Escaping from Bad Decisions (eBook)

A Behavioral Decision-Theoretic Perspective

Kazuhisa Takemura (Autor)

eBook Download: PDF | EPUB

2021 | 1. Auflage
542 Seiten
Elsevier Science (Verlag)
978-0-12-816033-6 (ISBN)

Infos

Escaping from Bad Decisions presents a modern conceptual and mathematical framework of the decision-making process. By interpreting ordinal utility theory as normative analysis examined in view of rationality, it shows how decision-making under certainty, risk, and uncertainty can be better understood. It provides a critical examination of psychological models in multi-attribute decision-making, and evaluates the constitutive elements of 'good' and 'bad' decisions. Multi-attribute decision-making is analysed descriptively, based on the psychological model of decision-making and computer simulations of decision strategies. Finally, prescriptive examinations of multi-attribute decision-making are performed, supporting the argument that decision-making from a pluralistic perspective creates results that can help 'escape' from bad decisions. This book will be of particular interest to graduate students and early career researchers in economics, decision-theory, behavioral economics, experimental economics, psychology, cognitive sciences, and decision neurosciences. - Provides a comprehensive background to the phenomena of bad decisions, considered in their economic, psychological and cognitive aspects - Reinterprets existing theories and phenomena and proposes a new overview of decision behaviors by integrating mathematical and psychological perspectives - Adapts model-based techniques, such as mathematical model based functional magnetic resonance imaging (fMRI) using mathematical models of the decision process

Kazuhisa Takemura is a Professor of Psychology and Economics, and the Director of the Center for Decision Research at Waseda University in Japan. His research focuses on human judgment and decision making, especially modeling of preferential judgment and choice. He received the Hayashi Award (Distinguished Scholar) from The Behaviormetric Society in 2002, the Excellent Paper Award from the Japan Society of Kansei Engineering in 2003, the Book Award from Japanese Society of Social Psychology in 2010, the Book Award from Behaviormetric Society in 2016, and the Fellow Award from International Association of Applied Psychology in 2018.

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Escaping from Bad Decisions presents a modern conceptual and mathematical framework of the decision-making process. By interpreting ordinal utility theory as normative analysis examined in view of rationality, it shows how decision-making under certainty, risk, and uncertainty can be better understood. It provides a critical examination of psychological models in multi-attribute decision-making, and evaluates the constitutive elements of "e;good"e; and "e;bad"e; decisions. Multi-attribute decision-making is analysed descriptively, based on the psychological model of decision-making and computer simulations of decision strategies. Finally, prescriptive examinations of multi-attribute decision-making are performed, supporting the argument that decision-making from a pluralistic perspective creates results that can help "e;escape"e; from bad decisions. This book will be of particular interest to graduate students and early career researchers in economics, decision-theory, behavioral economics, experimental economics, psychology, cognitive sciences, and decision neurosciences. - Provides a comprehensive background to the phenomena of bad decisions, considered in their economic, psychological and cognitive aspects- Reinterprets existing theories and phenomena and proposes a new overview of decision behaviors by integrating mathematical and psychological perspectives- Adapts model-based techniques, such as mathematical model based functional magnetic resonance imaging (fMRI) using mathematical models of the decision process

Produkt-Details

• Erscheint lt. Verlag: 27.7.2021
• Sprache: englisch
• Themenwelt: Wirtschaft ► Volkswirtschaftslehre ► Mikroökonomie
• ISBN-10: 0-12-816033-0 / 0128160330
• ISBN-13: 978-0-12-816033-6 / 9780128160336