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Reconceptualizing System Usage: An Approach and Empirical Test

Author

Listed:
  • Andrew Burton-Jones

    (Management Information Systems Division, Sauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver BC, V6T 1Z2 Canada)

  • Detmar W. Straub

    (Department of Computer Information Systems, J. Mack Robinson College of Business Administration, Georgia State University, Box 4015, Atlanta, Georgia 30302)

Abstract

Although DeLone, McLean, and others insist that system usage is a key variable in information systems research, the system usage construct has received little theoretical scrutiny, boasts no widely accepted definition, and has been operationalized by a diverse set of unsystematized measures. In this article, we present a systematic approach for reconceptualizing the system usage construct in particular nomological contexts. Comprising two stages, definition and selection, the approach enables researchers to develop clear and valid measures of system usage for a given theoretical and substantive context. The definition stage requires that researchers define system usage and explicate its underlying assumptions. In the selection stage, we suggest that system usage be conceptualized in terms of its structure and function. The structure of system usage is tripartite, comprising a user, system, and task, and researchers need to justify which elements of usage are most relevant for their study. In terms of function, researchers should choose measures for each element (i.e., user, system, and/or task) that tie closely to the other constructs in the researcher's nomological network.To provide evidence of the viability of the approach, we undertook an empirical investigation of the relationship between system usage and short-run task performance in cognitively engaging tasks. The results support the benefits of the approach and show how an inappropriate choice of usage measures can lead researchers to draw opposite conclusions in an empirical study. Together, the approach and the results of the empirical investigation suggest new directions for research into the nature of system usage, its antecedents, and its consequences.

Suggested Citation

  • Andrew Burton-Jones & Detmar W. Straub, 2006. "Reconceptualizing System Usage: An Approach and Empirical Test," Information Systems Research, INFORMS, vol. 17(3), pages 228-246, September.
  • Handle: RePEc:inm:orisre:v:17:y:2006:i:3:p:228-246
    DOI: 10.1287/isre.1060.0096
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    References listed on IDEAS

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    1. 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.
    2. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    3. Jon Hartwick & Henri Barki, 1994. "Explaining the Role of User Participation in Information System Use," Management Science, INFORMS, vol. 40(4), pages 440-465, April.
    4. Maryam Alavi & John C. Henderson, 1981. "An Evolutionary Strategy for Implementing a Decision Support System," Management Science, INFORMS, vol. 27(11), pages 1309-1323, November.
    5. Gerardine DeSanctis & Marshall Scott Poole, 1994. "Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory," Organization Science, INFORMS, vol. 5(2), pages 121-147, May.
    6. Allen S. Lee & Richard L. Baskerville, 2003. "Generalizing Generalizability in Information Systems Research," Information Systems Research, INFORMS, vol. 14(3), pages 221-243, September.
    7. Calder, Bobby J & Phillips, Lynn W & Tybout, Alice M, 1981. "Designing Research for Application," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 8(2), pages 197-207, September.
    8. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
    9. Terri L. Griffith & Gregory B. Northcraft, 1994. "Distinguishing Between the Forest and the Trees: Media, Features, and Methodology in Electronic Communication Research," Organization Science, INFORMS, vol. 5(2), pages 272-285, May.
    10. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    11. Nancy Paule Melone, 1990. "A Theoretical Assessment of the User-Satisfaction Construct in Information Systems Research," Management Science, INFORMS, vol. 36(1), pages 76-91, January.
    12. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    13. Peter B. Seddon, 1997. "A Respecification and Extension of the DeLone and McLean Model of IS Success," Information Systems Research, INFORMS, vol. 8(3), pages 240-253, September.
    14. Daniel Robey, 1996. "Research Commentary: Diversity in Information Systems Research: Threat, Promise, and Responsibility," Information Systems Research, INFORMS, vol. 7(4), pages 400-408, December.
    15. Michael J. Ginzberg, 1981. "Early Diagnosis of MIS Implementation Failure: Promising Results and Unanswered Questions," Management Science, INFORMS, vol. 27(4), pages 459-478, April.
    16. 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.
    17. Wynne W. Chin & Barbara L. Marcolin & Peter R. Newsted, 2003. "A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study," Information Systems Research, INFORMS, vol. 14(2), pages 189-217, June.
    18. 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.
    19. Wynne W. Chin & Peter R. Newsted, 1995. "Research Report ---The Importance of Specification in Causal Modeling: The Case of End-User Computing Satisfaction," Information Systems Research, INFORMS, vol. 6(1), pages 73-81, March.
    20. Wynne W. Chin & Abhijit Gopal & W. David Salisbury, 1997. "Advancing the Theory of Adaptive Structuration: The Development of a Scale to Measure Faithfulness of Appropriation," Information Systems Research, INFORMS, vol. 8(4), pages 342-367, December.
    21. Dale L. Goodhue, 1995. "Understanding User Evaluations of Information Systems," Management Science, INFORMS, vol. 41(12), pages 1827-1844, December.
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