Cost-oriented recommendation model for e-commerce

Contemporary Web stores offer a wide range of products to e-customers. However, online sales are strongly dominated by a limited number of bestsellers whereas other, less popular or niche products are stored in inventory for a long time. Thus, they contribute to the problem of frozen capital and high inventory costs. To cope with this problem, we propose using information on product cost in a recommender system for a Web store. We discuss the proposed recommendation model, in which two criteria have been included: a predicted degree of meeting customer’s needs by a product and the product cost.