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The Identification Level of Security, usability and Transparency Effects on Trust in B2C Commercial Websites Using Adaptive Neuro Fuzzy Inference System (ANFIS)
Mehrbakhsh Nilashi, Mohammad Fathian, Mohammad Reza Gholamian, Othman Bin Ibrahim, Alireza Khoshraftar
Pages - 126 - 149     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 2   Issue - 3    |    Publication Date - July / August 2011  Table of Contents
ANFIS, Fuzzy Logic, Trust, B2C, Electronic Commerce
This paper presents an Expert E-Commerce Trust System (EECTS), showing a possibility to confidence e-business processes by Adaptive Neuro-Fuzzy Inference Systems. The research has empirically tested the critical factors that influence an individual’s decision in the process of buying products or services online. The proposed model applies Adaptive Neuro-Fuzzy model to converging business processes to get the desired results. The system is adaptive since it uses neural network learning ability for its adaptation. The results of this study show that the security, web site design and familiarity, directly influence user’s trust in e-businesses since these factors lie the closest to the user and are deciding factors for the users and influence their decisions regarding transactions in e-commerce. These results can be of importance for vendors since they show how the customers perceive trust and which factors can directly influence their trust in a vendor and their experience with e-commerce and that the factors can play a deciding role on whether or not a customer will make a purchase. The study also provides a device for sellers to improve their commercial websites. The data was collected via interviews, surveys and B2C websites. 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. New method was compared with previous Expert E-Commerce Trust System (EECTS) that developed by Fuzzy Logic system too.
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Dr. Mehrbakhsh Nilashi
Islamic Azad University, Designation = Roudsar - Iran
Associate Professor Mohammad Fathian
Iran University Of Science And Technology - Iran
Associate Professor Mohammad Reza Gholamian
- Iran
Dr. Othman Bin Ibrahim
- Malaysia
Mr. Alireza Khoshraftar
- Malaysia