Sharing the proceeds from a hierarchical venture

We consider the problem of distributing the proceeds generated from a joint venture in which the participating agents are hierarchically organized. We introduce and characterize a family of allocation rules where revenue ‘bubbles up’ in the hierarchy. The family is flexible enough to accommodate the no-transfer rule where no revenue bubbles up) and the full-transfer rule (where all the revenues bubble up to the top of the hierarchy). Intermediate rules within the family are reminiscent of popular incentive mechanisms for social mobilization or multi-level marketing

Modeling the successes and failures of content-based platforms

Online platforms, such as Quora, Reddit, and Stack Exchange, provide substantial value to society through their original content. Content from these platforms informs many spheres of life—software development, finance, and academic research, among many others. Motivated by their content's powerful applications, we refer to these platforms as content-based platforms and study their successes and failures. The most common avenue of studying online platforms' successes and failures is to examine user growth. However, growth can be misleading. While many platforms initially attract a massive user base, a large fraction later exhibit post-growth failures. For example, despite their enormous growth, content-based platforms like Stack Exchange and Reddit have struggled with retaining users and generating high-quality content. Motivated by these post-growth failures, we ask: when are content-based platforms sustainable? This thesis aims to develop explanatory models that can shed light on the long-term successes and failures of content-based platforms. To this end, we conduct a series of large-scale empirical studies by developing explanatory and causal models. In the first study, we analyze the community question answering websites in Stack Exchange through the economic lens of a "market". We discover a curious phenomenon: in many Stack Exchange sites, platform success measures, such as the percentage of the answered questions, decline with an increase in the number of users. In the second study, we identify the causal factors that contribute to this decline. Specifically, we show that impression signals such as contributing user's reputation, aggregate vote thus far, and position of content significantly affect the votes on content in Stack Exchange sites. These unintended effects are known as voter biases, which in turn affect the future participation of users. In the third study, we develop a methodology for reasoning about alternative voting norms, specifically how they impact user retention. We show that if the Stack Exchange community members had voted based upon content-based criteria, such as length, readability, objectivity, and polarity, the platform would have attained higher user retention. In the fourth study, we examine the effect of user roles on the health of content-based platforms. We reveal that the composition of Stack Exchange communities (based on user roles) varies across topical categories. Further, these communities exhibit statistically significant differences in health metrics. Altogether, this thesis offers some fresh insights into understanding the successes and failures of content-based platforms