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Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development

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  • Bag, Surajit
  • Gupta, Shivam
  • Kumar, Sameer

Abstract

Industry 4.0 technologies provide digital solutions for the automation of manufacturing. In circular economy-based models, the resources stay in the system as it experiences one of the 10 R (Refuse, Rethink, Reduce, Reuse, Repair, Refurbish, Remanufacture, Repurpose, Recycle, and Recover) processes. These 10 R processes require the development of advanced manufacturing capabilities; however, 10 R processes suffer from various challenges and can be effectively overcome through Industry 4.0 technological applications. Although literature has indicated the use of various Industry 4.0 technologies, little information is available about firms’ views on the degree of Industry 4.0 application in the 10 R based advanced manufacturing area and its ability to achieve sustainable development. The current study aspires to examine how great an effect Industry 4.0 adoption has on 10 R advanced manufacturing capabilities and its outcome on sustainable development under the moderating effect of an Industry 4.0 delivery system. Practice-based view and Dynamic capability view theories are used to conceptualise the theoretical model. The research team statistically validated the theoretical model considering 124 data points that were collected using an online survey with a structured questionnaire. The findings point out that the path degree of Industry 4.0 adoption and 10 R advanced manufacturing capabilities are statistically significant. 10 R advanced manufacturing capabilities are found to have a positive influence on sustainable development outcomes. Industry 4.0 delivery system has a moderating effect on the path degree of I4.0 implementation and 10 R advanced manufacturing capabilities. The study concludes with key take away points for managers.

Suggested Citation

  • Bag, Surajit & Gupta, Shivam & Kumar, Sameer, 2021. "Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development," International Journal of Production Economics, Elsevier, vol. 231(C).
  • Handle: RePEc:eee:proeco:v:231:y:2021:i:c:s0925527320302103
    DOI: 10.1016/j.ijpe.2020.107844
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    as
    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Law, Kris M.Y. & Gunasekaran, Angappa, 2012. "Sustainability development in high-tech manufacturing firms in Hong Kong: Motivators and readiness," International Journal of Production Economics, Elsevier, vol. 137(1), pages 116-125.
    3. Ren, Shengce & Eisingerich, Andreas B. & Tsai, Huei-Ting, 2015. "How do marketing, research and development capabilities, and degree of internationalization synergistically affect the innovation performance of small and medium-sized enterprises (SMEs)? A panel data," International Business Review, Elsevier, vol. 24(4), pages 642-651.
    4. Frank, Alejandro Germán & Dalenogare, Lucas Santos & Ayala, Néstor Fabián, 2019. "Industry 4.0 technologies: Implementation patterns in manufacturing companies," International Journal of Production Economics, Elsevier, vol. 210(C), pages 15-26.
    5. 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.
    6. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    7. David J. Teece, 2007. "Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance," Strategic Management Journal, Wiley Blackwell, vol. 28(13), pages 1319-1350, December.
    8. Raafat, Feraidoon, 2002. "A comprehensive bibliography on justification of advanced manufacturing systems," International Journal of Production Economics, Elsevier, vol. 79(3), pages 197-208, October.
    9. Amoako-Gyampah, Kwasi & Acquaah, Moses, 2008. "Manufacturing strategy, competitive strategy and firm performance: An empirical study in a developing economy environment," International Journal of Production Economics, Elsevier, vol. 111(2), pages 575-592, February.
    10. Tortorella, Guilherme Luz & Cawley Vergara, Alejandro Mac & Garza-Reyes, Jose Arturo & Sawhney, Rapinder, 2020. "Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers," International Journal of Production Economics, Elsevier, vol. 219(C), pages 284-294.
    11. Lucianetti, Lorenzo & Chiappetta Jabbour, Charbel Jose & Gunasekaran, Angappa & Latan, Hengky, 2018. "Contingency factors and complementary effects of adopting advanced manufacturing tools and managerial practices: Effects on organizational measurement systems and firms' performance," International Journal of Production Economics, Elsevier, vol. 200(C), pages 318-328.
    12. Kolk, Ans & van Tulder, Rob, 2010. "International business, corporate social responsibility and sustainable development," International Business Review, Elsevier, vol. 19(2), pages 119-125, April.
    13. Hannibal, Martin & Knight, Gary, 2018. "Additive manufacturing and the global factory: Disruptive technologies and the location of international business," International Business Review, Elsevier, vol. 27(6), pages 1116-1127.
    14. Govindan, Kannan & Shankar, K. Madan & Kannan, Devika, 2020. "Achieving sustainable development goals through identifying and analyzing barriers to industrial sharing economy: A framework development," International Journal of Production Economics, Elsevier, vol. 227(C).
    15. Zhang, Yufeng & Yang, Zhibo & Zhang, Tao, 2018. "Strategic resource decisions to enhance the performance of global engineering services," International Business Review, Elsevier, vol. 27(3), pages 678-700.
    16. Benjamin T. Hazen & Diane A. Mollenkopf & Yacan Wang, 2017. "Remanufacturing for the Circular Economy: An Examination of Consumer Switching Behavior," Business Strategy and the Environment, Wiley Blackwell, vol. 26(4), pages 451-464, May.
    17. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    18. Ana Beatriz Lopes de Sousa Jabbour & Charbel Jose Chiappetta Jabbour & Moacir Godinho Filho & David Roubaud, 2018. "Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations," Annals of Operations Research, Springer, vol. 270(1), pages 273-286, November.
    19. Chan, Hing Kai & Griffin, James & Lim, Jia Jia & Zeng, Fangli & Chiu, Anthony S.F., 2018. "The impact of 3D Printing Technology on the supply chain: Manufacturing and legal perspectives," International Journal of Production Economics, Elsevier, vol. 205(C), pages 156-162.
    20. 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.
    21. Delic, Mia & Eyers, Daniel R., 2020. "The effect of additive manufacturing adoption on supply chain flexibility and performance: An empirical analysis from the automotive industry," International Journal of Production Economics, Elsevier, vol. 228(C).
    22. Gunnar Prause & Gunnar Prause & Sina Atari, 2017. "On sustainable production networks for Industry 4.0," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 4(4), pages 421-431, June.
    23. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    24. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    25. Sung, Tae Kyung, 2018. "Industry 4.0: A Korea perspective," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 40-45.
    26. Fahy, John, 2002. "A resource-based analysis of sustainable competitive advantage in a global environment," International Business Review, Elsevier, vol. 11(1), pages 57-77, February.
    27. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    28. 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.
    29. Li Da Xu & Eric L. Xu & Ling Li, 2018. "Industry 4.0: state of the art and future trends," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2941-2962, April.
    30. Gunnar Prause & Sina Atari, 2017. "On sustainable production networks for Industry 4.0," Post-Print hal-01860909, HAL.
    31. Kawai, Norifumi & Strange, Roger & Zucchella, Antonella, 2018. "Stakeholder pressures, EMS implementation, and green innovation in MNC overseas subsidiaries," International Business Review, Elsevier, vol. 27(5), pages 933-946.
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