skip to main content
research-article

Using a fuzzy classification approach to assess e-commerce Web sites: An empirical investigation

Published:30 July 2009Publication History
Skip Abstract Section

Abstract

E-commerce Web site assessment helps determine whether a corporation's Web site is effectively designed to meet its business needs and whether the investment in Web sites is well justified. Due to the complexity of commercial Web sites that may include hundreds of Web pages for many big corporations, there may inevitably exist uncertainties when human assessors express their subjective judgments in assessing e-commerce Web sites. Fuzzy set theory is widely used to model uncertain and imprecise information in applications. Prior studies in e-commerce Web site assessment identified some key factors to assess commercial Web sites by using a numeric assessment scale that may not be effective and efficient in modeling uncertainty. This study intends to propose an e-commerce Web site assessment framework using a fuzzy classification approach. Based on this framework, a Web-based e-commerce assessment system was designed and developed, which can provide online assessment services to corporations on evaluating their commercial Web sites. An empirical investigation into assessing commercial Web sites of the top 120 Fortune Corporations of the USA was conducted using the developed online assessment system to demonstrate the usefulness of the proposed framework. Research findings and implications are discussed.

References

  1. Aladwani, A. M. and Palvia, P. C. 2002. Developing and validating an instrument for measuring user-perceived Web quality. Inform. Manag. 39, 6, 467--476. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Archer, N. P. and Ghasemzadeh, F. 1999. An integrated framework for project portfolio selection. Inter. J. Proj. Manag. 17, 4, 207--216.Google ScholarGoogle ScholarCross RefCross Ref
  3. Bacheldor, B. 2000. The art of e-biz. Inform. Week. 773, 14, 42--44.Google ScholarGoogle Scholar
  4. Bickers, C. 2000. Getting noticed. Far East. Econ. Rev. 163, 9, 47--48.Google ScholarGoogle Scholar
  5. Biswas, R. 1995. An application of fuzzy sets in students' evaluation. Fuzzy Sets Syst. 74, 187--194. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Cell, B. 2000. Web site design: What do I need to know? Penn. CPA J. 71, 1, 15--19.Google ScholarGoogle Scholar
  7. Chen, S. and Lee, C. 1999. New methods for students' evaluation using fuzzy sets. Fuzzy Sets Syst. 104, 209--218. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Chen, Y. N., Huang, W., Chen, H. M., and Ching, R. K. H. 2006. E-government strategies in developed and developing countries: An implementation framework and case study. J. Global Inform. Manag. 14, 1, 24--47.Google ScholarGoogle ScholarCross RefCross Ref
  9. Cheung, W. M. and Huang, W. 2002. An investigation of commercial usage of the World Wide Web: A picture from Singapore. Inter. J. Inform. Manag. 22, 5, 377--388. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Coopee, T., Mitchell, L., Macdonald, T., and Steinacher, S. 2000. Catching net customers. Info World 22,14, 54--55.Google ScholarGoogle Scholar
  11. Echauz, J. R. and Vachtsevanos, G. J. 1995. Fuzzy grading system. IEEE Trans. Educ. 38, 2, 158--164. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Fairley, J. 2000. The 6 mistakes of highly ineffective Web sites. Bank Market. 32, 2, 36--40.Google ScholarGoogle Scholar
  13. Gefen, G. 2002. Customer loyalty in e-commerce. J. Assoc. Inform. Syst. 3, 27--51.Google ScholarGoogle ScholarCross RefCross Ref
  14. Gervasi, O., Catanzani, R., Riganelli, A., and Lagana, A. 2005. Integrating learning and assessment using the semantic Web. In Proceedings of the ICCSA. Lecture Notes in Computer Science, vol. 3480, 921--927. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Gomes, D. and Silva, M. J. 2005. Characterizing a national community Web. ACM Trans. Internet Tech. 5, 3, 508--531. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Gonzalez, F. and Palacios, T. 2004. Quantitative evaluation of commercial Web sites: An empirical study of Spanish firms. Inter. J. Inform. Manag. 24, 4, 313--328. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Herrera, F., Herrera-Viedma, E., and Verdegay, J. L. 1996. A linguistic decision process in group decision making. Group Decis. Negot. 5, 165--176.Google ScholarGoogle ScholarCross RefCross Ref
  18. Howitt, A., Clement, S., De Lusignan, S., Thiru, K., Goodwin, D., and Wells, S. 2002. An evaluation of general practice Web sites in the UK. Fam. Pract. 19, 5, 547--556.Google ScholarGoogle ScholarCross RefCross Ref
  19. Huang, W., Chen, Y. N., and Hee, J. 2006. STP technology: An overview and a conceptual framework. Inform. Manag. 43, 263--270. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Huang, J. H., Huang, W., Zhao, C. J., and Huang, H. 2004. An e-readiness assessment framework and two field studies. Comm. AIS 14, 364--386.Google ScholarGoogle Scholar
  21. Huizingh, E.K.R.E. and Vrolijk, H. C. 1997. A comparison of verbal and numerical judgments in the analytic hierarchy process. Org. Behav. Hum. Decis. Proc. 70, 3, 237--247.Google ScholarGoogle ScholarCross RefCross Ref
  22. Huizingh, E. 2000. The content and design of Web sites: An empirical study. Inform. Manag. 37, 1, 123--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Kalakota, R. and Whinston, A. 1997. Electronic Commerce: A Manager's Guide. Addison-Wesley, Reading. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Kennedy, S. D. 2000. Trapped in a Web of bad design. Inform. Today 17, 4, Article 5.Google ScholarGoogle Scholar
  25. Klir, G. J. and Folger, T. A. 1988. Fuzzy Sets, Uncertainty, and Information. Prentice Hall, Upper Saddlebrook, New Jersey. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Kumar, R. L. 1999. Understanding DSS value: An options perspective. Omega, Inter. J. Manag. Sci. 27, 3, 295--304.Google ScholarGoogle ScholarCross RefCross Ref
  27. Kwok, C. W. R., Ma, J., Voug, D., and Zhou, D. 2001. Collaborative assessment in education: An application of fuzzy GSS. Inform. Manag. 39, 3, 243--253.Google ScholarGoogle ScholarCross RefCross Ref
  28. Li, X. and Huang, W. 2007. Design a knowledge-based system to automatically assess commercial Web sites. Inter. J. Inform. Tech. Decision Making 6, 1, 43--60.Google ScholarGoogle ScholarCross RefCross Ref
  29. Lin, Z. X., Li, D. H., Janamanchi, B., and Huang, W. 2006. Reputation distribution and consumer-to-consumer online auction market structure. Decis. Supp. Syst. 41, 2006, 435--448. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Li, X., Huang, W., and Gandha, S. 2002. What Web features and functions are used by Australian corporations in their Web sites? A conceptual framework and an empirical investigation. In Proceedings of Annual Conference of Information Resources Management Association (IRMA).Google ScholarGoogle Scholar
  31. Liu, C., Arnett, K. P., Capella, L. M., and Beatty, R. C. 1997. Web sites of the Fortune 500 companies: Facing customers through home pages. Inform. Manag. 31, 6, 335--345. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Ma, J. and Zhou, D. 2000. Fuzzy set approach to the assessment of student-centered learning. IEEE Trans. Educ. 43, 2, 237--241. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Ross, T. J. 1995. Fuzzy Logic with Engineering Application. McGraw-Hill, New York, 315--317.Google ScholarGoogle Scholar
  34. Saaty, T. 1980. The Analytic Hierarchy Process. McGraw-Hill, New York.Google ScholarGoogle Scholar
  35. Scharl, A. 2000. Evolutionary Web Development. Springer, Berlin. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Scharl, A. 2004. A roadmap towards distributed web assessment. Web Engineering Processing. Lecture Notes in Computer Science, vol. 3140, 171--175.Google ScholarGoogle ScholarCross RefCross Ref
  37. Schubert, P. 2002. Extended Web assessment method (EWAM): Evaluation of electronic commerce applications from the customer's viewpoint. Inter. J. Electr. Comm. 7, 2, 51--80. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Shim, J. P., Shin, Y. B., and Nottingham, L. 2002. Retailer Web site influence on customer shopping: An exploratory study on key factors of customer satisfaction. J. Assoc. Inform. Syst. 3, 53--76.Google ScholarGoogle ScholarCross RefCross Ref
  39. Slater, J. 2000. How to score a Net success. Far East. Econ. Rev. 163, 9, 50--53.Google ScholarGoogle Scholar
  40. Sweeney, T. 2000. Getting it done: Creating a customer-friendly Web site. Madison 23, 6--6.Google ScholarGoogle Scholar
  41. Teo, S. H. and Huang, W. 2004. On electronic business. Inter. J. Global Inform. Manag. 12, 1, i--ii.Google ScholarGoogle Scholar
  42. Tsai, S. L. and Chai, S. K. 2005. Developing and validating a nursing website evaluation questionnaire. J. Advanced Nurs. 49, 4, 406--413.Google ScholarGoogle ScholarCross RefCross Ref
  43. Van De Walle, B. and Rurkowski, A.-F. 2006. A fuzzy decision support system for IT service continuity threat assessment. Decis. Supp. Syst. 42, 1931--1943. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Wang, J. and Hwang, W.-L. 2007. A fuzzy set approach for R&D portfolio selection using a real options valuation model. Omega, Inter. J. Manag. Sci. 35, 247--257.Google ScholarGoogle ScholarCross RefCross Ref
  45. Webb, H. W. and Webb, L. A. 2002. B2C electronic commerce Web sites: an analysis of quality factors. In Proceedings of 8th Americas Conference on Information Systems. 340--347.Google ScholarGoogle Scholar
  46. Wood, F. B., Benson, D., Lacroix, E. M., Siegel, E. R., and Fariss, S. 2005. Use of Internet audience measurement data to gauge market share for online health information services. J. Med. Internet Res. 7, 3:e31.Google ScholarGoogle ScholarCross RefCross Ref
  47. Xi, Y. M., Zhuang, Y. L., Huang, W., She, C. G., and Zhang, Z. P. 2007. The Quality assessment and content analysis of corporate Web sites in China: An empirical study. Inter. J. Inform. Tech. Decision Making 2, 2, 389--405.Google ScholarGoogle ScholarCross RefCross Ref
  48. Yasin, R. 2000. Site performance management by subscription. Internetweek 807, 80.Google ScholarGoogle Scholar
  49. Yeung, W. L. and Lu, M. T. 2004. Gaining competitive advantages through a functionality grid for Web site evaluation. J. Comput. Inform. Syst. 44, 4, 67--77.Google ScholarGoogle Scholar
  50. Zadeh, L. A. 1965. Fuzzy sets. Inform. Contr. 8, 338--353.Google ScholarGoogle ScholarCross RefCross Ref
  51. Zadeh, L. A. 1983. A computational approach to fuzzy quantifiers in natural languages. Comput. Math. Appl. 9, 149--184.Google ScholarGoogle ScholarCross RefCross Ref
  52. Zeleny, M. 1982. Multiple Criteria Decision Making. McGraw-Hill, New York.Google ScholarGoogle Scholar
  53. Zhou, D., Ma, J., and Turban, E. 2001. Journal quality assessment: An integrated subjective and objective approach. IEEE Trans. Engin. Manag. 48, 4, 479--490.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Using a fuzzy classification approach to assess e-commerce Web sites: An empirical investigation

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in

            Full Access

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader
            About Cookies On This Site

            We use cookies to ensure that we give you the best experience on our website.

            Learn more

            Got it!