Retail Deliveries by Drones: How Will Logistics Networks Change?

• 成果类型: Article
• 署名作者: Perera, Sandun; Dawande, Milind; Janakiraman, Ganesh; Mookerjee, Vijay
• 署名单位: Nevada System of Higher Education (NSHE); University of Nevada Reno; University of Texas System; University of Texas Dallas
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.13217
• 发表日期: 2020
• 页码: 2019-2034
• 关键词: traveling salesman problem; vehicle-routing problem; optimization; OPERATIONS; UAVs; DESIGN; price; truck; MODEL

摘要

Emerging technologies such as drone delivery services enable retailers to cost-effectively offer unprecedented delivery speed and adaptable delivery lead times using dedicated aerial vehicles for individual orders. A natural and important question arises: What is the impact of a drone delivery system (DDS) on a retailer's extant logistics parameters, for example, the number of customer-facing delivery centers (last-mile warehouses) it uses and delivery lead times it offers? On the one hand, the ability to reach customers faster than through traditional means argues for more centralization of delivery services. On the other hand, more decentralization can allow the retailer to offer hitherto unheard-of delivery lead times and thereby spur demand. We show that, as drone technology matures and becomes more cost-effective, delivery networks will become increasingly decentralized while delivering products at faster speeds. While perfect delivery customization-under which each demand location is offered a customized delivery guarantee-is theoretically feasible under a DDS, it may not be practical to implement such a finely differentiated delivery strategy. Instead, we show that retailers can recover a significant portion of the profit under this ideal scenario by offering limited delivery-time customization, that is, partitioning the market into a few delivery zones and offering the best feasible delivery guarantee for each zone. In physically congested metropolitan markets, where retailers may be forced to operate with only a few delivery centers, it may be optimal to operate a DDS by offering delivery guarantees that are inferior to the best possible in order to throttle unprofitable demand. In such markets, the effectiveness of limited delivery-time customization increases as the extent of physical congestion increases.