Maximin Safety: When Failing to Lose is Preferable to Trying to Win

TL;DR

This paper introduces maximin safety, a decision rule prioritizing avoiding worst outcomes, explaining certain behavioral effects and providing a normative framework similar to minimax regret.

Contribution

It proposes maximin safety as a novel decision rule, with axiomatic foundations and behavioral explanations, expanding understanding of decision-making strategies.

Findings

Maximin safety explains the decoy effect in preferences.

Maximin safety shares behavioral foundations with minimax regret.

Provides an axiomatic characterization of maximin safety preferences.

Abstract

We present a new decision rule, \emph{maximin safety}, that seeks to maintain a large margin from the worst outcome, in much the same way minimax regret seeks to minimize distance from the best. We argue that maximin safety is valuable both descriptively and normatively. Descriptively, maximin safety explains the well-known \emph{decoy effect}, in which the introduction of a dominated option changes preferences among the other options. Normatively, we provide an axiomatization that characterizes preferences induced by maximin safety, and show that maximin safety shares much of the same behavioral basis with minimax regret.