学术

【管院】2018年智慧供应链管理国际研讨会

编辑:应蓉珊 来源:管理学院 时间:2018年07月05日 访问次数:101  源地址

   近年来,随着互联网、电子商务、物联网的应用和普及,人工智能与互联网、电子商务和物联网产生的大数据深度融合,改变了人们的生活方式和思维模式,改变了传统的供应链管理模式。在消费变革、产业升级和技术创新的作用下,企业供应链的运营也从传统的链式供应链升级为网状供应体系。在大数据与人工智能交融的时代,未来供应链与互联网、物联网产生的大数据通过人工智能技术深度融合,赋予供应链大数据支撑、网络化共享、智能化协作的智慧化新特点。在大数据与人工智能的帮助下,供应链的整合能力和协同效率已经成为企业、产业乃至一国经济的核心竞争力,从供应链的历程来看,供应链已经进入现代供应链发展的新阶段,基于新技术的发展,供应链的创新和变革迫在眉睫。新现象和新事物的出现,引起实践者和学术界对未来供应链管理的商业模式和智能决策解决方案展开新一轮的探索。为了搭建国内学者和实践者与国际领先学者的学术交流平台,共同探讨智慧供应链管理方面挑战性问题以及新的研究机会,我们邀请新加坡管理大学 Yun-Fong Lim教授、香港理工大学 Pengfei Guo教授,美国Santa Clara University的Tao Li教授等国际上著名学者来交流他们最新的研究成果。
 
组织委员会主席:周伟华教授 
组织委员会副主席:王明征教授(执行),杨翼教授,陈熹教授
组织委员会成员:金庆伟副教授,马弘副教授,袁泉研究员,童昱研究员,章魏副教授,
           黄鹂强副教授,陈发动研究员
 
联系人:王明征教授  数据科学与管理工程学系
 
2018年智慧供应链管理国际研讨会日程安排
 
7月11日上午8:00-12:30, 浙大紫金港校区行政楼1102
 
主持人:王明征 教授 数据科学与管理工程学系
 

Keynote Speakers

Talk Titles

Vice Dean & Prof. Weihua Zhou 

Zhejiang University, China

Time: 825830

Open Speech

Prof. Yun-Fong Lim

Singapore Management University, Singapore

Time:  830—920

TitleMatching Supply with Demand for Online Retailing

Prof. Pengfei Guo

Polytechnic University of Technology, Hong Kong

Time:  920-1010

TitleOn the Benefit of Privatization in a Mixed Duopoly Service System

Prof. Tao Li

Santa Clara University, USA

Time:  1015-1105

Title: A Responsive-Pricing Retailer Sourcing from Competing Suppliers Facing Disruptions

Prof. Yiwei Chen

University of Cincinnati USA 

Time: 11:05-11:55

Title: On the Efficacy of Static Prices for Revenue Management in the Face of Strategic Customers

Workshop Summary

11:55-12:30

 

报告题目和摘要

Keynote Speaker 1:

Prof. Yun-Fong Lim,

Singapore Management University

 Prof. Yun-Fong Lim.png

题目: Matching Supply with Demand for Online Retailing

摘要:The aggressive expansion in e-commerce sales, which will amount to $4.058 trillion by 2020 (eMarketer, 2016), creates greater challenges to the online retailers' operations. An important characteristic that differentiates online retailers from brick-and-mortar retailers is that the former can choose which fulfillment centers (FCs) to satisfy demand. Although this flexibility improves service levels, it may increase the fulfillment cost and complicates inventory allocation and replenishments to the FCs. Therefore, we consider a joint replenishment, allocation, and fulfillment (JRAF) problem over multiple periods: In each period, an online retailer determines the replenishment quantity for each product from each supplier and then allocates the inventory to the FCs. After the demand is realized, the retailer chooses the FCs to satisfy it. The retailer’s objective is to minimize the expected total cost. The JRAF problem is generally intractable due to stochastic demand, which motivates us to develop a two-stage approach based on robust optimization to solve it. The first stage is to decide whether a product should be replenished from each supplier in each period (a binary decision). We pass these binary decisions to the second stage, where we determine the replenishment, allocation, and fulfillment quantities. A case study with a major apparel online retailer in Asia suggests that the two-stage approach can reduce the retailer’s current cost by 36.73%, demonstrating a significant value of joint optimization. A more general study confirms that the two-stage approach can handle realistic problem sizes and performs very close to a benchmark with perfect information. This is the first paper that integrates the replenishment, allocation, and fulfillment decisions in one model and our novel methodology can solve real-size problem instances (up to 1,000 products) of online retailing.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 marketplace analytics, inventory management, warehousing and fulfillment, sustainable urban logistics, and flexible workforce and resource management.

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, Temasek Holdings, and Zalora. Yun Fong obtained both his PhD and MSc degrees in Industrial and Systems Engineering from the Georgia Institute of Technology. 

作者简介:Yun Fong 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 marketplace analytics, inventory management, warehousing and fulfillment, sustainable urban logistics, and flexible workforce and resource management.

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, Temasek Holdings, and Zalora. Yun Fong obtained both his PhD and MSc degrees in Industrial and Systems Engineering from the Georgia Institute of Technology.

 

Keynote Speaker 2: 

Prof. Pengfei Guo,

 Polytechnic University of Technology

Prof. Pengfei Guo.png

 

题目: On the Benefit of Privatization in a Mixed Duopoly Service System

摘要:We consider a mixed duopoly service system in which a profit-maximizing private service provider (SP) competes against a welfare-maximizing public SP (or equivalently, a social planner). The two SPs’ service quality is differentiated and customers are heterogeneous on quality taste. We first consider the scenario where premium service is provided by the private SP and the regular one by the public SP. We show that welfare can be improved if the public SP is privatized and there exists an optimal level of privatization for the public SP in terms of welfare maximization; under some conditions, full privatization is optimal. We then extend our analysis to the other scenario where the premium service is provided by the public SP and the regular one by the private SP, and obtain similar findings. By comparing the maximal welfare of the two scenarios, we find that the latter scenario prevails when the service rate or/and the service quality of the premium service is/are relatively high. Furthermore, under the prevailed scenario, partial privatization is adopted.

作者简介:Pengfei Guo is current a full professor of the Department of Logistics and Maritime Studies, the Hong Kong Polytechnic University.  He joined Hong Kong PolyU in 2007, after having obtained his Ph.D. degree in business administration from Duke University.  He got a bachelor degree from Xi’an Jiaotong University and a master degree from Shanghai Jiaotong University.  His main research interest is on the design and control of service systems with strategic customers and he is also interested in inventory and supply chain management. He has published 30  papers and 12 of them are published on UTD journals such as Management Science, Operations Research, M&SOM and POM.  He is currently serving as a senior editor for the POM journal.

 

  

Keynote Speaker 3: 

Prof. Tao Li,

 Santa Clara University

Prof. Tao Li.png

题目: A Responsive-Pricing Retailer Sourcing from Competing Suppliers Facing Disruptions

摘要:We study a problem of a retailer who orders from two competing strategic suppliers subject to independent or correlated disruptions and responds by setting the retail price upon delivery, which we call responsive-pricing. The suppliers compete by setting their wholesale prices. We model this problem as a Stackelberg-Nash game with the suppliers as the leaders and the retailer as the follower, and obtain its equilibrium explicitly. We perform sensitivity analyses with respect to suppliers' production costs, reliabilities, and their correlation. Surprisingly, we find that an increase in the reliability of a supplier may, counter to our intuition, hurt him due to responsive-pricing. Furthermore, in contrast to literature, we find that a high disruption correlation may benefit a supplier who has a cost advantage, because of responsive-pricing, and total order quantity may increase in that correlation due to intense suppliers competition. This paper has important implications for unreliable suppliers because how reliability and correlation influence their profits depends on the retailer's pricing power and the competition intensity between the suppliers. With a responsive-pricing retailer, a supplier may not benefit from a higher reliability but may benefit from a higher correlation. This explains why a supplier that has a cost advantage may have the incentive to create a positively correlated supply network by building plants in the same geographic location with his competitor, or choosing the same tier 2 supplier to form a ``diamond-shaped supply chain strategically.

作者简介:Tao Li is an associate professor with tenure at Santa Clara University. He joined the Operations Management & Information Systems department in the Leavey School of Business at Santa Clara University in Fall 2012 as an assistant professor. Professor Li’s research interests include supply chain management with a special emphasis on sourcing strategy with unreliable suppliers, supply chain coordination, and the operations-marketing interface. His scholarship has appeared in leading academic journals such as Production and Operations Management, European Journal of Operational Research. His scholarship has been supported by the Santa Clara University Research Grant, the Leavey Research Grant, and the National Natural Science Foundation of China. He is the recipient of the Leavey School of Business Extraordinary Research Award.

Professor Li received a B.S. in material science and engineering, and a B.S. in financial management, as well as his M.S. in management science and engineering from Tianjin University (China). In addition, he received the MBA and M.S. in supply chain management from The University of Texas at Dallas, where he earned his Ph.D. in 2012.

Professor Li serves as a Senior Editor and a member of Editorial Review Board for Production and Operations Management and the treasurer of the Chinese Scholars Association for Management Science and Engineering. He has been a regular reviewer for top journals including Management Science, Operations Research, and Manufacturing & Service Operations Management.

 
Keynote Speaker 4:
 
Dr. Yiwei Chen,
 
Singapore University of Technology and Design
 
YC-photo.jpg
 
题目:On the Efficacy of Static Prices for Revenue Management in the Face of Strategic Customers
 
摘要:The present paper considers a canonical revenue management problem wherein a monopolist seller seeks to maximize revenues from selling a fixed inventory of a product to customers who arrive over time. We assume that customers are forward looking and strategize on the timing of their purchase, an empirically confirmed aspect of modern customer behavior. In the event that customers were myopic, foundational work by Gallego and Van Ryzin [1994] established that static prices are asymptotically optimal for this problem. In stark contrast, for the case where customers are forward looking, available results in mechanism design and dynamic pricing suggest a substantially more complicated prescription, and are often constrained by restrictive assumptions on customer type. 
The present paper studies this revenue management problem while assuming that customers are forward looking and strategic. We demonstrate that for a broad class of customer utility models, static prices surprisingly continue to remain asymptotically optimal in the regime where inventory and demand grow large. We further show that irrespective of regime, an optimally set static price guarantees the seller revenues that are within at least 63.2% of that under an optimal dynamic mechanism. The class of customer utility models we consider is parsimonious and enjoys empirical support. It subsumes many of the utility models considered for this problem in existing mechanism design research; we allow for multi-dimensional customer types. We also allow for a customer’s disutility from waiting to be positively correlated with his valuation. Our conclusions are thus robust and provide a simple prescription for a canonical RM problem that is near-optimal across a broad set of modeling assumptions. 
 
作者简介:Dr. Yiwei Chen is an Assistant Professor at Singapore University of Technology and Design, Pillar of Engineering Systems and Design. He will be joining the University of Cincinnati, College of Business as an Assistant Professor in August 2018. Dr. Chen received his Ph.D. from MIT Sloan School of Management. His primary research interests are revenue management and pricing, and sharing economy and innovative marketplaces. His papers have been published at Management Science, Mathematics of Operations Research, Operations Research, Production and Operations Management, Transportation Research Part B: Methodological.
 
 
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