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Ordered Weighted Averaging for the Evaluation of Urban Inequality in Sao Sebastiao Do Paraiso Publisher



Liborio MP1 ; Rabieidastjerdi H2, 6 ; Brunsdon C3 ; Pinto MDR1 ; Fusco E4 ; Vidoli F5
Authors
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Authors Affiliations
  1. 1. Pontifical Catholic University of Minas Gerais, Belo Horizonte, 30535-012, Brazil
  2. 2. School of Architecture, Planning and Environmental Policy & CeADAR (Ireland's National Centre for Applied Data Analytics & AI), University College Dublin (UCD), Dublin, Ireland
  3. 3. National Centre for Geocomputation, Maynooth University, Co. Kildare, Maynooth, Ireland
  4. 4. Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence, Florence, Italy
  5. 5. Department of Economics, Society and Politics, University of Urbino, Urbino, Italy
  6. 6. Social Determinants of Health Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Cities Published:2024


Abstract

Urban inequality is a highly complex and multidimensional phenomenon that involves several aspects, such as education, urban mobility, environment, technological or digital exclusion, food deserts, and inequalities in the distribution of urban facilities. Due to its impact on the living conditions of populations residing in the most deprived and unhealthy areas of cities, inequality in the distribution of urban public services is a particularly relevant issue. The measurement of urban inequality to discuss possible policy implications requires the synthesis of its sub-dimensions. Therefore, this paper applies the multicriteria method called ordered weighted averaging to evaluate the distribution of public goods in census tracts of the city of Sao Sebastiao do Paraiso in Brazil. In particular, ordered weighted averaging, which allows the calibration of different degrees of non-compensability between sub-indicators and considers the heterogeneity of the census tracts, permits the evaluation of both positive and negative aspects of the studied phenomena. Two different composite indicators are calculated: the “Tax Index,” which analyses the presence of public goods and the benefits in terms of property value and well-being that their presence generates, and the “Infrastructure Index,” which examines the areas with the greatest lack of infrastructure. © 2024 Elsevier Ltd