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Evaluation of customer oriented success factors in mobile commerce using fuzzy AHP

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DOI: 
doi:10.3926/jiem.2011.v4n2.p361-386
Abstract (2. Language): 
Purpose: With the development of information technology, ordinary commercial activities are evolving into e-commerce. In e-commerce, users can access services from any place as long as information technology is available. Currently, e-commerce is moving toward mobile commerce that allows users to do commercial activities while they are moving. This study aims to elucidate the factors that affect success in mobile commerce, and then evaluate and rate these factors by analyzing components of commercial activity in the mobile internet environment and give an evaluation method for mobile commerce in order to help researches and managers to determine the drawbacks and opportunities. Design/methodology/approach: A consumer survey was conducted through a structured undisguised questionnaire towards meeting the objectives of the study. An online questionnaire constituted the data collection instrument, while only internet users participated in the sample. The main goal of the questionnaire is to identify the success factors or criteria and sub-criteria for mobile commerce from the viewpoint of users' perception and to assess the decision-making executives for pair-wise comparisons using the fuzzy analytic hierarchical process (FAHP). Findings: A subjective and objective integrated approach has been put forward to determine attributes weights in Fuzzy AHP problems. The study identified the success factors or criteria and sub-criteria for mobile commerce from the viewpoint of users' perception. The main attractive factors for the customer are the trust and mobility factors. In addition, content quality, system quality, use, support, personalization factors are also important. Research limitations/implications: Sampling is a major limitation in this study. Since the survey was conducted based on a sample in Bangladesh, the prudent reader may need to interpret the results of the study with caution, particularly with respect to the generalization of research findings to Bangladesh mobile commerce customers as a whole. Practical implications: The principal practical implication is to identify the success factors or criteria and sub-criteria for mobile commerce from the viewpoint of users' perception. The criteria and decision alternatives or sub-criteria that are applied in this evaluation were selected based on the feedback from the questionnaire and literature review. On the other hand, from a professional point of view, future research should make several extensions to measure users' satisfaction with mobile commerce using user satisfaction index and evaluate commercial activities in ubiquitous environment, which is a process in the transition of commerce, using the success factors and alternatives of mobile commerce. Originality/value: There are no comparative studies about evaluation of customer oriented success factors for Bangladeshi mobile commerce users. A structured analysis of such customer-oriented factors provides good insights, and will help business managers to time the launch of mobile commerce businesses. It will become a useful assessment model for predicting and evaluating market tendencies.
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REFERENCES

References: 

Anand, D. M., Selvaraj, T., Kumanan, S., & Johnny, M. A. (2008). Application of multicriteria decision making for selection of robotic system using fuzzy analytic hierarchy process. International Journal of Management and Decision Making, 9(1), 75-98. doi:10.1504/IJMDM.2008.016043
Andreou, A. S., Leonidou, C., Chrysostomou, C., Pitsillides, A., Samaras, G., Schizas, C. N., & Mavromous, S. M. (2005). Key issues for the design and development of mobile commerce services and applications. International Journal of Mobile Communications, 3(3), 303-323. doi:10.1504/IJMC.2005.006586
Bozbura, F. T., & Beskese, A. (2007). Prioritization of organizational capital measurement indicators using fuzzy AHP. International Journal of Approximate Reasoning, 44(2), 124-147. doi:10.1016/j.ijar.2006.07.005
Bozbura, F. T., Beskese, A., & Kahraman, C. (2007). Prioritization of human capital measurement indicators using fuzzy AHP. Expert Systems with Applications,32(4), 1100-1112. doi:10.1016/j.eswa.2006.02.006
Bozdag, C. E., Kahraman, C., & Ruan, D. (2003). Fuzzy group decision making for selection among computer integrated manufacturing systems. Computers in Industry, 51(1), 13–29. doi:10.1016/S0166-3615(03)00029-0
Büyüközkan, G. (2009). Determining the mobile commerce user requirements using an analytic approach. Computer Standards & Interfaces, 31(1), 1144-152.
Çakir, E., Tozan, H., & Vayvay, O. (2009). A Method for Selecting Third Party Logistic Service Provider Using Fuzzy AHP. Journal of Naval Science and Engineering, 5(3), 38-54.
Chang, D. Y. (1992). Extent analysis and synthetic decision. Optimization Techniques and Applications, 1, 352-355.
Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655. doi:10.1016/0377-2217(95)00300-2
Chiu, Y. C., Shyu, J. Z., & Tzeng, G. H. (2004). Fuzzy MCDM for evaluating the e-commerce strategy. International Journal of Computer Applications in Technology, 19(1), 12-22. doi:10.1504/IJCAT.2004.003656
Delone, W. H., & Maclean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95. doi:10.1287/isre.3.1.60
Gunasekaran, A., & McGaughey, R. E. (2009). Mobile commerce: issues and obstacles. International Journal of Business Information Systems, 4(2), 245-261. doi:10.1504/IJBIS.2009.022826
Guo, S., & Shao, B. (2005, June). Quantitative Evaluation of E-Commercial Websites of Foreign Trade Enterprises in Chongquing. Proceedings of international conference on services systems and services management, Chongquing, China, 780-785.
Hsieh, C. T., Jones, C., & Lin, B. (2008). The new business potential with mobile commerce. International Journal of Mobile Communications, 6(4), 436 - 455. doi:10.1504/IJMC.2008.018052
Information Superhighways Newsletter (2011). Strategy Analytics Forecasts $230 Billion Mobile Commerce Market by 2006 - Brief Article. Retrieved January 14th, 2011, from http://findarticles.com/p/articles/mim 0IGM/is48/ai73554018/.
Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi-criteria Supplier Selection Using Fuzzy AHP. Logistics Information Management, 16(6), 382-394. doi:10.1108/09576050310503367
Kahraman, C., Cebeci, U., & Ruan, D. (2004). Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey. International Journal of Production Economics, 87(2), 171–184. doi:10.1016/S0925-5273(03)00099-9
Kim, J., & Hwang, C. S. (2005, June). Applying the analytic hierarchy process to the evaluation of customer-oriented success factors in mobile commerce. Proceedings of International Conference on Services Systems and Services Management, Chongquing, China, 1, 69-74.
Molla, A., & Licker, P. S. (2001). E-Commerce Systems Success: An Attempt to Extend and Respecify the Delone and Maclean Model of its Success. Journal of Electronic Commerce Research, 2(4), 131-141.
Muller-Veerse, F. (1999). Mobile commerce report. London: Durlacher Corporation. Retrieved from http://www.durlacher.com/downloads/mcomreport.pdf.
Oh, G. O., Kim, D., & Rhew, S. (2006). Selection of the Success Factors of Mobile Commerce and Evaluation using AHP. International Journal of Computer Science and Network Security, 6(7B), 127-134.
Saaty, T. L. (1998). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. Pittsburgh, PA: RWS Publications.
Sarker, S., & Wells, J. D. (2003). Understanding Mobile Handheld Device Use and Adaption. Communications of the ACM, 46(12), 35-40. doi:10.1145/953460.953484
Strategy Analytics (2000). Strategy Analytics forecasts $200 billion mobile commerce market by 2004. Retrieved January 10th, 2000, from http://www.wowcom.com/newsline/press_release.cfm? press_i d=826. Wowcompany, USA.
Tang, Y. C., & Beynon, M. J. (2005). Application and Development of a Fuzzy Analytic Hierarchy Process within a Capital Investment Study. Journal of Economics and Management, 1(2), 207-230.
Tarasewich, P. (2003). Designing Mobile Commerce Applications. Communications of the ACM, 46(12), 57-60. doi:10.1145/953460.953489
Tarasewich, P., Nickerson, R. C., & Warkentin, M. (2002). Issues in mobile e-commerce. CAIS, 8, 41-64.
Topcu, Y. I., & Burnaz, S. (2006, June). A multiple criteria decision making approach for the evaluation of retail location. Paper presented at the 18th International Conference on Multiple Criteria Decision Making, Chania, Greece.
Turban, E., King, D., Lee, J. K., Warkentin, M., & Chung, H. M. (2002). Electronic Commerce 2002 - A Managerial perspective (2nd ed.). New Jersey: Prentice Hall.
Varshney, U., & Vetter, R. (2002). Mobile Commerce: Framework, Applications and Networking Support. Mobile Networks and Applications, 7(3), 185-198. doi:10.1023/A:1014570512129
Venkatesh, V., Ramesh, V., & Massey, A. P. (2003). Understanding Usability in Mobile Commerce. Communications of the ACM, 46(12), 53-56. doi:10.1145/953460.953488
Warrington, T. B., Abgrab, N. J., & Caldwell, H. M. (2000). Building trust to develop competitive advantage in e-business relationships. Competitiveness Review, 10(2), 160-168.
Xia, W., & Wu, Z. (2007). Supplier Selection with Multiple Criteria in Volume Discount Environments. Omega, 35, 494-504. doi:10.1016/j.omega.2005.09.002
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353. doi:10.1016/S0019-9958(65)90241-X

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