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The adoption of digital technologies in supply chains: Drivers, process and impact

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  • Yang, Miying
  • Fu, Mingtao
  • Zhang, Zihan

Abstract

Digital technologies have been extensively studied in academic research and industry. However, little is known about the adoption of digital technologies in manufacturing firms at a supply chain level. This paper aims to understand why and how manufacturing firms adopt digital technologies, and the impact of the adoption on supply chains. The study uses literature review method, identifies the main drivers of manufacturing firms adopting digital technologies (why), develops a new model of the adoption process (how), and synthesizes the impact of the adoption on supply chains into four aspects (what): supply chain efficiency, supply chain structure, sustainability and innovation. The paper then proposes a conceptual framework consisting of driver, process and impact, and discusses their inter-relationships. The study identifies that the technological intelligence and supply chain cooperation are two important factors and proposes a two-dimentional levels of adopting digital technologies according to their low-to-high degrees. The proposed framework, in particular the levels of digital technology adoption, are novel to the existing literature. Each of the three parts of the framework and their inter-relationships lays a foundation for further empirical studies in this field. This study also provides guidance for practitioners adopting digital technologies for supply chain management and developing appropriate business strategies at different digitalization levels.

Suggested Citation

  • Yang, Miying & Fu, Mingtao & Zhang, Zihan, 2021. "The adoption of digital technologies in supply chains: Drivers, process and impact," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
  • Handle: RePEc:eee:tefoso:v:169:y:2021:i:c:s0040162521002274
    DOI: 10.1016/j.techfore.2021.120795
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    1. Fernando E. Garcia-Muiña & Rocío González-Sánchez & Anna Maria Ferrari & Davide Settembre-Blundo, 2018. "The Paradigms of Industry 4.0 and Circular Economy as Enabling Drivers for the Competitiveness of Businesses and Territories: The Case of an Italian Ceramic Tiles Manufacturing Company," Social Sciences, MDPI, vol. 7(12), pages 1-31, December.
    2. Bogers, Marcel & Hadar, Ronen & Bilberg, Arne, 2016. "Additive manufacturing for consumer-centric business models: Implications for supply chains in consumer goods manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 225-239.
    3. Min-Ren Yan & Kuo-Ming Chien & Tai-Ning Yang, 2016. "Green Component Procurement Collaboration for Improving Supply Chain Management in the High Technology Industries: A Case Study from the Systems Perspective," Sustainability, MDPI, vol. 8(2), pages 1-16, January.
    4. K. L. Choy & G. T. S. Ho & C. K. H. Lee, 2017. "A RFID-based storage assignment system for enhancing the efficiency of order picking," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 111-129, January.
    5. Caro, Felipe & Sadr, Ramin, 2019. "The Internet of Things (IoT) in retail: Bridging supply and demand," Business Horizons, Elsevier, vol. 62(1), pages 47-54.
    6. Shoufeng Ji & Qi Sun, 2017. "Low-Carbon Planning and Design in B&R Logistics Service: A Case Study of an E-Commerce Big Data Platform in China," Sustainability, MDPI, vol. 9(11), pages 1-27, November.
    7. 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.
    8. 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.
    9. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    10. Ding, Huiping & Guo, Baochun & Liu, Zhishuo, 2011. "Information sharing and profit allotment based on supply chain cooperation," International Journal of Production Economics, Elsevier, vol. 133(1), pages 70-79, September.
    11. Akhtar, Pervaiz & Khan, Zaheer & Tarba, Shlomo & Jayawickrama, Uchitha, 2018. "The Internet of Things, dynamic data and information processing capabilities, and operational agility," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 307-316.
    12. Yadegaridehkordi, Elaheh & Hourmand, Mehdi & Nilashi, Mehrbakhsh & Shuib, Liyana & Ahani, Ali & Ibrahim, Othman, 2018. "Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 199-210.
    13. Melo, Sandra & Macedo, Joaquim & Baptista, Patrícia, 2019. "Capacity-sharing in logistics solutions: A new pathway towards sustainability," Transport Policy, Elsevier, vol. 73(C), pages 143-151.
    14. Hendrik S. Birkel & Johannes W. Veile & Julian M. Müller & Evi Hartmann & Kai-Ingo Voigt, 2019. "Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers," Sustainability, MDPI, vol. 11(2), pages 1-27, January.
    15. Marcel Papert & Alexander Pflaum, 2017. "Development of an Ecosystem Model for the Realization of Internet of Things (IoT) Services in Supply Chain Management," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(2), pages 175-189, May.
    16. Shirish Jeble & Rameshwar Dubey & Stephen J. Childe & Thanos Papadopoulos & David Roubaud & Anand Prakash, 2018. "Impact of big data and predictive analytics capability on supply chain sustainability," Post-Print hal-02061341, HAL.
    17. Rodolphe Durand & Robert M. Grant & Tammy L. Madsen & David P. McIntyre & Arati Srinivasan, 2017. "Networks, platforms, and strategy: Emerging views and next steps," Strategic Management Journal, Wiley Blackwell, vol. 38(1), pages 141-160, January.
    18. Emma Brandon-Jones & Brian Squire & Chad W. Autry & Kenneth J. Petersen, 2014. "A Contingent Resource-Based Perspective of Supply Chain Resilience and Robustness," Journal of Supply Chain Management, Institute for Supply Management, vol. 50(3), pages 55-73, July.
    19. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 2018. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 763-788, April.
    20. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    21. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    22. Jaegul Lee & Nicholas Berente, 2012. "Digital Innovation and the Division of Innovative Labor: Digital Controls in the Automotive Industry," Organization Science, INFORMS, vol. 23(5), pages 1428-1447, October.
    23. Yu, Wantao & Chavez, Roberto & Jacobs, Mark A. & Feng, Mengying, 2018. "Data-driven supply chain capabilities and performance: A resource-based view," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 371-385.
    24. 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.
    25. 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.
    26. Davila, Antonio & Gupta, Mahendra & Palmer, Richard, 2003. "Moving Procurement Systems to the Internet:: the Adoption and Use of E-Procurement Technology Models," European Management Journal, Elsevier, vol. 21(1), pages 11-23, February.
    27. Hagelaar, Geoffrey J.L.F. & van der Vorst, Jack G.A.J., 2001. "Environmental Supply Chain Management: Using Life Cycle Assessment To Structure Supply Chains," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 4(4), pages 1-14.
    28. Surajit Bag, 2017. "Big Data and Predictive Analysis is Key to Superior Supply Chain Performance: A South African Experience," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 10(2), pages 66-84, April.
    29. D’Ignazio, Alessio & Giovannetti, Emanuele, 2014. "Continental differences in the clusters of integration: Empirical evidence from the digital commodities global supply chain networks," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 486-497.
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