Reward or punish: investigating output controls and content generation in the multi-sided platform context

Abstract

Purpose: E-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/approach: Choosing 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. Findings: Performance 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/value: This 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.