发表机构
INSEAD; NBS, NTU（欧洲工商管理学院; 南洋商学院，南洋理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究与印度一家LMD企业合作，通过工具变量回归发现配送代理虚假标注配送的不当行为会造成溢出性生产力损失，使次日成功配送减少1.60%、首次正确配送减少1.86%，并探讨了任务复杂性等因素的影响。
AI 中文摘要
在过去二十年里，受电子商务成功的推动，最后一英里配送（LMD）企业经历了巨大增长，实现了更快、更便宜的配送。由于利润率微薄，LMD企业力求首次配送成功，以避免重试带来的财务和声誉成本。配送代理（DAs）对LMD效率至关重要，影响着客户体验、配送成功率和生产力。然而，大多数LMD绩效提升研究侧重于流程、技术和激励措施，这些研究假定工人将遵守程序且监控工具将完美运行。但实际上，DAs会偏离预期行为，即从事不当行为，对配送效率产生负面影响，常常导致包裹退回。主要不当行为之一是虚假标注配送，即DAs故意不配送包裹并提供虚假原因。例如，即使未到达配送地址，DA也会标注“客户不在”并记录配送失败。在本研究中，我们与一家领先的印度LMD企业合作，使用工具变量回归发现，此类不当行为会导致溢出性生产力损失。该效应使次日成功配送减少1.60%，首次正确配送减少1.86%。我们讨论了不当行为与任务复杂性等因素的相关性，并就机会主义环境如何影响工人行为提供了新颖见解。
英文摘要
In the last two decades, last-mile delivery (LMD) firms have seen immense growth fueled by the success of e-commerce, leading to faster and cheaper deliveries. Operating on thin margins, LMD firms strive for successful first-time deliveries to avoid the financial and reputational costs of reattempts. Delivery Agents (DAs) are integral to LMD efficiency, influencing customer experience, delivery success, and productivity. However, most LMD performance enhancement research focuses on process, technology, and incentives, which presume workers will conform to procedures and monitoring tools will function flawlessly. Nevertheless, in practice, DAs deviate from expected behaviors, i.e., indulge in misconduct, negatively affecting delivery efficiency, often resulting in returned parcels. One of the major misconducts is fake remarked deliveries, wherein DAs intentionally do not deliver the parcels and provide a fake reason for it. For instance, even without reaching a delivery address, a DA remarks 'customer unavailable' and records a delivery failure. In this study, we collaborated with a leading Indian LMD firm and, using instrumental variable regression, find that such misconduct leads to a spillover productivity loss. This effect reduces the next day's successful deliveries by 1.60% and first-time-right deliveries by 1.86%. We discuss misconduct's correlation with factors such as task complexity and offer novel insights into how opportunistic circumstances can influence worker behavior.
