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The measurement of information system use: preliminary considerations

Published:13 April 2006Publication History

ABSTRACT

The concept of system use has suffered from a "too simplistic definition" (DeLone and McLean [9], p. 16). This paper reviews various attempts at conceptualization and measurement of system use and then proposes a re-conceptualization of it as "the level of incorporation of an information system within a user's processes." We then go on to develop the concept of a Functional Interface Point and four dimensions of system usage: automation level, the proportion of the business process encoded by the information system; extent, the proportion of the FIPs used by the business process; frequency, the rate at which FIPs are used by the participants in the process; and thoroughness, the level of use of information/functionality provided by the system at an FIP. The article concludes with a discussion of some implications of this re-conceptualization and areas for follow on research.

References

  1. Alter, S. (1999). A general, yet useful theory of information systems. Communications of the Association for Information Systems, 1(13), 1--69. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Alter, S. (2002a). Information systems the foundation of e-business (4th ed.). Delhi, India: Pearson Education (Singapore) Pte. Ltd. Indian Branch. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Alter, S. (2002b). The work system method for understanding information systems and information system research. Paper presented at the Eighth Americas Conference on Information Systems.Google ScholarGoogle Scholar
  4. Burton-Jones, A. (2005). New perspectives on the systems usage construct. Unpublished Dissertation, Georgia State University, Atlanta.Google ScholarGoogle Scholar
  5. Burton-Jones, A., & Straub, D. (2003). Minimizing method variance in measures of system usage. Paper presented at the Proceedings of the 7th Annual Conference of the Southern Association for Information Systems, Savannah, GA.Google ScholarGoogle Scholar
  6. Cuellar, M. J., & Johnson, R. D. (2005, October 28, 2005). Information systems and organizational knowledge. Paper presented at the ICKM, 2005, Charlotte, NC.Google ScholarGoogle Scholar
  7. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319--339.Google ScholarGoogle Scholar
  8. DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60--95.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: Information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Fagan, M. H., Neill, S., & Wooldridge, B. R. (2004). An empirical investigation into the relationship between computer self-efficacy, anxiety, experience, support and usage. Journal of Computer Information Systems, 95--104.Google ScholarGoogle Scholar
  11. Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213--233. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Guimares, T., & Igbaria, M. (1997). Client/server system success: Exploring the human side. Decision Sciences, 28(4), 851--876.Google ScholarGoogle ScholarCross RefCross Ref
  13. Igbaria, M., & Tan, M. (1997). The consequences of information technology acceptance on subsequent individual performance. Information & Management, 32, 113--121. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The technology assessment model: Past, present and future. Communications of the Association for Information Systems, 12(50), 752--780.Google ScholarGoogle Scholar
  15. McCloskey, D. (2003). Evaluating electronic commerce acceptance with the technology acceptance model. Journal of Computer Information Systems, 49--57.Google ScholarGoogle Scholar
  16. Orlikowski, W. J., & Iacono, C. S. (2001). Research commentary: Desperately seeking the "it" in it research-- a call to theorizing the it artifact. Information Systems Research, 12(2), 121--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325--343.Google ScholarGoogle ScholarCross RefCross Ref
  18. Straub, D., Limayem, M., & Karahanna, E. (1995). Measuring system usage: Implications for is theory testing. Management Science, 41(8), 1328--1342. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 37(3), 425--479. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Zain, M., Rose, R. C., Abdullah, I., & Masrom, M. (2005). The relationship between information technology acceptance and organizational agility in Malaysia. Information & Management, 42(6), 829--839. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Zhu, K., Kraemer, K., & Xu, S. (2003). Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors. European Journal Of Information Systems, 12, 251--268. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      SIGMIS CPR '06: Proceedings of the 2006 ACM SIGMIS CPR conference on computer personnel research: Forty four years of computer personnel research: achievements, challenges & the future
      April 2006
      368 pages
      ISBN:1595933492
      DOI:10.1145/1125170
      • General Chair:
      • Conrad Shayo,
      • Program Chairs:
      • Kate Kaiser,
      • Terry Ryan

      Copyright © 2006 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 April 2006

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