Sequential Selling with Sunk Cost Bias

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Authors: Association for Artificial Intelligence 2026, Yasushi Kawase, Tomohiro Nakayoshi
Cited by: 0

Abstract

We study a sequential selling problem in which an agent receives daily offers to sell a good, incurs a holding cost each day, and is subject to sunk cost bias---allowing past, irrecoverable costs to influence present decisions. We introduce a formal model parameterizing the degree of sunk cost bias and distinguish between three behavioral types: optimistic (who ignore future bias), naive (who assume their current bias persists), and sophisticated (who anticipate the evolution of their own bias). For each type, we characterize the optimal selling strategy and precisely quantify the worst-case gap in expected objective profit compared to an unbiased agent. Our results show that optimistic agents can suffer a quadratic loss in profit due to excessive waiting, naive agents perform identically to unbiased agents, and sophisticated agents limit their losses to a linear function of the time horizon. These findings clarify how different anticipations of sunk cost bias affect sequential decision-making and suggest targeted interventions to mitigate inefficiency.

Fields of Study & Subjects

Decision-Making and Behavioral Economics Optimization and Search Problems Financial Markets and Investment Strategies

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN