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Article
Publication date: 2 December 2021

Inanç Barutcu and Yusuf Tansel Ic

The authors present a location selection model for the field hospital to build after a possible earthquake in Ankara, Turkey using the VIKOR method.

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Abstract

Purpose

The authors present a location selection model for the field hospital to build after a possible earthquake in Ankara, Turkey using the VIKOR method.

Design/methodology/approach

Companies or governments that make location selection decisions to improve their performance in new investment decisions for different service industries. On the other hand, disasters, especially earthquakes, force the governments to evaluate their existing potentialities and develop action plans to improve their middle and long-term preparations. This paper proposes a VIKOR method-based location selection model for the field hospital to build after a possible earthquake. Also, the authors present a methodology using the VIKOR method that how government agencies take action for the field hospital's location selection process via VIKOR methodology.

Findings

The modeling and application results show that the field hospital's location selection decision-making process improves considerably using the VIKOR model. This paper shows that the proposed VIKOR-based model can rank alternatives suitability at various criteria targeting to minimize the possible earthquake's impact and obtains a single overall ranking score to select the best alternative.

Research limitations/implications

The study does not consider the uncertain nature of the field hospital selection problem. The application part is restricted to the Ankara case. But the proposed model can easily extend for different locations in the world.

Originality/value

This paper presents the multi-criteria decision-making (MCDM) framework study of the establishment of field hospitals and demonstrates its importance when criteria diversity is restricted.

Details

International Journal of Emergency Services, vol. 11 no. 1
Type: Research Article
ISSN: 2047-0894

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