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Propose a Model for Customer Purchase Decision in B2C Websites Using Adaptive Neuro-Fuzzy Inference System
Mehrbakhsh Nilashi, Mohammad Fathian, Mohammad Reza Gholamian, Othman bin Ibrahim
Pages - 1 - 18     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 2   Issue - 1    |    Publication Date - March / April 2011  Table of Contents
Anfis, Fuzzy Logic, E-commerce, Trust
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.
CITED BY (3)  
1 Nilashi, M., bin Ibrahim, O., & Ithnin, N. (2014). Multi-criteria collaborative filtering with high accuracy using higher order singular value decomposition and Neuro-Fuzzy system. Knowledge-Based Systems, 60, 82-101.
2 Safa, N. S. (2014). Modelling of multi-dimensional loyalty in electronic commerce (Doctoral dissertation, University Malaya).
3 Alqatan, S., Singh, D., & ahmad, K. (2012).study on success factors to enhance customer trust for mobile commerce in small and medium-sized tourism enterprises (smtes)--a conceptual model. journal of theoretical & applied information technology, 46(2).
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 C.Centeno, “Building Security and Consumer Trust in Internet Payments”, the potential of “soft” measures – Background Paper No. 7, Electronic Payment Systems Observatory(ePSO).
2 R.Pauline. “The Evolution of Trust in Businessto-Besiness E-Commerce”.Copyright 2006,Idea Group.
3 J.Benoit, John.I, “Consumer TRUST in E-commerce”, Copyright © 2006, Idea Group Inc.,distributing in print or electronic forms without written permission of IGI is prohibited.
4 O.Andrea, Jana.D. “Trust in E-Technologies”. Copyright © 2006, Idea Group Inc., distributing in print or electronic forms without written permission of IGI is prohibited.
5 L.Jo, Lisa .M. “How Does Personality Affect Trust in B2C c-Commerce?” ICEC’06, August [4-16 2006, Fredericton, Canada.
6 B.Shneiderman., “Designing Trust into Online Experiences”, Communications of the ACM,43(12), 2000, 57 -59.
7 A.Fahim, “Trust in Electronic Commerce: Social, Personal, and Technical Perspective”, In Proceedings of the International Conference of the Information Resources Management Association: Innovations through Information Technology, New Orleans, USA.
8 Allen C. Johnston , Merrill Warkentin "The online consumer trust construct: a web merchant practitioner perspective" , Proceedings of the 7th Annual Conference of the Southern Association for Information Systems.
9 Fukuyama, F. (1995). Trust: the social virtues and the creation of prosperity, the free press,New York.
10 Gefen, David. & Detmar W, Straub. (2004). Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and services. The international journal of management science. Omega 32, pp. 407-424.
11 Mayer, R.C., Davis, J. H. & Schoorman, F.D. (1995). An integration model of organizational trust. Academy of management review, 20(3), pp. 709-734.
12 Reichheld, F.F. & Schefter, P. (2000). ‘E-loyalty: your secret weapon on the web,’ Harvard business review,78. pp.105-113.
13 Lightner, Nancy. J. (2004). Evaluating e-Commerce functionality with a focus on customer Service. Communications of the ACM, Vol. 47 Issue 10, p.88, 5p; (AN 14523142).
14 Singh, M.,Costtabile, A., Paull, S. (2001). E-commerce and customer relationship management (eCRM), heidelberg press, Melbourne, pp.95-108.
15 Ciji Pearl Kurian , V.I.George, Jayadev Bhat & Radhakrishna S Aithal Manipal Institute of Technology Manipal – 576104, India"Anfis Model For The Time Series Prediction Of Interior Daylight Illuminance"
16 Sengur, A. (2008a). Wavelet transform and adaptive neuro-fuzzy inference system for color texture classification. Expert Systems with Applications, 34, 2120–2128.
17 Buragohain, M., & Mahanta, C. (2008). A novel approach for ANFIS modeling based on full factorial design. Applied Soft Computing, 8, 609–625.
18 Avci, E. (2008). Comparison of wavelet families for texture classification by using wavelet packet entropy adaptive network based fuzzy inference system. Applied Soft Computing, 8,225–231.
19 Ying, L. C., & Pan, M. C. (2008). Using adaptive network based fuzzy inferencesystem to forecast regional electricity loads. Energy Conversation and Management, 49, 205–211.
20 Kosko, B., (1992). Neural Networks and Fuzzy systems: A Dynamical Systems Approach to Machine Intelligence. Prentice-Hall, Englewood Cliffs, NJ.
21 Bezdek, J.C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum,New York.
Mr. Mehrbakhsh Nilashi
Islamic Azad University, Designation = Roudsar - Iran
Associate Professor Mohammad Fathian
University of Science & Technology - Iran
Dr. Mohammad Reza Gholamian
University of Science & Technology - Iran
Dr. Othman bin Ibrahim
Information Systems UTM University - Malaysia