A new generalized statistical model for continuous decisions under stochastic constraints and bounded rationality

Baibing Li

Transportation Research Part B: Methodological, 2024, vol. 190, issue C

Abstract: This paper develops a new generalized statistical modeling approach for choice problems where decision-makers are faced with a continuous set of alternatives. In the existing literature, decision-making behavior is usually analyzed in the context where there are only a few discrete alternatives from which decision-makers may choose. This paper generalizes this approach and investigates the scenario where the choice set of decision-makers is a continuous space characterized by stochastic nonlinear constraints. We develop a family of choice distributions to describe decision-makers’ choice behavior for continuous decision-making problems under stochastic constraints and bounded rationality. The proposed choice distribution family provides a generic statistical modeling and prediction approach based on the underlying mechanism that drives the decision-making process to reflect a trade-off between conflicting decision criteria and resource constraints. Finally, two case studies are used to illustrate the developed method.

Keywords: Bounded rationality; Continuous choice distribution; Decision-making behavior; Stochastic constraint; Uncertainty (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.trb.2024.103096

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