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Logistics service provider selection for disaster preparation: a socio-technical systems perspective

Author

Listed:
  • Seongtae Kim

    (Swiss Federal Institute of Technology Zurich)

  • M. Ramkumar

    (Swiss Federal Institute of Technology Zurich)

  • Nachiappan Subramanian

    (University of Sussex)

Abstract

Since 1990s, the world has seen a lot of advances in providing humanitarian aid through sophisticated logistics operations. The current consensus seems to be that humanitarian relief organizations (HROs) can improve their relief operations by collaborating with logistics service providers (CLSPs) in the commercial sector. The question remains: how can HROs select the most appropriate CLSP for disaster preparation? Despite its practical significance, no explicit effort has been done to identify the criteria/factors in prioritizing and selecting a CLSP for disaster relief. The present study aims to address this gap by consolidating the list of criteria from a socio-technical systems (STS) perspective. Then, to handle the interdependence among the criteria derived from the STS, we develop a hybrid multi-criteria decision making model for CLSP selection in the disaster preparedness stage. The proposed model is then evaluated by a real-life case study, providing insights into the decision-makers in both HROs and CLSPs.

Suggested Citation

  • Seongtae Kim & M. Ramkumar & Nachiappan Subramanian, 2019. "Logistics service provider selection for disaster preparation: a socio-technical systems perspective," Annals of Operations Research, Springer, vol. 283(1), pages 1259-1282, December.
    • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-018-03129-3
    DOI: 10.1007/s10479-018-03129-3
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    4. Choi, Tsan-Ming, 2020. "Innovative “Bring-Service-Near-Your-Home” operations under Corona-Virus (COVID-19/SARS-CoV-2) outbreak: Can logistics become the Messiah?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    5. Sha Fan & Hengjie Zhang & Huali Tang, 2019. "A Linguistic Hierarchy Model with Self-Confidence Preference Relations and Its Application in Co-Regulation of Food Safety in China," IJERPH, MDPI, vol. 16(16), pages 1-21, August.
    6. Libiao Bai & Kanyin Zheng & Zhiguo Wang & Jiale Liu, 2022. "Service provider portfolio selection for project management using a BP neural network," Annals of Operations Research, Springer, vol. 308(1), pages 41-62, January.
    7. Fabiana Santos Lima & Ricardo Villarroel Dávalos & Lucila M. S. Campos & Andréa Cristina Trierweiller, 2022. "Framework proposal to support the suppliers’ selection of Humanitarian assistance items: a Flood Case Study in Brazil," Annals of Operations Research, Springer, vol. 315(1), pages 317-340, August.
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    9. Vafadarnikjoo, Amin & Chalvatzis, Konstantinos & Botelho, Tiago & Bamford, David, 2023. "A stratified decision-making model for long-term planning: Application in flood risk management in Scotland," Omega, Elsevier, vol. 116(C).
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    11. R. Krishankumar & P. P. Amritha & K. S. Ravichandran, 2022. "RETRACTED ARTICLE: An integrated fuzzy decision model for prioritization of barriers affecting sustainability adoption within supply chains under unknown weight context," Operations Management Research, Springer, vol. 15(3), pages 1010-1027, December.
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