal Kent (5)
264 13 ANTICIPATION IN LAW
Hakan Üzeltürk
1. Introduction It seems quite difficult to differentiate meaning of the terms anticipation and expectation since they are used as synonyms in most cases. Expectation is the feeling of expecting something to happen1. Anticipation is a future-oriented action, decision, or behavior based on a (implicit or explicit) prediction2. The principle of the rule of law and the principle of supremacy of law are leading concepts in contemporary democratic societies. Within this frame, things people expect from who govern them make up the concept of anticipation in law. This concept is not only a lawful anticipation3 because of the will to coexist but it is also, with its ethical, political, economic and social sides apart from law and as philosophy of law, the practice of behaviours which are contemporary, correct, what is expected, accepted universally and what is reasonable and logical. First the state and its institutions must exercise it. This is because the state is both the guarantee of personal rights and freedoms as well as being the assurance and representative of the ones who come together for a better societal life. Nonetheless, different cultures and life conditions of different societies and also their law cultures bring about many problems. From this perspective, the concept of anticipation becomes a very wide one which also includes areas outside law itself. However, as the
1 Cambridge Dictionary. 2 Giovanni Pezzulo-Cristiano Castelfranchie-Martin Butz, the Anticipatory Approach: Definitions and Taxonomies, September-2008, Springer-Verlag Berlin Heidelberg 2008, p.25. 3 Turkish Constitutional Court Decision, E.2015/94, K.2016/27.
265 ANTICIPATION subject of this study must be limited to law, the concept of anticipation of law within the field of law making will be explained. In our treatment however, the subject will be explained within the concept of companies’ most important issue, namely the tax law. Within this frame, the following issues will be explained in scope of anticipation in tax law: the areas which cause problems, reasons for those problems, how application is done and approaches or ways of solving these problems. Decrees of law will be tried to be included in the study as much as they are related to the subject. In this scope, especially adjustments in the Turkish Constitution together with the universal principles of law will be explained to describe what could be the anticipations in tax law. This is because Constitution is the main law of a country in terms of domestic law. However, there are also other norms over the Constitution. There are sub norms in concept of hierarchy like acts, guidelines and regulations in order to make adjustments in the Constitution. All these related issues will be handled together to put forth what anticipation in tax law is.
2. Tax Principles It is secured through the authority given to legislative institutions with the 73rd article; under the heading “Duty of Tax”, in the Constitution of the Republic of Turkey that taxes, fees, duties and similar financial obligations will be imposed, amended and revoked by law. It is stated in the 4th paragraph of the same article, the Head of Turkish Republic may be empowered to make amendments regarding exemptions, exceptions, reductions and the rates of financial obligations such as taxes, fees and duties. These amendments, however, should be, only within the minimum and maximum limits prescribed by the same law. This arrangement appears to be a reaction against the long term issue that tax legislations could not be enacted without having the majority of the parliament. First of all, it is necessary to point out some basic issues regarding taxes in Turkish law. The state can apply legal enforcement regarding its taxation power while collecting the taxes in order to accommodate for the public expenses. Here what is meant by legal enforcement is that the duty of paying tax is provided by law and if tax is not paid some penal
266 ANTICIPATION IN LAW sanctions can be imposed. The principal of financial power is accepted for paying taxes and it is indicated in 73rd article of the Constitution that everyone will pay taxes according to his financial conditions in order to cover public expenditure. The principle of social state, described in the 2nd article of the Constitution is accepted as one of the main qualities of the Republic. This principle is intended to be actualized with the inclusion of another principle that “An equitable and balanced distribution of the tax burden is the social objective of fiscal policy” stated in the second paragraph of the 73rd article of the Constitution. It is very difficult to answer here how financial power can be measured and how the taxes can be said to be distributed “equitable” and “balanced”. It is especially a problem faced by almost every country how these issues can be actualized. Basically the first principle to be asserted within the taxation principals is that it should be legal. The fact that the state uses taxation power4 embodies intrinsic and clashes between the taxpayer and the state. Therefore the tax laws to be enacted should be as accurate as possible to imply legality to those obliged to pay those taxes5. It means that issues such as assessment, announcement, realization and collection and payment periods of the tax, the duty of the obliged, and the supervision of the obliged, penalties to be imposed, ways to be followed in cases of tax disputes and causes that eliminates tax obligation should be indicated in the text of law6. In addition to the subject matter of the related tax, the text should also include issues such as its rate, reductions, exceptions and exemptions, the ways to assess, announce, realize and collect taxes, apply sanctions and limitations. Constitutional Court explains the legality of tax in some of its decrees as follows7:
4 Nami Çağan, Vergilendirme Yetkisi, Ankara-1982. 5 Gülsen Güneş, Verginin Yasallığı İlkesi, İstanbul-1998, s. 14. 6 Ibid, 128. 7 Anayasa Mahkemesi, 29.11.1977 tarih, E: 1977/109, K: 1977/131 (RG 8.3.1978, 16222).
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“Constitutional legislator while ordering that all financial obligations should be set by law is undoubtedly aiming the objective that the principles that will avoid arbitrary and discretionary implementations should take place in the text of law. The case that the legislator allows a financial obligation to be charged to related parties only by specifying its content is not enough to warrant acceptance that it is implemented by law. The financial obligation has some aspects such as tax base and its rate, assessment and realization, collection procedures, sanctions and limitation. Due to these aspects, it is possible that a financial obligation could cause arbitrary practises that will affect individuals’ social and economic conditions and even basic rights if it is not very well framed with law. In this regard financial obligations have to be set definitely by the text with their main issues explained and their frames emphasized with clear lines.” The expression “Council of Ministers may be empowered to amend in their decisions regarding exemptions, exceptions, reductions and the rates of financial obligations such as taxes, fees and duties only within the minimum and maximum limits prescribed by law” is placed in the fourth paragraph of 73rd article of the Turkish Constitution. In this scope Council of Ministers will not be empowered to decide upon the essential components of tax such as the issue that generates the tax, the limitation, penalties and fees. Constitutional Court states as the issues to be set by law and limits of the power of adjustment given to executive organ of enforcement regarding tax and similar financial matters8 as below: “In order to avoid arbitrary practises in taxation that will affect individuals’ social and economic conditions, its essential constituents such as the issue that generates the tax, the tax base and its rate, its minimum and maximum limits, its assessments and realization and limitation need to be determined by law. When the laying out of all possible issues with its whole content and details by law, it is not possible the executive organ can be given an administrative power in an explicative and complementary nature regarding the applications but with the condition that a frame is drawn and its limits need to be complied with.”
8 Anayasa Mahkemesi, 16.1.2003 tarih E: 2001/36, K: 2003/3 (RG 21.11.2003, 25296).
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There are important outcomes of the authority given to the Council of Ministers. The use of this authority should not allow the replacement of the legislative body and hence damage the use of its authority. For example, if the power to reduce the tax percentage to zero is given to the Council of Ministers by law it does not technically mean that tax is revoked but with regard to its consequence it means that tax will not be collected. Therefore it is not legally correct if such a power could be exercised by the Council of Ministers. The expression of “the Council of Ministers” in paragraph 4 of Article 73 of the Constitution was changed as “the Head of the Turkish Republic” under the Act No. 6771 dated 21.1.20179. Regarding new changes, it is not possible to apply administrative courts anymore, against unlawful tax re- lated decisions of the Head of the Turkish Republic within the context of Article 73/4 of Turkish Constitution. This result is a serious law deficiency. The Constitutional Court believes that the broad power delegated to the Council of Ministers implies that the legislative power is handed over to the executive organ by damaging the principle of legality and hence concluded that10 the power delegated to the Council of Ministers for the readjustment of new rates as will not be more than %50 or less than %20 and also the power to increase these rates as much as twenty times is a) an unreasonable arrangement, b) does not comply with the equity of law and c) that causes the endorsement of legislative power it is also concluded that it does not comply with the principle of legality as it might cause arbitrary enforcement. The violation of the principle of legality is also expressed in another case by the 7. Circuit of Council of State who explained that the decision of the Council of Ministers which states that additional motor vehicle tax should be collected from the vehicles according to the type of fuel used should be cancelled. The circuit stated that the related injustice evident expressed in the decree for some vehicles has no connection with
9 RG: 11.2.2017, 29976. 10 Anayasa Mahkemesi, 16.1.2003 tarih E: 2001/36, K: 2003/3 (RG 21.11.2003, 25296).
269 ANTICIPATION the principle of equity in taxation and has no facets such as economic stability, the efficient use of country resources through the tax policy or the financial loss of the public as pointed out in the defence petition of the defendant administration11. There are other additional decisions which are similar to above of the Council of State12. Besides these regulations in article 73 of the Constitution there are also international restrictions of taxation. The power of taxation can be restricted by these with the treaties, international and supranational agreements and conventions that the states are party and consequent court decisions. The sanctions imposed by these rules are binding for the states and might also be above the national law rules. These kinds of agreement clauses or judicial decisions are expected to improve a state’s internal law in a direct manner. The avoidance of double taxation, European Convention on Human Rights and its additional protocols and the Universal Declaration of Human Rights could be named as examples of such international agreements signed by the countries to name a few. All these principals provide a basis for the legality for realization of rule of law while ensuring the fundamental rights and freedom of individuals. The rule of law is explained by the Turkish Constitutional Court as follows13: “The rule of law should be appropriate to all the known principles of law that all civilized countries accept and administrate. According to this principal, the state is accepted as a state where every action and proceeding is proper to law, is a) a state that respects humans rights and protects and reinforces these rights, b) that constructs a just system of law in every aspect and also continuously improves it, c) that abstains from conditions and conducts contrary to the Constitution, d) that declares law to be sovereign over all organs of state, e) that acknowledges itself to be affiliated by the superior rules of
11 Danıştay Yedinci Daire, 11.6.2001 tarih, E: 2001/1, K: 2001/2124. 12 Danıştay Yedinci Daire, 20.5.2002 tarih, E: 2001/626, K: 2002/1942; Danıştay Yedinci Daire, 14.5.2002 tarih, E: 2001/62, K: 2002/1859; Danıştay Dokuzuncu Daire, 12.12.2001 tarih, E: 2001/278, K: 2001/4848. 13 22.12.1964 tarih ve E. 1963/31, K. 1964/76 sayılı Kararı (AMKD, Sayı: 2, s. 291).
270 ANTICIPATION IN LAW law and f) opens itself to the judicial control and g) that knows it will not be valid if it is away from the consciousness that there are certain essential principles of law and Constitution above the law even the legislator cannot blemish”. In terms of Turkey many international norms were incorporated into internal law or included in to the Constitution identically or with some restrictions. The related article in the Turkish Constitution is the 90th article which states in the last paragraph that “Properly executed international agreements are in statutory effect. Constitutional Court cannot be applied with the claim that they are contrary to Constitution.” Here the expression of “statutory effect” is used to show its legal value and binding force more than to determine the place of international agreements within the order of rules14. The Council of State concludes the following in one of its decision15: “...This side of the expression of “statutory effect” in the last clause of article 90 of Constitution is emphasized and with this emphasis the nature of the international agreements as having direct results on the internal law system as mentioned above, that it is not possible to apply to the Constitutional Court for cancellation and thus preventing them from being invalid with newly formed internal procedures and that these agreements have an above the law status and have a binding force over enforcement and judicial bodies is emphasized. The 7th clause of the act dated 07.05.2004 and no. 5170 that states “The terms of the international agreement are always prior to when there are different explanations on the same issue between properly executed international agreements, regarding issues of fundamental rights and freedoms, and the law” is added to the last paragraph of article 90 of the Constitution which says; “Properly executed international agreements are in statutory effect. Constitutional Court cannot be applied with the
14 Mesut Gülmez, İnsan Hakları Uluslararası Sözleşmelerinin İç Hukukta Doğrudan Uygulanması, TBB İnsan Hakları Araştırma ve Uygulama Merkezi, Ulusal Toplantı, Adliye Sarayı, 5.11.2004, s. 46 vd. 15 Danıştay 5. Dairesi’nin 22.5.1991 günlü, E1986/1723; K1991/933 sayılı kararı, Danıştay Dergisi, Sayı 84-85, 1992S.325-328.
271 ANTICIPATION claim that they are contrary to Constitution.” As can be understood from the legal ground of the clause, when there are conflicts between properly executed international agreements, regarding issues of fundamental rights and freedoms, and the law, the expressions of the agreement will be accepted as superior and the national rule of law will be out of consideration and will not be used with this change in the 90th Article of the Constitution.
3. Authorizational Problems on Taxation As contrary to the Turkish Constitution, it is sometimes seen that the authority of taxation can be used by the Ministry of Finance apart from the Constitution and the international agreements. This situation shows itself as the clash between the regulations of the Ministry of Finance which is the authorized institution on taxation and the texts of law. There are too many reasons to these illegal applications. Some of can these reasons be listed as; failure to consider the concepts of tax and law in unity, the belief that the aim of tax collection cannot be actualized due to restrictions on legal regulations on the issue, the will to have quick solutions in cases of urgency and thus neglecting law as it takes more time to be practised, the general disbelief in law, the idea that tax-payers are seen as people who evade taxes, the concern of having a budgetary deficit and that the judicial decisions are not very well analysed. Besides these reasons, the legal faults or gaps in the regulations caused by the legislative body can also act as the roots for implanting certain contradictions to law. Several principles of taxation law are violated by these regulations with numerous amendments made on different occasions. It will be displayed below, within the frame of taxation principles and with some examples of problems of law in the issue of authorization of taxation, what kind of results different uses of taxation authority can lead to.
3.1. Application to Constitutional Court by Council of State 7th Circuit of Council of State which applied for the lawsuit works on private consumption tax. The issue is that an arrangement regarding
272 ANTICIPATION IN LAW private consumption tax is taken to Constitutional Court through an appeal. Both issues are related to section b of 2nd paragraph of 12th article of Special Consumption Tax Act no. 4760 and dated 6.6.2002. The case brought to 7th Circuit of Council of State is plead in order to get the past decisions of the Council of Ministers taken based upon this arrangement should be cancelled because the Council of State thinks that this arrangement is against 2nd, 10th and 73rd articles of the Constitution. Decisions of Constitutional Court, no. 2008/61 and 2008/62, on taxes are at the same related to each other. Constitutional Court decided by majority of votes that, since the decision in section b of 2nd paragraph of 12th article of Act on Special Consumption was changed with Act no. 5228 dated 16.7.2004 which was published on Official Gazette no. 25539 on 31.7.2004, the authority given to Council of Ministers was also changed and therefore there was no point in appealing for nullification and there was no reason to make a decision. Constitutional Court came to the same decision, regarding the change made in the same paragraph in 2004 this time with of the Act no. 5479 dated 30.3.2006, in its decision no. 2008/62. As can be seen, it did not see a reason for an analysis in terms of content. However, with regards to law it was very important to do that. The points defined by three members, who are against the decisions taken, are very important and show the defects in both decisions and also the problems the decision will cause in current lawsuits.
1. It cannot be accepted that the rule of law, is not enforceable during the lawsuit conducted in Council of State because it is changed at a late date. 2. Though the lawsuit is against the objective arranging process and since it will be concluded with the use of the rule which is the issue of objection, there exist no ground for not analysing the core of the issue, instead of continuing the Constitutional supervision, thinking that it will be decided in the lawsuit pleaded in Council of State that there is not a situation to be decided upon 3. It is set by rule and stated in the 153rd article of the Constitution that decisions of annulment cannot move retrospectively, in 152nd article
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that if a decision is not made within five months for the lawsuits plead by judiciary institutions, the court will decide based upon the acts of law in use and that the court has to obey if the decision of Constitutional Court arrives until considered judgment is certified. 4. Decision of the Council of Ministers, which is among administrational processes, is in a way the enforcement of the legal rule. The fact that it is considered as a regulative process by Council of Ministers does not change this situation. Decision of the Council of Ministers, which is also taken as basis for the calculation of due amount regarding special consumption tax, is the first determining enforcement process that introduce the percentage and also fixed minimum tax amount to be used on the goods which are the subject of taxation. 5. According to established enforcements of Constitutional Court, the fact that the clause which established the basis for annulations required for the objections is later changed, does not affect the inspection of conformity to Constitution of the said clause.
As it is seen, the unanimous decisions taken by the Council of State neither serves the purpose of the appeal nor solves the problem.
3.2. The Prevention of Limitation In Turkish law system, there is a time limitation period for public debts that have not been collected for 5 year years within the context of “Act no. 6183 On Method of Collection of Public Debts” after which the file should be closed. The statement of one employee of Ministry of Finance officially marked a method used and known for a long time until 2008. In this method the Financial Officers, when they cannot find the public debtor in the file they are working on, prevent the public debt from being outlawed in 5 years by contributing a symbolical “1 Turkish Lira” themselves for the collection of the debt. The issues in scope of the Act no. 6183 are specified in the 1st article. According to this: “The acts in subject are enforced regarding the debts and the costs incurring in the related legal proceedings of taxes, fees, duties and principal public debts such as court fee, tax penalty
274 ANTICIPATION IN LAW and ancillary public debts like default fee, interest and the remaining public debts occurring during the execution of public services of the administrations apart from the ones that occur in contracts tortuous acts and unjust enrichment. The decisions in the act regarding the collection methods on fees and their conversion to imprisonment are secured”. According to the statement there are 29.938 files of lawsuits of public debts pending by the end of 2007. According to this method the officers prevent the limitation of 5 years with the symbolical 1 TL they contribute themselves when they cannot find or locate the public debtor. The 1 TL deposited extends the related file for 5 more years. Its legal ground is as follows: “The closing of a public debt file due to limitation not only causes the loss of millions of TLs of debt to be collected but also puts the assigned officer in a difficult position. That is why our officers’ with their sensitive conducts prevent the state from a big loss and also themselves from a difficult position.” This situation can be discussed from many aspects. The officers are running after the collection of debts to the state. They spend time and energy. They collect some but cannot collect the others. This workload and working conditions create negativities in terms of pursuing debts and some of the debtors escape from prosecution due to limitation. Therefore it is argued that the state is prevented from being injured with this sensitive and affirmative conducts of the officers. If we look at the matter form the viewpoint of the debtors, some of them do run away from the collectors and get rid of them and some of them are feeling all inequities of the system the upon themselves. Besides those who are notified about their debts close to the end of the limitation period, there are also those who are not summoned though they have known residency addresses but only notified learn about their debt at the end of the payment period. In addition to this, those who have problems regarding law, such as missing the application period because their addresses were written wrong on the summons, as being under prosecution for falling into a debtor situation due to voids in the act or being taken responsible for the debts of the others, are injured by the prosecutions and filing lawsuits.
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It will be more complicated in terms of law if those who are deposited 1 TL in their accounts refuse it by saying that they have no disposal about the issue, if they appeal for a lawsuit against people who deposit the amount in their account and against the amounts which they will be asked to pay later, if they ask to the authorities why they play with law instead of changing the act and limitation periods, if they want to learn how the debts of the people increased disproportionately and ask if they are aware that due to this legal degeneration there is no faith left in law. This situation is also a good example of Administration’s abuse of its authority by implementing an illegal procedure in order prevents its tax claims from not being paid because limitation period has expired. It is both the violation of principle of legal administration and the annulment of some legally set rights and opportunities.
3.3. The Protection of the Taxpayer in Terms of Taxes Collected Illegally Taxes should be in accordance with law within the concept of rule of law. It is not possible to conclude that a tax system is in accordance with law which is not constituted within the frame of principles stated in 73rd article in our Constitution. In a state of law, the balance need to be set in terms of the losses of both parties to tax; the state and the tax payer, stemming from the procedures against law. When it is the case of the losses of the state from taxation, the balance is desired to be set with the default interest paid by the tax payer. Conversely, for the cases where the legislator had collected illegally from the taxpayer it can be seen that this balance is not set at all. Therefore, though it is the case of penalties for the tax payers who pay their debt late this balance is violated against the tax payer in paying back of illegal collection after the court decision. This situation not only damages the feeling for justice but also acts as a justification for the tax payer to evade taxes. Taxpayer needs to be refunded for unlawful tax collections by the State, reimbursed with the loss he had in the process of collection. The missing points in the legislation needs to be corrected with judicial decisions. According to decision no. 1998/79 of Constitutional Court, the losses
276 ANTICIPATION IN LAW faced with the illegal acts of the administration should be amended with payment of indemnity. Within this context, below points are stated in joint council decision no. 2005/968 of 7th and 9th Circuits of the Council of State besides the decision no 2005/239 of 7th Circuit of Council of State16:
• The use of the money by people or institutions other than the ones who own it leads to the result that the owner is deprived this of economic value. • The loss caused by the use of the money other than its owner is reprimanded in systems of law with additional payments called interest. • In this case interest is the payment of the loss given by the use of the money other than its owner, namely it is the indemnity. • It is inconceivable to look for a clear rule of law in a state of law in order to compensate for the loss under the name of interest or under any other name. • It is the requirement of the constitutional rule and principle of state of law that the losses of the tax payers stemming from the illegal taxation procedures should be paid by tax administration which caused the loss.
This clearly stated decision, together with the Council of State which indicates that a legal ground is necessary had resulted in correct expansions especially for the tax payers. The decision no. 2005/2261 of 4th Circuit of Council of State is also in this effect. The decision included in the last paragraph of the 112th article of Tax Procedure Act clearly demonstrates that the legal balance between the state and the taxpayer is not established and that it is against the tax payer: “Taxes which were collected inappropriately or more than due amount and which need to be refunded with regards to tax laws has to be paid within three months from the accomplishment and submission of the information and documents by the tax payer. Otherwise the interest, calculated in the
16 Turgut Candan, Vergilendirme Yöntemleri ve Uzlaşma, Ankara-2006.
277 ANTICIPATION same period according to deferment interest percentage set in act law no. 6183, that accumulates in the period beginning after three months until the amendment bill is summoned to the tax payer, needs to be paid as well as the tax refund in accord with decrees stated in 120th article.” Besides the injustices in the actualization of the conditions in the article, the interest rates applied to the state and the taxpayer are not equal as well. The state has to pay to tax payer under the same conditions and at the same amount the tax payer pays the state. Therefore the paragraph in question is against the Constitution and law. Although regarding Turkish Constitutional Court Decision 2011/37 dated 10.2.2011 and following changes at article 112 of Tax Procedure Act by Act no.6322 dated 31.5.2012, unlawful situation is still in effect to date.
3.4. Resource Utilization Support Fund This example will probably be one of the most interesting examples in a system of law. Resource Utilization Support Fund known as KKDF was founded by the Turkish Central Bank of with no. 88/12944 decision of Council of Ministers and its legal ground is the no. 3182 Bank Act. The practise of this fund was carried out in accordance with the declarations of Central Bank of the Republic of Turkey. The mentioned authority of Council of Ministers continued in the act no. 4389 which replaced the above mentioned act. Later, with act no. 4684 issued in 2001, this authority of Council of Ministers was nullified and this new regulation was in execution beginning from 1.1.2002. However, in temporary article 3/a of the act it was stated that KKDF deductions would continue to be collected according to the nullified decisions of that act until a new arrangement is made about the issue. The execution of KKDF today, in a contrary fashion to law, is carried out according to an article which is not enforced and also according to no. 2001/4 and dated 31.12.2001 circular order of Central Bank. To state in another way, a financial obligation is collected by taking up an article, nullified by an act, as the legal ground. Here first the act by which the fund can be collected is nullified and then by adding a temporary clause it was stated that the collection could continue based on
278 ANTICIPATION IN LAW the temporary article. It does not seem possible to understand this from the logical perspective of law. Today, KKDF is collected illegally since 1.1.2002 and the collection sums amount to huge numbers. There are judicial decisions on the subject as well. 1st Tax Court of Ankara has a decision in 2003 stating that the fund is not in enforcement17. In the decision, it was not seen as in accordance with law in the subject matter of the case that Resource Utilization Support Fund deductions can be made because there is not an institution of fund newly founded or in use as of 1.1.2002. This decision was made final with the affirmation of Ankara District Administrative Court18. Moreover, the application for the amendment of the decision was also rejected19. Also, 5th Tax Court of Ankara has given a decision in the same manner20. Another interesting point in the issue is that in the “C Columns” of the budget rules belonging to the year 2002 and after, there is no regulation regarding the collection of KKDF. The fact that authority of collection is not given with the budget rules means, in terms of budget law, that related income cannot be collected for that year. Within this perspective, KKDF is contrary to rules of the budget and also to its law. All these explanations show that collection of fund is being made with the use of an illegal authority.
3.5. Reconciliation on Taxes Reconciliation is a method used by the tax payers and the tax offices to resolve the issue of tax payments through the conditions specified in the act and without applying to court. Here, the tax payer does not get involved in the long and laborious judicial procedures and pay due tax in less sums and the creditor administration gets the expected payment quicker. Consequently, it is beneficial for both parties.
17 Ankara 1. Vergi Mahkemesi, T. 24.12.2003, E.2004/727, K.2004/1054. 18 Ankara Bölge İdare Mahkemesi, T. 13.5.2004, E. 2004/1093, K.204/1385. 19 Ankara Bölge İdare Mahkemesi, T.7.10.2004, E. 2004/2842, K.204/3078. 20 Ankara 5. Vergi Mahkemesi, T. 17.9.2004, E.2004/631, K. 2004/866.
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It is not enough that reconciliation is regulated only by law. There must be some main regulations in the text of law regarding the process of reconciliation. As seen here in the annulations of all or most of taxes and fees, which is the most problematic issue, in exemplary situation, there are no regulations about having a restriction on the decisions of the administration. When there is not such a regulation there are arbitrary points in the decisions of the administration and justice on taxation is not achieved as everyone pays a different sum of tax. Beyond that, the current enforcement and regulation is against the explanations in article 73 of the Constitution. The unlimited authority that Ministry of Finance uses in reconciliation cases is actually an authority that must be used through law. In this case the authority of legislation laid down in 7th article of Constitution is handed over as contrary to law. For this reason, as there are different agreements with the tax payers, they find the concept of reconciliation unjust. It is not possible especially to explain this to taxpayers who pay the whole amount on time from the point of justice. The subject of devolution of authority is debated in doctrine and placed as below in various Constitutional Court decisions21:
• The legislator can give authority to the government after determining the legal grounds. (Decision no.1985/7) • When legislator gives authority to the government they also need to outline the limits and frame of the authority by law. (Decision no.1965/12 and 1965/57) • The precautions to be taken by the body of enforcement based upon the rule of law must be objective in its nature and should not give an extensive decisive authority that might lead to arbitrary enforcement. (Decision no.1966/6 and 1985/7) • The contrariness of the rule of law to principle of non-devolution of authority in Constitution is that it does not set main rules and principles about certain issues; it does not outline a frame and leaves
21 Erdoğan Teziç, Anayasa Hukuku, İstanbul-2004, s.17 vd.
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an unlimited, uncertain area to the regulation of administration. (Decision no.1988/8).
The contrariness in reconciliation against Constitution can be seen very clearly with these decisions and explanations.
3.6. Amnesty Act When tax amnesty was the issue, though votes of the 330 members of the parliament, which makes the 3/5 majority of the total number of parliament members, are needed to make the draft proposal into law and votes of members of the ruling party were enough. There are mistakes in decisions taken and the arrangements made by legislation in some of the regulations. This can be both in terms of content or procedural. As an example, like many others, “The Bill on Collection of Some Public Debts through Reconciliation” was accepted on 20.2.2008 with Act no. 5736. 318 members of the parliament participated in the voting of the bill. 298 votes were in favour and 20 of them were against the bill which was not actualized and the Bill is not actually accepted in parliament. In order to decide whether this arrangement is tax reconciliation or an amnesty under the name of reconciliation one needs to analyse not only its name but also the content of the act. Constitutional Court is not bound with the name of the arrangement submitted. The qualified majority needed was achieved in previous years after the warning of Mr. Sezer, President of Republic, who pinpointed that some expressions in the arrangement called Tax Peace are amnesty rules in nature that qualified majority will be needed for amnesty articles. Because, according to Constitutional Court the total or partial abdication of collection of tax penalties and fees is in same nature as amnesty. In spite of the fact that the name of the act is reconciliation, statements regarding amnesty in its content show clearly that this is an amnesty on tax.
1. There is a new opportunity of reconciliation for those who applied for reconciliation before but did not have reconciliation due to some problem and applied for court. Administration is offering
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reconciliation to those with whom it refused to reconcile before. This is amnesty. 2. Even though administration says that this is a reconciliation and not amnesty and that they will reconcile and even though they do actually reconcile in the end, collection of some of the interest up to current date is abdicated with the clause that “Collection of the debt remaining from the total amount which was the issue of reconciliation will be abdicated under the condition that instalment amounts will be paid in total, together with the interest calculated as % 0.2 separately for each month and for each dividend payout, in 18 months and in 18 equal instalments from the beginning of instalment payment period” and this is a clear statement of amnesty. Again, in 3rd and 5th articles of the act there are similar arrangements for the abdication of default interest and default fee. 3. Mesne profits, which were specified and confirmed and summoned to related people before 1.7.2007 but were not paid, in spite of this, until the date the act was issued are also made issue of reconciliation. In this case debts which were made certified earlier but were not paid are also within the scope of the act and thus carry a clear quality of amnesty. 4. The statement in 3rd paragraph of the act is also an arrangement of amnesty: “In case that bank fulfils the requirements, corporate tax assessments regarding the related years are amended without considering the expressions on limitations set in act no. 213.” 5. The statement “assessments cannot be made, previous assessments are abdicated, accruing amounts are cancelled” that takes place in 4th article of the act also mentions amnesty. 6. The statement “the collections of the due amounts which were supposed to be paid but were not paid by the time this article is enforced are abdicated” that takes place in 5th article of the act is, again, pointing out to amnesty.
As can be clearly seen, the act includes statements of amnesty in some aspects rather than reconciliation. So long as these clauses are in the
282 ANTICIPATION IN LAW text, besides the passing of the act by simple majority the authorization of Ministry of Finance, regarding the main points on the enforcement of the clauses, mean the devolution of authority and it is against both law and Constitution. Following 2008 Act there are many more other unlawful amnesty acts with different names and today legal problems still continues as of today.
4. Conclusions Anticipation is the art of predicting the future and acting accordingly. Hence, anticipation in law requires the diagnosis of current deficiencies in law and foresees what kind of problems they would create in the future. Tax laws in Turkey are studied on several examples of major violations is described in this Chapter. It is demonstrated that the authority of taxation is not currently employed within the frame of the Constitution and the supremacy of principles dominated by international treaties and rules are violated. This result in violation of the rights of taxpayers, causes financial loses and while slowing down the operation of taxation system with unnecessary work, harms the social belief in the judiciary system. This anticipation work is expected to guide the legislative organ that the law making process should be along the Constitutional principles and any approach and regulation that may disable the use of this authority must be avoided.
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14 A SCENARIO APPROACH FOR BETTER ANTICIPATING THE OIL MARKET SHIFTS
Soufiane Naime, Christophe Bisson
Abstract The oil industry has entered into a new era of turmoil and the market exhibits high uncertainties due mainly to climate change and the new world energy geopolitics. Thus, it is becoming vital for oil companies to anticipate future market shifts in order to remain competitive. If most of these companies are at best using scanning to detect changes, there is also room for improvement concerning scenario analysis in this field. With that aim, this paper presents a new framework for developing scenarios as images of future oil markets. New drivers of change and their related sub-factors can be determined and more robust scenarios can be built to help companies and governments to better prepare for facing such a volatile and strategic market. Keywords: Scenarios, Anticipation, Oil, Energy, 10 forces, Pestel.
Introduction Since 2014, the oil industry has entered into a tough period, with oil at a very low price, (Baumeister and Kilian, 2016) as the new world energy geopolitics is much more pluralistic, rendering this market even more unstable. Yet climate change is obliging politicians, consumers and companies to reconsider the use of fossil fuels in general. Thereby, producing countries and the “seven sisters” (i.e. Aramco, Gazprom, CNPC, NIOC, Petrobras, Petronas and PDVSA) were compelled to reduce their investments significantly and made major lay-offs. Obviously, it is not the first crisis/shock in the history of petroleum (e.g. 1973 and 1979). However, the hegemony of oil in 2017 is not any more what it used to be.
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In such a context, it is at stake for oil companies to be nimble and anticipate as much as possible or adapt in the fastest way to energy market shifts, in order to remain competitive. Indeed, to anticipate can lead one to get an opportunity or avoid a threat as it encompasses a forward-looking attitude which triggers an action (Poli, 2017).To anticipate volatile and uncertain market movements, most companies at best use scanning to detect weak signals (Bisson, 2014) which are ‘‘imprecise early indications about impending impactful events’’ (Ansoff, 1980, p. 131). Unlike most oil companies, “Shell is one of the few that routinely employs alternative outlooks as a core strategic tool” (Bentham, 2014, p.88). Hence, they create scenarios as images of the future (Ramirez et al., 2015) to build their strategy, which for several decades has made billion- dollar sum impacts in that industry (Bentham, 2014). Linderoth (2002) emphasized that big forecast errors in International Energy Agency (IEA) member countries arose in both stable and unstable periods. Thus, to deal with the difficulties in providing precise forecasts (Silberglitt et al. 2003), scenario analysis has been applied to build futures (Borjeson et al., 2006). Scenarios describe variables, dynamics and interconnections (Rotmans et al., 2000). Shell’s scenario creation is built upon four main areas: “economics, geopolitics and socio-cultural issues, energy, and the environment to understand how consumers, governments, energy producers, and regulators are likely to behave and respond to change in the decades ahead” (Bentham, 2014, p.88). Therein, they focus mainly on macro factors that can be evaluated with PESTEL (Bisson and Yasar Diner, 2017) which deals with political, economic, social, technological, environmental and legal factors (Kotler and Armstrong, 2004). We use a new framework to additionally address the micro environment (Bisson, 2016) for oil companies. Thereby, based on macro and micro factors, exploratory scenarios will be constructed based on these drivers of change (Schwartz, 1996; Van der Heijden, 2005). Hence, as suggested by Daurios et al., (2014) and Bisson (2013) the most likely, the optimistic and the pessimistic scenarios will be created for the oil market in 2030 as our foresight (Graf, 1999).The remainder of the chapter is organized as follows: we initially provide a short literature
286 A SCENARIO APPROACH FOR BETTER ANTICIPATING THE OIL MARKET SHIFTS survey on the rise of scenario planning and its use in the energy sector as an anticipation tool. Then, we detail the methodology of our research. Next, our findings are outlined and discussed. Finally, our conclusion emphasizes the implications of our findings for academics as well as for managers and indicate the avenues for further research.
Background The rise of scenario planning and its use in the energy sector as an anticipation tool : For several decades, companies are increasingly involved in understanding their competitive environment as it becomes more complex and uncertain. Hence, they explore short, medium and long terms, aiming to anticipate which can be construed as strategic grail since it could lead them to get an advantage and/or to avoid a threat as much as possible. Many tools and methods have been developed for this purpose and during the last 50 years scenario planning has become essential. Historically, its primary use was made in the 19th century by Clausewitz and Von Moltke (Prussian strategists) during military battles (Bradfield and al. 2005). From a business perspective, Kahn is considered as the forerunner of scenario planning with his work done in the 50s at the Rand Corporation (Varum and Melo, 2010). Several scenario approaches have been built during recent decades. Indeed, scenario planning is used to think about the future (Brummell and MacGillivray, 2008) but others built scenarios to understand the competition, such as Fink and Schlake (2000) through their tri- dimensional method. Yet, Peter Schwartz has demonstrated the usefulness of scenarios in understanding future uncertainties via the notion of “alternative future” vs. “hypothetical sequence of event” defended by Kahn (Von derGracht 2008). Since the 1970s, Shell has remained the industry benchmark in scenario developments (Bradfield et al 2005). Indeed, the “Year 2000” scenario developed by Wack and his team has become a reference since it has succeeded in predicting the crisis of 1973 (unprecedented for the sector).
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The logic of scenario analysis encompasses the notion of risk that must be taken into consideration and the oil sector has particularly adopted it well (Brummell and MacGillivray, 2008). The sequence of events is crucial in controlling these risks, since it can lead to different effects in the future (Millet 2009). Facing this wide range of risk factors, the oil sector has quickly broken away from the conventional approach (Schnaars 1987) which was very dependent of the current trend, characterized by a single sequence of events thereby limiting the understanding of the future (such as trend projection). Thus, it developed a multi-channel approach (Bood and Postma,1997) considering several sequences of events which are discussed in depth and lead to a multitude of scenarios. This approach also offers the possibility of interacting with different types of risk. The current world of energy has to deal with issues related to climate (which involves all issues around Carbon dioxide (CO2) ) and the diversification of the energy mix (the most visible example is the increase in the share of renewable energy) have undeniably blurred the future horizon establishing a palpable uncertainty. The major energy players are currently thinking about how to adapt to a future world with a multitude of possibilities. This is why most of these actors rely today on the scenario planning method in order to better anticipate and be prepared for the future. Yet, Upham et al (2016, 48) state that “typically in the development of energy scenarios, scientific models are used that embody more less widely accepted, empirically-derived relationships between variables, representing aspects of the world”. The oil sector has widely adopted the scenario planning. Each organization such as the International Energy Agency, the Energy Information Administration (for US), Wood MacKenzie or even each operator now create their own their scenarios (i.e. their own vision of the future). Many different scenarios based on various approaches for the energy market, however, may be detrimental for companies to make clear and quick decision. Moreover, “the energy industries need to better identify change factors and to design sustainable strategies and operations” (Alizadeh et al., 2016, p.162).
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Methodology We used PESTEL as a grid to get the drivers of change from the macro forces of the environment that can impact the oil sector. Likewise, to explore the micro environment, the 10 forces i.e. the 5 forces of Porter (1980) and the 5 forces of Bisson (2016) were used. Thus, to Porter’s forces (i.e. the rivalry between established firms, the barriers to enter the market, the products / services / technologies of substitution, the bargaining power of customers and the bargaining power of suppliers) were added to the 5 forces of Bisson which are: The bargaining power of skilled workers, the complementary products, the bargaining power of distributors, the influence of mass media and the influence of organizations of quality. Thereby, a new framework to detect drivers of change and related sub factors is proposed in order to build more accurate scenarios that could allow oil companies to be better prepared for the future. Moreover, we collaborated with 5 oil experts to define the main drivers of change through analyzing the micro and macro environments with PESTEL and the 10 forces. For each stated driver of change obtained, its sub-factors were determined. In order to ensure the right determination and evaluation of such drivers, we followed the Delphi method (Bell, 2000). Drawing on Daurios et al., (2014) and Bisson (2013), we aimed to build the pessimistic, the optimistic and the most likely scenarios for the oil market in 2030, based on the drivers of change, their sub-factors, the evaluation of their impacts and their variation (i.e. positive, stable or negative). Therein, after completing two sets of online questionnaires, these oil experts after agreeing on the drivers of change provided an evaluation of their impact following a five-point Likert scale (from 1 meaning very low to 5 meaning very high) and their variation (i.e. negative or stable or positive) for the 3 scenarios. Since our distribution was not symmetric, the median score determined the impacts of the sub- factors for the three scenarios (Morris, 2005). To narrate the scenarios, we chose as models those of Karaca and Oner (2015).
Findings and Discussion Based on the PESTEL analysis, geopolitics (Supply disruption and unplanned outages) has been identified as a main driver of change, since governments are more and more involved because oil is a key factor in
289 ANTICIPATION countries’ development. For a decade now, supply and demand (S&D) factors have been seen as fundamental drivers responsible for the current market shift. Thus, very often nowadays, we observe how S&D dynamics mitigate and sometimes inhibit the impacts of geopolitics. The notion of S&D dynamics is complex and comprises many sub- variables :
On the Demand side: • As oil is a key factor of development at both domestic and global levels, Gross Domestic Product (GDP) represents a strong indicator of the market evolution. But it is not only since the notion of going “green” emerged that the oil intensity of the global economy also changed . We started observing the notion of energy efficiency, fuel substitution etc. which mainly participate in the market shift process. Those sub- variables which have become part of the changes in people’s standard of living impacted indirectly on the price elasticity of demand (of oil).
On the Supply side: • The population growth and globalization played a huge role in making Oil and Gas (O&G) a booming market. Oil companies increased their production significantly to meet the growing demand. This continuous pumping affected oil reservoirs and the observed rise in their depletion rate forced companies to search for new resources which mainly consists of offshore sources to maintain the flow of oil. Legacy production decline as a sub-variable of Supply is a key indicator assessing the decline of oil supply we face every single year. The cost of new production also drives supply, especially in this period where the barrel price is low. If the breakeven oil barrel price is too high, oil majors face profitability issues and then have to consider reducing their output. In order to monitor profitability and possible oil shock, OPEC (Organization of Petroleum Exporting Countries) implemented quotas in 2016. OPEC quotas ( level of OPEC’s output) must be followed carefully as they have a direct impact on Oil Supply. In parallel, the level of tight oil (LTO) especially coming from Permian (USA) has to be scrutinized as a key sub-variable.
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The Market is also influenced by the following short term drivers : • The oil inventory provides insights concerning the market situation, with its excess oil inventory as a sub-variable (compared with the 5-year average). • The Financial market and USD exchange rate sub-variable plays an important role in understanding market fluctuation. • For the micro environment, working with the 10 forces showed that the threat of substitutes is a key factor in the energy market today. ° The Power sector has modified the structure of the current oil market and is highly linked to: - Renewable economics (RENEc) associated with development of the solar / wind market. Implicitly, innovation is linked to this variable. A better RENEc variable will entail a higher level of innovation which will lead to lower prices for access technologies. - Carbon regulations have become a key factor since the COP 21
in Paris. Now countries all over the world recognize that CO2 is
the main cause of global warming. Reducing the CO2 footprint is part of their roadmap. Following this sub-variable on a short term basis is critical as it can tremendously affect the oil market
(such as defining the price of CO2). - Battery storage is the main trend for replacing fossil fuels by green energies (electricity). The monitoring of innovations in this field is very important as it will indicate insights into what the market will be like tomorrow. ° The Transportation sector as the major consumer of oil supply might also modify the market future. - Electric Vehicles have begun to gain market share since electrical engines with increased efficiency have arrived (in terms of autonomy) that has strong importance for the carbon emission slump. Their evolution in the coming months and years is strategic, as its impact could be drastic.. - Vehicle Fuel Economy also aims at reducing the carbon footprint in the transportation sector and arises as an alternative
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to the impact of the electrical vehicle. On this topic, there’s an underlying notion of innovation and it involves all car makers in developing and designing efficient engines with less and less carbon emission (following this sub-variable implies being focused on car makers’ innovations). - Aviation is a high oil consuming market and the trend of biofuels (as a substitute for kerozene) which has appeared lately, could become disruptive. This variable should be also closely monitored.
It appears that the US, its international relations and quotas are its main impacting sub factors. Clearly, oil has a strong relation with the global economy and is related to Gross Domestic Product (GDP) and CPI (Consumer Price Index). Technology (innovations) and environmental dimensions (depending on the Price of CO2/t and level of CO2) are also very important factors.
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The 3 scenarios and their components are summarized in Table 1.
The Most Likely The Pessimistic The Optimistic Scenario Scenario Scenario Sub VARIABLES Trend Impact Trend Impact Trend Impact VARIABLES GDP stable 3 stable 3 stable 3 Oil intensity of positive 3 negative positive 4 global economy 3 Price elasticity stable 3 negative stable 3 of demand 3 Legacy Oil Supply and production negative 3 positive stable 3 Demand decline 3 New positive 4 positive stable 2 production cost 4 LTO positive 4 positive 4 stable 3 OPEC production positive 4 negative negative 2 level 4 Excess Oil inventory commercial stable 3 positive stable 2 inventory 3 USD exchange stable 3 stable stable 2 Financial rate 2 market Barrel price stable 4 negative stable 3 4 Supply disruptions Geopolitics stable 4 positive stable 3 and unplanned outages 4 Renewable stable 2 negative positive 4 economics 2 Carbon Power stable 3 negative positive 4 regulation 2 Battery storage stable 2 stable 2 positive 4 Electric stable 2 stable positive 4 vehicles 2 Vehicle fuel Transportation stable 2 stable positive 4 economy 2 Aviation stable 2 stable positive 4 biofuels 1 Table 1. Construction of 3 scenarios for the oil market in 2030
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Based upon the inputs in Table 1, we were able to narrate the most likely, the pessimistic and the optimistic scenarios. Scenario 1: S&D equilibrium, Price orientation (The most likely) In 2030, S&D dynamics dominates the market drivers. The Peak oil demand theory drives the market, supported by a large GDP growth rate. Demand increases by 1.3-1.5 million barrels per day (Mbpd) till 2030. With relation to supply, the US shale revolution brings an increased number of barrels onto the market, mainly due to technical and financial improvements (cost reduction and well performance improvement) enabling access to more low-cost supply. Inversely, the OPEC quotas policy continues to protect prices at $60-65, (confirming the deal extension talks over the last few weeks) stabilizing the S&D dynamics. However, the geopolitical situation may affect it (such as Venezuela bringing OPEC compliance rate up to 150%, its highest ever production prices). The balance (S&D balance) exists but it is fragile: shale will be playing the role of market price reducer in the event that prices surge (this explains why we currently see more majors investing in the Permian basin, buying acreage or stakes to diversify their portfolio to also control the market stability in the future). To follow the peak oil demand curve supposed to be reached in 2030, the oil companies increase investments to first offset the under- investment which happened during the 2014-2017 period which led to the increased depletion rate of mature fields. From now to 2030 many final investment decision (FIDs) will be taken so as to fulfilll the demand (many projects will start and be online this year). From now to 2030, companies have to source 3 to 5 Mbpd in addition to the demand growth to supply the world (because of the under-investment during the last crisis). In order to decrease risks to new developments, companies rely on cost reduction (since 2014, 50% cost reduction has been reached) by developing brownfield more than greenfield projects and fast return investment ones. They also develop technologies to accommodate the oil intensity of the global economy, in order to use less oil for the same usage. Another option to reduce risks is to maintain a viable gap between the cost of production and the market price (i.e. the economics
294 A SCENARIO APPROACH FOR BETTER ANTICIPATING THE OIL MARKET SHIFTS of exhaustible resources; see.Hotteling, 1931). Inventories in 2030 are set at a comfortable level aiming at reducing the impact of the demand price elasticity, keeping consumers loyal to oil products. In addition, CO2 emissions are growing but are stable in comparison to a few years ago (approximately 32 Giga tons/year). We get closer and closer to the acceptable limit of 2900 Giga tons but we are still on the right side of the line. In terms of carbon regulations, the price of CO2 is still not clearly determined, but all countries envision a price around of $30/ton which would leave coal (which is the top CO2 emitter) out of the equation. The increasing amount of CO2 in the atmosphere obliges countries which are strongly dependent on fossil fuels to diversify. The affordable price of oil does not benefit the quick development of alternative energies. A stable level in terms of innovations such as battery storage renders green electricity still secondary and will limit the development of clean transportation (electric vehicles) or renewable energies. In the meantime, oil majors innovate and accommodate climate change by introducing more and more gas into their business model. With less emission and high capability of covering energy demand growth, this solution is the one chosen by companies which are already in the market. Scenario 2: Oil superabundance, market share orientation (The pessimistic) Geopolitical crises are numerous. OPEC countries such as Venezuela are struggling to retrieve their original level of production, while Libya and Nigeria register their lowest output ever. Iran being still uncertain regarding their nuclear agreement keeps the market unstable. The GDP growth remains stable which stabilizes oil demand over time. The USA has recently decided to become the world’s leading oil producer; thus, their willingness to be self-sustainable is now a reality and they even become the top exporter (in 2030) thanks to their tight oil business. Facing this aggressive US position, OPEC sets out to ramp back up production (after the end of quotas in 2019) which will oversupply the market. From 2019 to 2030 we are in a position of an overabundance of oil (assumption of this scenario). OPEC becomes the market share focus
295 ANTICIPATION and there is no more targeting of price stabilization. This new strategy allows the price/barrel to significantly go down below what we have seen in the last crisis (approx. $40). Low prices boost several sectors such as transport, heating etc., making people less attracted to other alternatives (low level of demand for elasticity , low intensity of global economy). The 2014 crisis significantly helped companies in operating a tremendous cost deflation through innovations and other applications which has enabled the lowering of the break even point (making alternative energies’ ascent more difficult). In this scenario, a low break even point enables the oil industry to survive even with a very low price per barrel, but it does not allow for diversification and investments in alternative energies such as in the renewable ones. With no efficient carbon regulation decision, over-production and the use of fossil fuels increases CO2 emission in the atmosphere above the average of 32Gt/year (2018). Many climate events occur (e.g. floods, hurricanes), the ice melting phenomenon accelerates and climatic migrations hit 100 million people. Innovation remains at its preliminary stage as oil prices tumble down. Battery storage stagnation impacts the renewables economy and the transportation sector making their own development bottom out, making them economically still expensive in relation to oil products. In this scenario, climate degradation, CO2 level increase and poor advancement of alternative energies should force governments to consider applying policies enabling them to quickly reach a sufficient level of renewable energy capacity to offset these effects. Scenario 3: The optimistic The energy market has diversified. With the end of the fossil fuels hegemony and a balanced energy mix, governments all over the world set a price of CO2 higher than $30/t due to the climatic emergency (between $30 and $45). This decision has immediate effects such as penalizing the development and consumption of fossil fuels. This leads to a drastic reduction in CO2 emissions. In fact, concerned companies invest in alternative energies and technologies to offset the effects of fossil fuels (energy efficiency and/or fuel substitutes). Therein, improvements
296 A SCENARIO APPROACH FOR BETTER ANTICIPATING THE OIL MARKET SHIFTS regarding energy storage, CO2 capture and storage, energy efficiency or hydrogen are going to give birth to the first functional applications. For example, reducing the cost of batteries by 50 to 60% will provide huge opportunities for electrical vehicles and their numbers may rise from 5 million electric cars today to 25 million in 2030. Renewable energy efficiency significantly surges and brings prices down to the same level as fossil Fuels (same cost per KWh – $0.15). However, fossil fuels remain dominant.The proportion of renewable energy and of fossil fuels enables the energy market to adapt quickly whether to an increase in the CO2 rate in the atmosphere or to an unpredictable demand growth. GDP is less impacted by the fossil fuels market and is more under control thanks to renewable energies (due to their accessibility characteristics). This new situation significantly mitigates the economic recession caused by the oil market, as seen in the past (the 1973 shock for example).
Conclusion The oil industry is a strategic market which faces strong turmoils and high uncertainties. In such a context, it is important for these companies to anticipate market shifts. If most of these firms are at best using scanning to detect changes, there is room for improvement concerning scenario analysis in that field. Thus, this new framework applied to the oil market can help to determine new drivers of change and their related sub factors. Therein, it could lead to the creation of more robust scenarios as images of the future, thereby helping companies and governments to better anticipate movements of this highly volatile market. For further research, the model to build scenarios for the oil market could be reinforced by getting the inputs of more experts.
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Forecast, Soc. 70 (4), pp. 297–315. Upham, P., Klapper, R., & Carney, S. (2016), Participatory energy scenario development as dramatic scripting: A structural narrative analysis. Technological Forecasting & Social change, 103, pp. 47-56. Van der Heijden, K. (2005), Scenarios: The art of strategic conversation (2nd ed.), Chichester: John Wiley and Sons. Varum, C.A. & Melo, C. (2010), Directions in scenario planning literature - A review of the past decades, Futures, 42, pp. 355-369. von der Gracht, H.A. (2008), The Future of Logistics: Scenarios for 2025, Frankfurt/Main: Gabler Edition Wissenschaft.
300 ABOUT THE AUTHOR’S
Cihan Akın: has received his bachelors degree in Economics from Yeditepe University. He continues his graduate studies in Economics at Galatasaray University. His areas of study are Behavioral Economics and Financial Markets. e-mail: [email protected]
Deniz Palalar Alkan: Assistant professor in the Department of Business Administration at Yeditepe University. Deniz Palalar Alkan has earned her baccalaureate degree from Florida Atlantic University majoring in International Business and Trade. She got her Master’s Degree from Lynn University and received her Ph. D. degree from Istanbul University. After obtaining her bachelor’s degree, she started to work at several institutions, including Citibank N.A. and insurance brokerage firms. At Yeditepe University, she is instructing several courses, including Leadership, Business Management, and Entrepreneurship. e-mail: [email protected]
Ece Ceylan Baba: Associate Professor in Department of Architecture at Yeditepe University. She received her undergraduate degree from Mimar Sinan Academy of Fine Arts University. After receiving her master’s degree from the Department of Architecture at Yeditepe University, she pursued her PhD degree at the Department of Architecture at Mimar Sinan Fine Arts University and gained Associate Professor Degree in 2016. Her areas of expertise are utopias and dystopias in architecture, globalization, metropolitan areas, high rise buildings, urbanization, urban regeneration, user participation, environment and urban psychology, housing typologies, and lofts, on which she continues her researches and publications. Baba has two books, her first book, titled “Tasarım Demokrasisi ve İstanbul” (”Democracy of Design and İstanbul”), was published in September
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2012, and her second book titled “Loft: Modernizmden Postmodernizme Geçiş Sürecinde Loft Mimarisi ve İstanbul’daki Yansımaları” (“Loft: Loft Architecture and Its Projection in İstanbul during the Transition from Modernism to Postmodernism”), was published in May 2015. In addition to her academic work, she pursues her professional architecture career and as the founding partner of Baba Mimarlık. Baba has 4 design awards in different fields. She also is a board member of İMSAD (Association of Turkish Construction Materials Producers). e-mail: [email protected]
H. Senem Göl Beşer: Associate Professor in the Department of Business Administration at Yeditepe University. She has an undergraduate degree in Business Administration (in English) from Marmara University, Istanbul; received her MBA in International Business from University of Nebraska-Lincoln in 1998 and PhD from Management and Organization from Yeditepe University in 2008. Her teaching experience in the department of business administration at Yeditepe University includes courses such as; Management, Contemporary Business, International Business, Business Policy and Strategic Management, HRM (graduate level), Leadership, Gender Issues in Management, Cross-cultural Management, Learning Organizations, Organization Theory and Design, Multicultural Business Communication. Her current research interests are Foresight Studies, Strategy, International Business, Management and Organization, Sustainable Business/Economics and Gender Issues. Her primary research goals are toward understanding the diversity, sustainability and business triangle. She is an active referee in academic journals including Foresight, Futures and Technological Forecasting and Social Change, Journal of Entrepreneurship and Innovation Management (JEIM) and European Academy of Management (EURAM). She is currently the UN-PRME (Principles for Responsible Management Education) Coordinator, of Yeditepe University, Department of Business Administration. She is on the board of UNESCO Chair in Anticipatory Systems, Università degli Studi di Trento, since 2014. e-mail: [email protected]
302 ABOUT THE AUTHOR’S
Christophe Bisson: Christophe BISSON, Ph.D. is Scientific Director of the Msc “International Strategy & Influence” and Associate Professor at SKEMA Business School. He received an academic award in 2017 from the International Organization of Competitive & Strategic Intelligence. His book entitled “Guide de Gestion Stratégique de l’Information pour les PME”, articles have been selected by the French Inter-Ministerial Strategic Economic Affairs Directorate. Yet, he received research funds from the American NSF, EU, the French Ministry of Research, Turkey and Peru. He is the Europe Associate Editor of Journal of Intelligence Studies in Business, published in Futures, Journal of Organizational End User Computing, IT & People, Journal of Strategic Marketing among others. He is also board member of several International Organizations and holds a PhD in the field of Competitive Intelligence from the Aix- Marseille University. e-mail: [email protected]
A. Gönül Demirel: Associate Professor in the Department of Business Administration at Yeditepe University. She has an undergraduate degree in Sociology from Bogaziçi University, Istanbul; received a certificate in Marketing from the Chartered Institute of Marketing, UK; received her MBA in Management and Organizations from Yeditepe University, Istanbul; and PhD in Management and Organization from Yeditepe University in 2008 with a thesis on “An Exploratory Study on Developing and Testing Integrated Stakeholder Relationships Management Model” under the supervision of Prof. Dr. M.Atilla Öner.She has been teaching courses at the Department of Business Administration since 2004 in undergraduate, graduate and Doctorate level. Her teaching experience includes courses such as: Business Research Methodology and Data Analysis, Organization Theory and Design, Management, Contemporary Business, Human Resources Management, Business Communications. Her primary research interests are stakeholder theory, managerial values, leadership and corporate governance.Her recent research focuses on the influence of Big Data on Management and Organization issues. e-mail: [email protected]
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Yusuf Can Erdem: Associate Professor in the Department of Business Administraion, Yeditepe University.He has earned his baccalaurate degree from Middle East Technical University majoring in Management. He got his Master’s Degree from East Carolina University, and received his Ph.D. degree from Yeditepe University. After obtaining his MBA, he has worked at several institutions like, PWC, Fresenius and General Electric. He is teaching undergraduate and graduate courses at Yeditepe University and co-authored two books on Customer Experience Management. His research interests include Customer Experience Management, Consumer Behavior and International Marketing. e-mail: [email protected]
Çiğdem Kaya: Assistant Professor of Management and Organization in the Department of Business Administration at Istanbul Arel University. Her research interests are organization theory, technology strategy and innovation, and organizational behavior. She supervises MBA theses on organization theory and organizational behavior. She has authored and co-authored articles on institutional logics, population ecology theory, social responsibility, and organizational behavior. e-mail: [email protected]
Soufiane Naime:Soufiane Naime has graduated from the Advanced Master of SMIB at ESSEC Business School. Yet, he is the Sales and Marketing Manager for a leading oil services company. He is currently in charge of diversifying the group’s activities for the MEA region. e-mail: [email protected]
Özlem Kunday: Associate Professor and Vice Chair in the Department of Business Administration at Yeditepe University, Istanbul Turkey. She is member of GEM Project Team in Turkey and the Director of Management Application and Research Center (YUVAM). Her primary research interests are entrepreneurship, start-ups, SME management and human resources management. She has authored, co-authored, translated and edited books on entrepreneurship, contemporary management, healthcare management and human resource management. e-mail: [email protected]
304 ABOUT THE AUTHOR’S
M. Atilla Öner: Professor of Technology and Operations Management in the Department of Business Administration and the chairman of the board of directors of Management Application and Research Center at Yeditepe University. He is an associate editor of Technological Forecasting and Social Change. His research interests are futures and foresight theory and methodology, technology roadmapping, R&D management and technology management. He supervises MS/MBA and PhD theses on national innovation systems, pilot national (sectoral) foresight studies and system dynamics modeling of R&D management, project management and public policy issues. He is on the editorial board of Technological Forecasting and Social Change, Foresight, Futures, International Journal of Innovation and Technology Management and Journal of European Theoretical and Applied Studies. He has auhored, co-authored and edited books on foresight, project management, R&D management and economics and management of technical change.
Sara Saban: Assistant Professor in the Department of Psychology at Faculty of Arts and Sciences, Yeditepe University, Istanbul, Turkey. She has a B.A. degree in Psychology from Bogaziçi University, Istanbul; received an M.A. degree in Clinical Psychology from Bogaziçi University, an M.S. degree in Pedagogy from University of Bergen, and a PhD degree in Cognitive Neuroscience from University of Bergen, Norway. Her research areas are cognitive processes such as attention, memory, implicit/ explicit processing, neuro-psychology of sleep deprivation, using psychological and neuropsychological tests, psychophysiological measurements and brain imaging. e-mail: [email protected]
Ayşe Sevencan: Works as an Assistant Professor in Economics at Yeditepe University. She received her PhD in Ecocomics from Yeditepe University (2010) , master of arts in Applied Economics from University of North Carolina (2004) and bachelors degree in Economics from Bilkent University (2001). Her research interests include Applied Macroeconomics, Financial markets, economic growth and development. e-mail: ayse.sevencan@[email protected]
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Pınar Şenoğlu: She has an undergraduate degree in Law from Istanbul University Law Faculty and received a license of attorney from Istanbul Bar Association. Her profession is in banking sector. She has worked as account manager, assistant vice president and branch manager in Türkiye İş Bankası A.S., Fortis Bank A.Ş., Abn Ambro N.V., Istanbul and Royal Bank of Scotland N.V. Her research subjects are futures studies, foresight, anticipation, decision-making and uncertainty as a concept. Her former thesis instructor was Prof. Dr. Atilla Öner, after his passing her new thesis instructer is Assoc. Prof. Dr. Senem Göl Beşer. e-mail: [email protected]
Özlem Şenvar: Ozlem Senvar is an Associate Professor at Marmara University in Department of Industrial Engineering. Ozlem Senvar earned PhD degree in Industrial Engineering in 2012. She was officially granted a research fund (Ref.2013/327-350) awarded by the European Commission for her post-doctoral researches in France. She has been author of many peer reviewed international articles, book chapters, and conference papers. Her research interests involve Production and Operations Management, Advanced Quality Engineering, Statistics, Decision-Making, Machine Learning and Artificial Intelligence. e-mail: [email protected] ; [email protected]
Nihat Tavşan: Dr. Tavşan, following about two decades of working as a practitioner and an executive career, earned his Ph.D. degree from Yeditepe University after receiving an MBA degree from Istanbul Technical University. He is currently eat Business Department, MEF University. His major research areas are consumer behavior, organizational transformation, customer experience management and data science. His primary specialization is consumer behavior, and secondary specialization is quantitative methods. MEF University; Economical, Administrative and Social Sciences Faculty; Department of Business Administration e-mail: [email protected]
306 ABOUT THE AUTHOR’S
A. Kemal Tuğcu: Dr. Tuğcu is an Executive Coach at MENTOR Leadership Development, Turkey. B.S. (1978) in Mechanical Engineering at Boğazici University, Istanbul, Turkey. M.S. (1980) and Ph.D. (1984) in Mechanical and Systems Engineering at the University of Illinois at Urbana – Champaign, Urbana, Illinois. USA. He worked at General Motors Research Laboratories, Warren, MI; USA as a Senior Reseach Engineer (1984 -1988). From 1989 on he worked for Arcelik A.S. (a household appliance manufacturer company in Turkey) and held the positions of Research Manager, Product Development Manager and finally Human Resources and Quality Director until his retirement in 2001. His past research and publications mostly deal with mathematical modeling of natural (World Climatic Fluctuations and Ice Ages) and mechanical systems (Ship Steering, Automotive Powertrains and Home Appliances) with self-tuning adaptive control applications. He has extensive experience in R&D, Product Development, Human Resources, Strategic Planning, Organisation Design, Change and Quality Management fields. Dr. Tuğcu currently works as an executive coach where he provides personal one-on-one training for newly appointed top executives in their new positions. e-mail: [email protected]
Hande Tek Turan: Asst. Prof. Dr. in the department of Public Administration at Yeditepe University, Istanbul, Turkey. She received a bachelor’s degree in Political Science and Public Administration from Faculty of Economics and Administrative Sciences at Marmara University in 1996-2001. In 2002, she took her master’s degree in France, the University of Montesquieu Bordeaux IV, at IEP Bordeaux, Sciences Po, with the French government scholarship. In 2010 she obtained her PhD from the University Pierre Mendès France of Grenoble, IEP Grenoble, Sciences Po. Her research interests are new public management, governance, local and regional authorities, decentralization / decentralized cooperation, regional policy / local and regional development, smart cities, new emergent technologies and digital transformation in the public sector; she also participates in conferences and seminars at national and international platforms.
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Additionally she works as a consultant / expert within the projects of the development banks and international financial institutions such as AFD, UNDP, KfW and EU projects concerning local governments in Turkey, public administration and decentralisation reform, including regional development agencies. e-mail: [email protected]
Hakan Üzeltürk: Prof. Üzeltürk is one of the first graduates of Marmara University Law Faculty in 1986 and he became the first assistant of Tax Law Chair again the same year. He completed his post-graduate degree at Marmara University Social Sciences Institute in 1988 and doctorate degree in “International Tax Law” at Edinburgh University Law Faculty in 1997. He is a professor of tax law both at Galatasaray and Yeditepe University Law Faculty. He also has Advocate and Certified Public Accountant (CPA) titles. He was founder and manager of Galatasaray University Selim Kaneti-Adnan Tezel Tax Law Centre (2005-2014). He acted as the member of Tax Council and Tax Council Executive Committee (2003- 2009). He is the founder and editor of Legal Journal of Fiscal Law that is published monthly since 2005 and editor of Legal Journal of Bank and Finance Law. He is the owner TUSIAD Science Award 1992. He became a member of IFA, IIPF ve EATLP ve EATLP Academic Committee. He is the Turkey Reporter of International Bar Association Tax Committee. He is the Founding President and Head of Executive Committee of Istanbul Tax Centre. He has over 100 articles, over 250 newspaper columns and 15 national/international books/book parts. e-mail: [email protected]
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