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Examining the impact of deep learning technology capability on manufacturing firms: moderating roles of technology turbulence and top management support

Author

Listed:
  • Sheshadri Chatterjee

    (Indian Institute of Technology Kharagpur)

  • Ranjan Chaudhuri

    (National Institute of Industrial Engineering (NITIE))

  • Demetris Vrontis

    (University of Nicosia)

  • Thanos Papadopoulos

    (University of Kent)

Abstract

Data science can create value by extracting structured and unstructured data using an appropriate algorithm. Data science operations have undergone drastic changes because of accelerated deep learning progress. Deep learning is an advanced process of machine learning algorithm. Its simple process of presenting data to the system is sharply different from other machine learning processes. Deep learning uses advanced analytics to solve complex problems for accurate business decisions. Deep leaning is considered a promising area for creating additional value in firms’ productivity and sustainability as they develop their smart manufacturing activities. Deep learning capability can help a manufacturing firm’s predictive maintenance, quality control, and anomaly detection. The impact of deep learning technology capability on manufacturing firms is an underexplored area in the literature. With this background, the purpose of this study is to examine the impact of deep learning technology capability on manufacturing firms with moderating roles of deep learning related technology turbulence and top management support of the manufacturing firms. With the help of literature review and theories, a conceptual model has been prepared, which is then validated with the PLS-SEM technique analyzing 473 responses from employees of manufacturing firms. The study shows the significance of deep learning technology capability on smart manufacturing systems. Also, the study highlights the moderating impacts of top management team (TMT) support as well as the moderating impacts of deep learning related technology turbulence on smart manufacturing systems.

Suggested Citation

  • Sheshadri Chatterjee & Ranjan Chaudhuri & Demetris Vrontis & Thanos Papadopoulos, 2024. "Examining the impact of deep learning technology capability on manufacturing firms: moderating roles of technology turbulence and top management support," Annals of Operations Research, Springer, vol. 339(1), pages 163-183, August.
    • Handle: RePEc:spr:annopr:v:339:y:2024:i:1:d:10.1007_s10479-021-04505-2
    DOI: 10.1007/s10479-021-04505-2
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    1. Florian Schuberth & Jörg Henseler & Theo K. Dijkstra, 2018. "Partial least squares path modeling using ordinal categorical indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 9-35, January.
    2. Wamba, Samuel Fosso & Dubey, Rameshwar & Gunasekaran, Angappa & Akter, Shahriar, 2020. "The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism," International Journal of Production Economics, Elsevier, vol. 222(C).
    3. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    4. Bhaveshkumar Nandanram Pasi & Subhash K. Mahajan & Santosh B. Rane, 2020. "The current sustainability scenario of Industry 4.0 enabling technologies in Indian manufacturing industries," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 70(5), pages 1017-1048, December.
    5. David J. Teece, 2012. "Dynamic Capabilities: Routines versus Entrepreneurial Action," Journal of Management Studies, Wiley Blackwell, vol. 49(8), pages 1395-1401, December.
    6. Harmancioglu, Nukhet & Grinstein, Amir & Goldman, Arieh, 2010. "Innovation and performance outcomes of market information collection efforts: The role of top management team involvement," International Journal of Research in Marketing, Elsevier, vol. 27(1), pages 33-43.
    7. Michael Song & Cornelia Droge & Sangphet Hanvanich & Roger Calantone, 2005. "Marketing and technology resource complementarity: an analysis of their interaction effect in two environmental contexts," Strategic Management Journal, Wiley Blackwell, vol. 26(3), pages 259-276, March.
    8. Thakur, Ramendra & Angriawan, Arifin & Summey, John H., 2016. "Technological opinion leadership: The role of personal innovativeness, gadget love, and technological innovativeness," Journal of Business Research, Elsevier, vol. 69(8), pages 2764-2773.
    9. Kraus, Mathias & Feuerriegel, Stefan & Oztekin, Asil, 2020. "Deep learning in business analytics and operations research: Models, applications and managerial implications," European Journal of Operational Research, Elsevier, vol. 281(3), pages 628-641.
    10. Vineet Jain & Puneeta Ajmera, 2020. "Modelling the enablers of industry 4.0 in the Indian manufacturing industry," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 70(6), pages 1233-1262, June.
    11. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    12. 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.
    13. Mishra, Anubhav & Maheswarappa, Satish S. & Maity, Moutusy & Samu, Sridhar, 2018. "Adolescent's eWOM intentions: An investigation into the roles of peers, the Internet and gender," Journal of Business Research, Elsevier, vol. 86(C), pages 394-405.
    14. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    15. Jajja, Muhammad Shakeel Sadiq & Chatha, Kamran Ali & Farooq, Sami, 2018. "Impact of supply chain risk on agility performance: Mediating role of supply chain integration," International Journal of Production Economics, Elsevier, vol. 205(C), pages 118-138.
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