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

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  • Li, Baibing

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.

Suggested Citation

  • Li, Baibing, 2024. "A new generalized statistical model for continuous decisions under stochastic constraints and bounded rationality," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:transb:v:190:y:2024:i:c:s0191261524002200
    DOI: 10.1016/j.trb.2024.103096
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