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Driving Factors and Mechanisms of AMT Application Levels for Equipment Manufacturing Enterprises: Based on Programmatic Grounded Theory

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  • Guilian Wang

    (School of Management Science and Engineering, Tianjin University of Finance and Economics, Tianjin 300222, China
    Development Center for Innovation and Entrepreneurship, Tianjin Sino-German University of Applied Sciences, Tianjin 300350, China)

  • Liyan Zhang

    (Center for Innovation and Entrepreneurship, Tianjin University of Finance and Economics, Tianjin 300222, China)

  • Jing Guo

    (Business School, Tianjin University of Finance and Economics, Tianjin 300222, China)

Abstract

As a major part of the global manufacturing industry attaining technological upgrades, the adoption and application of advanced manufacturing technology (AMT) plays a vital role in the development of enterprises. Thus, it is of the utmost significance to examine the driving factors that affect AMT application levels in equipment manufacturing enterprises. Through extensive interviews, the use of the qualitative research method of grounded theory, and the three-stage coding of the interview data from intelligent manufacturing pilot demonstration enterprises and projects, this study identified the key influencing factors for the AMT application levels of equipment manufacturing enterprises. We obtained 46 concepts and extracted 18 key categories and 6 main categories. Then, the logical relationships between the main categories were established. Finally, a driving factor model for the AMT application levels of equipment manufacturing enterprises was constructed. The results reveal that the driving factors that affect the AMT application levels of equipment manufacturing enterprises can be summarized as capability factors (technical capability, market capability, and management capability), motivation factors (material incentives and development incentives), and opportunity factors (external stakeholders). Overall, this study proposed a mechanism from the three aspects of ability, motivation, and opportunity.

Suggested Citation

  • Guilian Wang & Liyan Zhang & Jing Guo, 2022. "Driving Factors and Mechanisms of AMT Application Levels for Equipment Manufacturing Enterprises: Based on Programmatic Grounded Theory," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8415-:d:859103
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    1. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    2. Nola Hewitt-Dundas, 2004. "The Adoption Of Advanced Manufacturing Technology And Innovation Strategy In Small Firms," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 17-36.
    3. Samford, Steven & Warrian, Peter & Goracinova, Elena, 2017. "Public and private goods in the development of additive manufacturing capacity," Business and Politics, Cambridge University Press, vol. 19(3), pages 482-509, September.
    4. Yeh, Ching-Chiang & Chen, Yi-Fan, 2018. "Critical success factors for adoption of 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 209-216.
    5. Müller, Julian Marius & Buliga, Oana & Voigt, Kai-Ingo, 2018. "Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 2-17.
    6. Rakesh Narain & R.C. Yadav & Joseph Sarkis, 2007. "Investment justification of advanced manufacturing technology: a review," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 3(1), pages 41-73.
    7. Lindbeck, Assar & Snower, Dennis J, 2000. "Multitask Learning and the Reorganization of Work: From Tayloristic to Holistic Organization," Journal of Labor Economics, University of Chicago Press, vol. 18(3), pages 353-376, July.
    8. Qinghua Fu & Abdul Aziz Abdul Rahman & Hui Jiang & Jawad Abbas & Ubaldo Comite, 2022. "Sustainable Supply Chain and Business Performance: The Impact of Strategy, Network Design, Information Systems, and Organizational Structure," Sustainability, MDPI, vol. 14(3), pages 1-15, January.
    9. Kimberly A. Bates & Susan D. Amundson & Roger G. Schroeder & William T. Morris, 1995. "The Crucial Interrelationship Between Manufacturing Strategy and Organizational Culture," Management Science, INFORMS, vol. 41(10), pages 1565-1580, October.
    10. Bourke, Jane & Roper, Stephen, 2016. "AMT adoption and innovation: An investigation of dynamic and complementary effects," Technovation, Elsevier, vol. 55, pages 42-55.
    11. Dangayach, G. S. & Deshmukh, S. G., 2003. "Evidence of manufacturing strategies in Indian industry: a survey," International Journal of Production Economics, Elsevier, vol. 83(3), pages 279-298, March.
    12. Kiel, Daniel & Arnold, Christian & Voigt, Kai-Ingo, 2017. "The influence of the Industrial Internet of Things on business models of established manufacturing companies – A business level perspective," Technovation, Elsevier, vol. 68(C), pages 4-19.
    13. Waldeck, Nancy E. & Leffakis, Zachary M., 2007. "HR perceptions and the provision of workforce training in an AMT environment: An empirical study," Omega, Elsevier, vol. 35(2), pages 161-172, April.
    14. Ancarani, Alessandro & Di Mauro, Carmela & Mascali, Francesco, 2019. "Backshoring strategy and the adoption of Industry 4.0: Evidence from Europe," Journal of World Business, Elsevier, vol. 54(4), pages 360-371.
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