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DESCRIPTION:\n\nMr. Quan Zhou\, a doctoral student at 91ºÚÁÏÍø in 
 the area of Operations Management will be presenting his research proposal
  entitled:\n\nEssays on E-commerce Order Fulfillment and Customer Behavior
  \n\n \n\nMonday\, September 16\, 2024 at 10:00am – 12:00pm \n\nStudent Co
 mmittee Chair: Professor Mehmet Gumus\n\nPlease note that the presentation
  will be conducted virtually on Zoom. If you wish to attend the presentati
 on\, kindly reach out to the PhD Office for the Zoom link.\n\n\nABSTRACT: 
 \n\nThis research\, with its practical implications\, seeks to optimize sm
 all and medium-sized businesses (SMBs) operations by understanding custome
 r behavior\, designing company-consumer online shopping interfaces\, and d
 eveloping effective fulfillment policies. The optimization problems encoun
 tered in these settings often do not yield tractable optimal solutions due
  to the stochastic and multi-dimensional nature of demand. Therefore\, my 
 research takes an approximation approach.\n\nIn the first paper\, we explo
 re the optimization of the middle-mile fulfillment process in the context 
 of e-commerce. In collaboration with a prominent e-commerce retailer in No
 rth America specializing in electronics and computer products\, we develop
 ed a stochastic optimization problem to demonstrate how an efficient middl
 e mile can alleviate strain on the critical last mile\, leading to cost re
 duction and improved performance. We introduce a Lagrangian relaxation-bas
 ed policy (referred to as tLR) as a heuristic approach for fulfillment dec
 isions and prove its performance guarantee. Our study highlights the benef
 its of multi-period fulfillment windows and the cost-reducing capabilities
  of the tLR policy. We conclude by emphasizing the importance of dynamic f
 ulfillment strategies and the considerations that e-commerce companies sho
 uld consider when selecting their fulfillment policies.\n\nIn the second p
 aper\, we explore the joint optimization of the order fulfillment process 
 with personalized delivery options in the context of e-commerce. Customers
  can choose from a customized set of fulfillment options to proceed with t
 he purchase or leave with no purchase. Fulfillment assignments of purchase
 d orders are determined periodically. We model customer behavior with a ge
 neral discrete choice model and formulate the joint optimization as a stoc
 hastic dynamic program. We propose a tractable deterministic approximation
  and develop a computationally efficient heuristic with a provable perform
 ance guarantee. Using real datasets collected from our industrial partner\
 , we demonstrate the value of personalizing fulfillment options for the cu
 stomers and jointly optimizing the options with fulfillment assignments.\n
DTSTART:20240916T140000Z
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SUMMARY:PhD Research Proposal Presentation: Mr. Quan Zhou
URL:/desautels/channels/event/phd-research-proposal-pr
 esentation-mr-quan-zhou-359485
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