Dissertation Defense: Kin-Ping Jeremy Wong
Candidate Name: Kin-Ping Jeremy Wong
Advisor: John Rush, Ph.D.
Title: Essays on the For-Hire Vehicle Industry
In chapter 1, I present a dynamic spatial matching game model to study the effects of matching improvements including e-hail dispatch platforms, and flexible fare and leasing schedules on drivers' income, utilization rates, and consumer surplus for passengers. With the aid of real time price and waiting time data collected from Uber, I estimate the price and waiting time elasticities on the demand side to predict the response on net demand for taxicabs under different regimes. Counterfactual results indicate that replacing 30% street hail demand with e-hail technology generates 22% earnings and 23% utilization gains for e-hail drivers relative to the computed equilibrium. Using a flexible leasing schedule increases the number of completed trips by 3,710 and improved average shift earnings by $7.2. Waiving the current e-hail booking fee and improving the network strength result in higher usage of e-hail, generating an additional consumer surplus of $0.074 per commuter per day, aggregating to $12.3 million per year. This suggests that operating taxicabs under a large, centralized matching platform network without additional surcharge can be a way to improve the taxicab market.
Chapter 2 studies the for-hire vehicle industry operated by centralized ride hailing dispatchers. Dynamic pricing in the for-hire vehicle industry has been shown to filter excess demand and incentivize supply in busy times and locations (Chen & Sheldon (2015), Hall et al (2015)). I found evidence of spatial reallocation of Uber drivers under price surges in real time data collected from Uber's application programming interface. Even though the taxicab market has begun to adopt centralized dispatch matching ("e-hail"), flexible pricing on e-hail taxi platforms was not approved until August 2018. To study the welfare effects on drivers and passengers under different pricing strategies and industrial organization in the e-hail taxi market, I extend the structural model of taxicab market presented in chapter 1. This model factors in drivers' and passengers' contribution to surplus of each other under the presence of network externalities. Using demand estimates to calibrate the model, simulation experiments suggest that under an exogenous rail-hailing platform competitor, regional pricing is more beneficial for the disadvantaged firm when e-hail market is fragmented, and social welfare is maximized when the e-hail is operated by a monopolist that adopts real time surge pricing.
Friday, April 26, 2019 at 10:30am to 12:30pm
Edward B. Bunn, S.J. Intercultural Center, 550
37th and O St., N.W., Washington