PhD Thesis Defense Presentation: Quan Zhou
Quan Zhou, a doctoral student at 涩里番 in the Operations Management area will be presenting his thesis defense entitled:
Essays on e-commerce fulfillment optimization and consumer response to delivery policies
Thursday, April 30, 2026, at 11:00 AM
(The defense will be conducted in hybrid mode)
Student Committee Co-chairs: Prof. Mehmet Gumus
Thesis Defences are only open to members of the 涩里番 community (Students, Professors and Staff) and not the general public. Members of the 涩里番 community may participate in-person. Due to limited space availability, please contact the PhD office and we will provide you with the room number.
Abstract
The rapid growth of e-commerce has intensified pressure on online retailers to optimize their fulfillment operations while meeting increasingly diverse customer expectations for delivery. This dissertation comprises three essays that examine e-commerce fulfillment from both operational and behavioral perspectives, develop optimization frameworks, and provide empirical insights to inform the design of effective fulfillment and shipping policies.
The first essay addresses middle-mile fulfillment optimization in the presence of limited fulfillment windows. In collaboration with a North American e-commerce retailer, we formulate the problem as a stochastic dynamic program and prove that the optimal policy takes a state-dependent threshold form. To overcome computational challenges arising from the curse of dimensionality, we develop a threshold Lagrangian relaxation (tLR) heuristic and establish a performance guarantee for it. Our study highlights the benefits of multi-period fulfillment windows and the cost-reducing capabilities of the tLR policy. We conclude by emphasizing the importance of dynamic fulfillment strategies and the considerations that e-commerce companies should consider when selecting their fulfillment policies.
The second essay investigates the joint optimization of personalized delivery options and fulfillment assignments. Motivated by collaboration with an online grocery platform, we model customer choice over fulfillment options using a discrete choice framework and formulate the joint problem as a stochastic program. We propose a tractable deterministic approximation and develop a computationally efficient heuristic with a provable performance guarantee. Using real datasets collected from our industrial partner, we demonstrate the value of personalizing fulfillment options for the customers and jointly optimizing the options with fulfillment assignments. Our results show that demand management through personalized fulfillment options is prominent when customers prefer faster fulfillment and when fulfillment capacity is limited. However, an optimized fulfillment operation becomes more critical when customers are more willing to wait.
The third essay empirically examines how adjustments to contingent free-shipping thresholds influence consumer purchasing behavior. Using transaction and clickstream data from an online grocery retailer that raised its free-shipping threshold, we employ a difference-in-differences design to estimate causal effects. We find that increasing the threshold reduced consumer monthly spending by 19.4%, driven primarily by lower average cart values rather than reduced shopping frequency. Consumers also purchased fewer product varieties, shifted toward lower-priced items, and relied less on popular products. We identify two mechanisms underlying these behavioral changes: anchored goal attainability, whereby consumers anchored to the original threshold perceive the new requirement as less attainable, and heterogeneous search effort, whereby consumers facing high search costs for additional items respond more negatively to higher thresholds. Our counterfactual analysis reveals that the observed average cart value is a misleading signal for threshold-setting decisions and proposes a gradual rollout strategy to mitigate negative impacts.
Collectively, these essays contribute to the operations management literature by advancing our understanding of e-commerce fulfillment optimization and the behavioral consequences of delivery policy design. The findings offer actionable insights for online retailers seeking to balance operational efficiency with customer satisfaction in an increasingly competitive landscape.
