考虑消费者退货的供应链中直播与合作模式研究
Research on Live Streaming and Cooperative Models in Supply Chains Considering Consumer Returns
DOI: 10.12677/mse.2026.151019, PDF,   
作者: 王琳斐, 周建亨*:东华大学旭日工商管理学院,上海;项旭东, 桂昌厚:用友汽车信息科技(上海)股份有限公司,上海
关键词: 电商平台直播退货销售模式直播营销粉丝效应E-Commerce Platform Live-Streaming Returns Distribution Model Live-Streaming Marketing Fan Effect
摘要: 本文针对直播电商中消费者退货风险对供应链决策的影响,研究了在转售与代理两种合作模式下,品牌商与平台在“不直播、店播、达播”三种策略中的最优选择。研究发现:在转售模式下,电商平台的直播策略受到消费者满意率和退货成本的影响,当满意率较低时,不引入直播为最优策略;满意率较高时选择达人直播;满意率位于中等区间时,如果退货成本较低,则自营直播更优,反之达人直播更为有利。退货成本上升会抑制自营直播的服务努力投入,但达人直播因佣金激励仍可维持较高服务水平。在代理模式下,当平台服务费率较低时,代理模式占优,而费率较高时转售模式更利于风险分担;达人粉丝比例超过阈值时,其粉丝效应可抵消高费率影响,进一步拓展了代理模式的适用区间。
Abstract: This study investigates the impact of consumer return risk on supply chain decision in live streaming e-commerce, analyzing the optimal strategies for brands and platforms among “no live streaming”, “store-operated live streaming”, and “influencer live streaming” under both resale and agency cooperation models. The findings indicate that under the resale model, the platform’s live streaming strategy is influenced by consumer satisfaction rates and return costs: when satisfaction is low, refraining from live streaming is optimal; when satisfaction is high, influencer live streaming is preferred; and in moderate satisfaction scenarios, store-operated live streaming is more advantageous if return costs are low, whereas influencer live streaming becomes more favorable if return costs are high. Rising return costs suppress service effort inputs in store-operated live streaming, but influencer live streaming maintains higher service levels due to commission incentives. Under the agency model, the agency model dominates when the platform service fee rate is low, while the resale model is more conducive to risk sharing when the fee rate is high. When the influencer’s follower ratio exceeds a certain threshold, their fan effect can offset the impact of high service fees, thereby expanding the applicable scope of the agency model.
文章引用:王琳斐, 周建亨, 项旭东, 桂昌厚. 考虑消费者退货的供应链中直播与合作模式研究[J]. 管理科学与工程, 2026, 15(1): 181-191. https://doi.org/10.12677/mse.2026.151019

参考文献

[1] Yan, Y.C., Zhao, R.Q. and Liu, Z.B. (2018) Strategic Introduction of the Marketplace Channel under Spillovers from Online to Offline Sales. European Journal of Operational Research, 267, 65-77. [Google Scholar] [CrossRef
[2] Wang, C.X., Leng, M.M. and Liang, L.P. (2018) Choosing an Online Retail Channel for a Manufacturer: Direct Sales or Consignment? International Journal of Production Economics, 195, 338-358. [Google Scholar] [CrossRef
[3] Shen, Y.L., Willems, S.P. and Dai, Y. (2019) Channel Selection and Contracting in the Presence of a Retail Platform. Production and Operations Management, 28, 1173-1185. [Google Scholar] [CrossRef
[4] 王辰宇, 孙静春, 史思雨. 电商平台中销售模式选择与直播营销策略研究[J]. 管理工程学报, 2023, 37(5): 190-199.
[5] Yang, L., Zheng, C. and Hao, C. (2022) Optimal Platform Sales Mode in Live Streaming Commerce Supply Chains. Electronic Commerce Research, 24, 1017-1070. [Google Scholar] [CrossRef
[6] Xu, F.S., Hou, J. and Shen, H.C. (2021) A Model of Livestream Selling with the Online Influencers.
[7] 熊浩, 陈锦怡, 鄢慧丽, 等. 考虑主播特征的直播带货双渠道供应链定价与协调[J]. 管理工程学报, 2023, 37(4): 188-195.
[8] 胡娇, 李莉, 张华, 等. 考虑参照效应和主播影响力的网络直播平台动态定价决策[J]. 系统工程理论与实践, 2022, 42(3): 755-766.
[9] Davis, S. (1995) Money Back Guarantees in Retailing: Matching Products to Consumer Tastes. Journal of Retailing, 71, 7-22. [Google Scholar] [CrossRef
[10] Guo, L. (2009) Service Cancellation and Competitive Refund Policy. Marketing Science, 28, 901-917. [Google Scholar] [CrossRef
[11] 陈飔佳, 王桦, 赵娜. 考虑消费者存在投机与预期后悔行为时在线零售商引入展厅机制后的策略研究[J]. 运筹与管理, 2024, 1-8.
[12] 占济舟, 晋雅琪. 考虑退货运费险的竞争型电商平台定价策略研究[J]. 中国管理科学, 2024, 32(5): 325-334.