ARTICLE IN PRESS Computers Operations Research I(aIm)Ill-Ill Contents lists available at Science Direct Computers Operations research ELSEVIER journalhomepagewww.elsevier.com/locate/caor A strategy-oriented operation module for recommender systems In e-commerce Hsiao-Fan Wang, Cheng-Ting Wu Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Section 2 Kuang Fu Road, Hsinchu, Taiwan 30013, ROC ARTICLE INFO ABSTRACT Electronic commerce(EC)has become an important support for business and is regarded as an efficient Keywords: ystem that connects suppliers with online users. Among the applications of EC, a recommender system (RS)is undoubtedly a popular issue to make the best recommendation to the users. Even if many approaches have been proposed to perfect the recommendation, a comprehensive module comprising of essential sub-modules of input profiles, a recommendation scheme, and an output interface of Clique-effects collaborative filtering recommendations in the Rs is still lacking. Besides, the fundamental issue of profit consideration for an C company is not stressed in general terms. Therefore, this study aims struct an rs with a strategy-oriented operation module regarding the above aspects; and with this module, an approach named clique-effects collaborative filtering(CECF) for predicting the consumers purchase behavior was proposed. Finally, we applied our proposed module to a 3C retailer in Taiwan, and promising results Scope and Purpose: This study aims to construct a comprehensive module for the recommender recommender system. By utilizing the proposed module with marketing strategies and an effective on-line interface scheme, the recommender system could emphasize not only the customer satisfaction as conventional recommender system suggested, but also the suppliers profit which shall be an important issue to an E-commerce company. Thus, a better recommendation environment could e 2010 Elsevier Ltd. All rights reserved. 1. Introduction system is urgent and essential for an EC company. By providing more helpful information to users, faster and more satisfactory Electronic commerce(EC) has been widely used by online decisions can be made: and thus, opportunities of retaining users to perform different daily activities through the Internet. customers and gaining profits are higher Online shopping is one of the popular applications among these Many EC suppliers use the recommender systems(RSs)to activities. Instead of conventional shopping. EC provides alter- out the preferences of target users so that the right products can native ways for users to get information on products such as price, be suggested [45 ] A well-established RS can add value to an EC availability, suppliers, substitutes, and even manufacturing company in several ways-(1) users can retrieve product process [39, 54]. For competitiveness, Ec companies need to information easily, (2) cross-selling for users can be enhanced, develop higher business interoperability on their electronic and (3)users' loyalty can be sustained by good service. There are market places by improving the electronic market functions numerous studies in the fields of social networks [34] and [52, 53]. The enhancement of electronic market functions could information filtering techniques [42]. In social networks, people lead to an overall reduction of interaction cost for business with similar characteristics tend to associate with each other The interoperation on all types of electronic market places [15]. use of social network structure generally allows the ec to identify among the numerous EC functions which provide so the products of likely interest to the target users based on some vailable information, it is difficult for online users to information provided by the members of the network [ 19, 28.On ick and effective decisions [48]. Facing fierce market the other hand, information filtering techniques that analyze competition and impatient users, a personalized decision support users' preferences and help EC Web sites achieve accurate product selection By filtering the information provided by the users, the techniques aim to track the purchase behavior of users Corresponding author. TeL: +88635742654x42654: fax: +88635722685 and recommend proper products. Among information filtering techniques, collaborative filtering(CF[25. 45 46 is one of the er e 2010 Elsevier Ltd. All rights reserved. doi:10.1016jc Please cite this article as: Wang H-F, Wu C-T. A strategy-oriented operation module for recommender systems in E-commerce. Computers and Operations Research(2010). doi: 10. 1016 j cor. 2010.03.011A strategy-oriented operation module for recommender systems in E-commerce Hsiao-Fan Wang , Cheng-Ting Wu Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Section 2 Kuang Fu Road, Hsinchu, Taiwan 30013, ROC article info Keywords: Electronic commerce Recommender system Marketing strategy Clique-effects collaborative filtering abstract Electronic commerce (EC) has become an important support for business and is regarded as an efficient system that connects suppliers with online users. Among the applications of EC, a recommender system (RS) is undoubtedly a popular issue to make the best recommendation to the users. Even if many approaches have been proposed to perfect the recommendation, a comprehensive module comprising of essential sub-modules of input profiles, a recommendation scheme, and an output interface of recommendations in the RS is still lacking. Besides, the fundamental issue of profit consideration for an EC company is not stressed in general terms. Therefore, this study aims to construct an RS with a strategy-oriented operation module regarding the above aspects; and with this module, an approach named clique-effects collaborative filtering (CECF) for predicting the consumer’s purchase behavior was proposed. Finally, we applied our proposed module to a 3C retailer in Taiwan, and promising results were obtained. Scope and Purpose: This study aims to construct a comprehensive module for the recommender systems. The proposed strategy-oriented operation module comprises the essential parts of a recommender system. By utilizing the proposed module with marketing strategies and an effective on-line interface scheme, the recommender system could emphasize not only the customer’s satisfaction as conventional recommender system suggested, but also the supplier’s profit which shall be an important issue to an E-commerce company. Thus, a better recommendation environment could be displayed. & 2010 Elsevier Ltd. All rights reserved. 1. Introduction Electronic commerce (EC) has been widely used by online users to perform different daily activities through the Internet. Online shopping is one of the popular applications among these activities. Instead of conventional shopping, EC provides alter￾native ways for users to get information on products such as price, availability, suppliers, substitutes, and even manufacturing process [39,54]. For competitiveness, EC companies need to develop higher business interoperability on their electronic market places by improving the electronic market functions [52,53]. The enhancement of electronic market functions could lead to an overall reduction of interaction cost for business interoperation on all types of electronic market places [15]. However, among the numerous EC functions which provide so much available information, it is difficult for online users to make quick and effective decisions [48]. Facing fierce market competition and impatient users, a personalized decision support system is urgent and essential for an EC company. By providing more helpful information to users, faster and more satisfactory decisions can be made; and thus, opportunities of retaining customers and gaining profits are higher. Many EC suppliers use the recommender systems (RSs) to find out the preferences of target users so that the right products can be suggested [45]. A well-established RS can add value to an EC company in several ways—(1) users can retrieve product information easily, (2) cross-selling for users can be enhanced, and (3) users’ loyalty can be sustained by good service. There are numerous studies in the fields of social networks [34] and information filtering techniques [42]. In social networks, people with similar characteristics tend to associate with each other. The use of social network structure generally allows the EC to identify the products of likely interest to the target users based on some information provided by the members of the network [19,28]. On the other hand, information filtering techniques that analyze users’ preferences and help EC Web sites achieve accurate product selection. By filtering the information provided by the users, the techniques aim to track the purchase behavior of users and recommend proper products. Among information filtering techniques, collaborative filtering (CF) [25,45,46] is one of the ARTICLE IN PRESS Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/caor Computers & Operations Research 0305-0548/$ - see front matter & 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.cor.2010.03.011 Corresponding author. Tel.: +886 3 5742654x42654; fax: +886 3 5722685. E-mail address: hfwang@ie.nthu.edu.tw (H.-F. Wang). Please cite this article as: Wang H-F, Wu C-T. A strategy-oriented operation module for recommender systems in E-commerce. Computers and Operations Research (2010), doi:10.1016/j.cor.2010.03.011 Computers & Operations Research ] (]]]]) ]]]–]]]