Propose a Model for Customer Purchase Decision in B2C Websites Using Adaptive Neuro-Fuzzy Inference System

Mehrbakhsh Nilashi (), Mohammad Fathian (), Mohammad Reza Gholamian () and Othman bin Ibrahim ()
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Mehrbakhsh Nilashi: Islamic Azad University, Designation = Roudsar, Iran
Mohammad Fathian: University of Science & Technology , Iran
Mohammad Reza Gholamian: University of Science & Technology , Iran
Othman bin Ibrahim: Information Systems UTM University, Malaysia

International Journal of Business Research and Management (IJBRM), 2011, vol. 2, issue 1, 1-18

Abstract: The Internet and all other electronic means have changed our way of doing business.Today, many of our businesses and transactions are conducted online. Yet consumers' marketers fight for building trust between one other. In this Paper a new model would be suggested based on Fuzzy Logical System which depicts some of the hidden relationships between the critical factors such as security, familiarity, and designing in a B2C commercial website on one hand, and the competitive factor to other competitors on other hand. Then, the impacts of these factors on purchasing decision of consumers in B2C commercial websites are extracted. Also, the factor influence in B2C trading would be analyzed. We are going to find the impact of these factors on the decision-making process of people to buy through the B2C commercial websites, and we also will analyze how these factors influence the results of the B2C trading. The study also provides a device for sellers to improve their commercial websites; in addition, it provides a helping device for on-line customers to buy through the commercial websites. Two questionnaire 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 use to analyze the generated factors in the model.

Keywords: Anfis; Fuzzy Logic; E-commerce; Trust (search for similar items in EconPapers)
JEL-codes: M0 (search for similar items in EconPapers)
Date: 2011
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