明天早上送货比今天晚送货好?客户对网络卖家物流服务质量感知中的时间效应

IF 1.1 4区 工程技术 Q4 MANAGEMENT
Fei (Sophie) Song, Yuhang Xu, Heng Chen, Kunpeng Zhang
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引用次数: 0

摘要

本研究借鉴了能量消耗理论和期望不确认理论,旨在深入探讨送货时间对顾客感知网络卖家物流服务质量(LSQ)的影响。我们推测,顾客对物流服务质量的评价会随着一天中送货时间的不同而变化(即时间效应)。在阿里巴巴超过 4200 万个订单的大样本中,混合效应有序 Logit 模型的结果证实了时间-日期效应,并且承诺的配送服务与时间-日期效应相互作用,加强了时间-日期效应。随后,研究人员利用机器学习技术量化了不同预测因素的重要性,结果表明时间效应是最重要的预测因素。这项研究揭示了一种与时间相关的新属性,为 LSQ 框架做出了贡献,并对从业人员具有重要的管理意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Better to deliver tomorrow morning than late today? The time‐of‐day effect in customer perception of online sellers' logistics service quality
Drawing upon energy depletion theory and expectancy disconfirmation theory, this study aims to zoom in on the effect of delivery time on customer perception of online seller logistics service quality (LSQ). We conjecture that customer rating of LSQ will vary depending on the delivery time in a day (i.e., the time‐of‐day effect). With a large sample consisting of more than 42 million orders from Alibaba, the results from mixed‐effects ordered logit model corroborate the time‐of‐day effect and that promised delivery service interacts with the time‐of‐day effect by strengthening it. Following that, machine learning techniques are employed to quantify the importance of the different predictors and results show that the time‐of‐day effect is the most important predictor. The study reveals a new time‐related attribute, contributes to the LSQ framework, and has important managerial implications for practitioners.
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来源期刊
CiteScore
2.40
自引率
4.30%
发文量
6
期刊介绍: Transportation Journal is devoted to the publication of articles that present new knowledge relating to all sectors of the supply chain/logistics/transportation field. These sectors include supply chain/logistics management strategies and techniques; carrier (transport firm) and contract logistics firm (3PL and 4PL) management strategies and techniques; transport economics; regulation, promotion, and other dimensions of public policy toward transport and logistics; and education.
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