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Gauging the Technology Acceptance of Manufacturing Employees: A New Measure for Pre-Implementation

Author

Listed:
  • Kristen Haynes

    (Industrial & Systems Engineering, Auburn University, Auburn, AL 36849, USA)

  • Gregory Harris

    (Industrial & Systems Engineering, Auburn University, Auburn, AL 36849, USA)

  • Mark C. Schall

    (Industrial & Systems Engineering, Auburn University, Auburn, AL 36849, USA)

  • Jia Liu

    (Industrial & Systems Engineering, Auburn University, Auburn, AL 36849, USA)

  • Jerry Davis

    (Industrial & Systems Engineering, Auburn University, Auburn, AL 36849, USA)

Abstract

Recent technological advances are bringing about the digitalization of manufacturing, enabled by introducing and integrating new and improved technologies into existing processes and activities. Integrating advanced technologies into the workplace can have a positive effect on manufacturing efficiency and competitiveness, as well as sustainability and environmental impact. Employee acceptance of these new technologies is critical for manufacturing organizations to achieve these goals. Unfortunately, a notable deficiency of tools to assess the readiness of an employee work group or organization to accept a new technology exists. The objective of this study was to develop and validate a new tool for gauging employee technology acceptance in a pre-implementation decision context known as the Technology Acceptance in a Manufacturing Environment (TAME). Statistical validation measures were conducted on survey responses from 823 respondents across seven locations of one large organization. The results indicate that TAME is appropriate for assessing readiness for technology acceptance among manufacturing workers with little to no training or knowledge of the technology being considered for implementation (R 2 = 86%). TAME can facilitate the organizational assessment of employee perception of new technologies before implementation, increasing the chances of a successful launch. This research results in the first known application of technology acceptance models in a pre-implementation context in a manufacturing environment.

Suggested Citation

  • Kristen Haynes & Gregory Harris & Mark C. Schall & Jia Liu & Jerry Davis, 2024. "Gauging the Technology Acceptance of Manufacturing Employees: A New Measure for Pre-Implementation," Sustainability, MDPI, vol. 16(12), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:12:p:4969-:d:1412342
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    References listed on IDEAS

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    1. Pfeiffer, Sabine, 2016. "Robots, Industry 4.0 and humans, or why assembly work is more than routine work," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 6(2 (Articl), pages 1-26.
    2. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    3. Metcalfe, Stan & Ramlogan, Ronnie, 2008. "Innovation systems and the competitive process in developing economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(2), pages 433-446, May.
    4. 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.
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