Behavior-Based Pricing in Congestion-Prone Systems
Dr. Dongyuan Zhan
UCL School of Management
University College London
Recent years have witnessed the widespread use of data to recognize repeat and new consumers to offer them different prices, i.e., behavior-based pricing (BBP). While extant research has examined the impacts of BBP on the market, most of this research ignores the congestion effect in serving each consumer. This research extends the literature by investigating the effect of promised delay (PD) on platforms and consumers and reveals the implications of BBP in competing congestion-prone systems such as DoorDash and Uber Eats. We establish a two-period dynamic game-theoretic duopoly model embedded with a queueing system, where a PD that captures the service quality is committed to consumers before the start of the sales season. We uncover that the heterogeneity of PD fundamentally affects the impacts of BBP. First, we find that BBP may benefit the platform that provides a lower service quality because of the free riding effect. Second, contrary to the conventional wisdom that BBP always reduces social welfare because of inefficient consumer switching in the second period, we reveal that, somewhat surprisingly, overall social welfare can be improved by using BBP due to the load balancing effect. Third, when PD decisions are endogenized, the practice of BBP may lower the service quality and increase the operational efficiency of the industry in the long run, reversing its benefit to consumers but improving the profits of platforms. Moreover, endogenized PD results in a Matthew effect where the platform with higher base value commits to a lower PD. BBP exacerbates this effect and further widens the quality gap between platforms.
This is joint work with Lei Fang, Ying Ouyang and Zhongbin Wang.
Dongyuan Zhan is an Assistant Professor at UCL School of Management. He studies service operations, platform design with an emphasis on strategic behavior of servers or agents whose payoff may include behavioral concerns. For example, he studies compensation for call center representatives competing for calls when there is a speed quality tradeoff; he investigates information acquisition equilibrium in MOOC peer grading platforms when the students care about both fairness and social comparison; he demonstrates how lying aversion impacts the optimal schedule in a priority queue where customers may cheat for priority. His papers have won the Second Place of CSAMSE Best Paper Award, and won twice NET Institute Summer Research Grants. He is on the Editorial Review Board of POMS. He holds a Ph.D. degree from Marshall School of Business at University of Southern California, and an MS and a BS degree from Tsinghua University.