Abstract
Purpose: The aim of this research is to improve the responsiveness of the healthcare network of a large city to a major earthquake, by applying a combined methodology to reduce human suffering and death. Design/methodology/approach: Scenario analysis, a non-linear programming (NLP) model, and the analytical network process are sequentially applied to find the “best location pattern”. Findings: When considering the occurrence of major earthquakes in cities with high population density, as a rule of thumb, the location of healthcare facilities should prioritize areas characteristically overcrowded and/or that were built based on poor standards of seismic resistance. Research limitations/implications: The proposed research design does not include a cost criterion in the set of decision variables involved. Furthermore, the results derived from the NLP-model are restricted by the input simulation data. Practical implications: The performance of the “best location pattern” is compared with the current location of healthcare facilities in terms of their distances to the affected zones. Metropolis areas worldwide with similar conditions to the city under consideration could be benefited from applying the general methodology for relocation of healthcare facilities described in this research. Originality/value: This research implements a diverse combination of methodologies to examine the problem of relocating of healthcare facilities in a large city in the wake of an assumed earthquake. In addition, to the best of authors' knowledge, this is the first study of its kind that proposes improvements in the responsiveness of the healthcare facilities' network in the city in question.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 220-248 |
| Number of pages | 29 |
| Journal | Journal of Humanitarian Logistics and Supply Chain Management |
| Volume | 12 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 22 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Management Information Systems
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