Quantity Versus Quality: Non-cooperative Production on an Online Knowledge Sharing Platform, joint with Jian Ni, Qiaowei Shen and Yan Xu, prepare to be submitted

  Online question-and-answer platforms allow consumers to learn various knowledge from crowd wisdom. Such platforms’ performance critically depends on both quantity and variety of knowledge contents contributed by the crowd. This paper studies how early-stage knowledge production outcomes influence the future crowd’s knowledge production behavior. Using a novel data set from one of the largest question-and-answer platforms, we construct measures of knowledge variety using an unsupervised learning method. We find early knowledge content has substantial effects on the quantity and variety of the knowledge content the future crowd produces on the knowledge-sharing platform. Specifically, we document that (1) longer early knowledge content decreases the quantity of future knowledge contents but increases the variety; (2) a higher number of upvotes of early knowledge content leads to more diversified future knowledge contents but does not affect the quantity. Moreover, we find that whether the early knowledge producer is an expert moderates the interrelationship between early knowledge content and future knowledge content under the same question on the platform. We discuss the implications for the question-and-answer platform’s interventions to trigger high volume and diversified knowledge content.