IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11939-d667127.html
   My bibliography  Save this article

Investigating the Drivers of Supply Chain Resilience in the Wake of the COVID-19 Pandemic: Empirical Evidence from an Emerging Economy

Author

Listed:
  • Mohammad Ali Yamin

    (Department of Human Resources Management, Collage of Business, University of Jeddah, Jeddah 23454, Saudi Arabia)

Abstract

The COVID-19 pandemic has disrupted supply chain operations globally. Nevertheless, resilient firms have the capacity to combat an unprecedented situation with the right strategic approach. The current research has developed an integrated research model that combines factors such as supply chain intelligence, supply chain communication, leadership commitment, risk management orientation, supply chain capability and network complexity to investigate supply chain resilience. The research model of this study was empirically tested with 309 responses collected from supply chain managers. Results revealed that supply chain resilience is measured with supply chain intelligence, supply chain communication, leadership commitment, risk management orientation, supply chain capability and network complexity and demonstrated a substantial variance R 2 of 0.548% towards supply chain resilience. Practically, this study suggests that supply chain managers should focus on factors such as big data analytics, risk management orientation,1 supply chain communication and leadership commitment to enhance supply chain resilience and sustainable supply chain performance.

Suggested Citation

  • Mohammad Ali Yamin, 2021. "Investigating the Drivers of Supply Chain Resilience in the Wake of the COVID-19 Pandemic: Empirical Evidence from an Emerging Economy," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11939-:d:667127
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11939/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/21/11939/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    2. Belhadi, Amine & Kamble, Sachin & Jabbour, Charbel Jose Chiappetta & Gunasekaran, Angappa & Ndubisi, Nelson Oly & Venkatesh, Mani, 2021. "Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. GROTSCH, Volker M. & BLOME, Constantin & SCHLEPER, Martin C., 2013. "Antecedents of proactive supply chain risk management - a contingency theory perspective," LIDAM Reprints CORE 2490, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Lin, Cheng-Chang & Wang, Tsai-Hsin, 2011. "Build-to-order supply chain network design under supply and demand uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1162-1176, September.
    5. Brusset, Xavier & Teller, Christoph, 2017. "Supply chain capabilities, risks, and resilience," International Journal of Production Economics, Elsevier, vol. 184(C), pages 59-68.
    6. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    7. Podsakoff, Philip M. & Bommer, William H. & Podsakoff, Nathan P. & MacKenzie, Scott B., 2006. "Relationships between leader reward and punishment behavior and subordinate attitudes, perceptions, and behaviors: A meta-analytic review of existing and new research," Organizational Behavior and Human Decision Processes, Elsevier, vol. 99(2), pages 113-142, March.
    8. 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.
    9. Samar Rahi & Mazuri Abd Ghani & Abdul Hafaz Ngah, 2020. "Factors propelling the adoption of internet banking: the role of e-customer service, website design, brand image and customer satisfaction," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 33(4), pages 549-569.
    10. 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.
    11. Jenny Rowley, 2014. "Designing and using research questionnaires," Management Research Review, Emerald Group Publishing Limited, vol. 37(3), pages 308-330, March.
    12. Rameshwar Dubey & Angappa Gunasekaran & Stephen J. Childe & Samuel Fosso Wamba & David Roubaud & Cyril Foropon, 2021. "Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 110-128, January.
    13. Zhang, Qingyu & Cao, Mei, 2018. "Exploring antecedents of supply chain collaboration: Effects of culture and interorganizational system appropriation," International Journal of Production Economics, Elsevier, vol. 195(C), pages 146-157.
    14. Henri Barki & Alain Pinsonneault, 2005. "A Model of Organizational Integration, Implementation Effort, and Performance," Organization Science, INFORMS, vol. 16(2), pages 165-179, April.
    15. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    16. Schmitt, Amanda J., 2011. "Strategies for customer service level protection under multi-echelon supply chain disruption risk," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1266-1283, September.
    17. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    18. Mohammed Ali Yousef Yamin & Mohamed Sultan Mahasneh, 2018. "The Impact of Values-based Leadership on Ethical Loyalty in Saudi Arabian Health Organizations," International Review of Management and Marketing, Econjournals, vol. 8(3), pages 6-13.
    19. Yu, Wantao & Zhao, Gen & Liu, Qi & Song, Yongtao, 2021. "Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lorenzo Bruno Prataviera & Alessandro Creazza & Marco Melacini & Fabrizio Dallari, 2022. "Heading for Tomorrow: Resilience Strategies for Post-COVID-19 Grocery Supply Chains," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    2. Ali Falah Dalain, 2023. "Nurturing Employee Engagement at Workplace and Organizational Innovation in Time of Crisis With Moderating Effect of Servant Leadership," SAGE Open, , vol. 13(2), pages 21582440231, May.
    3. Catherine Marinagi & Panagiotis Reklitis & Panagiotis Trivellas & Damianos Sakas, 2023. "The Impact of Industry 4.0 Technologies on Key Performance Indicators for a Resilient Supply Chain 4.0," Sustainability, MDPI, vol. 15(6), pages 1-31, March.
    4. Wei Cao & Xifu Wang, 2022. "Brittleness Evolution Model of the Supply Chain Network Based on Adaptive Agent Graph Theory under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(19), pages 1-24, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
    2. Francesco Badia & Fabio Donato, 2022. "Opportunities and risks in using big data to support management control systems: A multiple case study," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(3), pages 39-63.
    3. Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. Chih-Hung Hsu & Ming-Ge Li & Ting-Yi Zhang & An-Yuan Chang & Shu-Zhen Shangguan & Wan-Ling Liu, 2022. "Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework," Mathematics, MDPI, vol. 10(8), pages 1-35, April.
    5. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    6. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    7. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    8. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    9. Candice WALLS & Brian BARNARD, 2020. "Success Factors of Big Data to Achieve Organisational Performance: Theoretical Perspectives," Expert Journal of Business and Management, Sprint Investify, vol. 8(1), pages 1-16.
    10. Wamba, Samuel Fosso & Dubey, Rameshwar & Gunasekaran, Angappa & Akter, Shahriar, 2020. "The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism," International Journal of Production Economics, Elsevier, vol. 222(C).
    11. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    12. Papanagnou, Christos & Seiler, Andreas & Spanaki, Konstantina & Papadopoulos, Thanos & Bourlakis, Michael, 2022. "Data-driven digital transformation for emergency situations: The case of the UK retail sector," International Journal of Production Economics, Elsevier, vol. 250(C).
    13. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    14. Pan Liu & Shu-ping Yi, 2018. "Investment decision-making and coordination of a three-stage supply chain considering Data Company in the Big Data era," Annals of Operations Research, Springer, vol. 270(1), pages 255-271, November.
    15. Jianlan Zhong & Han Cheng & Fu Jia, 2024. "Supply chain resilience capability factors in agri-food supply chains," Operations Management Research, Springer, vol. 17(3), pages 850-868, September.
    16. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    17. 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.
    18. Liu, Hua & Xu, Xiaoping & Cheng, T.C.E. & Yu, Yugang, 2024. "Building resilience or maintaining robustness: Insights from relational view and information processing perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    19. Iftikhar, Anas & Purvis, Laura & Giannoccaro, Ilaria, 2021. "A meta-analytical review of antecedents and outcomes of firm resilience," Journal of Business Research, Elsevier, vol. 135(C), pages 408-425.
    20. S. Vijayakumar Bharathi, 2017. "Prioritizing and Ranking the Big Data Information Security Risk Spectrum," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 183-201, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11939-:d:667127. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.