Topic: Last Mile Innovation: The Case of the Locker Alliance Network

Speaker: Lv Guodong, School of Business, Hong Kong University of Science and Technology

Time: March 29, 2024, 9AM

Venue: EMS 513

Organizer: Management Science and Engineering Department

Abstract: The Locker Alliance Network (LAN), a cutting-edge initiative under Singapore's Smart Nation vision, aims to revolutionize parcel pickup processes. This government-led project seeks to implement two major changes in Singapore's urban logistics: (i) establishing an open-access facility for all Logistic Service Providers (LSPs), and (ii) enhancing the last mile delivery efficiency of each LSP, thereby reducing their operational footprint. This research investigates the impact of locker network design on the delivery efficiency of individual LSPs and explores strategies for the government to construct an inclusive network for all LSPs. Using the LAN pilot program data, we show that the currently deployed locker network surprisingly reduces last mile delivery efficiency. This inefficiency is not attributed to poor network design or the mode of delivery but rather to low customer adoption rate -- an improvement in adoption rate enhances delivery efficiency, especially in the mixed-trip mode. Our research emphasizes the significance of customer engagement and the adoption rate of locker-pickup within the population as key factors for the success of the LAN. The government's role in facilitating this engagement, alongside optimizing locker network design and delivery operations, is crucial for realizing the full potential of this smart nation initiative.

Guest Bio: Lu Guodong, an assistant professor in the Department of Operations Management at the Hong Kong University of Science and Technology. His research focuses on data-driven operational decision-making and optimization, and applies it to areas such as supply chain management, smart city operations, and sustainable development. His main research methods include online optimization, robust optimization, empirical analysis, and machine learning. He has collaborated with government agencies such as the Infocomm Media Development Authority of Singapore, Singapore Post, and Didi Chuxing, as well as corporations, to solve relevant operational management problems in industry. His research findings have been published in journals such as MS/OR/MSOM. He obtained his PhD in Operations Management from the National University of Singapore, and his PhD thesis won the 2019 INFORMS George B. Dantzig Best Dissertation Award.