Give rookies a chance: A trust-based institutional online supplier recommendation framework

Abstract

Trust and reputation systems are widely adopted to help online consumers choose trustworthy suppliers. One problem is that consumers are only attracted by high-reputation holders, which disadvantages the newcomers entering the market, even they provide better goods or services. In this paper, we propose an online supplier selection model in which online consumers interact with a web institution, where online suppliers are registered in, and the web institution will recommend trustworthy suppliers according to a trust-based algorithm. This new recommendation model finds a balance point between minimizing the defective interactions as well as granting opportunities to newcomers. In addition, it saves consumers' efforts to look for trustworthy suppliers. We propose a framework to help realize the new interaction mode. We also use experiments to show its effectiveness. © 2012 IFIP International Federation for Information Processing.