Improving and Measuring the Effectiveness of Decision Analysis: Linking Decision Analysis and Behavioral Decision Research

Robert T. Clemen ()
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Robert T. Clemen: Duke University

A chapter in Decision Modeling and Behavior in Complex and Uncertain Environments, 2008, pp 3-31 from Springer

Abstract: Although behavioral research and decision analysis began with a close connection, that connection appears to have diminished over time. This chapter discusses how to re-establish the connection between the disciplines in two distinct ways. First, theoretical and empirical results in behavioral research in many cases provide a basis for crafting improved prescriptive decision analysis methods. Several productive applications of behavioral results to decision analysis are reviewed, and suggestions are made for additional areas in which behavioral results can be brought to bear on decision analysis methods in precise ways. Pursuing behaviorally based improvements in prescriptive techniques will go a long way toward re-establishing the link between the two fields. The second way to reconnect behavioral research and decision analysis involves the development of new empirical methods for evaluating the effectiveness of prescriptive techniques. New techniques, including behaviorally based ones such as those proposed above, will undoubtedly be subjected to validation studies as part of the development process. However, validation studies typically focus on specific aspects of the decision-making process and do not answer a more fundamental question. Are the proposed methods effective in helping people achieve their objectives? More generally, if we use decision analysis techniques, will we do a better job of getting what we want over the long run than we would if we used some other decisionmaking method? In order to answer these questions, we must develop methods that will allow us to measure the effectiveness of decision-making methods. In our framework, we identify two types of effectiveness. We begin with the idea that individuals typically make choices based on their own preferences and often before all uncertainties are resolved. A decision-making method is said to be weakly effective if it leads to choices that can be shown to be preferred (in a way that we make precise) before consequences are experienced. In contrast, when the decision maker actually experiences his or her consequences, the question is whether decision analysis helps individuals do a better job of achieving their objectives in the long run. A decisionmaking method that does so is called strongly effective.We propose some methods for measuring effectiveness, discuss potential research paradigms, and suggest possible research projects. The chapter concludes with a discussion of the beneficial interplay between research on specific prescriptive methods and effectiveness studies.

Keywords: Decision Maker; Analytic Hierarchy Process; Decision Analysis; Subjective Probability; Prospect Theory (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/978-0-387-77131-1_1

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