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Research Report: Better Theory Through Measurement—Developing a Scale to Capture Consensus on Appropriation

Author

Listed:
  • Wm. David Salisbury

    (Management Information Systems Department, Ohio University, 209 Copeland Hall, Athens, Ohio 45701)

  • Wynne W. Chin

    (C. T. Bauer College of Business Administration, University of Houston, Melcher Hall 280D, Houston, Texas 77204-6282)

  • Abhijit Gopal

    (Richard Ivey School of Business, The University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada N6A 3K7)

  • Peter R. Newsted

    (Centre for Innovative Management, Athabasca University, 22 Sir Winston Churchill Avenue, St. Albert, Alberta, Canada T8N 1B4)

Abstract

Proper measurement is critical to the advancement of theory (Blalock 1979). Adaptive Structuration Theory (AST) is rapidly becoming an important theoretical paradigm for comprehending the impacts of advanced information technologies (DeSanctis and Poole 1994). Intended as a complement to the faithfulness of appropriation scale developed by Chin et al. (1997), this research note describes the development of an instrument to capture the AST construct of consensus on appropriation. Consensus on appropriation (COA) is the extent to which group participants perceive that they have agreed on how to adopt and use a technology. While consensus on appropriation is an important component of AST, no scale is currently available to capture this construct. This research note develops a COA instrument in the context of electronic meeting systems use. Initial item development, statistical analyses, and validity assessment (convergent, discriminant, and nomological) are described here in detail. The contribution of this effort is twofold: First, a scale is provided for an important construct from AST. Second, this report serves as an example of rigorous scale development using structural equation modeling. Employing rigorous procedures in the development of instruments to capture AST constructs is critical if the sound theoretical base provided by AST is to be fully exploited in understanding phenomena related to the use of advanced information technologies.

Suggested Citation

  • Wm. David Salisbury & Wynne W. Chin & Abhijit Gopal & Peter R. Newsted, 2002. "Research Report: Better Theory Through Measurement—Developing a Scale to Capture Consensus on Appropriation," Information Systems Research, INFORMS, vol. 13(1), pages 91-103, March.
    • Handle: RePEc:inm:orisre:v:13:y:2002:i:1:p:91-103
    DOI: 10.1287/isre.13.1.91.93
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    References listed on IDEAS

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    1. Kenneth Bollen, 1986. "Sample size and bentler and Bonett's nonnormed fit index," Psychometrika, Springer;The Psychometric Society, vol. 51(3), pages 375-377, September.
    2. V. Sambamurthy & Marshall Scott Poole, 1992. "The Effects of Variations in Capabilities of GDSS Designs on Management of Cognitive Conflict in Groups," Information Systems Research, INFORMS, vol. 3(3), pages 224-251, September.
    3. Ledyard Tucker & Charles Lewis, 1973. "A reliability coefficient for maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 38(1), pages 1-10, March.
    4. 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.
    5. 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.
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    Cited by:

    1. T. S. Ragu-Nathan & Monideepa Tarafdar & Bhanu S. Ragu-Nathan & Qiang Tu, 2008. "The Consequences of Technostress for End Users in Organizations: Conceptual Development and Empirical Validation," Information Systems Research, INFORMS, vol. 19(4), pages 417-433, December.
    2. Christopher D. Allport & William A. Kerler, 2003. "A Research Note Regarding the Development of the Consensus on Appropriation Scale," Information Systems Research, INFORMS, vol. 14(4), pages 356-359, December.
    3. Bruce A. Reinig & Robert O. Briggs, 2008. "On The Relationship Between Idea-Quantity and Idea-Quality During Ideation," Group Decision and Negotiation, Springer, vol. 17(5), pages 403-420, September.
    4. Christian Maier & Sven Laumer & Tim Weitzel, 2022. "A Dark Side of Telework: A Social Comparison-Based Study from the Perspective of Office Workers," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(6), pages 793-811, December.
    5. Sora Kang & Kai H. Lim & Min Soo Kim & Hee-Dong Yang, 2012. "Research Note ---A Multilevel Analysis of the Effect of Group Appropriation on Collaborative Technologies Use and Performance," Information Systems Research, INFORMS, vol. 23(1), pages 214-230, March.
    6. Jacek Adamek & Ma³gorzata Solarz, 2023. "Adoption factors in digital lending services offered by FinTech lenders," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 169-212, March.
    7. Verhagen, T., 2008. "Investigating the impact of C2C electronic marketplace quality on trust," Serie Research Memoranda 0008, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. Wynne W. Chin & Wm. David Salisbury & Abhijit Gopal & Peter R. Newsted, 2003. "Authors' Reply to Allport and Kerler (2003)," Information Systems Research, INFORMS, vol. 14(4), pages 360-363, December.
    9. Lee, Lorraine & Petter, Stacie & Fayard, Dutch & Robinson, Shani, 2011. "On the use of partial least squares path modeling in accounting research," International Journal of Accounting Information Systems, Elsevier, vol. 12(4), pages 305-328.
    10. Jean-François Stich & Monideepa Tarafdar & Patrick Stacey & Cary L. Cooper, 2019. "E-mail load, workload stress and desired e-mail load: a cybernetic approach," Post-Print hal-01881947, HAL.

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