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Examining the Influence of Big Data Analytics and Additive Manufacturing on Supply Chain Risk Control and Resilience: An Empirical Study

Author

Listed:
  • S. Gupta
  • S. Bag
  • S. Modgil
  • Ana Beatriz Lopes de Sousa Jabbour

    (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie)

  • A. Kumar

Abstract

Drawing upon the contingent resource-based perspective of supply chain resilience, this study tests whether fourth industrial revolution (4IR) technologies such as big data analytics (BDA) and additive manufacturing (AM) control risks and develop supply chain (SC) resilience under flexible orientation and control orientation. Primary data was collected from 190 samples in India and the PLS-SEM technique was then used to perform data analysis. The findings indicate that big data analytics and additive manufacturing can aid in risk control and in turn improve the SC resilience of a firm and further minimize the propagation of the supply chain ripple effect in case of disruption. This study sheds light on firms' 4IR resources (BDA and AM) that can be useful in developing risk control capabilities to deal with disruptions in supply chains. BDA, in particular, impacts risk intelligence, whereas AM impacts both preparedness and intelligence risk control. Distinguishing between BDA and AM is therefore important when firms are considering which technology to adopt. Therefore, for the sample analyzed, BDA has a prominent role in building risk control and resilience capabilities. These findings are an important contribution to SC risk management theory and this study also creates new research opportunities. Firms need to adopt collaborative planning, forecasting, smart manufacturing, and replenishments initiatives for vulnerable supply chain activities to reduce the SC ripple effect. Lastly, flexible, real-time production helps reduce the SC ripple effect. \textcopyright 2022 Elsevier Ltd

Suggested Citation

  • S. Gupta & S. Bag & S. Modgil & Ana Beatriz Lopes de Sousa Jabbour & A. Kumar, 2022. "Examining the Influence of Big Data Analytics and Additive Manufacturing on Supply Chain Risk Control and Resilience: An Empirical Study," Post-Print hal-04276056, HAL.
    • Handle: RePEc:hal:journl:hal-04276056
    DOI: 10.1016/j.cie.2022.108629
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    Cited by:

    1. Montree Chinsomboon & Pallop Piriyasurawong, 2024. "Supply Chain Management for Pre-Teacher Preparation of Higher Education in Thailand Model," Higher Education Studies, Canadian Center of Science and Education, vol. 14(1), pages 1-8, February.
    2. Padhi, Sidhartha S. & Mukherjee, Soumyatanu & Edwin Cheng, T.C., 2024. "Optimal investment decision for industry 4.0 under uncertainties of capability and competence building for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 267(C).
    3. Lin, Jiabao & Fan, Yuchen, 2024. "Seeking sustainable performance through organizational resilience: Examining the role of supply chain integration and digital technology usage," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    4. Munir, Muhammad Adeel & Hussain, Amjad & Farooq, Muhammad & Rehman, Ateekh Ur & Masood, Tariq, 2024. "Building resilient supply chains: Empirical evidence on the contributions of ambidexterity, risk management, and analytics capability," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

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