性爱影片

（单位）

林云峰

(新加坡管理大学)

主持人

（单位）

李四杰、金子亮

（性爱影片 ）

讲座时间

2026年7月6日10点00分

讲座地点

人文社科综合楼314

性爱影片 简介

Yun Fong LIM is Lee Kong Chian Professor of Operations Management at the Lee Kong Chian School of Business, Singapore Management University (SMU). He has been a Chang Jiang Chair Professor, Lee Kong Chian Fellow, MPA Research Fellow, and 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, A*STAR, RGC-HK, and NNSF, and media coverage by Financial Times, The Business Times, CNA938, and Channel 8. His current research interests include online retailing (supply chains and fulfillment), online platforms (business model innovations), sustainable urban systems, and flexible workforce and resource management. Yun Fong serves as Senior Editor for Production and Operations Management and Associate Editor for Naval Research Logistics. He has placed his PhD students and postdoc to CUHK (Shenzhen), USTC, SUSS, and ShanghaiTech as well as supervised DBA students who lead influential firms in Asia. At SMU, Yun Fong founded the OM PhD Program. He also served as Academic Director of the Master of Science in Management (MiM) Program in 2020-2023 and played an instrumental role in elevating the program from 83rd to 41st worldwide in the Financial Times Rankings. 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 service and executive development to corporations such as Alibaba, 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.

讲座内容摘要

A significant percentage of online consumers place consecutive orders within a short duration. To reduce the total order arrangement cost, an online retailer may consolidate consecutive orders from the same consumer. We investigate how long the retailer should hold the consumer's orders before sending them to a third-party logistics provider (3PL) for processing. In this order-holding problem, we optimize the holding time to balance the total order arrangement cost and the potential delay in delivery. We model the order-holding problem as a Markov Decision Process. We show that the optimal order-holding decisions follow a threshold-type policy that is straightforward to implement: Hold any pending orders if the holding time is within a threshold, or send them to the 3PL otherwise. Whenever the consumer places a new order, the holding time is reset and the threshold is updated based on a cumulative set of her past consecutive orders in her shopping journey. Using a consumer's sequential decision model, we personalize the threshold by finding its closed-form expression in the consumer's order features. We determine the model's coefficients and evaluate the threshold-type policy using the data of the 2020 MSOM Data Driven Research Challenge. Extensive numerical experiments suggest that the personalized threshold-type policy outperforms two commonly-used benchmarks by having fewer order arrangements or shorter holding times. Furthermore, personalizing the order-holding decisions is significantly more valuable for “enterprise” customers.  Our research suggests a higher threshold for consumers who are more likely to place consecutive orders within a short duration. The consumers' demographic information has a significant effect on the threshold. Specifically, the threshold is higher for “plus” consumers, female consumers, and consumers in the age group of 16-25. The threshold for tier-1 cities is lower than that for tier-2 to tier-4 cities but higher than that for tier-5 cities.