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Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model

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  • Chatterjee, Sheshadri
  • Rana, Nripendra P.
  • Dwivedi, Yogesh K.
  • Baabdullah, Abdullah M.

Abstract

This study aims to identify how environmental, technological, and social factors influence the adoption of Industry 4.0 in the context of digital manufacturing. The Industry 4.0 era has brought a breakthrough in advanced technologies in fields such as nanotechnology, quantum computing, biotechnology, artificial intelligence, robotics, the Internet of Things, fifth-generation wireless technology, fully autonomous vehicles, 3D printing and so on. In this study, we attempted to identify the socioenvironmental and technological factors that influence the adoption of artificial intelligence embedded technology by digital manufacturing and production organizations. In doing so, the extended technology-organization-environment (TOE) framework is used to explore the applicability of Industry 4.0. A conceptual model was proposed that used an integrated technology acceptance model (TAM)-TOE model and was tested using survey-based data collected from 340 employees of small, medium and large organizations. The results highlight that all the relationships, except organizational readiness, organizational compatibility and partner support on perceived ease of use, were found to be significant in the context of digital manufacturing and production organizations. The results further indicated that leadership support acts as a countable factor to moderate such an adoption.

Suggested Citation

  • Chatterjee, Sheshadri & Rana, Nripendra P. & Dwivedi, Yogesh K. & Baabdullah, Abdullah M., 2021. "Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    • Handle: RePEc:eee:tefoso:v:170:y:2021:i:c:s0040162521003127
    DOI: 10.1016/j.techfore.2021.120880
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    1. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Manisha Tiwari & Yogesh Dwivedi & Sarah Schiffling, 2021. "An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1586-1605, March.
    2. Navid Asgari & Kulwant Singh & Will Mitchell, 2017. "Alliance portfolio reconfiguration following a technological discontinuity," Strategic Management Journal, Wiley Blackwell, vol. 38(5), pages 1062-1081, May.
    3. Yanfeng Zheng & Haibin Yang, 2015. "Does Familiarity Foster Innovation? The Impact of Alliance Partner Repeatedness on Breakthrough Innovations," Journal of Management Studies, Wiley Blackwell, vol. 52(2), pages 213-230, March.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    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. Alexandre Moeuf & Robert Pellerin & Samir Lamouri & Simon Tamayo-Giraldo & Rodolphe Barbaray, 2018. "The industrial management of SMEs in the era of Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1118-1136, February.
    7. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    8. Richard F. J. Haans & Constant Pieters & Zi-Lin He, 2016. "Thinking about U: Theorizing and testing U- and inverted U-shaped relationships in strategy research," Strategic Management Journal, Wiley Blackwell, vol. 37(7), pages 1177-1195, July.
    9. Reischauer, Georg, 2018. "Industry 4.0 as policy-driven discourse to institutionalize innovation systems in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 26-33.
    10. Bag, Surajit & Pretorius, Jan Ham Christiaan & Gupta, Shivam & Dwivedi, Yogesh K., 2021. "Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    11. Qian Hu & Yaobin Lu & Zhao Pan & Yeming Gong & Zhiling Yang, 2021. "Can AI artifacts influence human cognition? : The effects of artificial autonomy in intelligent personal assistants," Post-Print hal-03188233, HAL.
    12. Jabbour, Charbel Jose Chiappetta & Jabbour, Ana Beatriz Lopes de Sousa & Sarkis, Joseph & Filho, Moacir Godinho, 2019. "Unlocking the circular economy through new business models based on large-scale data: An integrative framework and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 546-552.
    13. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    14. Sven-Vegard Buer & Jan Ola Strandhagen & Felix T. S. Chan, 2018. "The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2924-2940, April.
    15. Chen, Lei-Da & Tan, Justin, 2004. "Technology Adaptation in E-commerce:: Key Determinants of Virtual Stores Acceptance," European Management Journal, Elsevier, vol. 22(1), pages 74-86, February.
    16. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    17. Chidlow, Agnieszka & Ghauri, Pervez N. & Yeniyurt, Sengun & Cavusgil, S. Tamer, 2015. "Establishing rigor in mail-survey procedures in international business research," Journal of World Business, Elsevier, vol. 50(1), pages 26-35.
    18. Se-Joon Hong & Kar Yan Tam, 2006. "Understanding the Adoption of Multipurpose Information Appliances: The Case of Mobile Data Services," Information Systems Research, INFORMS, vol. 17(2), pages 162-179, June.
    19. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
    20. Metallo, Concetta & Agrifoglio, Rocco & Schiavone, Francesco & Mueller, Jens, 2018. "Understanding business model in the Internet of Things industry," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 298-306.
    21. Ilias O. Pappas & Patrick Mikalef & Michail N. Giannakos & John Krogstie & George Lekakos, 2018. "Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies," Information Systems and e-Business Management, Springer, vol. 16(3), pages 479-491, August.
    22. George Baryannis & Sahar Validi & Samir Dani & Grigoris Antoniou, 2019. "Supply chain risk management and artificial intelligence: state of the art and future research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2179-2202, April.
    23. Peter Géczy & Noriaki Izumi & Kôiti Hasida, 2012. "Cloudsourcing: Managing Cloud Adoption," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 6(2), pages 57-70.
    24. Shareef, Mahmud Akhter & Kumar, Vinod & Dwivedi, Yogesh K. & Kumar, Uma & Akram, Muhammad Shakaib & Raman, Ramakrishnan, 2021. "A new health care system enabled by machine intelligence: Elderly people's trust or losing self control," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    25. 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.
    26. Frank, Alejandro G. & Mendes, Glauco H.S. & Ayala, Néstor F. & Ghezzi, Antonio, 2019. "Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 341-351.
    27. Sung, Tae Kyung, 2018. "Industry 4.0: A Korea perspective," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 40-45.
    28. Chen, Jiandong & Gao, Ming & Mangla, Sachin Kumar & Song, Malin & Wen, Jie, 2020. "Effects of technological changes on China's carbon emissions," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    29. Clay M. Voorhees & Michael K. Brady & Roger Calantone & Edward Ramirez, 2016. "Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies," Journal of the Academy of Marketing Science, Springer, vol. 44(1), pages 119-134, January.
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