{"title":"Tactical operations of service region dimensioning, bundling, and matching for on-demand food delivery services","authors":"Kaihang Zhang , Jintao Ke , Hai Wang , Yafeng Yin","doi":"10.1016/j.trc.2025.105069","DOIUrl":null,"url":null,"abstract":"<div><div>On-demand food delivery (OFD) services have experienced a significant surge in popularity in recent years, which poses various challenges for service operators. To address these challenges, this paper presents an analytical model that captures the complex interplay of the OFD system by considering factors such as adjustable service region size and order bundling. We investigate how key decision variables, namely the maximum delivery distance and bundling ratio, affect the system’s endogenous variables and two critical system performance metrics: customer total waiting time and order throughput. Our analysis yields several intriguing managerial insights. First, the maximum delivery distance has a non-monotonic impact on the customer accumulation time, delivery time, and total waiting time, and there is a “win-win” situation in which increasing the maximum delivery distance benefits both the customer total waiting time and order throughput. Second, order bundling is crucial under high customer demand to ensure adequate food delivery supply, but it is less desirable under low customer demand due to increased detour distances in delivery. We further explore strategies for minimizing customer total waiting time (by setting small service regions and bundling ratios) and order throughput (by establishing larger service regions). Recognizing the partial conflict between these two objectives, we identify a Pareto-efficient frontier that serves as a guideline for service operators in balancing these competing goals.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"174 ","pages":"Article 105069"},"PeriodicalIF":7.6000,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X25000737","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
On-demand food delivery (OFD) services have experienced a significant surge in popularity in recent years, which poses various challenges for service operators. To address these challenges, this paper presents an analytical model that captures the complex interplay of the OFD system by considering factors such as adjustable service region size and order bundling. We investigate how key decision variables, namely the maximum delivery distance and bundling ratio, affect the system’s endogenous variables and two critical system performance metrics: customer total waiting time and order throughput. Our analysis yields several intriguing managerial insights. First, the maximum delivery distance has a non-monotonic impact on the customer accumulation time, delivery time, and total waiting time, and there is a “win-win” situation in which increasing the maximum delivery distance benefits both the customer total waiting time and order throughput. Second, order bundling is crucial under high customer demand to ensure adequate food delivery supply, but it is less desirable under low customer demand due to increased detour distances in delivery. We further explore strategies for minimizing customer total waiting time (by setting small service regions and bundling ratios) and order throughput (by establishing larger service regions). Recognizing the partial conflict between these two objectives, we identify a Pareto-efficient frontier that serves as a guideline for service operators in balancing these competing goals.
期刊介绍:
Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.