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1

Takemura, Kazuhisa. Behavioral Decision Theory. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5453-4.

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2

Takemura, Kazuhisa. Behavioral Decision Theory. Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-54580-4.

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3

Behavioral decision theory: A new approach. Cambridge University Press, 1994.

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4

W, Brock Horace, Wood Arnold S, and Association for Investment Management and Research., eds. Behavioral finance and decision theory in investment management: Proceedings of the AIMR seminar, Improving the investment decision-making process: behavioral finance and decision theory. Association for Investment Management and Research, 1995.

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5

Goncalves, Duarte. Uncertainty and Complexity: Essays on Statistical Decision Theory and Behavioral Economics. [publisher not identified], 2021.

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6

Takemura, Kazuhisa. Behavioral Decision Theory: Psychological and Mathematical Descriptions of Human Choice Behavior. Springer, 2014.

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7

Crisman, Karl-Dieter, and Michael A. Jones. The mathematics of decisions, elections, and games. American Mathematical Society, 2014.

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8

G, March James, ed. A behavioral theory of the firm. 2nd ed. Blackwell Business, 1992.

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9

Xing wei jin rong li lun yu shi zheng: Behavioral finance theory and evidence. Hunan da xue chu ban she, 2004.

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10

Bayesian methods: A social and behavioral sciences approach. 2nd ed. Chapman & Hall CRC, 2008.

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11

A course in behavioral economics. Palgrave Macmillan, 2012.

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12

Dowling, J. Malcolm. Modern developments in behavioral economics: Social science perspectives on choice and decision making. World Scientific, 2007.

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13

Giannoccaro, Ilaria. Behavioral Issues in Operations Management: New Trends in Design, Management, and Methodologies. Springer London, 2013.

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14

Poulton, E. C. Behavioral Decision Theory: A New Approach. Cambridge University Press, 2010.

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15

Poulton, E. C. Behavioral Decision Theory: A New Approach. Cambridge University Press, 2011.

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16

Shapira, Zur. On The Implications of Behavioral Decision Theory for Managerial Decision Making: Contributions and Challenges. Edited by Gerard P. Hodgkinson and William H. Starbuck. Oxford University Press, 2008. http://dx.doi.org/10.1093/oxfordhb/9780199290468.003.0015.

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17

Takemura, Kazuhisa. Behavioral Decision Theory: Psychological and Mathematical Descriptions of Human Choice Behavior. Springer, 2016.

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18

Takemura, Kazuhisa. Behavioral Decision Theory: Psychological and Mathematical Descriptions of Human Choice Behavior. Springer, 2022.

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19

Takemura, Kazuhisa. Behavioral Decision Theory: Psychological and Mathematical Descriptions of Human Choice Behavior. Springer Singapore Pte. Limited, 2021.

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20

Rauhut, Heiko. Game Theory. Edited by Wim Bernasco, Jean-Louis van Gelder, and Henk Elffers. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199338801.013.7.

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Game theory analyzes strategic decision making of multiple interdependent actors and has become influential in economics, political science, and sociology. It provides novel insights in criminology because it is a universal language for the unification of the social and behavioral sciences and allows deriving new hypotheses from fundamental assumptions about decision making. This chapter first reviews foundations and assumptions of game theory, basic concepts, and definitions. This includes applications of game theory to offender decision making in different strategic interaction settings: simultaneous and sequential games and signaling games. Next, the chapter illustrates the benefits (and problems) of game theoretical models for the analysis of crime and punishment by providing an in-depth discussion of the “inspection game.” The formal analytics are described, point predictions are derived, and hypotheses are tested by laboratory experiments. The chapter concludes with a discussion of theoretical and practical implications of results from the inspection game.
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21

Dowling, Michael, and Brian Lucey. The Future of Behavioral Finance. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190269999.003.0030.

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The future of behavioral finance necessitates that the research areas of behavioral corporate finance and investor psychology develop richer models of financial decision-making behavior. Behavioral corporate finance requires expanding the focus from chief executive officer characteristics to those of the entire top management team, and also involves greater understanding of organizational theory. A greater focus is needed on cross-cultural factors and how they interact with behavioral influences. Investor psychology needs a more comprehensive theory of the drivers of investor behavior and better data. This need is strong for investor sentiment research, which might offer the most potential to advance understanding of psychological influences on asset pricing. The chapter expands on these ideas and discusses an overall context of the future philosophical development of behavioral finance and the inevitable push for greater openness, replicability, and reliability in research.
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22

Bickel, Warren, E. Terry Mueller, James MacKillop, and Richard Yi. Behavioral-Economic and Neuroeconomic Perspectives on Addiction. Edited by Kenneth J. Sher. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199381678.013.015.

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Behavioral economics construes addiction as a pattern of pathological decisions favoring consumption of drugs versus healthy reinforcers. This chapter introduces basic behavioral-economic concepts and reviews results from operant laboratory studies, purchase task studies, and clinical studies that validate the concepts’ utility in addiction research. Research and theory about the economic significance of the delay to receipt of a chosen commodity (delay discounting) is reviewed. Additionally, research bearing on the validity of the competing neurobehavioral decision systems hypothesis, a neuroeconomic theory, is considered by drawing on a diversity of data including functional magnetic resonance imaging (fRMI) and genetic studies. This new theory proposes that addiction is due to hyperactive impulsive and hypoactive executive systems in the brain. Future directions for research and treatment are reviewed.
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23

Eisenberg, Melvin A. Behavioral Economics and Contract Law. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199731404.003.0011.

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Chapter 11 concerns behavioral economics. Classical contract law was implicitly based on a rational-actor or expected-utility model of psychology. Under this model, actors who make decisions in the face of uncertainty rationally maximize their expected utility, with all future benefits and costs properly discounted to present value. Rationality, in turn, requires that when consequences are uncertain their likelihood must be evaluated without violating the basic rules of probability theory. Within the last half century a great body of theoretical and empirical work in cognitive psychology, known as behavioral economics, has shown that due to the limits of cognition the expected-utility model often diverges from the actual psychology of choice. Some of the decision-making rules that people use yield systematic errors, and other aspects of peoples’ cognitive capabilities are also systematically defective.
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24

Behavioral Game Theory: Experiments in Strategic Interaction (The Roundtable Series in Behavioral Economics). Princeton University Press, 2003.

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25

Taliaferro, Jeffrey W. Prospect Theory and Foreign Policy Analysis. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190846626.013.281.

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Prospect theory is one of the most influential behavioral theories in the international relations (IR) field, particularly among scholars of security studies, political psychology, and foreign policy analysis. Developed by Israeli psychologists Daniel Kahneman and Amos Tversky, prospect theory provides key insights into decision making under conditions of risk and uncertainty. For example, most individuals are risk averse to secure gains, but risk acceptant to avoid losses (loss aversion). In addition, most people value items they already posses more than they value items they want to acquire (endowment effect), and tend to be risk averse if they perceive themselves to be facing gains relative to their reference point (risk propensity). Prospect theory has generated an enormous volume of scholarship in IR, which can be divided into two “generations”. The first generation (1990–1999) sought to establish prospect theory’s plausibility in the “real world” by testing hypotheses derived from it against subjective expected-utility theory or rational choice models of foreign policy decision making. The second generation (2000–present) began to incorporate concepts associated with prospect theory and related experimental literature on group risk taking into existing mid-level theories of IR and foreign policy behavior. Two substantive areas covered by scholars during this period are coercive diplomacy and great power intervention in the periphery as they relate to loss aversion. Both generations of prospect theory literature suffer from conceptual and methodological difficulties, mainly around the issues of reference point selection, framing, and preference reversal outside laboratory settings.
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26

Milliken, Christopher, Ehsan Nikbakht, and Andrew Spieler. Traditional Asset Allocation Securities. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190269999.003.0020.

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Asset allocation models have evolved in complexity with the development of modern portfolio theory, but they continue to operate under the assumption of investor rationality and other assumptions that do not hold in the real world. For this reason, academics and industry professionals make efforts to understand the behavioral biases of decision makers and the implications these biases have on asset allocation strategies. This chapter reviews the building blocks of asset allocation, involving stocks, bonds, real estate, and cash. It also examines the history and theory behind two of the most popular portfolio management strategies: mean-variance optimization and the Black-Litterman Model. Finally, the chapter examines five common behavioral biases that have direct implications for asset allocation: familiarity, status quo, framing, mental accounting, and overconfidence. Each behavioral bias discussion contains examples, warning signs, and steps to correct the emotional or cognitive errors in decision making.
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27

Angner, Erik. Course in Behavioral Economics. Palgrave Macmillan, 2016.

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28

Ricciardi, Victor. The Financial Psychology of Players, Services, and Products. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190269999.003.0002.

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This chapter provides an overview of the emerging cognitive and emotional themes of behavioral finance that influence individual behavior. The behavioral finance perspective of risk incorporates both qualitative (subjective) and quantitative (objective) aspects of the decision-making process. An emerging subject of research interest and investigation in behavioral finance is the inverse (negative) relation between perceived risk and expected return (perceived return). The chapter highlights important topics such as representativeness, framing, anchoring, mental accounting, control issues, familiarity bias, trust, worry, and regret theory. It also examines the role of negative affective reactions on financial decisions. A host of biases that depend on specific aspects of the financial product or investment service influence the judgment and decision-making process of most financial players.
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29

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach. Taylor & Francis Group, 2002.

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30

Bayesian Methods: A Social and Behavioral Sciences Approach. Chapman & Hall/CRC, 2002.

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31

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition. Taylor & Francis Group, 2014.

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32

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition. Taylor & Francis Group, 2014.

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33

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition. Taylor & Francis Group, 2014.

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34

Hudson, Todd E. Bayesian Data Analysis for the Behavioral and Neural Sciences: Non-Calculus Fundamentals. University of Cambridge ESOL Examinations, 2021.

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35

Hudson, Todd E. Bayesian Data Analysis for the Behavioral and Neural Sciences: Non-Calculus Fundamentals. University of Cambridge ESOL Examinations, 2021.

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36

Hudson, Todd E. Bayesian Data Analysis for the Behavioral and Neural Sciences: Non-Calculus Fundamentals. University of Cambridge ESOL Examinations, 2021.

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37

Bhattacharya, Sukanto. Utility, Rationality and Beyond: From Behavioral Finance to Informational Finance (Ph. D. Dissertation at Bond University, Australia). Hexis, 2005.

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38

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach, Second Edition (Chapman & Hall/Crc Statistics). 2nd ed. Chapman & Hall/CRC, 2007.

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39

A Course in Behavioral Economics. Red Globe Press, 2020.

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40

A Course in Behavioral Economics. Springer, 2016.

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41

Modern Developments in Behavioral Economics: Social Science Perspectves on Choice and Decision. World Scientific Publishing Company, 2007.

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42

Giannoccaro, Ilaria. Behavioral Issues in Operations Management: New Trends in Design, Management, and Methodologies. Springer, 2013.

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43

Apel, Robert, and Daniel S. Nagin. Perceptual Deterrence. Edited by Wim Bernasco, Jean-Louis van Gelder, and Henk Elffers. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199338801.013.6.

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In theory, deterrence is a behavioral response to an individual’s perceptions about the certainty and/or severity of criminal justice sanctions. The perceptual underpinnings of compliance with the law are therefore of long-standing interest in perceptual deterrence scholarship. This chapter provides an overview of the broad scope of this scholarship. After reviewing the basic perceptual elements of crime decision-making models, attention turns to a consideration of research on the determinants of sanction perceptions. First, the overall accuracy of sanction perceptions with respect to existing statutes and penalties is discussed. Second, the degree to which an individual’s sanction perceptions are updated in response to his or her experiences as a successful or unsuccessful offender is examined. Third, the manifold research traditions speaking to situational influences on sanction perceptions are surveyed. Emerging dual-process models inspired by research on judgment and decision making are finally considered.
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44

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists (Statistics for Social and Behavioral Sciences). Springer, 2007.

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45

Giannoccaro, Ilaria. Behavioral Issues in Operations Management: New Trends in Design, Management, and Methodologies. Springer, 2015.

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46

Chu, C. Y. Cyrus. Population Dynamics. Oxford University Press, 1998. http://dx.doi.org/10.1093/oso/9780195121582.001.0001.

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Population Dynamics fills the gap between the classical supply-side population theory of Malthus and the modern demand-side theory of economic demography. In doing so, author Cyrus Chu investigates specifically the dynamic macro implications of various static micro family economic decisions. Holding the characteristic composition of the macro population to always be an aggregate result of some corresponding individual micro decision, Chu extends his research on the fertility-related decisions of families to an analysis of other economic determinations. Within this framework, Chu studies the income distribution, attitude composition, job structure, and aggregate savings and pensions of the population. While in some cases a micro-macro connection is easily established under regular behavioral assumptions, in several chapters Chu enlists the mathematical tool of branching processes to determine the connection. Offering a wealth of detail, this book provides a balanced discussion of background motivation, theoretical characterization, and empirical evidence in an effort to bring about a renewal in the economic approach to population dynamics. This welcome addition to the research and theory of economic demography will interest professional economists as well as professors and graduate students of economics.
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47

Castleman, Benjamin L. 160-Character Solution: How Text Messages and Other Behavioral Strategies Can Improve Education. Johns Hopkins University Press, 2015.

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48

160-Character Solution: How Text Messages and Other Behavioral Strategies Can Improve Education. Johns Hopkins University Press, 2015.

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49

Menkel-Meadow, Carrie. Negotiation: A Very Short Introduction. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/actrade/9780198851400.001.0001.

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Abstract Everyone negotiates. Whenever we need someone else to help us achieve our goals we negotiate. This book introduces theories of negotiation, including assumptions of scarcity and competition, or possibilities of integration of parties’ needs and interests and problem-solving approaches to achieve both joint and individual gain. The book provides analysis and guidance on how to assess what is at stake in each negotiation and how contexts vary to help us choose appropriate behaviors, including different strategies and tactics for achieving both joint and individually preferred outcomes. Illustrations and examples come from historical, diplomatic, international, legal, employment, relationship, business, family, and everyday negotiations. Drawing on the varied disciplines of game theory, economics, psychology, sociology, law, political science, and anthropology, negotiation is described as a multi-disciplinary process, involving both cognitive analysis and behavior. The book looks at modern applications of negotiation in complex multi-party, multi-issue situations, with cultural, racial, class, ethnic, and gender differences and use of negotiation processes in new dispute resolution and transactional settings, like mediation, facilitation, deliberative democracy, decision making, and restorative justice. Challenges to good negotiations in ethical dilemmas, legal enforcement, and behavioral barriers are explored.
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