The purpose of this research was to create a Matching Consignees/Shippers Recommendation System (MCSRS). We used the association rule to identify product associations, the clustering technique to group shippers and consignees according to behaviors when receiving goods from similar shipper groups, and the decision tree to identify possible matches between shippers and consignees. Finally, Monte Carlo simulation was used to estimate potential revenue. The case study is a courier company in Thailand. The results showed that garment products and clothes were the products with the highest association. Shippers and consignees of these products were segmented according to recency, frequency, monetary factors, number of customers, number of product items, weight, and day. Three rules are proposed that enabled the assignment of 8 consignees to 56 shippers with an estimated increase in revenue by 36%. This approach helps decision-makers to develop an effective cost-saving new marketing, inclusive strategy quickly.

中文翻译：

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使用数据分析匹配快递服务中的收货人/发货人推荐系统

这项研究的目的是创建一个匹配的收货人/托运人推荐系统 (MCRSS)。我们使用关联规则来识别产品关联，使用聚类技术根据从相似托运人组接收货物时的行为对托运人和收货人进行分组，并使用决策树来识别托运人和收货人之间可能的匹配。最后，使用蒙特卡罗模拟来估计潜在收入。案例研究是泰国的一家快递公司。结果表明，服装产品和衣服是关联度最高的产品。这些产品的托运人和收货人根据新近度、频率、货币因素、客户数量、产品项目数量、重量和日期进行细分。提出了三项规则，可以将 8 个收货人分配给 56 个托运人，预计收入增加 36%。这种方法有助于决策者快速制定有效的节约成本的新营销包容性战略。