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Decision analysis and behavioral research

TL;DR: In this article, the authors present an integrative presentation of the principles of decision analysis in a behavioral context, including sensitivity analysis, value-utility distinction, multistage inference, attitudes toward risk, and attempt to make intuitive sense out of what have been treated in the literature as endemic biases and other errors of human judgement.
Abstract: Decision analysis is a technology designed to help individuals and organizations make wise inferences and decisions. It synthesises ideas from economics, statistics, psychology, operations research, and other disciplines. A great deal of behavioural research is relevant to decision analysis; behavioural scientists have both suggested easy and natural ways to describe and quantify problems and shown the kind of errors to which unaided intuitive judgements can lead. This long-awaited book offers the4first integrative presentation of the principles of decision analysis in a behavioural context. The authors break new ground on a variety of technical topics (sensitivity analysis, the value-utility distinction, multistage inference, attitudes toward risk), and attempt to make intuitive sense out of what have been treated in the literature as endemic biases and other errors of human judgement. Those interested in artificial intelligence will find it the easiest presentation of hierarchical Bayesian inference available.
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Journal ArticleDOI
TL;DR: In this article, the authors report the results of a rigorous study of the empirical linkages between financial and social performance, finding that corporate social performance (CSP) is positively associated with prior financial performance, supporting the theory that slack resource availability and CSP are positively related.
Abstract: Strategic managers are consistently faced with the decision of how to allocate scarce corporate resources in an environment that is placing more and more pressures on them. Recent scholarship in strategic management suggests that many of these pressures come directly from sources associated with social issues in management, rather than traditional arenas of strategic management. Using a greatly improved source of data on corporate social performance, this paper reports the results of a rigorous study of the empirical linkages between financial and social performance. Corporate social performance (CSP) is found to be positively associated with prior financial performance, supporting the theory that slack resource availability and CSP are positively related. CSP is also found to be positively associated with future financial performance, supporting the theory that good management and CSP are positively related.? 1997 by John Wiley & Sons, Ltd

5,922 citations

Book
01 Jul 2002
TL;DR: In this article, a review is presented of the book "Heuristics and Biases: The Psychology of Intuitive Judgment, edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman".
Abstract: A review is presented of the book “Heuristics and Biases: The Psychology of Intuitive Judgment,” edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman.

3,642 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap, including performance errors, computational limitations, the wrong norm being applied by the experi- menter, and a different construal of the task by the subject.
Abstract: Much research in the last two decades has demon- strated that human responses deviate from the performance deemed normative according to various models of decision mak- ing and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be inter- preted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experi- menter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance er- rors are a minor factor in the gap; computational limitations un- derlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Un- expected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.

3,068 citations

Journal ArticleDOI
TL;DR: In this article, a theory of norms and normality is presented and applied to some phenomena of emotional responses, social judgment, and conversations about causes, such as emotional response to events that have abnormal causes, the generation of predictions and inferences from observations of behavior and the role of norms in causal questions and answers.
Abstract: A theory of norms and normality is presented and applied to some phenomena of emotional responses, social judgment, and conversations about causes. Norms are assumed to be constructed ad hoc by recruiting specific representations. Category norms are derived by recruiting exemplars. Specific objects or events generate their own norms by retrieval of similar experiences stored in memory or by construction of counterfactual alternatives. The normality of a stimulus is evaluated by comparing it to the norms that it evokes after the fact, rather than to precomputed expectations. Norm theory is applied in analyses of the enhanced emotional response to events that have abnormal causes, of the generation of predictions and inferences from observations of behavior, and of the role of norms in causal questions and answers. This article is concerned with category norms that represent knowledge of concepts and with stimulus norms that govern comparative judgments and designate experiences as surprising. In the tradition of adaptation level theory (Appley, 1971; Helson, 1964), the concept of norm is applied to events that range in complexity from single visual displays to social interactions. We first propose a model of an activation process that produces norms, then explore the role of norms in social cognition. The central idea of the present treatment is that norms are computed after the event rather than in advance. We sketch a supplement to the generally accepted idea that events in the stream of experience are interpreted and evaluated by consulting precomputed schemas and frames of reference. The view developed here is that each stimulus selectively recruits its own alternatives (Garner, 1962, 1970) and is interpreted in a rich context of remembered and constructed representations of what it could have been, might have been, or should have been. Thus, each event brings its own frame of reference into being. We also explore the idea that knowledge of categories (e.g., "encounters with Jim") can be derived on-line by selectively evoking stored representations of discrete episodes and exemplars. The present model assumes that a number of representations can be recruited in parallel, by either a stimulus event or an

2,910 citations

References
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Book
01 Jan 1974
TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Abstract: This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.

31,082 citations

Journal ArticleDOI
TL;DR: Three heuristics that are employed in making judgements under uncertainty are described: representativeness, availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development.

5,935 citations

Journal ArticleDOI
TL;DR: This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory to welfare economics,The theory of risky choices, transitivity of choices, and the theories of games and statistical decision functions.
Abstract: This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions The theories surveyed assume rational behavior: individuals have transitive preferences (“… if A is preferred to B, and B is preferred to C, then A is preferred to C”), choosing from among alternatives in order to “… maximize utility or expected utility” 209-item bibliography (PsycINFO Database Record (c) 2006 APA, all rights reserved)

2,197 citations


"Decision analysis and behavioral re..." refers background in this paper

  • ...decision research as a new field in psychology ( Edwards, 1954, 1961 )....

    [...]

  • ...In his 1954 Psychological Review article ( Edwards, 1954 ) he introduced the...

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Journal ArticleDOI
TL;DR: The likelihood principle emphasized in Bayesian statistics implies that the rules governing when data collection stops are irrelevant to data interpretation, and it is entirely appropriate to collect data until a point has been proven or disproven.
Abstract: Bayesian statistics, a currently controversial viewpoint concerning statistical inference, is based on a definition of probability as a particular measure of the opinions of ideally consistent people. Statistical inference is modification of these opinions in the light of evidence, and Bayes’ theorem specifies how such modifications should be made. The tools of Bayesian statistics include the theory of specific distributions and the principle of stable estimation, which specifies when actual prior opinions may be satisfactorily approximated by a uniform distribution. A common feature of many classical significance tests is that a sharp null hypothesis is compared with a diffuse alternative hypothesis. Often evidence which, for a Bayesian statistician, strikingly supports the null hypothesis leads to rejection of that hypothesis by standard classical procedures. The likelihood principle emphasized in Bayesian statistics implies, among other things, that the rules governing when data collection stops are irrelevant to data interpretation. It is entirely appropriate to collect data until a point has been proven or disproven, or until the data collector runs out of time, money, or patience.

1,387 citations


"Decision analysis and behavioral re..." refers background in this paper

  • ...Psychological Review paper ( Edwards, Lindman, and Savage, 1963 )....

    [...]

Journal ArticleDOI

1,030 citations