PurposeE-commerce content platforms are a typical type of multi-sided platform that combines transactions with social media platforms. To solve the managerial dilemma of balancing the tension between control and autonomy of influencers' output performance, this study aims to investigate how exercising output controls through performance rewards and performance punishments impact the quantity and quality of influencers' content generation.Design/methodology/approachChoosing JD WeChat Shopping Circle as the research context and leveraging the introduction of a double commission subsidy policy and a removal policy as quasi-natural experiments, this study applied the difference-in-differences (DID) method to empirically test hypotheses.FindingsPerformance rewards incentivize influencers to generate high-quality content, but such incentivizing effects attenuate over time. Performance punishment drives influencers to generate expected pieces of high-quality content, and such safeguarding effects accentuate over time.Originality/valueThis study proposes output controls as an important form of governance mechanism in multi-sided platforms and substantiates how rewards and punishments as two facets of incentives affect complementors' behaviors. In addition, by distinguishing performance-contingent rewards from completion-contingent rewards, this study helps resolve the mixed findings on the effects of monetary rewards in the user-generated content (UGC) literature.

The sustainability of market performance of mobile applications (apps) updates is a vital goal for e-commerce firms to continuously innovate for products and functions. E-commerce firms must formulate effective app update strategies and tackle the temporal uncertainties associated with different types of app updates. However, the existing literature on app updates mainly focuses on the effects of update frequency. At the same time, scant attention has been paid to clarifying the temporal effects of different types of app updates. Accordingly, based on the framework of exploration vs. exploitation, we investigate the temporal effects of different kinds of app updates on market performance in the hypercompetitive context of online travel mobile applications. We collected data on release notes and downloads of seven Chinese online travel apps available from the Android Market from April 2013 to January 2015; conducted structured content analysis to identify different types of app updates; and adopted the feasible generalized least-squares (FGLS) estimation to test our model. We found that exploitative app updates have an instant and continuous positive impact on market performance, while explorative app updates have no significant effect in the short term but will have a positive effect on market performance in the long term. Moreover, competition intensity shortens the duration of the positive effect of exploitative app updates and delays the time that explorative app updates have to take effect. By studying the different impacts that two types of app updates have on market performance from a time dimension, this study helps resolve the mixed findings on the effects of app updates and guides e-commerce firms on how to effectively formulate app update strategies in a hypercompetitive context.