Content Contribution for Revenue Sharing and Reputation in Social Media: A Dynamic Structural Model

• 成果类型: Article
• 署名作者: Tang, Qian; Gu, Bin; Whinston, Andrew B.
• 署名单位: University of Texas System; University of Texas Austin; Arizona State University; Arizona State University-Tempe
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.2753/MIS0742-1222290203
• 发表日期: 2012
• 页码: 41-75
• 关键词: OPEN SOURCE SOFTWARE; knowledge contribution; PARTICIPATION; INFORMATION; estimators; strangers; consumers; IMPACT

摘要

This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is driven by a contributor's desire for exposure, revenue sharing, and reputation and that the contributor makes decisions dynamically.