Abstract: The response time of the recovery of instant delivery disruption under the background of new retail affects the experience of high-quality users and the connectivity of various delivery components. Combining scenario response and data-driven ideas, this paper classifies disruption scenarios and generates and stores historical disruption scenarios in the preparatory stage before any disruption occurs. In the scenario response decision-making stage after the interference occurs, it introduces a hybrid approach that combines traditional scenario response methods with data-driven techniques, and develops a matching and response rule based on the historical scenario storage format, enabling rapid recovery and decision-making. To evaluate the effectiveness of the method, it conducts a simulation analysis. The parameter sensitivity analysis shows how to set the similarity threshold and the number of classifications (k) to reduce costs and improve the speed under different levels of time urgency in interference processing. These findings provide reference and suggestions for the rapid response of instant delivery interference recovery decision-making in the new retail context.

Key words: new retail, instant delivery, disruption recovery, quick response, scenario response

摘要： 新零售背景下即时配送干扰恢复的响应时长影响了高品质用户的体验和配送各环节的衔接密度。基于此，针对新零售背景下的即时配送干扰管理问题，提出了基于情景应对和数据驱动的两阶段决策方法。在干扰发生前的准备阶段，进行干扰情景的分类、历史干扰情景的生成与存储；在干扰发生后的情景应对决策阶段，以传统的情景应对方法结合数据驱动，按照历史情景存储格式给出一种匹配和应对规则，以便快速得到恢复决策方案。最后，采用模拟数据分析了方法的有效性，同时通过参数敏感度分析给出了干扰处理时间紧迫性不同情况下应该如何设置相似度阈值以及分类数量k以达到降本增速的目的，从而为新零售背景下的即时配送干扰恢复决策的快速响应提供参考和建议。

关键词: 新零售, 即时配送, 干扰恢复, 快速响应, 情景应对