Author List: Tang, Qian; Gu, Bin; Whinston, Andrew B.;
Journal of Management Information Systems, 2012, Volume 29, Issue 2, Page 41-76.
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.
Keywords: content contribution; contribution motivation; dynamic structural model; reputation; revenue sharing; social media; YouTube
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#245 0.238 knowledge sharing contribution practice electronic expertise individuals repositories management technical repository knowledge-sharing shared contributors novelty features peripheral share benefit seekers
#128 0.168 dynamic time dynamics model change study data process different changes using longitudinal understanding decisions develop temporal reveal associated state identifies
#131 0.141 media social content user-generated ugc blogs study online traditional popularity suggest different discourse news making anonymity marketing videos choices page
#19 0.135 content providers sharing incentive delivery provider net incentives internet service neutrality broadband allow capacity congestion revenue cost efficient enhanced provides
#75 0.106 behavior behaviors behavioral study individuals affect model outcomes psychological individual responses negative influence explain hypotheses expected theories consequences impact theory
#202 0.075 online uncertainty reputation sellers buyers seller marketplaces markets marketplace buyer price signaling auctions market premiums ebay transaction reverse literature comments
#162 0.052 structural modeling scale equation implications economies large future framework perspective propose broad scope resulting identified leading analyzed second interviews analysis