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Behavioral decision theory draws on experimental research in cognitive psychology to provide a descriptively accurate model of human behavior. It shows that people systematically violate the normative assumptions of economic rationality by miscalculating probabilities and making choices based on one-economic criteria. Behavioral decision theory's ability to capture the complexity of human judgments and choices makes it a useful foundation for improving public policy analysis, design, and implementation. Originally published in 2001, this volume showcases the research of leading scholars who are working on applications of behavioral decision theory in diverse policy settings. It is designed to give policy analysts and practitioners who are non-psychologists a clearer understanding of the complexities of human judgment and choice, and suggest how to integrate behavioral decision theoretic insights into the policy sciences. This interdisciplinary volume should be insightful and useful wherever people's judgments and choices matter for policy formulation, acceptance, and effectiveness

Much of the prior literature on arbitrator acceptability is focused primarily on demographic characteristics of arbitrators and parties. This article draws from several behavioral theories to build a single conceptual model of arbitrator acceptability. Key concepts from the theory of planned behavior, control theory, organizational justice theories, and the decision making literature are integrated into a single framework that enhances our understanding of this topic and provides useful directions for future research.

ABSTRACTIn Vroom's [45] original formulation of expectancy theory, the relationship between affect and perceived instrumentality was assumed to be linear. Others have suggested that such a relationship may be better modeled by a nonlinear, utility‐type function [30]. The current research contrasts the predictive ability of two linear and four nonlinear functions. Using four levels of McClelland's [26] needs for achievement, affiliation, and power as instrumentalities, 101 subjects provided more than 12,900 decisions on the valences of jobs in a behavioral decision‐making experiment. Nearly 40 percent of the subjects exhibited nonlinear valence functions. The results emphasize the need to specify the appropriate functional form of the valence component to enhance predictive accuracy and to prevent misspecification problems.