Career: Reputation with Limited Information, Theory and Applications

职业：信息、理论和应用有限的声誉

• 批准号: 2337566
• 负责人: Di Pei
• 金额: $ 46.24万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-03-15 至 2029-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2337566&HistoricalAwards=false
• 关键词: Career; Reputation; Limited; Information; Theory

This award funds research in economic theory. The principal investigator plans to use game theory to understand the circumstances under which economic agents (such as firms and politicians) have incentives to take socially desirable actions in long-term relationships. The research seeks to answer the following specific questions. First, does a firm have incentives to supply a high quality product when the market has limited information about its past behavior? Second, what kind of information should online platforms provide to consumers in order to motivate sellers to build a reputation for supplying high quality product? Third, can researchers deliver robust predictions on firms’ behaviors that can be tested using data?The principal investigator will answer these questions by using novel methods in the theory of repeated games, reputation, and learning. The first project analyzes how consumers’ ability to observe other consumers’ choices (i.e., observational learning) affects each seller’s incentives to build a reputation for supplying high quality. Consumers’ information is summarized by a stochastic network, which determines whether a consumer’s action can be observed by each of their successors. The results identify network structures under which observational learning strengthens reputational incentives as well as those that cause reputational incentives to break down. The second project analyzes situations where consumers do not have detailed information about the firm’s history. The analysis sheds light on the effects of long social memories, the coarsening of market information, the heterogeneous quality of consumer information on the seller’s incentives to sustain a reputation, and on consumers’ welfare. The third project analyzes situations where long-lived agents (e.g., sellers, politicians) can manipulate their past records, for example, they can erase signals from their records at some cost. This is motivated by applications to online platforms in which sellers can bribe consumers in exchange for taking down the negative reviews. The main result shows that, when sellers are sufficiently long-lived, their returns from building reputations are entirely wiped out, even when the market suspects that they may erase records with a low probability. It also shows that players’ incentives to sustain cooperation do not necessarily increase with their expected lifespans; and this finding stands in contrast to the standard predictions found in the literature on repeated games.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项资助经济理论研究。首席研究员计划使用博弈论来理解经济主体（如公司和政治家）在长期关系中采取社会可取行动的动机。本研究试图回答以下具体问题。第一，当市场对其过去行为的信息有限时，企业是否有提供高质量产品的动机？第二，为了激励卖家建立提供高质量产品的声誉，在线平台应该向消费者提供什么样的信息？第三，研究人员能否对企业的行为做出可靠的预测，并通过数据进行检验？首席研究员将通过使用重复博弈、声誉和学习理论中的新方法来回答这些问题。第一个项目分析消费者如何观察其他消费者的选择（即，观察学习）影响每个卖家建立高质量声誉的动机。消费者的信息由一个随机网络总结，该网络决定消费者的行为是否可以被他们的每个后继者观察到。研究结果确定了网络结构，观察学习加强声誉激励，以及那些导致声誉激励打破。第二个项目分析了消费者没有关于公司历史的详细信息的情况。分析揭示了长期的社会记忆的影响，粗化的市场信息，异质质量的消费者信息对卖方的激励，以维持声誉，和消费者的福利。第三个项目分析了长寿命代理（例如，卖家，政客）可以操纵他们过去的记录，例如，他们可以以一定的代价从他们的记录中删除信号。这是由于在线平台的应用程序，卖家可以贿赂消费者以换取删除负面评论。主要结果表明，当卖家的寿命足够长时，他们建立声誉的回报会完全消失，即使市场怀疑他们可能会以较低的概率删除记录。这也表明，参与者保持合作的动机并不一定随着他们的预期寿命而增加，这一发现与文献中关于重复游戏的标准预测相反。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。