The retail collaborative recommendations for personalized product recommendations
學年 113
學期 2
出版（發表）日期 2025-04-14
作品名稱 The retail collaborative recommendations for personalized product recommendations
作品名稱（其他語言）
著者 Shu-hsien Liao; Retno Widowati; Shang-Chen Chan
單位
出版者
著錄名稱、卷期、頁數 International Journal of Retail & Distribution Management 53(5), p.431-447
摘要 Purpose The delivery service business model is the final link in logistics for both online-and-offline (O2O) businesses. O2O business models combine e-commerce and physical commerce, using online marketing techniques to drive consumption in physical channels. Regarding collaborative recommendation, a recommendation mechanism involves two or more parties, such as logistics, retail firms and e-commerce operators, working together to obtain necessary consumer information and knowledge, such as profiles and preferences, as the basis for personalized product recommendations. Thus, delivery service and O2O purchasing integration for retail collaborative recommendations development are valuable research issues on retail and distribution management. Design/methodology/approach This study implements two-stage data mining analytics for clustering and association rules analysis, to investigate Taiwan consumers' (n = 2,169) preferences for delivery service. This process clarifies delivery service and O2O purchasing behaviours and preferences to find knowledge profiles/patterns/rules for retail collaborative recommendations. Findings This study first found several knowledge profiles/patterns/rules on our subjects. Discussion and implications for Taiwan retail and delivery service operators are also presented. The research findings show that delivery service is a valuable resource for O2O business models for retail collaborative recommendations. Originality/value Regarding originality and value, collaborative recommendation is a mechanism that seeks to understand consumers' lives and context. From the retail perspective, delivery and retail operators can join to discover valuable data on the platform through interactive data on consumer preferences for delivery service and O2O purchasing. These operators can then summarize the information to make collaborative recommendations more accurately, thus increasing O2O purchasing.
關鍵字 Retail; Delivery service; Online-and-offline; Collaborative recommendations; Data mining analytics
語言 en
ISSN 1758-6690; 0959-0552
期刊性質 國外
收錄於 SSCI
產學合作
通訊作者
審稿制度 否
國別 GBR
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/126869 )