Books: 'Decision-making heuristics'

1

Ling, Ling. Computer based approaches to managerial decision making: Optimisation, heuristics, and simulation. Birmingham: Aston University. Aston Business School, 1995.

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2

Linda, Heath, Loyola University of Chicago. Applied Social Psychology Graduate Program., and Society for the Psychological Study of Social Issues., eds. Applications of heuristics and biases to social issues. New York: Plenum Press, 1994.

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3

Bröder, Arndt. Entscheiden mit der "adaptiven Werkzeugkiste": Ein empirisches Forschungsprogramm. Lengerich: Pabst Science Publishers, 2005.

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4

Facione, Peter A. Thinking and reasoning in human decision making: The method of argument and heuristic analysis. Milbrae, CA: California Academic Press, 2007.

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5

Bröder, Arndt. Entscheiden mit der "adaptiven Werkzeugkiste": Ein empirisches Forschungsprogramm. Lengerich: Pabst Science Publishers, 2005.

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6

Bröder, Arndt. "Take the best--ignore the rest": Wann entscheiden Menschen begrenzt rational? Lengerich: Pabst Science Publishers, 2000.

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7

Improved Decision-making in Data Mining: A Heuristic Rule Induction Approach to Decision Tree Creation and Model Selection. Saarbrücken: VDM Verlag Dr. Müller, 2008.

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8

J, Blesa María, and LINK (Online service), eds. Hybrid metaheuristics: Second international workshop, HM 2005, Barcelona, Spain, August 29-30, 2005 : proceedings. Berlin: Springer, 2005.

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9

Stützle, Thomas, Vittorio Maniezzo, and Stefan Voss. Matheuristics: Hybridizing metaheuristics and mathematical programming. New York: Springer, 2009.

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10

Dassen, Andreas. Entscheidungsunterstützung für Investitionen in flexible Fertigungssysteme (FFS): Entwicklung einer entscheidungstheoretisch motivierten Heuristik. Berlin: Köster, 1993.

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11

Houston, David Joseph. Cognitive heuristics in administrative decision making. 1987.

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12

Marek Hetmański. Rationality and Decision Making: From Normative Rules to Heuristics. BRILL, 2018.

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13

Matthews, Gerald, Jeremy Burrus, Robert Schneider, Franklin Zaromb, and Abigail Gertner. What We Know about Heuristics and Biases: Learning, Work, and Everyday Life. Taylor & Francis Group, 2023.

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14

Matthews, Gerald, Jeremy Burrus, Robert Schneider, Franklin Zaromb, and Abigail Gertner. What We Know about Heuristics and Biases: Learning, Work, and Everyday Life. Taylor & Francis Group, 2023.

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15

Matthews, Gerald, Jeremy Burrus, Robert Schneider, Franklin Zaromb, and Abigail Gertner. What We Know about Heuristics and Biases: Learning, Work, and Everyday Life. Taylor & Francis Group, 2018.

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16

Montbriand, Muriel J. DECISION HEURISTICS OF PATIENTS WITH CANCER: ALTERNATE AND BIOMEDICAL CHOICES (DECISION-MAKING, HEALTH CARE CHOICES). 1994.

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17

Heath, Linda. Applications of Heuristics and Biases to Social Issues. Springer, 2013.

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18

John, Edwards, Fred B. Bryant, Linda Heath, Emil J. Posavac, and R. Scott Tindale. Applications of Heuristics and Biases to Social Issues. Springer London, Limited, 2013.

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19

John, Edwards, Linda Heath, and R. Scott Tindale. Applications of Heuristics and Biases to Social Issues. Springer, 2013.

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20

Collins, Megan Eileen, and Thomas A. Loughran. Rational Choice Theory, Heuristics, and Biases. Edited by Wim Bernasco, Jean-Louis van Gelder, and Henk Elffers. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199338801.013.1.

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A growing body of research on offender decision making has focused on studying the use of heuristic biases, or cognitive shortcuts taken in certain situations, when offenders make decisions in the face of uncertainty. The idea is that when offenders (or any individuals) are contemplating uncertain decisions with limited time, information, or resources to make a rational choice calculus, heuristics enable a suitable decision to be reached quickly. However, often heuristics can lead to biases, errors, preference reversals, or suboptimal decisions. This chapter considers departures from rational behavior and heuristics and biases, specifically how the latter have been integrated into the study of offenders’ choice calculus. In particular, it reviews how biases and deviations from rationality have been routinely observed when studying offender decisions.

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21

McNeill, Fiona, and Carlos Andre Reis Pinheiro. Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World. Wiley & Sons, Incorporated, John, 2014.

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22

McNeill, Fiona, and Carlos Andre Reis Pinheiro. Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World. Wiley & Sons, Incorporated, John, 2014.

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23

Wadeson, Nigel. Cognitive Aspects of Entrepreneurship: Decision-Making and Attitudes to Risk. Edited by Anuradha Basu, Mark Casson, Nigel Wadeson, and Bernard Yeung. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199546992.003.0004.

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This article reviews literature on the study of the cognition of entrepreneurs, and how this affects their attitudes to risk. The review begins with the heuristics and biases approach. Various decision-making biases related to over-optimism are then considered. Following this perceived self-efficacy, intrinsic motivation and intentions-based models are discussed. Some theories dealing specifically with attitudes to risk are then covered. These include prospect theory, Kahneman and Lovalo's model of risk-taking, and Das and Teng's theory of risk horizons and future orientations. Finally, the option value and information cost approach to the analysis of entrepreneurs' decision-making is discussed. Some relevant references to culture research are also given in the conclusion.

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24

McNeill, Fiona, and Carlos Andre Reis Pinheiro. Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World. Wiley & Sons, Limited, John, 2015.

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25

Pinheiro, Carlos Andre, and Fiona McNeill. Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World. Wiley & Sons, Incorporated, John, 2014.

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26

Heuristics in Analytics: A Practical Perspective of What Influences Our Analytical World. Wiley, 2014.

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27

Peters, Ellen. Overcoming Innumeracy and the Use of Heuristics When Communicating Science. Edited by Kathleen Hall Jamieson, Dan M. Kahan, and Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.42.

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Science communication is difficult because, rather than understanding and using important, often numeric, information, lay people and experts alike resort to superficial heuristic processing of information. This chapter examines heuristic processing with respect to the power of experience, the affect heuristic, and framing effects along with their interactions with innumeracy. Recommendations are made for how to improve science communication to decrease use of heuristic processing and improve use of numeric information in risk perceptions and decision making. Based on existing evidence, science communicators should carefully identify communication goals and then choose evidence-based strategies to meet them. Evidence-based strategies include providing numeric information (as opposed to not providing it), reducing cognitive effort, increasing affective meaning, and drawing attention to key information.

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28

Anthony, Clark, Rudolf Grünig, Richard Kühn, Maude Montani, and Claire O'Dea. Solving Complex Decision Problems: A Heuristic Process. Springer Berlin / Heidelberg, 2017.

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29

Anthony, Clark, Rudolf Grünig, Richard Kühn, Maude Montani, and Claire O'Dea. Solving Complex Decision Problems: A Heuristic Process. Springer, 2018.

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30

Anthony, Clark, Rudolf Grünig, Richard Kühn, Maude Montani, and Claire O'Dea. Solving Complex Decision Problems: A Heuristic Process. Springer, 2017.

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31

Thinking and Reasoning in Human Decision Making. The California Academic Press / Insight Assessment, 2007.

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32

Pontes, Manuel C. The effects of accountability and heuristic cues on choice. 1993.

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33

Buchanan, Allen. A Richer Jus Ad Bellum. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190878436.003.0003.

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This chapter argues for greatly expanding the scope of just war theorizing. Once one realizes that institutions matter to the morality of war, the list of issues that just war theory should address expands greatly beyond the question of what are the criteria for the rightness of war-making acts. These issues include the moral evaluation of social practices regarding what is considered to be a legitimate justification for going to war, the moral evaluation of decision-makers, the moral evaluation of institutions within which decisions to go to war are made, the moral evaluation of norm/institution packages, and the proper role of heuristics versus directly action-guiding norms.

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34

Schulz, Armin W. Efficient Cognition. The MIT Press, 2018. http://dx.doi.org/10.7551/mitpress/9780262037600.001.0001.

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It is now widely accepted that many organisms (including humans) don’t just react to the world using behavioral reflexes, but also, at times, decide what to do by relying on mental representations. More specifically, the behavior of many organisms is not simply triggered by a perception of the state of their environment, but inferred using higher-level mental states downstream from their perceptual states. What is far less clear is why this is the case: what benefits does representational decision making bring to an organism, and what implications do these benefits have for the exact role that mental representations play in an organism’s decision making machinery? In my book, I provide answers to these questions. Specifically, I defend a cognitive-efficiency-based account of the evolution of mental representations, according to which a key driver of the evolution of representational decision making is the fact that mental representations can enable an organism to save a number of cognitive resources and to adjust more easily to changed environments. I then apply this account to a number of open questions in different sciences, including: when should we expect cognition to essentially involve parts of the environment? When should we expect decision making to rely on simple, satisficing heuristics? When should we expect organisms to be altruistically motivated to help others? Along the way, I also respond to concerns about the plausibility of evolutionary psychological projects more generally.

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35

Borum, Randy. Targeted Violence in Schools. Edited by Phillip M. Kleespies. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199352722.013.9.

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Though targeted attacks at schools are rare events, educators and behavioral health professionals working in those settings must evaluate threats and threatening situations when they occur. Schools across the world have experimented with different methods over time, but the threat assessment approach—particularly executed by an interdisciplinary team—has emerged as abest practice. This chapter describes the results of the Safe School Initiative, an in-depth case analysis of 37 targeted school attacks involving 41 attackers over a 25-year period, and their implications for understanding the attackers, the situations, the settings, and the targets. It addresses the continuum of threats that schools may encounter and offers some heuristics for decision making, including recent research on key indicators of intent. It concludes by emphasizing the need for schools to have incident and post-incident response plans to mitigate harm if an attack does occur.

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36

Smithson, Michael. Human Understandings of Probability. Edited by Alan Hájek and Christopher Hitchcock. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199607617.013.29.

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In this chapter developments in theories and research on human understandings and judgements of probability are examined. The concept of probability as a degree of belief and the systematic study of human probability judgements have emerged only recently, but have stimulated numerous fruitful debates about the nature of rationality, belief formation, decision-making, and uncertainty itself. The chapter begins with a review of how the connection between probability and degrees of belief was developed and elaborated to form a prescriptive framework, followed by a brief summary of debates concerning rationality and uncertainty. It then surveys models of human probability judgements based on probability weighting functions, ways in which these judgements depend on how relevant information is presented, mental shortcuts (or “heuristics”) underpinning such judgements, the extent to which probability judgements are miscalibrated, fallacies in judgements of probabilities of compound and conditional events, and debates concerning the effective communication of probabilistic information.

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37

McHoskey, John W. The group attribution error: The effect of knowledge of a prior attitude, intra-group variability, and heuristic versus systematic information processing on attributions toward group members. 1992.

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38

Boschetti, Marco Antonio, Thomas Stützle, and Vittorio Maniezzo. Matheuristics: Algorithms and Implementations. Springer International Publishing AG, 2022.

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39

Boschetti, Marco Antonio, Thomas Stützle, and Vittorio Maniezzo. Matheuristics: Algorithms and Implementations. Springer International Publishing AG, 2021.

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40

Stützle, Thomas, Stefan Voß, and Vittorio Maniezzo. Matheuristics: Hybridizing Metaheuristics and Mathematical Programming. Springer London, Limited, 2009.

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41

Héritier, Adrienne. Fritz W. Scharpf, “The Joint-Decision Trap: Lessons from German Federalism and European Integration”. Edited by Martin Lodge, Edward C. Page, and Steven J. Balla. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199646135.013.32.

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This chapter examines the joint decision trap (JDT), a decision-making mechanism developed in 1988 by Fritz Scharpf to show the link between higher level government’s decisions and the unanimous or consensus agreement of lower level governments. JDT explains how the interlinking of decision-making processes translates to suboptimal policy outcomes because higher level decisions can be blocked by each lower level actor. The chapter discusses how the concept and theory of JDT offer important insights into the dynamic of European decision-making, but by no means all of its aspects. It considers the definition of JDT and its important contribution to theoretical and empirical and research on European decision-making. It then evaluates some of the arguments against JDT and the limits of its explanatory power, as well as Scharpf’s alternative to the theoretical debate between (liberal) intergovernmentalism and neofunctionalism. The chapter concludes by assessing the continuing heuristic value of JDT.

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42

Braman, Eileen. Cognition in the Courts. Edited by Lee Epstein and Stefanie A. Lindquist. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199579891.013.31.

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This chapter critically evaluates how experiments are used to study cognitive processes involved in legal reasoning. Looking at research on legal presumptions, heuristic processing, and various types of bias in judicial decision-making, the analysis considers how experiments with judges, lay participants, and other legally trained populations have contributed to our understanding of the psychological processes involved in fact-finding and legal decision-making. It explores how behavioral economics, dual process models, cultural cognition, and motivated reasoning frameworks have been used to inform experimental research. The chapter concludes with a discussion of what findings add to our normative understanding of issues like accuracy and neutrality in decision-making and a call to better integrate knowledge gained through experimental methods across disciplinary boundaries.

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43

Böschen, Stefan, Armin Grunwald, Bettina-Johanna Krings, and Christine Rösch, eds. Technikfolgenabschätzung. Nomos Verlagsgesellschaft mbH & Co. KG, 2021. http://dx.doi.org/10.5771/9783748901990.

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The complexity of socio-technological challenges and the uncertainty of decisions are both increasing. Therefore, there is a need for knowledge-based and option-oriented assessment and advice. Technology assessment (TA) can offer alternative approaches to and perspectives on current decision-making processes. This handbook provides guidance in developing new answers to the problems under investigation. It pursues three objectives. Firstly, it reflects on TA by looking at developments in TA. Secondly, it serves as a compass for orientation by providing heuristics for the systematic contextualisation of TA knowledge. Thirdly and finally, it reveals the prospects for the future development of TA. With contributions by Suzana Alpsancar, Manuel Baumann, Richard Beecroft, Alexander Bogner, Stefan Böschen, Helmut Breitmeier, Andrés Checa, Kerstin Cuhls, Bert Droste-Franke, Elisabeth Ehrensperger, Torsten Fleischer, Antje Grobe, Armin Grunwald, Reinhard Grünwald, Martina Haase, Julia Hahn, Christiane Hauser, Roger Häußling, Leonhard Hennen, Nils Heyen, Regine Kollek, Kornelia Konrad, Jürgen Kopfmüller, Bettina-Johanna Krings, Miltos Ladikas, Roh Pin Lee, Annette Leßmöllmann, Peter Letmathe, Ralf Lindner, Andreas Lösch, Jacob Manderbach, Martin Meister, Linda Nierling, Maren Paegert, Oliver Parodi, Walter Peissl, Witold-Roger Poganietz, Christine Rösch, Maximilian Roßmann, Martin Sand, Jens Schippl, Jan C. Schmidt, Christoph Schneider, Jan-Felix Schrape, Ingo Schulz-Schaeffer, Sandra Schwindenhammer, Hans-Jörg Sigwart, Mahshid Sotoudeh, Magdalena Tanzer, Helge Torgesen, Peter Wehling, Christina Wulf, Petra Zapp and Silke Zimmer-Merkle.

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44

Vogel, Jason, David N. Cherney, and Elizabeth A. Lowham. The Policy Sciences as a Transdisciplinary Approach for Policy Studies. Edited by Robert Frodeman. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198733522.013.29.

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The policy sciences tradition is a comprehensive transdisciplinary approach to develop insight into real-world decision-making, resolve problems, and improve policy outcomes. The policy sciences draw freely from the methods of many conventional disciplines, as well as offer a framework to integrate the insights from those disciplines into a more holistic understanding of any policy process. This unique approach to policy analysis uses a set of interdisciplinary frameworks and propositions as a heuristic device or “mental model” that provides a transdisciplinary instrument for integrating the insights of policy scholarship, social research, and practical experience across disciplines and substantive specialties. This facilitates the integration of knowledge and practice to improve problem solving and policy analysis by calling attention to the potentially relevant parts of any problem, decision process, or social context. This chapter reviews the history and development of the policy sciences and provides an overview of some key frameworks and propositions.

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45

Bahrami, Bahador. Making the most of individual differences in joint decisions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789710.003.0004.

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Evidence for and against the idea that “two heads are better than one” is abundant. This chapter considers the contextual conditions and social norms that predict madness or wisdom of crowds to identify the adaptive value of collective decision-making beyond increased accuracy. Similarity of competence among members of a collective impacts collective accuracy, but interacting individuals often seem to operate under the assumption that they are equally competent even when direct evidence suggest the opposite and dyadic performance suffers. Cross-cultural data from Iran, China, and Denmark support this assumption of similarity (i.e., equality bias) as a sensible heuristic that works most of the time and simplifies social interaction. Crowds often trade off accuracy for other collective benefits such as diffusion of responsibility and reduction of regret. Consequently, two heads are sometimes better than one, but no-one holds the collective accountable, not even for the most disastrous of outcomes.

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46

Lee, Juneseok, and Jonathan Keck, eds. Embracing Analytics in the Drinking Water Industry. IWA Publishing, 2022. http://dx.doi.org/10.2166/9781789062380.

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Abstract Analytics can support numerous aspects of water industry planning, management, and operations. Given this wide range of touchpoints and applications, it is becoming increasingly imperative that the championship and capability of broad-based analytics needs to be developed and practically integrated to address the current and transitional challenges facing the drinking water industry. Analytics will contribute substantially to future efforts to provide innovative solutions that make the water industry more sustainable and resilient. The purpose of this book is to introduce analytics to practicing water engineers so they can deploy the covered subjects, approaches, and detailed techniques in their daily operations, management, and decision-making processes. Also, undergraduate students as well as early graduate students who are in the water concentrations will be exposed to established analytical techniques, along with many methods that are currently considered to be new or emerging/maturing. This book covers a broad spectrum of water industry analytics topics in an easy-to-follow manner. The overall background and contexts are motivated by (and directly drawn from) actual water utility projects that the authors have worked on numerous recent years. The authors strongly believe that the water industry should embrace and integrate data-driven fundamentals and methods into their daily operations and decision-making process(es) to replace established “rule-of-thumb” and weak heuristic approaches – and an analytics viewpoint, approach, and culture is key to this industry transformation. ISBN: 9781789062373 (paperback) ISBN: 9781789062380 (eBook) ISBN: 9781789062397 (ePub)

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Books on the topic 'Decision-making heuristics'

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