Evidence-based models to support humanitarian operations and crisis management

Authors

  • Ashraf Labib University of Portsmouth, PBS, Operations & Systems Management, United Kingdom
  • M. Reza Abdi Manufacturing Systems Analyst Additive Design Ltd. Broad Gate, United Kingdom
  • Sara Hadleigh-Dunn University of Portsmouth, PBS, Strategy, Enterprise, and Innovation, United Kingdom
  • Morteza Yazdani Universidad Autónoma de Madrid, Spain

DOI:

https://doi.org/10.31181/dmame030222100y

Keywords:

Operations management, analytic hierarchy process, humanitarian operations management, organizational learning, fault tree analysis.

Abstract

Term humanitarian operation (HO) is a concept extracted from the need to perform supply chain operations in special, risky, and critical events. Understanding and implementing operations under such conditions is a strategic responsibility. Due to its importance, we design a framework for organizational learning from major incidents through root cause analysis. The case studies contain a purely industrial disaster at Bhopal and a mixed industrial-natural disaster at Fukushima. An approach is proposed for organizational safety by incorporating techniques related to root cause analysis applied to one case study. Moreover, we employ the analytic hierarchy process, which is applied to the second case study. We incorporate operations management models to analyse data related to two major disasters. The case studies in two organizations are then compared with respect to their causes and effects along with the models adopted to support HO& crisis management (CM). The contribution is the use of hybrid modelling techniques to analyse disasters in terms of humanitarian operations and crisis management.

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Published

2022-03-20

How to Cite

Labib, A., Abdi, M. R. ., Hadleigh-Dunn, S., & Yazdani, M. (2022). Evidence-based models to support humanitarian operations and crisis management. Decision Making: Applications in Management and Engineering, 5(1), 113–134. https://doi.org/10.31181/dmame030222100y