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Adoption of Artificial Intelligence and Cutting-Edge Technologies for Production System Sustainability: A Moderator-Mediation Analysis

Author

Listed:
  • Sheshadri Chatterjee

    (Indian Institute of Technology)

  • Ranjan Chaudhuri

    (Indian Institute of Management)

  • Sachin Kamble

    (EDHEC Business School)

  • Shivam Gupta

    (NEOMA Business School)

  • Uthayasankar Sivarajah

    (University of Bradford)

Abstract

Cutting-edge technologies like big data analytics (BDA), artificial intelligence (AI), quantum computing, blockchain, and digital twins have a profound impact on the sustainability of the production system. In addition, it is argued that turbulence in technology could negatively impact the adoption of these technologies and adversely impact the sustainability of the production system of the firm. The present study has demonstrated that the role of technological turbulence as a moderator could impact the relationships between the sustainability the of production system with its predictors. The study further analyses the mediating role of operational sustainability which could impact the firm performance. A theoretical model has been developed that is underpinned by dynamic capability view (DCV) theory and firm absorptive capacity theory. This model was verified by PLS-SEM with 412 responses from various manufacturing firms in India. There exists a positive and significant influence of AI and other cutting-edge technologies for keeping the production system sustainable.

Suggested Citation

  • Sheshadri Chatterjee & Ranjan Chaudhuri & Sachin Kamble & Shivam Gupta & Uthayasankar Sivarajah, 2023. "Adoption of Artificial Intelligence and Cutting-Edge Technologies for Production System Sustainability: A Moderator-Mediation Analysis," Information Systems Frontiers, Springer, vol. 25(5), pages 1779-1794, October.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:5:d:10.1007_s10796-022-10317-x
    DOI: 10.1007/s10796-022-10317-x
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    1. Alexandre Dolgui & Manoj Kumar Tiwari & Yerasani Sinjana & Sri Krishna Kumar & Young-Jun Son, 2018. "Optimising integrated inventory policy for perishable items in a multi-stage supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 902-925, January.
    2. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2020. "Reconfigurable supply chain: the X-network," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4138-4163, July.
    3. Sachin S. Kamble & Angappa Gunasekaran, 2020. "Big data-driven supply chain performance measurement system: a review and framework for implementation," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 65-86, January.
    4. Shahriar Akter & Samuel Fosso Wamba, 2016. "Big data analytics in E-commerce: a systematic review and agenda for future research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 173-194, May.
    5. Longoni, Annachiara & Golini, Ruggero & Cagliano, Raffaella, 2014. "The role of New Forms of Work Organization in developing sustainability strategies in operations," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 147-160.
    6. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Thrassou, Alkis & Vrontis, Demetris, 2021. "Antecedents and consequences of knowledge hiding: The moderating role of knowledge hiders and knowledge seekers in organizations," Journal of Business Research, Elsevier, vol. 128(C), pages 303-313.
    7. Jacob Biamonte & Peter Wittek & Nicola Pancotti & Patrick Rebentrost & Nathan Wiebe & Seth Lloyd, 2017. "Quantum machine learning," Nature, Nature, vol. 549(7671), pages 195-202, September.
    8. Suaad Jassem & Zarina Zakaria & Anna Che Azmi, 2021. "Sustainability balanced scorecard architecture and environmental performance outcomes: a systematic review," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 71(5), pages 1728-1760, February.
    9. 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.
    10. Klaus Werner Schmidt & Öncü Hazır, 2019. "Formulation and solution of an optimal control problem for industrial project control," Annals of Operations Research, Springer, vol. 280(1), pages 337-350, September.
    11. Kamble, Sachin S. & Gunasekaran, Angappa & Ghadge, Abhijeet & Raut, Rakesh, 2020. "A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs- A review and empirical investigation," International Journal of Production Economics, Elsevier, vol. 229(C).
    12. Oscar Rodríguez-Espíndola & Soumyadeb Chowdhury & Ahmad Beltagui & Pavel Albores, 2020. "The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, Artificial Intelligence and 3D printing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(15), pages 4610-4630, July.
    13. Joseph Geunes & Yiqiang Su, 2020. "Single-period assortment and stock-level decisions for dual sales channels with capacity limits and uncertain demand," International Journal of Production Research, Taylor & Francis Journals, vol. 58(18), pages 5579-5600, September.
    14. Paul Rimba & An Binh Tran & Ingo Weber & Mark Staples & Alexander Ponomarev & Xiwei Xu, 2020. "Correction to: Quantifying the Cost of Distrust: Comparing Blockchain and Cloud Services for Business Process Execution," Information Systems Frontiers, Springer, vol. 22(2), pages 509-510, April.
    15. 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).
    16. R.P. Mohanty & Anand Prakash, 2017. "Searching for definitions and boundaries in sustainable production system," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 27(1), pages 122-143.
    17. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    18. Alexandre Dolgui & Dmitry Ivanov & Suresh P. Sethi & Boris Sokolov, 2019. "Scheduling in production, supply chain and Industry 4.0 systems by optimal control: fundamentals, state-of-the-art and applications," International Journal of Production Research, Taylor & Francis Journals, vol. 57(2), pages 411-432, January.
    19. 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.
    20. Angappa Gunasekaran & Yahaya Y. Yusuf & Ezekiel O. Adeleye & Thanos Papadopoulos, 2018. "Agile manufacturing practices: the role of big data and business analytics with multiple case studies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 385-397, January.
    21. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    22. Ye Wang & Teodoro Alamo & Vicenç Puig & Gabriela Cembrano, 2018. "Economic Model Predictive Control with Nonlinear Constraint Relaxation for the Operational Management of Water Distribution Networks," Energies, MDPI, vol. 11(4), pages 1-20, April.
    23. Frank Lozada-Contreras & Karen L. Orengo-Serra & Maria Sanchez-Jauregui, 2021. "Adaptive customer relationship management contingency model under disruptive events," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 19(2), pages 198-219, May.
    24. Anindita Chakravarty & Rajdeep Grewal & V. Sambamurthy, 2013. "Information Technology Competencies, Organizational Agility, and Firm Performance: Enabling and Facilitating Roles," Information Systems Research, INFORMS, vol. 24(4), pages 976-997, December.
    25. David J. Teece, 2012. "Dynamic Capabilities: Routines versus Entrepreneurial Action," Journal of Management Studies, Wiley Blackwell, vol. 49(8), pages 1395-1401, December.
    26. Oprișan Oana & Tileagă Cosmin & Niţu Claudiu Valentin, 2017. "Artificial Intelligence - A New Field of Computer Science Which Any Business Should Consider," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 356-360, June.
    27. Gimenez, Cristina & Sierra, Vicenta & Rodon, Juan, 2012. "Sustainable operations: Their impact on the triple bottom line," International Journal of Production Economics, Elsevier, vol. 140(1), pages 149-159.
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