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Application and Impact of New Technologies in the Supply Chain Management During COVID-19 Pandemic: A Systematic Literature Review

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  • Muhammad Rahies Khan
  • Amir Manzoor

Abstract

Purpose: The purpose of this study is to examine the application of emerging technologies during the COVID-19 pandemic and their impact on supply chain management. Design/Methodology/approach: A systematic literature review was conducted to identify the application and impact of new technologies on supply chain management. Findings: The findings revealed that blockchain technology, IoT, artificial intelligence, big data analytics, cloud computing, 5G and smartphone application, and the use of robots and drones are the key technologies used during COVID-19 in supply chain management, and they showed a substantial impact on the supply chain resilience, agility, and adaptability. Key barriers include higher investment costs, lack of government regulations and support, and deficiency of skilled and technical human resources faced during these technologies' implementation. Practical Implications: This study evaluated the systematic review through the google scholar search engine and only adopted peer-reviewed scholarly journals, conference proceedings, and opinion papers. The study provides valuable insight to supply chain officials, policymakers, and governments. The emerging technologies have the crucial potential to resolve the supply chain disruptions, if they are addressed seriously. Originality/ value: This study provides social implications by providing insight regarding the improved standards of living. This study is the first to address emerging technologies in supply chain management during COVID-19.

Suggested Citation

  • Muhammad Rahies Khan & Amir Manzoor, 2021. "Application and Impact of New Technologies in the Supply Chain Management During COVID-19 Pandemic: A Systematic Literature Review," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 277-292.
  • Handle: RePEc:ers:ijebaa:v:ix:y:2021:i:2:p:277-292
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    References listed on IDEAS

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    1. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    2. Dmitry Ivanov, 2018. "Supply Chain Risk Management: Bullwhip Effect and Ripple Effect," International Series in Operations Research & Management Science, in: Structural Dynamics and Resilience in Supply Chain Risk Management, chapter 0, pages 19-44, Springer.
    3. Hamed Mamani & Stephen E. Chick & David Simchi-Levi, 2013. "A Game-Theoretic Model of International Influenza Vaccination Coordination," Management Science, INFORMS, vol. 59(7), pages 1650-1670, July.
    4. Landon Kleis & Paul Chwelos & Ronald V. Ramirez & Iain Cockburn, 2012. "Information Technology and Intangible Output: The Impact of IT Investment on Innovation Productivity," Information Systems Research, INFORMS, vol. 23(1), pages 42-59, March.
    5. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    6. Jelena Končar & Aleksandar Grubor & Radenko Marić & Sonja Vučenović & Goran Vukmirović, 2020. "Setbacks to IoT Implementation in the Function of FMCG Supply Chain Sustainability during COVID-19 Pandemic," Sustainability, MDPI, vol. 12(18), pages 1-21, September.
    7. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    8. Hoda Parvin & Shervin Beygi & Jonathan E. Helm & Peter S. Larson & Mark P. Van Oyen, 2018. "Distribution of Medication Considering Information, Transshipment, and Clustering: Malaria in Malawi," Production and Operations Management, Production and Operations Management Society, vol. 27(4), pages 774-797, April.
    9. Büyüktahtakın, İ. Esra & des-Bordes, Emmanuel & Kıbış, Eyyüb Y., 2018. "A new epidemics–logistics model: Insights into controlling the Ebola virus disease in West Africa," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1046-1063.
    10. Robert J. David & Shin‐Kap Han, 2004. "A systematic assessment of the empirical support for transaction cost economics," Strategic Management Journal, Wiley Blackwell, vol. 25(1), pages 39-58, January.
    11. Riccardo Aldrighetti & Ilenia Zennaro & Serena Finco & Daria Battini, 2019. "Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 81-102, December.
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