Pandora's Box Reopened: Robust Search and Choice Overload

Abstract

This paper revisits the classic Pandora's box problem, studying a decision-maker (DM) who seeks to minimize her maximal ex-post regret. The DM decides how many options to explore and in what order, before choosing one or taking an outside option. We characterize the regret-minimizing search rule and show that the likelihood of opting out often increases as more options become available for exploration. We show that this ``choice overload" is driven by the DM's fear of ``selection error" -- the regret from searching the wrong options -- suggesting that steering choice via recommendations or cost heterogeneity can mitigate regret and encourage search.