Human Behavioral Models Using Utility Theory and Prospect Theory

TL;DR

This paper reviews human behavioral models based on Utility Theory and Prospect Theory, highlighting their applications in cyber-physical systems and transportation, and discusses their theoretical implications and differences.

Contribution

It introduces and compares Utility Theory and Prospect Theory models for human decision-making in cyber-physical systems, with practical transportation examples.

Findings

Prospect Theory captures subjective decision-making under risk.

Utility Theory has been effective in resource allocation problems.

Prospect Theory offers an alternative to traditional utility models.

Abstract

Several examples of Cyber-physical human systems (CPHS) include real-time decisions from humans as a necessary building block for the successful performance of the overall system. Many of these decision-making problems necessitate an appropriate model of human behavior. Tools from Utility Theory have been used successfully in several problems in transportation for resource allocation and balance of supply and demand \citep{ben1985discrete}. More recently, Prospect Theory has been demonstrated as a useful tool in behavioral economics and cognitive psychology for deriving human behavioral models that characterize their subjective decision-making in the presence of stochastic uncertainties and risks, as an alternative to conventional Utility Theory \citep{kahneman_prospect_2012}. These models will be described in this article. Theoretical implications of Prospect Theory are also discussed. Examples will be drawn from transportation use cases such as shared mobility to illustrate these models as well as the distinctions between Utility Theory and Prospect Theory.