A Preliminary Study on Consumer Behavior Analytics of a Supermarket in the Chinese New Year

被引:0
作者
Lee, Kuan-Hua [1 ]
Yang, Hao-Wei [2 ]
Lo, Ming-Min [3 ]
Wu, Hsin-Hung [1 ,4 ]
机构
[1] Department of Business Administration, National Changhua University of Education
[2] Department of Marketing and Logistics Management, Chaoyang University of Technology
[3] Department of Finance, Chaoyang University of Technology
[4] Faculty of Education, State University of Malang
来源
Journal of Quality | 2025年 / 32卷 / 02期
关键词
Apriori algorithm; association rule mining; customer behavior; product bundle; supermarket;
D O I
10.6220/joq.202504_32(2).0003
中图分类号
学科分类号
摘要
Product bundling is one of the marketing strategies commonly seen in retailing industry. In addition, customers’ shopping behaviors might be different for the Chinese New Year holiday. This study uses the Apriori algorithm with support of 1%, confidence of 75%, and lift greater than 1 to analyze if member customers’ behaviors are different in terms of product bundles from a database of a supermarket in Taiwan. A fourteen-day period is split into two periods for a comparison purpose. Three rules are generated in the first period, while seventy-one rules are found in the second period, which can be further summarized into 24 general rules. The majority of product bundles in the second period include rhizomes combining other commonly purchased items such as pork, leafy vegetables, fresh eggs, flowers and fruits, mushrooms, soy products, and spices. Three general rules are exclusively found without rhizomes including combinations of coffee coupon and coffee (creamer) and mushrooms, hot pot ingredients, and flowers and fruits, and supermarket management should pay attention to not only rhizomes-related product bundles but also these three general rules without rhizomes. This empirical study provides how product bundling can be made based on the database of a supermarket in Taiwan. The process performed in this study can be further applied to other supermarkets for cross-selling, up-selling, and new product integration. © 2025, Chinese Society for Quality. All rights reserved.
引用
收藏
页码:123 / 138
页数:15
相关论文
共 46 条
[31]  
Malagueno R., Golgeci I., Fearne A., Customer categorization, relational justice and SME performance in supermarket supply chains, Supply Chain Management: An International Journal, 24, 3, pp. 417-429, (2019)
[32]  
Nguyen S.P., Deep customer segmentation with applications to a Vietnamese supermarkets’ data, Soft Computing, 25, pp. 7785-7793, (2021)
[33]  
Patron H., Gomez L., A market basket analysis of the US auto-repair industry, Journal of Business Analytics, 3, 2, pp. 79-92, (2020)
[34]  
Pillai A.R., Jolhe D.A., Market Basket Analysis: Case Study of a Supermarket, in Advances in Mechanical Engineering, pp. 727-734, (2021)
[35]  
Rokaha B., Ghale D.P., Gautam B.P., Enhancement of supermarket business and market plan by using hierarchical clustering and association mining technique, In Proceedings of the 2018 International Conference on Networking and Network Applications (Nana), Xi’an, China, pp. 384-389, (2018)
[36]  
Romeo-Arroyoa E., Mora M., Vazquez-Araujo L., Consumer behavior in confinement times: Food choice and cooking attitudes in Spain, International Journal of Gastronomy and Food Science, 21, (2020)
[37]  
Tang Y.-T., Wu H.-H., Yang H.-W., Lo M.-M., Customers’ behavior analysis before and during the Chinese New Year: An empirical study from a supermarket in Taiwan, IAENG International Journal of Applied Mathematics, 53, 2, pp. 684-689, (2023)
[38]  
Tang Y.-T., Wu H.-H., Yang H.-W., Shieh J.-I., Lo M.-M., Customer behavior analysis of the Chinese New Year from a supermarket in Taiwan, Proceedings of the 2022 2Nd International Conference on Information Technology and Education (ICIT&E), pp. 156-159, (2022)
[39]  
Tang Y.-T., Yang H.-W., Lo M.-M., Wu H.-H., A data examination on a supermarket dataset in Taiwan, The TQM Journal, 34, 6, pp. 1942-1957, (2022)
[40]  
Unvan Y.A., Market basket analysis with association rules, Communications in Statistics-Theory and Methods, 50, 7, pp. 1615-1628, (2021)