Technology Adoption In A Hierarchical Network: A Structural Empirical Approach [Job Market Paper]
This paper studies the technology diffusion process through input-output networks, in the setting of Python programming language. We model the adoption decision from Python 2 to Python 3 faced by package developers. Python 3 provides more advanced but incompatible features. The adoption decision involves not only updating a package's own code base, but also dealing with dependencies not yet supporting Python 3. The packages form an input-output network through such dependency requirements. With a complete dataset of package characteristics for all historical releases and user downloads, we build and estimate a dynamic model of technology adoption where each package developer makes an irreversible decision to adopt Python 3. The rich dataset enables us to draw the complete hierarchical structure of the packages, and we group packages into layers based on the dependency relationship to simplify the estimation. Then we study how decisions made by individual packages propagate through the input-output network. We also test the effect of various policies on the diffusion of Python 3 adoption through the whole network.
with Xintong Han (Concordia University),
What Makes Geeks Tick? A Study of Stack Overflow Careers
Many online platforms such as Yahoo! Answers and GitHub rely on users to voluntarily provide content. What motivates users to contribute content for free however is not well understood. In this paper, we use a revealed preference approach to show that career concerns play an important role in user contributions to Stack Overflow, the largest online Q&A community. We investigate how activities that can enhance a user’s reputation vary before and after the user finds a new job. We contrast this with activities that do not help in enhancing a user’s reputation. After finding a new job, users contribute 25% less in reputation-generating activity on Stack Overflow. By contrast, they reduce their non-reputation-generating activity by only 8% after finding a new job. These findings suggest that users contribute to Stack Overflow in part because they perceive this as a way to improve future employment prospects. We provide direct evidence against alternative explanations such as integer constraints, skills mismatch, and dynamic selection effects. The results also suggest that, beyond altruism, career concerns play an important role in explaining voluntary contributions on Stack Overflow.
with Tingting Nian (NYU Stern) and Luis Cabral (NYU Stern),
Platform Competition with Local Network Effects
This paper presents a dynamic model of price competition between two networks in which consumers value local network effects. Specifically, each consumer’s utility level depends on the number of her neighbors in the same network. Consumers in different neighborhoods choose their networks, and each network competes for new customers in different neighborhoods with a homogeneous entry price. I characterize equilibrium market structure with a combination of analytical and numerical solutions, and compare them to results from network effect models that are global, in which a consumer benefits from all other consumers in the same network. I provide sufficient conditions such that one firm dominants both local markets, as well as sufficient conditions that each firm is the dominant one in each local market.
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Multi-Market Contact in Chinese Airlines Industry
with Wenbo Wang (HKUST) and Lai Jiang (UBC)