A new recommendation system on the basis of consumer initiative decision based on an associative classification approach

作者：Yin, Chengxin; Guo, Yan^*; Yang, Jianguo; Ren, Xiaoting

来源：Industrial Management & Data Systems, 2018, 118(1): 188-203.

DOI：10.1108/IMDS-02-2017-0057

• Electronic commerce
• Customer satisfaction
• Recommendation system
• Initiative decision

Purpose - The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.
Design/methodology/approach - By employing an innovative associative classification method, this paper is able to predict a customer's pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer's characteristics, a product will be recommended to the potential buyer if the model predicts that he/she will click to view the product. That is, he/she is satisfied with the recommended product. Finally, the feasibility of the proposed recommendation system is validated through a Taobao shop.
Findings - The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer's satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision.
Originality/value - Conventionally, customers are considered as passive recipients of the recommendation system. However, customers are tired of the recommendation system, and they can do nothing sometimes. This paper designs a new recommendation system on the basis of consumer initiative decision. The proposed recommendation system maximizes the customer's satisfaction during the online while-recommending process.

• 出版日期2018
• 单位中国矿业大学（北京）; 成都理工大学