BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20260420T002739EDT-0077sSRT4s@132.216.98.100 DTSTAMP:20260420T042739Z DESCRIPTION:\n\nQuan Zhou\, a doctoral student at ɬÀï·¬ in the Operations Management area will be presenting his thesis defense entitled: \n\nEssays on e-commerce fulfillment optimization and consumer response to delivery policies\n\nThursday\, April 30\, 2026\, at 11:00 AM \n (The defe nse will be conducted in hybrid mode)\n\nStudent Committee Co-chairs: Prof . Mehmet Gumus\n\nThesis Defences are only open to members of the ɬÀï·¬ c ommunity (Students\, Professors and Staff) and not the general public. Mem bers of the ɬÀï·¬ community may participate in-person. Due to limited spa ce availability\, please contact the PhD office and we will provide you wi th the room number.\n\n\nAbstract\n\nThe rapid growth of e-commerce has in tensified pressure on online retailers to optimize their fulfillment opera tions while meeting increasingly diverse customer expectations for deliver y. This dissertation comprises three essays that examine e-commerce fulfil lment from both operational and behavioral perspectives\, develop optimiza tion frameworks\, and provide empirical insights to inform the design of e ffective fulfillment and shipping policies.\n\nThe first essay addresses m iddle-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 o ptimal policy takes a state-dependent threshold form. To overcome computat ional challenges arising from the curse of dimensionality\, we develop a t hreshold Lagrangian relaxation (tLR) heuristic and establish a performance guarantee for it. Our study highlights the benefits of multi-period fulfi llment windows and the cost-reducing capabilities of the tLR policy. We co nclude by emphasizing the importance of dynamic fulfillment strategies and the considerations that e-commerce companies should consider when selecti ng their fulfillment policies.\n\nThe second essay investigates the joint optimization of personalized delivery options and fulfillment assignments. Motivated by collaboration with an online grocery platform\, we model cus tomer choice over fulfillment options using a discrete choice framework an d formulate the joint problem as a stochastic program. We propose a tracta ble deterministic approximation and develop a computationally efficient he uristic with a provable performance guarantee. Using real datasets collect ed 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 thro ugh personalized fulfillment options is prominent when customers prefer fa ster fulfillment and when fulfillment capacity is limited. However\, an op timized fulfillment operation becomes more critical when customers are mor e willing to wait.\n\nThe third essay empirically examines how adjustments to contingent free-shipping thresholds influence consumer purchasing beha vior. Using transaction and clickstream data from an online grocery retail er that raised its free-shipping threshold\, we employ a difference-in-dif ferences design to estimate causal effects. We find that increasing the th reshold reduced consumer monthly spending by 19.4%\, driven primarily by l ower average cart values rather than reduced shopping frequency. Consumers also purchased fewer product varieties\, shifted toward lower-priced item s\, and relied less on popular products. We identify two mechanisms underl ying these behavioral changes: anchored goal attainability\, whereby consu mers anchored to the original threshold perceive the new requirement as le ss 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 prop oses a gradual rollout strategy to mitigate negative impacts.\n\nCollectiv ely\, these essays contribute to the operations management literature by a dvancing our understanding of e-commerce fulfillment optimization and the behavioral consequences of delivery policy design. The findings offer acti onable insights for online retailers seeking to balance operational effici ency with customer satisfaction in an increasingly competitive landscape. \n DTSTART:20260430T150000Z DTEND:20260430T170000Z SUMMARY:PhD Thesis Defense Presentation: Quan Zhou URL:/bensadoun-school/channels/event/phd-thesis-defens e-presentation-quan-zhou-372614 END:VEVENT END:VCALENDAR