Fuzzy rule base for consumer trustworthiness in Internet marketing: An interactive fuzzy rule classification approach

This paper deals with the notion of constructing an efficient fuzzy rule-base (FRB) as a knowledgebase (KB) from raw fuzzy rules to build a fuzzy expert system (FES) for consumer trustworthiness in Internet marketing. No business transaction can be performed without trust. Trust is not only a short-term issue but also the most significant long-term barrier for realizing the potential of Internet marketing to consumers. Due to the increasing complexity of the systems, many factors affecting trust are defined by fuzzy variables for more meaningful representation. The fuzzy responses for the factors are given by fuzzy rules for fuzzy decision making about trust. In fact, a large numbers of rules are surveyed heuristically at the initial stage where redundancy, inconsistency and conflicting rules may be present, which may lead to contradictory decision. In order to remove such problems, an interactive fuzzy rule classification approach based on a fuzzy rule similarity index is introduced with a decision-maker's satisfaction level. Finally an application of generating a fuzzy rule base for online purchasing is illustrated in order to apply the proposed methodology.