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Data-driven digital transformation and the implications for antifragility in the humanitarian supply chain

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  • Bag, Surajit
  • Rahman, Muhammad Sabbir
  • Srivastava, Gautam
  • Giannakis, Mihalis
  • Foropon, Cyril

Abstract

Digital technologies often create confusion among donors involved in the humanitarian supply chain (HSC). Specifically, donors are unsure about whether to rely on their application. Moreover, while studies have continuously discussed improving resilience in HSC, scant studies have sought to improve antifragility in the HSC. Hence, this study aimed to investigate the impact of donor confidence in digital technology on antifragility in the HSC through the mediating influence of digital technology applications in sourcing, material flow, and distribution, with trust in digital technologies and perceived overall effective digital technology governance playing moderating roles. The theoretical model was developed using resource dependence theory. Primary data were collected by surveying 296 nongovernmental organizations (NGOs) involved in humanitarian operations. To test the measurement and structural models, partial least squares–based structural equation modeling (PLS-SEM) was applied in SmartPLS. The data supported all of the hypotheses. This study bridges the gap between theory and practice by highlighting that digital technology application in sourcing, material flow, and distribution is a critical mediator in building an antifragile HSC. Moreover, donor confidence in digital technologies is critical, which NGOs should keep in mind when making any digital technology-related decisions. They should focus on improving trust in digital technologies as well as the perception of the effectiveness of digital technology governance to remove obstacles related to digital technology applications for digital transformation in the HSC.

Suggested Citation

  • Bag, Surajit & Rahman, Muhammad Sabbir & Srivastava, Gautam & Giannakis, Mihalis & Foropon, Cyril, 2023. "Data-driven digital transformation and the implications for antifragility in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:proeco:v:266:y:2023:i:c:s0925527323002918
    DOI: 10.1016/j.ijpe.2023.109059
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    as
    1. Ramezani, Javaneh & Camarinha-Matos, Luis M., 2020. "Approaches for resilience and antifragility in collaborative business ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    2. Gupta, Shivam & Modgil, Sachin & Kumar, Ajay & Sivarajah, Uthayasankar & Irani, Zahir, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," International Journal of Production Economics, Elsevier, vol. 254(C).
    3. Rameshwar Dubey & Angappa Gunasekaran & David J. Bryde & Yogesh K. Dwivedi & Thanos Papadopoulos, 2020. "Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3381-3398, June.
    4. Sachin S. Kamble & Angappa Gunasekaran, 2020. "Big data-driven supply chain performance measurement system: a review and framework for implementation," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 65-86, January.
    5. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Manisha Tiwari & Yogesh Dwivedi & Sarah Schiffling, 2021. "An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1586-1605, March.
    6. 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.
    7. Erica Gralla & Jarrod Goentzel & Charles Fine, 2014. "Assessing Trade-offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences," Production and Operations Management, Production and Operations Management Society, vol. 23(6), pages 978-989, June.
    8. Dubey, Rameshwar & Bryde, David J. & Dwivedi, Yogesh K. & Graham, Gary & Foropon, Cyril, 2022. "Impact of artificial intelligence-driven big data analytics culture on agility and resilience in humanitarian supply chain: A practice-based view," International Journal of Production Economics, Elsevier, vol. 250(C).
    9. 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).
    10. 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.
    11. Benjamin R. Tukamuhabwa & Mark Stevenson & Jerry Busby & Marta Zorzini, 2015. "Supply chain resilience: definition, review and theoretical foundations for further study," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5592-5623, September.
    12. Balcik, Burcu & Beamon, Benita M. & Krejci, Caroline C. & Muramatsu, Kyle M. & Ramirez, Magaly, 2010. "Coordination in humanitarian relief chains: Practices, challenges and opportunities," International Journal of Production Economics, Elsevier, vol. 126(1), pages 22-34, July.
    13. Rameshwar Dubey & David James Bryde & Cyril Foropon & Gary Graham & Mihalis Giannakis & Deepa Bhatt Mishra, 2020. "Agility in humanitarian supply chain: An organizational information processing perspective and relational view," Post-Print hal-03539292, HAL.
    14. Hamann-Lohmer, Jacob & Bendig, Miriam & Lasch, Rainer, 2023. "Investigating the impact of digital transformation on relationship and collaboration dynamics in supply chains and manufacturing networks – A multi-case study," International Journal of Production Economics, Elsevier, vol. 262(C).
    15. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    16. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    17. Alessandra Cozzolino, 2021. "Platforms Enhancing the Engagement of the Private Sector in Humanitarian Relief Operations," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    18. Jaya Priyadarshini & Rajesh Kr Singh & Ruchi Mishra & Surajit Bag, 2022. "Investigating the interaction of factors for implementing additive manufacturing to build an antifragile supply chain: TISM-MICMAC approach," Operations Management Research, Springer, vol. 15(1), pages 567-588, June.
    19. Oliveira, Fabio & Kakabadse, Nada & Khan, Nadeem, 2022. "Board engagement with digital technologies: A resource dependence framework," Journal of Business Research, Elsevier, vol. 139(C), pages 804-818.
    20. Li, Feng, 2020. "The digital transformation of business models in the creative industries: A holistic framework and emerging trends," Technovation, Elsevier, vol. 92.
    21. Shivam Gupta & Sachin Modgil & Ajay Kumar & Uthayasankar Sivarajah & Zahir Irani, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," Post-Print hal-04325638, HAL.
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