The Identification Level of Security, Usability and Transparency Effects on Trust in B2C Commercial Websites Using Adaptive Neuro Fuzzy Inference System (ANFIS)

With the rapid development of Internet, the number of online customers is growing fast. This growth is supported by spreading of Internet usage around the globe. However, the question of security and trust within e-commerce has always been in doubt. This study generates general knowledge about e-commerce. This study specifically gives an overview to understand different factors about security and trust between companies and their consumers. In order to Three e-stores and their websites were examined based on the model proposed . This study also mentions that security and trust work parallel and close to each other. If a consumer feels that an online deal is secured and they can trust the seller, it leads to a confident e-commerce’s trade. The main focus of this study is to find out a suitable way to resolve security and trust issues that make e-commerce an uncertain market place for all parties. The findings of this study indicate that, character of security is regarded as the most important to building trust of B2C websites. The proposed model applies Adaptive NeuroFuzzy model to get the desired results. Two questionnaires were used in this study. The first questionnaire was developed for e-commerce experts, and the second one was designed for the customers of commercial websites. Also, Expert Choice is used to determine the priority of factors in the first questionnaire, and MATLAB and Excel are used for developing the Fuzzy rules. Finally, the Fuzzy logical kit was used to analyze the generated factors in the model.