Academic journal article International Journal of Electronic Commerce Studies

Interaction Commerce, a Technological Architecture Focused on Recommender System

Academic journal article International Journal of Electronic Commerce Studies

Interaction Commerce, a Technological Architecture Focused on Recommender System

Article excerpt

1.INTRODUCTION

With the advent of social media, particularly of social networks, people spend increasingly more time in front of some kind of device in order to communicate and exchange information, ideas, or data pertaining to their work and also personal environment1, 2 We are truly witnessing a quick and radical change in how the Internet is used. This change also affects e-commerce platforms that are almost forced to adapt and meet their customers' new needs. This innovative current has benefited the consumer but also the seller who now has the opportunity to increase its volume of sales3.

Currently companies prefer not to use the old general and massive advertising techniques but prefer to establish a relationship with their customers in order to offer recommendations specifically aimed at their buying habits. Before deciding on the purchase of a product, customers try to establish contact with other users paying attention: for example, to comments left, preferably someone known to them. In short, the customers are becoming participating content writers in order to communicate and exchange opinions4. According to many other researchers, social activities may lead to increased sales due to the creation of stable relations of trust among the actors3, 5.

In the last few years, the above-mentioned phenomenon has been expanding considerably, becoming a significant opportunity for theoretical and practical research. This phenomenon is called social commerce and refers to e-commerce activities that lead to online purchases, using social media and Web 2.06. This system enhances the potential of e-commerce, increasing the user's opportunity for social relations through the use of social media. Some experts in this sector and researchers consider e-commerce as collaboration amongst customers aimed at finalizing purchases in an environment similar to a social network2, 7 Others offer an interpretation stemming from the sellers' viewpoint and define it as collaboration of sellers to achieve business advantage8, 9 Even though the literature offers many definitions of this phenomenon, all concur that the most important difference between e-commerce and social commerce is that, in e-commerce, users decide alone on their purchases, while in social commerce they interact with the community thanks to the tools offered by the platform.

In parallel with studies on e-commerce and later on social commerce, particular attention was given by the researchers to the topic of recommender systems. These systems have evolved as much as the phenomenon of social commerce because their purposes is to offer personalized support to filter and order the large amount of information available, according to the customers' interests and tastes. The recommender system can be defined as a system that guides the user through a large number of options to allow him or her to find elements to suit its needs and interests10. It provides a platform that can guarantee finding the right knowledge, within the right context, for the right person, and in the right amount11.

The scope of this paper, as well as the reason for its writing, is to offer a description of social commerce architecture. According to the results of current studies, there is a lack of articles that provide an innovative structure that could be implemented for social commerce, one that could help researchers and those who need to implement such a platform. To go into detail, this work would like to demonstrate how this approach can, among other advantages, help to better optimize how all the components work together. On this subject, it describes the advantages that a recommender system can obtain when inserted into a social environment. If, in fact, on one hand, it is possible to build a valid recommender system by knowing the ratings (implicit or explicit) that a user gives to a product within the social commerce platform; on the other hand, the recommender systems can be utilized from the first time the user accesses the platform, by acquiring from the social network its tastes and aptitudes. …

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