IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i7p6171-d1115187.html
   My bibliography  Save this article

A Decision Framework for Identifying Methods to Construct Stable Composite Indicators That Capture the Concept of Multidimensional Social Phenomena: The Case of Social Exclusion

Author

Listed:
  • Matheus Pereira Libório

    (Graduate Program in Computer Science, Pontifical Catholic University of Minas Gerais, Belo Horizonte 30535-901, Brazil)

  • Alexandre Magno Alves Diniz

    (Graduate Program in Geography, Pontifical Catholic University of Minas Gerais, Belo Horizonte 30535-901, Brazil)

  • Hamidreza Rabiei-Dastjerd

    (School of Architecture, Planning, and Environmental Policy & CeADAR, University College Dublin (UCD), D04 V1W8 Dublin, Ireland
    Social Determinants of Health Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran)

  • Oseias da Silva Martinuci

    (Department of Geography, Maringá State University, Maringá 87020-900, Brazil)

  • Carlos Augusto Paiva da Silva Martins

    (Graduate Program in Computer Science, Pontifical Catholic University of Minas Gerais, Belo Horizonte 30535-901, Brazil)

  • Petr Iakovlevitch Ekel

    (Graduate Program in Computer Science, Pontifical Catholic University of Minas Gerais, Belo Horizonte 30535-901, Brazil)

Abstract

This research proposes a decision framework that allows for the identification of the most suitable methods to construct stable composite indicators that capture the concept of multidimensional social phenomena. This decision framework is applied to discover which method among six best represents the social exclusion of eight medium-sized Brazilian cities. The results indicate that space is important in the definition and performance of the method, and ease methods to apply present the best performance. However, one of them fails to capture the concept of the multidimensional phenomenon in two cities. The research makes six important contributions to the literature. First, it offers a decision framework for choosing the best-fit method to construct a composite social indicator. Second, it shows to what extent geographic space matters in defining the best-fit method. Third, it identifies the best-fit method regarding stability and linkage with the conceptually most significant indicator of social exclusion. Fourth, it reveals the methods to be avoided, given their poor performance. Fifth, it indicates the mathematical properties that best represent composite social phenomena. Sixth, it illuminates the debate on social exclusion from a geographical and public policy perspective.

Suggested Citation

  • Matheus Pereira Libório & Alexandre Magno Alves Diniz & Hamidreza Rabiei-Dastjerd & Oseias da Silva Martinuci & Carlos Augusto Paiva da Silva Martins & Petr Iakovlevitch Ekel, 2023. "A Decision Framework for Identifying Methods to Construct Stable Composite Indicators That Capture the Concept of Multidimensional Social Phenomena: The Case of Social Exclusion," Sustainability, MDPI, vol. 15(7), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:6171-:d:1115187
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/7/6171/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/7/6171/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charles J. Kowalski, 1972. "On the Effects of Non‐Normality on the Distribution of the Sample Product‐Moment Correlation Coefficient," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(1), pages 1-12, March.
    2. Itismita Mohanty & Martin Edvardsson & Annie Abello & Deanna Eldridge, 2016. "Child Social Exclusion Risk and Child Health Outcomes in Australia," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-16, May.
    3. Marta Kuc-Czarnecka & Samuele Lo Piano & Andrea Saltelli, 2020. "Quantitative Storytelling in the Making of a Composite Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 775-802, June.
    4. Carlo Drago, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach," Economies, MDPI, vol. 9(4), pages 1-17, October.
    5. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2018. "OECD: One or Many? Ranking Countries with a Composite Well-Being Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(3), pages 847-869, October.
    6. Fusco, Elisa & Vidoli, Francesco & Sahoo, Biresh K., 2018. "Spatial heterogeneity in composite indicator: A methodological proposal," Omega, Elsevier, vol. 77(C), pages 1-14.
    7. Matteo Mazziotta & Adriano Pareto, 2019. "Use and Misuse of PCA for Measuring Well-Being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 451-476, April.
    8. Jens S. Dangschat, 2009. "Space Matters — Marginalization and Its Places," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 33(3), pages 835-840, September.
    9. Ajit Bhalla & Frédéric Lapeyre, 1997. "Social Exclusion: Towards an Analytical and Operational Framework," Development and Change, International Institute of Social Studies, vol. 28(3), pages 413-433, July.
    10. Matheus Pereira Libório & Lívia Maria Leite Silva & Petr Iakovlevitch Ekel & Letícia Ribeiro Figueiredo & Patrícia Bernardes, 2022. "Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1073-1099, December.
    11. Tim Schwanen & Donggen Wang, 2014. "Well-Being, Context, and Everyday Activities in Space and Time," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 104(4), pages 833-851, July.
    12. Carlo Drago, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator," Working Papers 2021.21, Fondazione Eni Enrico Mattei.
    13. Alfredo Cartone & Domenica Panzera, 2021. "Deprivation at local level: Practical problems and policy implications for the province of Milan," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 43-61, February.
    14. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
    15. Hamidreza Rabiei‐Dastjerdi & Stephen A. Matthews, 2021. "Who gets what, where, and how much? Composite index of spatial inequality for small areas in Tehran," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 191-205, February.
    16. Sinéad Keogh & Stephen O’Neill & Kieran Walsh, 2021. "Composite Measures for Assessing Multidimensional Social Exclusion in Later Life: Conceptual and Methodological Challenges," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(2), pages 389-410, June.
    17. Salvatore Greco & Alessio Ishizaka & Benedetto Matarazzo & Gianpiero Torrisi, 2018. "Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions," Regional Studies, Taylor & Francis Journals, vol. 52(4), pages 585-600, April.
    18. Rui Xiao & Guofeng Wang & Meng Wang, 2018. "Transportation Disadvantage and Neighborhood Sociodemographics: A Composite Indicator Approach to Examining Social Inequalities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(1), pages 29-43, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    2. Drago, Carlo & Gatto, Andrea, 2022. "Policy, regulation effectiveness, and sustainability in the energy sector: A worldwide interval-based composite indicator," Energy Policy, Elsevier, vol. 167(C).
    3. Marek Walesiak & Grażyna Dehnel, 2023. "A Measurement of Social Cohesion in Poland’s NUTS2 Regions in the Period 2010–2019 by Applying Dynamic Relative Taxonomy to Interval-Valued Data," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    4. Drago, Carlo & Di Nallo, Loris & Russotto, Maria Lucetta, 2023. "Social Sustainability in European Banks: A Machine Learning Approach using Interval- Based Composite Indicators," FEEM Working Papers 336986, Fondazione Eni Enrico Mattei (FEEM).
    5. Panagiotis Artelaris, 2022. "A development index for the Greek regions," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1261-1281, June.
    6. Jiménez-Fernández, Eduardo & Sánchez, Angeles & Ortega-Pérez, Mario, 2022. "Dealing with weighting scheme in composite indicators: An unsupervised distance-machine learning proposal for quantitative data," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    7. Alexei Manso Correa Machado & Petr Iakovlevitch Ekel & Matheus Pereira Libório, 2023. "Goal-based participatory weighting scheme: balancing objectivity and subjectivity in the construction of composite indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4387-4407, October.
    8. Carlo Drago & Andrea Gatto, 2022. "An interval‐valued composite indicator for energy efficiency and green entrepreneurship," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2107-2126, July.
    9. Peiró-Palomino, Jesús & Picazo-Tadeo, Andrés J. & Tortosa-Ausina, Emili, 2021. "Measuring well-being in Colombian departments. The role of geography and demography," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    10. Mariateresa Ciommi & Chiara Gigliarano & Francesco M. Chelli & Mauro Gallegati, 2022. "It is the Total that Does [Not] Make the Sum: Nature, Economy and Society in the Equitable and Sustainable Well-Being of the Italian Provinces," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 491-522, June.
    11. Rajko Tomaš, 2022. "Measurement of the Concentration of Potential Quality of Life in Local Communities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 79-109, August.
    12. Tsionas, Mike G., 2020. "A note on Sigma–Mu efficiency analysis as a methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1187-1196.
    13. Giuliano Resce & Fritz Schiltz, 2021. "Sustainable Development in Europe: A Multicriteria Decision Analysis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(2), pages 509-529, June.
    14. Gianluca Gucciardi, 2022. "Measuring the relative development and integration of EU countries’ capital markets using composite indicators and cluster analysis," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(4), pages 1043-1083, November.
    15. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "Sigma-Mu efficiency analysis: A methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 278(3), pages 942-960.
    16. Yizhong Huan & Lingqing Wang & Mark Burgman & Haitao Li & Yurong Yu & Jianpeng Zhang & Tao Liang, 2022. "A multi‐perspective composite assessment framework for prioritizing targets of sustainable development goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 833-847, October.
    17. Giuseppe Coco & Raffaele Lagravinese & Giuliano Resce, 2020. "Beyond the weights: a multicriteria approach to evaluate inequality in education," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 469-489, December.
    18. Ruiz, Francisco & El Gibari, Samira & Cabello, José M. & Gómez, Trinidad, 2020. "MRP-WSCI: Multiple reference point based weak and strong composite indicators," Omega, Elsevier, vol. 95(C).
    19. Carlo Drago, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach," Economies, MDPI, vol. 9(4), pages 1-17, October.
    20. Alessia Arcidiacono & Gianpiero Torrisi, 2022. "Decentralisation and Resilience: A Multidimensional Approach," Sustainability, MDPI, vol. 14(16), pages 1-25, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:6171-:d:1115187. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.