A Qualitative Method for Identifying Factors that Influence User Satisfaction

  • Bernard J. Terrill
  • Andrew Flitman
Conference paper


Understanding what influences users’ satisfaction, or otherwise, with computer systems is a topic of importance to many within the field of information systems. Research into this question has typically relied on quantitative methods; in the course of a formal research project, a new method was developed which investigates the question using qualitative techniques. The method, along with the practical and theoretical context that gives it relevance, is described in this paper. For clarity, the method will be referred to herein as MIFIUS-QI (a Method for the Identification of Factors Influencing User Satisfaction — Qualitative).


User Satisfaction Management Information System Knowledge Management System Repertory Grid Parent Category 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Alavi, M., and Leidner, D. E., 2001, Knowledge management and knowledge management systems: Conceptual foundations and research issues, MIS Quarterly, 25: 107–136.CrossRefGoogle Scholar
  2. Ballantine, J., Bonner, M., Levy, M., Martin, A., Munro, I., and Powell, P. L., 1998, Developing a 3-D model of information systems success, in: Information Systems Success Measurement, E. J. Garrity and G. L. Sanders, eds., Idea Group Publishing, Hershey, pp. 46–59.Google Scholar
  3. Becker, H., and Geer, B., 1982, Participant observation: The analysis of qualitative field data, in: Field Research: A Sourcebook and Field Manual, R. Burgess, ed., Allen & Unwin, London.Google Scholar
  4. Bliss, J., Monk, M., and Ogborn, J., 1983, Qualitative Data Analysis for Educational Research: A Guide to Uses of Systemic Networks, Croom Helm, London.Google Scholar
  5. Burgess, R. G., 1984, In the Field: An Introduction to Field Research,Allen & Unwin, London.Google Scholar
  6. DeLone, W. H., and McLean, E. R., 1992, Information Systems success: The quest for the dependent variable, Information Systems Research, 3: 60–95.CrossRefGoogle Scholar
  7. Dey, I., 1993, Qualitative Data Analysis: A User-friendly Guide for Social Scientists, Routtedge, London.CrossRefGoogle Scholar
  8. Fransella, F., and Bannister, D., 1977, A Manual for Repertory Grid Technique, Academic Press, London.Google Scholar
  9. Hinkle, D., 1965, The Change of Personal Constructs from the View Point of a Theory of Construct Implications, Unpublished PhD Thesis, Ohio State University, Ohio.Google Scholar
  10. Hunter, M. G., 1997, The use of RepGrids to gather interview data about information systems analysts, Information Systems Journal, 7: 67–81.CrossRefGoogle Scholar
  11. Keen, P. G., 1980, Reference disciplines and a cumulative tradition, Proceedings of the First International Conference on Information Systems, pp. 9–18.Google Scholar
  12. Kelly, G. A., 1955, The Psychology of Personal Constructs, W. W. Norton & Company Inc., New York.Google Scholar
  13. Kumar, R., 1996, Research Methodology. A Step-by-step Guide for Beginners, Addison Wesley Longman, Melbourne, Victoria.Google Scholar
  14. Kvale, S., 1996, Interviews: An Introduction to Qualitative Research Interviewing, Sage Publications, Thousand Oaks, Calif.Google Scholar
  15. Miles, M. B., and Huberman, A. M., 1994, Qualitative Data Analysis: An Expanded Sourcebook, Sage Publications, Thousand Oaks, Calif.Google Scholar
  16. Minichiello, V., Aroni, R., Timewell, E., and Alexander, L., 1995, In-Depth Interviewing: Principles, Techniques, Analysis., ( 2nd ed. ), Longman Cheshire, Melbourne.Google Scholar
  17. Neuman, L. W., 1999, Social Research Methods: Qualitative and Quantitative Approaches, ( 4th ed. ), Allyn and Bacon, Boston.Google Scholar
  18. Patton, M., 1980, Qualitative Evaluation Methods, Sage, London.Google Scholar
  19. Rollo, C., and Clarke, T., 2001, International Best Practice — Case studies in Knowledge Management. HB 275 Supplement 1–2001, Standards Australia, Sydney.Google Scholar
  20. Smith, H. W., 1991, Strategies of Social Research, ( 3rd ed. ), Holt, Rinehart and Winston, Orlando.Google Scholar
  21. Stewart, V., and Stewart, A., 1981, Business Applications of Repertory Grid, McGraw-Hill, London.Google Scholar
  22. Strauss, A., 1987, Qualitative Analysis for Social Scientists, Cambridge University Press, Cambridge.CrossRefGoogle Scholar
  23. Strauss, A., and Corbin, J., 1990, Basics of Qualitative Research: Grounded Theory Procedures and Techniques, Sage Publications, Newbury Park, Calif.Google Scholar
  24. Terrill, B. J., and Flitman, A., 2002, Using Repertory Grid Analysis to gather qualitative data for information systems research, Proceedings of the Thirteenth Australasian Conference on Information Systems (ACIS), Melbourne, Australia, December 4–6, 2002, pp. 745–756.Google Scholar
  25. Terrill, B. J., and Flitman, A., 2003, Factors influencing users’ satisfaction with integrative knowledge management systems: A preliminary investigation, Proceedings of the 11th European Conference on Information Systems (ECIS), Naples, Italy, June 19–21, 2003.Google Scholar

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Bernard J. Terrill
    • 1
  • Andrew Flitman
    • 1
  1. 1.School of Business SystemsMonash UniversityMelbourneAustralia

Personalised recommendations