Supply Chain Resilience Strategies in the Digital Era
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DOI:
https://doi.org/10.67228/3071642X/IJCFDE-2018PII5N2QPublished 08-03-2018
Supply Chain Resilience, Digital Transformation, Industry 4.0, Risk Management, Big Data Analytics, Blockchain, IoT Issue
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ArticlesHow to Cite
Bianchi, M. (2018). Supply Chain Resilience Strategies in the Digital Era. International Journal of Commerce, Finance and Digital Economy, 1(2), 01-16. https://doi.org/10.67228/3071642X/IJCFDE-2018PII5N2QAbstract
The global supply chains have also become susceptible to disruptions that are inflicted due to the geopolitical tensions, pandemics, cyber threats, climate change, and market volatility. With the advent of the digital era, the development of the supply chain in organizations has been revolutionized in the way they are designing, managing, and recovering their supply chains. There are new opportunities offered by digital technologies in order to improve supply chain resilience (SCR), created by artificial intelligence, blockchain, Internet of Things (IoT), big data analytics, and cloud computing. The current paper is the extensive exploration of the supply chain resilience in the digital era with the focus on the way the digitalization process allows identifying the risks in advance, implementing the adaptive response mechanisms, and providing quick recovery opportunities. The article methodically examines the available literature to formulate the main dimensions of resilience and digital enablers alongside strategic models used. It suggests a systematic approach, which includes both digital maturity assessment and resiliency capability modeling as well as performance evaluation metrics. The empirical evidence draws your attention to the issue of digital technologies and their role in supply chain robustness, agility, and sustainability. Findings show transforming her supply chains with digital capabilities allows having better disruption preparedness, led to lower recovery time, and enhanced decision-making quality. The article has a value to both theory and practice as it summarizes constructs of digital resilience and has practical implications to managers interested in developing resilient supply chains that meet the needs of future consumers.
References
[1] Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1–14.
[2] Sheffi, Y., & Rice, J. B. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 47(1), 41–48.
[3] Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124–143.
[4] Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, 31(1), 1–21.
[5] Tukamuhabwa, B. R., Stevenson, M., Busby, J., & Zorzini, M. (2015). Supply chain resilience: Definition, review and theoretical foundations. International Journal of Production Research, 53(18), 5592–5623.
[6] Wieland, A., & Wallenburg, C. M. (2013). The influence of relational competencies on supply chain resilience. Journal of Business Logistics, 34(1), 14–28.
[7] Choi, T. M., Wallace, S. W., & Wang, Y. (2018). Big data analytics in operations management. Production and Operations Management, 27(10), 1868–1883.
[8] Papadopoulos, T., Baltas, K. N., & Balta, M. E. (2017). The use of digital technologies for supply chain resilience. International Journal of Information Management, 37(1), 59–70.
[9] Hohenstein, N. O., Feisel, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience. International Journal of Physical Distribution & Logistics Management, 45(1/2), 90–117.
[10] Brusset, X., & Teller, C. (2017). Supply chain capabilities, risks, and resilience. International Journal of Production Economics, 184, 59–68.
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How to Cite
Bianchi, M. (2018). Supply Chain Resilience Strategies in the Digital Era. International Journal of Commerce, Finance and Digital Economy, 1(2), 01-16. https://doi.org/10.67228/3071642X/IJCFDE-2018PII5N2Q
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