IDEAS home Printed from
   My bibliography  Save this article

Measuring System Usage: Implications for IS Theory Testing


  • Detmar Straub

    (College of Business Administration, Georgia State University, Atlanta, Georgia 30302)

  • Moez Limayem

    (Universite Laval, Apvillon Palasis Prince, Quebec, Quebec, Canada G1K 7P1)

  • Elena Karahanna-Evaristo

    (University of Cyprus, Nicosia 141, Cyprus)


There is widespread agreement among researchers that system usage, defined as the utilization of information technology (IT) by individuals, groups, or organizations, is the primary variable through which IT affects white collar performance. Despite the number of studies targeted at explaining system usage, there are crucial differences in the way the variable has been conceptualized and operationalized. This wide variation of system usage measures hinders the efforts of MIS researchers to compare findings across studies, thus impeding the accumulation of knowledge and theory in this area. The purpose of this paper is to address conceptual as well as methodological issues related to measuring system usage. First, via LISREL measurement modeling techniques, we compare subjective and objective measures of system usage, namely, self-reported versus computer-recorded measures. Next, using a modified form of Davis' Technology Acceptance Model (TAM) as a nomological net, we test the nomological validity of these system usage constructs and measures. Results of the LISREL measurement and nomological net analysis suggest that system usage should be factored into self-reported system usage and computer-recorded system usage. Contrary to expectations, these constructs do not appear to be strongly related to each other. Moreover, while self-reported measures of system usage are related to self-reported measures of TAM independent variables, objective, computer-recorded measures show distinctly weaker links. In the face of such counter-evidence, it is tempting to argue that research that has relied on subjective measures of system usage (for example, research confirming TAM) may be artifactual. There are several alternative explanations, though, that maintain the integrity of TAM and studies that measure system usage subjectively. These alternative explanations suggest directions for further research as well as new approaches to measurement.

Suggested Citation

  • Detmar Straub & Moez Limayem & Elena Karahanna-Evaristo, 1995. "Measuring System Usage: Implications for IS Theory Testing," Management Science, INFORMS, vol. 41(8), pages 1328-1342, August.
  • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:8:p:1328-1342

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. JS Armstrong & Fred Collopy, 2004. "Causal Forces: Structuring Knowledge for Time-series Extrapolation," General Economics and Teaching 0412003, EconWPA.
    2. Fildes, Robert & Lusk, Edward J, 1984. "The choice of a forecasting model," Omega, Elsevier, vol. 12(5), pages 427-435.
    3. Scott Armstrong, J., 1988. "Research needs in forecasting," International Journal of Forecasting, Elsevier, vol. 4(3), pages 449-465.
    4. Robert Carbone & JS Armstrong, 2004. "Evaluation of Extrapolative Forecasting Methods: Results of a Survey of Academicians and Practitioners," General Economics and Teaching 0412008, EconWPA.
    5. Robert Carbone & Spyros Makridakis, 1986. "Forecasting When Pattern Changes Occur Beyond the Historical Data," Management Science, INFORMS, vol. 32(3), pages 257-271, March.
    6. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    7. Sanders, NR & Ritzman, LP, 1990. "Improving short-term forecasts," Omega, Elsevier, vol. 18(4), pages 365-373.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Hernández, Blanca & Jiménez, Julio & Martín, M. José, 2010. "Customer behavior in electronic commerce: The moderating effect of e-purchasing experience," Journal of Business Research, Elsevier, vol. 63(9-10), pages 964-971, September.
    2. repec:dau:papers:123456789/11679 is not listed on IDEAS
    3. repec:dau:papers:123456789/7962 is not listed on IDEAS
    4. Raphaëlle Laubie & Christophe Elie-Dit-Cosaque, 2012. "Exploring and Predicting Online Collective Action on Patients' Virtual Communities: A Multi-method Investigation in France," Post-Print hal-01630383, HAL.
    5. repec:pal:jorsoc:v:59:y:2008:i:9:d:10.1057_palgrave.jors.2602429 is not listed on IDEAS
    6. Memili, Esra & Eddleston, Kimberly A. & Kellermanns, Franz W. & Zellweger, Thomas M. & Barnett, Tim, 2010. "The critical path to family firm success through entrepreneurial risk taking and image," Journal of Family Business Strategy, Elsevier, vol. 1(4), pages 200-209, December.
    7. Koo, Chulmo & Chung, Namho, 2014. "Examining the eco-technological knowledge of Smart Green IT adoption behavior: A self-determination perspective," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 140-155.
    8. Heijden, Hans van der, 2000. "E-Tam : a revision of the Technology Acceptance Model to explain website revisits," Serie Research Memoranda 0029, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    9. Edward Conlon & Sarv Devaraj & Khalil F. Matta, 2001. "The Relationship Between Initial Quality Perceptions and Maintenance Behavior: The Case of the Automotive Industry," Management Science, INFORMS, vol. 47(9), pages 1191-1202, September.
    10. Denolf, Janne.M. & Wognum, Nel P.M. & Trienekens, Jacques H. & van der Vorst, Jack G.A.J. & Omta, S.W.F. (Onno), 2012. "Towards a Supply-Chain Instrument to Monitor an Information Technology Implementation," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144968, International European Forum on Innovation and System Dynamics in Food Networks.
    11. Sung S. Kim & Naresh K. Malhotra, 2005. "A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena," Management Science, INFORMS, vol. 51(5), pages 741-755, May.
    12. Xuemei Tian & Libo Liu, 2017. "Does big data mean big knowledge? Integration of big data analysis and conceptual model for social commerce research," Electronic Commerce Research, Springer, vol. 17(1), pages 169-183, March.
    13. Sarv Devaraj & Rajiv Kohli, 2003. "Performance Impacts of Information Technology: Is Actual Usage the Missing Link?," Management Science, INFORMS, vol. 49(3), pages 273-289, March.
    14. Jaeki Song & Fatemeh Mariam Zahedi, 2005. "A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model," Management Science, INFORMS, vol. 51(8), pages 1219-1235, August.
    15. Roland Kidwell & Franz Kellermanns & Kimberly Eddleston, 2012. "Harmony, Justice, Confusion, and Conflict in Family Firms: Implications for Ethical Climate and the “Fredo Effect”," Journal of Business Ethics, Springer, vol. 106(4), pages 503-517, April.
    16. repec:spr:infosf:v:14:y:2012:i:5:d:10.1007_s10796-011-9331-z is not listed on IDEAS
    17. Alexander Benlian & Thomas Hess & Peter Buxmann, 2009. "Drivers of SaaS-Adoption – An Empirical Study of Different Application Types," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 1(5), pages 357-369, October.
    18. Eddleston, Kimberly A. & Kellermanns, Franz W., 2007. "Destructive and productive family relationships: A stewardship theory perspective," Journal of Business Venturing, Elsevier, vol. 22(4), pages 545-565, July.
    19. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:41:y:1995:i:8:p:1328-1342. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.