A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator

Pereira Libório, Matheus; Ekel, Petr Iakovlevitch; Laudares, Sandro; Martins, Carlos Augusto Paiva da Silva

doi:10.1016/j.mex.2024.102575

MethodsX

2024

DOI: 10.1016/j.mex.2024.102575

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A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator

Matheus Pereira Libório,

Petr Iakovlevitch Ekel,

Sandro Laudares

et al.

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Cited by 1 publication

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Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

Samani,

Alesheikh,

Karimi

et al. 2024

Sustainability

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This study provides an innovative collaborative spatial decision support system (SDSS) that aims to ensure an equitable spatial distribution of healthcare services. Evaluating the equality of access to health services across different geographical areas is important, as it requires the analysis of various criteria such as the proximity of health centres and hospitals (HCHs), the quality of services offered, connectivity to primary roads, the availability of public transportation hubs, and the density and distribution patterns of HCHs. This purpose is accomplished via the use of geographic information systems (GIS) and multi-criteria decision analysis (MCDA) methods. The proposed model includes the weights of the criteria, which are determined through the ordered weighted average (OWA) and evaluated based on their ORness, which ranges from 0 to 1. Furthermore, this model is improved by the best–worst fuzzy method (F-BWM). This approach produces a spatial map that clearly shows the equity of healthcare systems in urban environments. The findings show that the maximum score observed in this study was 0.38% (with an ORness value of 1), whilst the minimum score recorded was 0.28%. In the most severe scenario (ORness = 0), over 70% of the region shows different degrees of fairness, ranging from moderate to suitable and very suitable conditions. Governments and health authorities can use this information strategically to allocate resources and address inequities in access to healthcare facilities.

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Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

Samani,

Alesheikh,

Karimi

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

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A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator

Cited by 1 publication

References 35 publications

Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

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