From Ms CHANG Ching Chen _ on November 18th, 2017
Professor Yun Fong LIM was enticed by a paradoxical observation that despite a strong growth of online and Omni-channel Retailing in South-East Asia, many companies in this industry do not make a high profit. He highlights the logistical challenges of the complex operations behind online and Omni-channel shopping. Professor Lim also describes an exciting technology that he develops with his colleagues at SMU to help retailers integrate their replenishment, allocation, and fulfillment decisions.
Lim is Associate Professor of Operations Management and Lee Kong Chian Fellow
at the Lee Kong Chian School of Business, Singapore Management University
(SMU). He is also Chang Jiang Chaired Professor and has been an NOL Fellow. Yun
Fong’s research has appeared in Operations Research, Management Science,
Manufacturing and Service Operations Management, and Production and Operations
Management. He has delivered keynote and plenary speeches in several
international conferences. In addition, his work has received funding by MOE
and A*STAR and media coverage by The Business Times, Capital 95.8, and 93.8
Live. His current research interests include
e-Commerce and Omni-channel Retailing, warehousing and fulfillment, inventory management, workforce management, and sustainable urban logistics.
Yun Fong is a recipient of the SMU Teaching Excellence Innovative Teacher Award. He teaches both undergraduate and postgraduate courses in Operations Management. He has provided consulting and executive development to corporations such as Maersk, McMaster-Carr Company, Resorts World Sentosa, Schneider Electrics, and Temasek Holdings. Yun Fong obtained both his PhD and MSc degrees in Industrial and Systems Engineering from the Georgia Institute of Technology.
Faculty profile: https://business.smu.edu.sg/faculty/profile/9512/LIM-Yun-Fong
About the Paper
Matching Supply with Demand for Online Retailing
Yun Fong LIM, Singapore Management University
Song JIU, Singapore Management University
Marcus ANG, Singapore Management University
We consider an online retailer selling multiple products to different zones over a multi-period horizon. The retailer replenishes the products from different suppliers and stores the inventory in multiple fulfillment centers (FCs) with limited capacities. We consider a joint replenishment, allocation, and fulfillment (JRAF) problem: At the start of each period, the retailer determines the replenishment quantity for each product from each supplier. The retailer then allocates the inventory to different FCs. At the end of the period, the demands are realized and the retailer chooses the FCs to satisfy the demands of each zone. The retailer's objective is to minimize the expected total cost over the selling horizon. The JRAF problem is generally intractable due to the stochastic demands, which motivates us to propose a two-stage approach to solve the problem. The first stage is to decide whether a product should be replenished from each supplier in each period (a binary decision). We formulate the JRAF problem as a target-oriented robust optimization problem, where a static decision rule is optimal. We pass the binary replenishment decisions to the second stage, where we assume a factor-based demand model and solve the JRAF problem using a linear decision rule. We obtain an adaptive and non-anticipative policy to determine the replenishment, allocation, and fulfillment quantities. A case study with a major apparel online retailer in Asia suggests that the two-stage approach reduces the total cumulative cost of the retailer's status quo policy by 36.73%. A further numerical study based on more general problem settings suggests that the two-stage approach can handle realistic problem sizes and its performance is very close to a benchmark with perfect information.
LIM, Yun Fong, JIU, Song, ANG, Marcus. Matching Supply with Demand for Online Retailing, Working Paper, Lee Kong Chian School of Business, Singapore Management University.
This paper is available at: http://www.mysmu.edu.sg/faculty/yflim/
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