报告人简介：Keran Zhao is Assistant Professor in the Department of Decision and Information Systems at the C.T. Bauer School of Business, University of Houston. Keran’s research interests lie in the area of digital platform design and artificial intelligence. His research investigates the design and the user behavior of the online live streaming and healthcare community with video analysis and predictive analysis. His research has been accepted/published at top Information Systems Journals such as Information System Research (ISR, UTD24) and Journal for Association of Information Systems (JAIS, flagship journal of AIS, SCI, SSCI), as well as premier conferences such as International Conference on Information Systems (ICIS) and Americas Conference on Information Systems (AMCIS), among others. Prior to arriving at the University of Houston, Keran earned his Bachelor in IM & IS from Donghua University (2014), Master of Information Science at University of Pittsburgh (2016), and Ph.D. from University of Illinois (2021).

报告简介：Content providers in online social media platforms, particularly live streaming, often switch content categories. Despite the uniqueness and importance, there is a dearth of academic research examining the unintended effects of providers’ content switching. We study the direct and indirect spillover effects of content switching for live streamers--individuals who broadcast content through live streaming platforms. We propose a framework based on theories related to viewer flow and network effects to conceptualize the direct and indirect spillover effects of entrant streamers’ content switching on the incumbent streamers. Contrary to conventional wisdom which concerns about the negative effects on the incumbent’s viewership due to network congestion, we propose two positive spillover effects that are unique to the social media platform setting: a) the entrant streamers not just increases network congestion, but they also bring their own viewers to the new category, which benefit the incumbent streamers due to a streaming flow effect (direct spillover); and (b) the entrant streamers influences incumbent streamers’ viewer size by boosting category visibility through indirect network effects (indirect spillover). We also propose that the two spillover effects are contingent on the size of the entrant streamers’ follower base. Based on a unique observational dataset from the leading live streaming platform (Twitch.tv), particularly with viewer flows data at the streamer-session level, we first estimate that an average content switching is associated with a 1.3% net increase in direct net viewer flow from the entrant to an incumbent. And this direct spillover effect is attenuated by the size of entrant streamers’ follower base. We also estimate that an average content switching is associated with a 2.1% net increase in (indirect) net viewer flow from outside categories to an incumbent streamer. And this indirect spillover effect is reinforced by the entrant streamers’ follower base size. This study contributes to the emerging literature on the dynamics of content switching on social media platforms in the emerging context of live streaming. We discuss the managerial implications of this study for streaming strategies and platform management.