Annals of Computer Science and Information Systems, Volume 14

DOI: http://dx.doi.org/10.15439/2017KM37

Citation: Proceedings of the 2017 International Conference on Information Technology and Knowledge Management, Ajay Jaiswal, Vijender Kumar Solanki, Zhongyu (Joan) Lu, Nikhil Rajput (eds). ACSIS, Vol. 14, pages 13–19 (2017)

Full text

Abstract. Today internet has emerged as a huge marketplace of products and services for meeting needs of more than a million customers worldwide. It provides users a platform to access information globally in electronic form as well as in terms of business transaction, such as,e-payments, e-orders and e-booking etc. The advent of the internet has led to the establishment of electronic commerce. Today a large number of B2C e-commerce websites are available, which makes it difficult not only for the customers to find right product at right price, but also for a company to choose a better site for selling its product. Thus, there is need to rank e-commerce websites in B2C electronic commerce. The objective of this paper is to rank e-commerce websites on the basis of success factors, namely, System Quality, Content Quality, Usages, Trust, Customer Support, Online Customer Feedback and Personalization. Here we have used a two stage approach combining maximum entropy-ordered weighted averaging aggregation (ME-OWA) with fuzzy Analytic Hierarchy Process (FAHP) for choosing the best B2C e-commerce website.

References

1. Cyr, D. and C. Bonanni. Design and e-loyalty across cultures in electronic commerce. in Proceedings of the 6th international conference on Electronic commerce. ACM, (2004).
2. DeLone, W.H. and E.R. McLean, Information systems success: The quest for the dependent variable. Information systems research. 3(1), pp. 60-95. (1992).
3. Molla, A. and P.S. Licker, E-commerce systems success: An attempt to extend and respecify the Delone and MacLean model of IS success. J. Electron. Commerce Res. 2(4), pp. 131-141. (2001).
4. DeLone, W.H. and E.R. McLean. Information systems success revisited. in System Sciences, 2002. HICSS. Proceedings of the 35th Annual Hawaii International Conference on. IEEE, (2002).
5. Delone, W.H. and E.R. McLean, The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems. 19(4), pp. 9-30. (2003).
6. Delone, W.H. and E.R. Mclean, Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce. 9(1), pp. 31-47. (2004).
7. Chevalier, J.A. and D. Mayzlin, The effect of word of mouth on sales: Online book reviews. Journal of marketing research. 43(3), pp. 345-354. (2006).
8. Ghose, A. and P.G. Ipeirotis, Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE Transactions on Knowledge and Data Engineering. 23(10), pp. 1498-1512. (2011).
9. Andreou, A.S., et al., Key issues for the design and development of mobile commerce services and applications. International Journal of Mobile Communications. 3(3), pp. 303-323. (2005).
10. Yager, R.R., On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on systems, Man, and Cybernetics. 18(1), pp. 183-190. (1988).
11. O'Hagan, M. Aggregating template or rule antecedents in real-time expert systems with fuzzy set logic. in Signals, Systems and Computers, 1988. Twenty-Second Asilomar Conference on. IEEE, (1988).
12. Fullér, R. and P. Majlender, An analytic approach for obtaining maximal entropy OWA operator weights. Fuzzy Sets and Systems. 124(1), pp. 53-57. (2001).
13. Zadeh, L.A., Fuzzy sets. Information and control. 8(3), pp. 338-353. (1965).
14. Saaty, T.L., The Analytic Hierarchy Process, NY. McGraw-Hill, USA. Cook WD and Seiford LM.(1978). Priority ranking and consensus formation, Management Science.24, pp. 1721-1732. (1980).
15. Kwong, C.-K. and H. Bai, Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach. Iie Transactions. 35(7), pp. 619-626. (2003).
16. Buckley, J.J., Fuzzy hierarchical analysis. Fuzzy sets and systems. 17(3), pp. 233-247. (1985).
17. Chang, D.-Y., Applications of the extent analysis method on fuzzy AHP. European journal of operational research. 95(3), pp. 649-655. (1996).
18. Lee, S.-H., Using fuzzy AHP to develop intellectual capital evaluation model for assessing their performance contribution in a university. Expert systems with applications. 37(7), pp. 4941-4947. (2010).
19. Bozbura, F.T., A. Beskese, and C. Kahraman, Prioritization of human capital measurement indicators using fuzzy AHP. Expert Systems with Applications. 32(4), pp. 1100-1112. (2007).