Journal of Management Information Systems · 2012 · 246 citations · 56 references
Social SciencesCommunicationEconomicsAdvertisingIncentive SystemsSocial Media MarketingBehavioral IncentivesContent AnalyticsReputationReputation ManagementRevenue SharingSocial MediaContent MonetizationDynamic Structural AnalysisMotivations For SharingSocial Media SharingStructural Dynamic AnalysisUtility Function Estimation
Content contribution decisions are dynamic and forward‑looking, with contributors anticipating future rewards. The study investigates how exposure, reputation, and revenue‑sharing incentives drive content contribution in social media. A dynamic structural model is used to infer contributors’ utility functions from observed behavior, incorporating revenue‑sharing incentives. YouTube data reveal that exposure, revenue sharing, and reputation jointly motivate dynamic content contribution decisions.
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.
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