Optimal operational policies of a dual-channel supply chain considering return service

被引:10
作者
Wang, Qiang [1 ]
Wu, Jie [1 ]
Zhao, Nenggui [2 ]
机构
[1] Univ Sci & Technol China, Int Inst Finance, Sch Management, Hefei 230026, Peoples R China
[2] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Dual-channel; Delivery distance; Consumer returns; Stackelberg game; Numerical simulation; PRICING POLICIES; STRATEGIC ANALYSIS; FLEXIBLE RETURN; QUALITY; COORDINATION; COMPETITION; DECISIONS; DEMAND; MODEL; RISK;
D O I
10.1016/j.matcom.2022.04.009
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This study investigates the operational policies in a dual-channel supply chain, in which the manufacturer can sell products online and indirectly via an independent retailer to end consumers. By using a two-stage optimization method and the Stackelberg game, we explore the optimal decisions regarding delivery distance, allowable return period, and price strategies for the manufacturer and retailer, in both a centralized and decentralized dual-channel supply chain. The results show that for any given delivery distance and allowable return period, the optimal retail price and the direct selling price in a centralized supply chain are equal to the optimal wholesale price and the direct selling price in a decentralized supply chain, respectively. Besides, the basic demand proportion of the retail channel and the demand loss proportion differences significantly affect the supply chain members' equilibrium decisions. For the retail price, there are thresholds about the delivery distance and the allowable return period. On both sides of the thresholds, the retailer's retail price has different structural properties. Interestingly, the total profit of the retailer and the manufacturer in the decentralized supply chain is always lower than that in the centralized supply chain. Our research provides some management implications for enterprises. For example, the manufacturer could raise the direct selling price for consumers who are close to the warehouse, but offer a lower price for consumers who are farther away. (c) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:414 / 437
页数:24
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