 Retail Deliveries by Drones: How Will Logistics Networks Change?Sandun Perera, Milind Dawande, Ganesh Janakiraman and Vijay Mookerjee Production and Operations Management, 2020, vol. 29, issue 9, 2019-2034 Abstract: 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. Date: 2020 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:29:y:2020:i:9:p:2019-2034 Ordering information: This journal article can be ordered from Access Statistics for this article Production and Operations Management is currently edited by Kalyan Singhal More articles in Production and Operations Management from Production and Operations Management Society |
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