{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T14:00:22Z","timestamp":1762351222212,"version":"3.41.2"},"reference-count":44,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T00:00:00Z","timestamp":1517788800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2018,2,5]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>By employing an innovative associative classification method, this paper is able to predict a customer\u2019s pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer\u2019s 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer\u2019s satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>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\u2019s satisfaction during the online while-recommending process.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/imds-02-2017-0057","type":"journal-article","created":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T07:17:52Z","timestamp":1514531872000},"page":"188-203","source":"Crossref","is-referenced-by-count":16,"title":["A new recommendation system on the basis of consumer initiative decision based on an associative classification approach"],"prefix":"10.1108","volume":"118","author":[{"given":"Chengxin","family":"Yin","sequence":"first","affiliation":[]},{"given":"Yan","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Jianguo","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Xiaoting","family":"Ren","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"year":"1994","key":"key2020093023111645400_ref001","article-title":"Fast algorithms for mining association rules in 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