This dissertation contains essays that explore the incentives, mechanisms and strategies of platforms in concentrated internet markets.
The first essay studies how two-sided platforms compete and set dynamic prices. In the daily deals industry, an expected increase in competition for seller participation prompted a cross-side response by the dominant platform, Groupon, to lower prices on deal coupons sold to attract platform users. I use a dynamic model of competing daily deals platforms to investigate why we observe a larger downward price response in markets where platforms have similar shares of users. Simulations show a sharp increase in value of an additional user as cross-side competition intensifies for profits from being the future platform leader.
The second essay---coauthored with Benjamin G. Edelman---examines how competition is mediated by search intermediaries, looking at the design of search engines' own services and the effects on users' choices. We evaluate a natural experiment, and find that Google's prominent placement of its Flight Search service increased clicks on paid advertising listings while decreasing the clicks on organic search listings by a similar quantity. Empirical results and a controlled experiment links the mechanism to users' heterogeneous methods of search.
The third essay---coauthored with Michael Egesdal and Che-Lin Su---develops empirical tools for estimating dynamic discrete-choice games. We formulate the maximum-likelihood estimator as a constrained optimization problem to be solved using state-of-the-art constrained optimization solvers. Monte Carlo results show that the constrained optimization approach has improved convergence properties over other popular computational methods. / Economics
| Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/17467354 |
| Date | 17 July 2015 |
| Creators | Lai, Zhenyu |
| Contributors | Pakes, Ariel, Lewis, Gregory, Edelman, Benjamin G. |
| Publisher | Harvard University |
| Source Sets | Harvard University |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation, text |
| Format | application/pdf |
| Rights | open |
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