密歇根大学助理教授黄彦:论成绩反馈在动态众包竞赛中的作用——基于结构模型的实证分析

密歇根大学助理教授黄彦:论成绩反馈在动态众包竞赛中的作用——基于结构模型的实证分析

【主讲】密歇根大学助理教授黄彦

【题目】论成绩反馈在动态众包竞赛中的作用——基于结构模型的实证分析

【时间】2017年6月22日 (周四)10:30-12:00

【地点】清华经管学院 伟伦楼453

【语言】英文 

【主办】管理科学与工程系

【简历】黄彦老师的简历

 

Yan Huang, Assistant Professor, University of Michigan:The Role of Feedback in Dynamic Crowdsourcing Contests: A Structural Empirical Analysis 

【Speaker】Yan Huang, Assistant Professor, University of Michigan

【Title】The Role of Feedback in Dynamic Crowdsourcing Contests: A Structural Empirical Analysis

【Time】June.22,Thursday,10:30-12:00

【Venue】Room 453, Weilun Building, Tsinghua SEM 

【Language 】English

【Organizer】Department of Management Science and Engineering

【Abstract】In this paper, we empirically examine the impact of performance feedback on the outcome of crowdsourcing contests. We develop a dynamic structural model to capture the economic processes that drive contest participants’ behavior, and estimate the model using a rich data set collected from a major online crowdsourcing design platform. The model captures key features of the crowdsourcing context, including a large participant pool, entries by new participants throughout the contest, exploitation (revision of previous submissions) and exploration (radically novel submissions) behaviors by contest incumbents, and the participants’ strategic choice among these entry, exploration, and exploitation decisions in a dynamic game. We find that the cost associated with exploratory actions is higher than the cost associated with exploitative actions. High-performers prefer the exploitative strategy, while low-performers tend to make fewer follow-up submissions and prefer the exploratory strategy. Using counter-factual simulations, we compare the outcome of crowdsourcing contests under alternative feedback disclosure policies and award levels. Our simulation results suggest that the full feedback policy (providing feedback throughout the contest) may not be optimal. The late feedback policy (providing feedback only in the second half of the contest) leads to a better overall contest outcome.