위치기반 주문 연관규칙 데이터 마이닝을 통한 점포기반 온라인 주문이행 전략

초록

In-store fulfillment is one of the omnichannel retailing strategies utilizing store inventories to fulfill online orders either by home delivery or allowing customers to pick them up in stores. However, implementing in-store fulfillment service for all the stores and product groups can be inefficient and costly. To address this issue, this study suggests a location-based association rule mining approach for effective in-store online order fulfillment strategy. This approach integrates association rule mining and spatial statistical methods based on the online customer order data from an omnichannel retailer in South Korea. The outcome of this research can provide store-specific customized retailing strategies to improve the effectiveness of the in-store fulfillment services.

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