A mathematical model for product selection strategies in a recommender system

Electronic commerce (EC) has become an important support for business. EC is regarded as an efficient platform to bridge the gape between the suppliers and consumers, but how to make use of a huge amount of transaction data and identify potential customers on the internet remains a challenge for an EC company. In particular, to recommend proper products to customers, the preferences of the targeted customers need to be accurately specified and their preferences should be taken into account. This is not only to show the goodwill of the company, but also to retain the customer relation. This study aims to construct a recommender system by focusing on the on-line decision support module with respect to customers’ characteristics and supplier’s profits. For effective decision support, a mathematical model is developed so that the right product can be recommended to the right person with the best profit for the company. A numerical example is used to illustrate how this model works when both supplier’s and consumers’ desires are taken into consideration to achieve an optimal Win–Win Strategy for market expansion.