Motivational Ratings

• 成果类型: Article
• 署名作者: Hoerner, Johannes; Lambert, Nicolas S.
• 署名单位: Yale University; Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics; Stanford University
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.1093/restud/rdaa070
• 发表日期: 2021
• 页码: 1892-1935
• 关键词: recommender systems; career concerns; INFORMATION; BIAS; mechanisms; feedback; impacts; mixture; default

摘要

Performance evaluation (rating) systems not only provide information to users but also motivate the rated worker. This article solves for the optimal (effort-maximizing) rating within the standard career concerns framework. We prove that this rating is a linear function of past observations. The rating, however, is not aMarkov process, but rather the sum of twoMarkov processes. We showhowit combines information of different types and vintages. An increase in effort may adversely affect some (but not all) future ratings.