Journal
GEOJOURNAL
Volume 87, Issue 5, Pages 3507-3528Publisher
SPRINGER
DOI: 10.1007/s10708-021-10445-y
Keywords
Hospital site selection; Geographic information system (GIS); Multi-criteria decision analysis (MCDA); Analytic hierarchy process (AHP); Fuzzy AHP (FAHP); Sensitivity analysis
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Identification and ranking of hospital sites for planning and development of health infrastructure are crucial. This research compares the use of AHP and FAHP methods in selecting new hospital sites, suggesting that FAHP may be a better approach. The study highlights the importance of sensitivity analysis and constant variation in site ranking when weight change analysis is performed using AHP.
Identification of hospital sites and their ranking is important for the planning and development of any country's health infrastructure. The site selection problem is a typical multi-criteria decision making problem involving multiple stakeholders and their interests. Multi-Criteria Decision Analysis (MCDA) is a promising approach to solve a location-based problem due to the constitution of various criteria involved in decision making. In this research, eleven criterion are chosen which are classified under three main criteria; socio-economic, geographical and environmental. This research aims to identify the appropriate MCDA method for the selection of a new hospital sites. Here, two MCDA methods named Analytical Hierarchy Process (AHP) and Fuzzy AHP (FAHP) are used. Further, Geographical Information System (GIS) based MCDA methodology is proposed in this paper. The results obtained with both AHP and FAHP methods are compared. This comparison is based on criterion rankings, proposed hospital locations and sensitivity analysis. The main difference in results is shown in the result of sensitivity analysis in which constant variation in site ranking is obtained when weight change analysis is performed using AHP. The FAHP result shows only one variation in site ranking after a change in weight from +10 to +20%. The result suggests that FAHP may be a better approach to the hospital site selection problem.
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