A normative theory of luck
File(s)
Published version
Author(s)
Liu, Chengwei
Tsay, Chia-Jung
Type
Journal Article
Abstract
Psychologists have identified heuristics and biases that can cause people to make assumptions about factors that contribute to the success of individuals and firms, whose outcomes may have actually resulted primarily from randomness. Yet the interpretation of these biases becomes ambiguous when they represent reasonable cognitive shortcuts that offer certain advantages. This paper addresses this ambiguity by presenting four versions (weak, semi-weak, semi-strong, strong) of a normative theory of luck that integrates insights from psychology with the chance model approach to predict the circumstances under which performance non-monotonicity occurs: higher performance may not only indicate greater luck, but also lower expected merit or quality. The semi-strong version is illustrated by examining the decoupling of citations of academic publications and their impact, illuminating when higher citations indicate lower quality. We conclude by discussing the broader implications of a normative theory of luck, emphasizing strategies to address situations where people mistake luck for skill.
Date Issued
2023-11-10
Date Acceptance
2023-10-25
Citation
Frontiers in Psychology, 2023, 14
ISSN
1664-1078
Publisher
Frontiers Media S.A.
Journal / Book Title
Frontiers in Psychology
Volume
14
Copyright Statement
Copyright © 2023 Liu and Tsay. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
License URL
Identifier
http://dx.doi.org/10.3389/fpsyg.2023.1157527
Publication Status
Published
Article Number
1157527
Date Publish Online
2023-11-10