A recommender system for finding products from next door virtual manufacturer or supplier: A conceptual study

Electronic Commerce (EC) platform which is widely known as E-Marketplace handles millions of transactions over the internet. While individual users of E-Marketplace frequently interact with a shorter supply chain, Business-to-Business (B2B) users, on the other hand, manage multiple interactions with multiple layers of partners such as manufacturers or suppliers. This complexity, however, introduces problems of information overload where the users only require pertinent information based on their interests. Although recommender systems (RSs) are widely used in resolving such problems, the current RSs in the literature are still suffering several limitations, such as overspecialised recommendation, and scalability issues. Moreover, there is an urgency to introduce manufacturing companies or suppliers to online business buyers within to trade with the shortest paths between the users. This paper presents a conceptual idea of the B2B recommendation model to present potentially useful products to virtual manufacturers or suppliers to business users. The concept highlighted the effectiveness of social network information for the recommender to alleviate the current issues of RSs to support the complexity introduced in the B2B environment.