A Revisit to Sunk Cost Fallacy for Two-Stage Stochastic Binary Decision Making

Author:

Tian Xuecheng1,Jiang Bo2ORCID,Pang King-Wah1,Du Yuquan3,Jin Yong1,Wang Shuaian1

Affiliation:

1. Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

2. Institute of Data and Information, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China

3. La Trobe Business School, La Trobe University, Melbourne, VIC 3086, Australia

Abstract

This paper undertakes a revisit of the sunk cost fallacy, which refers to the tendency of people to persist investing resources into something, even if it is destined to have no good outcome. We emphasize that the utilities associated with different alternatives are not static for decision makers, which is exactly opposite to the traditional perspective. This paper argues that the utility of an option may change due to the choice of another option, suggesting that decisions considered irrational by the traditional analytical method, i.e., sunk cost fallacy, may be rational. We propose a novel analytical method for decision making with sunk cost when considering the utility change and validate the effectiveness of this method through mathematical modeling and computational experiments. This paper mathematically describes such decision-making problems, analyzing the impact of changes in the utilities across different alternatives on decision making with a real-world example. Furthermore, we develop a two-stage stochastic optimization model for such decision-making problems and employ the sample average approximation (SAA) method to solve them. The results from computational experiments indicate that some decisions traditionally considered irrational are, in fact, rational when the utility of an option changes as a result of choosing another option. This paper, therefore, highlights the significance of incorporating utility changes into the decision-making process and stands as a valuable addition to the literature, offering a refreshed and effective decision-making method for improved decision making.

Funder

AF Competitive Grants of The Hong Kong Polytechnic University

Publisher

MDPI AG

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