Theses Doctoral

The Operations and Design of Markets with Spatial and Incentive Considerations

Castro, Francisco

Technology has greatly impacted how economic agents interact in various markets, including transportation and online display advertising. This calls for a better understanding of some of the key features of these marketplaces and the development of fundamental insights for this class of problems. In this thesis, we study markets for which spatial and incentive considerations are crucial factors for their operational and economic success. In particular, we study pricing and staffing decisions for ride-hailing platforms. We also consider the contract design problem faced by Ad Exchanges when buyers' strategic behavior and inherent business constraints limit these platforms' decisions.
Firstly, we investigate the pricing challenges of ride-hailing platforms and propose a general measure-theoretical framework in which a platform selects prices for different locations, and drivers respond by choosing where to relocate based on prices, travel costs, and market congestion levels. Our results identify the revenue-maximizing pricing policy and showcase the importance of accounting for global network effects. Secondly, we develop a queuing approach to study the link between capacity and performance for a service firm with spatial operations. In a classical M/M/n queueing model, the square root safety (SRS) staffing rule balances server utilization and customer wait times. By contrast, we find that the SRS rule does not lead to such a balance in spatial systems. In these settings, a service firm should use a higher safety factor, proportional to the offered load to the power of 2/3.
Lastly, motivated by the online display advertising market where publishers frequently use transaction-contingent fees instead of up-front fees, we study the classic sequential screening problem and isolate the impact of buyers' ex-post participation constraints. We characterize the optimal selling mechanism and provide an intuitive necessary and sufficient condition under which screening is better than pooling.

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More About This Work

Academic Units
Business
Thesis Advisors
Besbes, Omar
Degree
Ph.D., Columbia University
Published Here
April 30, 2019