IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v57y2023i5d10.1007_s11135-022-01546-y.html
   My bibliography  Save this article

Goal-based participatory weighting scheme: balancing objectivity and subjectivity in the construction of composite indicators

Author

Listed:
  • Alexei Manso Correa Machado

    (Pontifical Catholic University of Minas Gerais)

  • Petr Iakovlevitch Ekel

    (Pontifical Catholic University of Minas Gerais)

  • Matheus Pereira Libório

    (Pontifical Catholic University of Minas Gerais)

Abstract

The weighting of sub-indicators is a controversial topic in the literature, being the object of investigation by many researchers. The absence of a clear definition for the most appropriate sub-indicator weighting scheme has led researchers to combine subjective and objective weighting schemes. In this work, an innovative sub-indicator weighting scheme, the Goal-based Participatory weighting scheme, is proposed. It employs the Generalized Reduced Gradient (GRG) to achieve two. Objectives: First, to construct composite indicators more correlated with the variable of greater conceptual significance in the multidimensional phenomenon, ensuring its external validity; Second, to define weights for the sub-indicators respecting the opinion of the group of experts, ensuring its consensus degree. Eleven composite indicators for the Equal Weights (EW), Participatory and Data-driven weighting schemes were constructed by the Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS). The results show that the Goal-based Participatory weighting allows for a more balanced solution regarding external validity and consensus degree when compared to other weighting schemes. The external validity obtained by the Goal-based Participatory weighting is greater than the one obtained by the EW, Participatory, and Data-driven weighting in 91% of the composite indicators analyzed, being 30% higher in 15% of the composite indicators and 37% higher than one of the composite indicators constructed by the Participatory weighting. All composite indicators constructed using the GRG showed a higher consensus degree when compared to composite indicators constructed by the EW and Data-driven weighting schemes.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:qualqt:v:57:y:2023:i:5:d:10.1007_s11135-022-01546-y
    DOI: 10.1007/s11135-022-01546-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-022-01546-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11135-022-01546-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Seong-Yun Hong & Yukio Sadahiro, 2014. "Measuring geographic segregation: a graph-based approach," Journal of Geographical Systems, Springer, vol. 16(2), pages 211-231, April.
    2. 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.
    3. 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.
    4. Milica Maricic & Jose A. Egea & Veljko Jeremic, 2019. "A Hybrid Enhanced Scatter Search—Composite I-Distance Indicator (eSS-CIDI) Optimization Approach for Determining Weights Within Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 497-537, July.
    5. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    6. Yelin Fu & Kong Xiangtianrui & Hao Luo & Lean Yu, 2020. "Constructing Composite Indicators with Collective Choice and Interval-Valued TOPSIS: The Case of Value Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 117-135, November.
    7. Yelin Fu & Kong Xiangtianrui & Hao Luo & Lean Yu, 2020. "Correction to: Constructing Composite Indicators with Collective Choice and Interval-Valued TOPSIS: The Case of Value Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(3), pages 1213-1213, December.
    8. Weiwei Li & Pingtao Yi & Danning Zhang, 2018. "Sustainability Evaluation of Cities in Northeastern China Using Dynamic TOPSIS-Entropy Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    9. Yeonjoo Kim & Eun-Sung Chung, 2013. "Assessing climate change vulnerability with group multi-criteria decision making approaches," Climatic Change, Springer, vol. 121(2), pages 301-315, November.
    10. Grupp, Hariolf & Schubert, Torben, 2010. "Review and new evidence on composite innovation indicators for evaluating national performance," Research Policy, Elsevier, vol. 39(1), pages 67-78, February.
    11. Matheus Pereira Libório & Oseias da Silva Martinuci & Sandro Laudares & Renata de Mello Lyrio & Alexei Manso Correa Machado & Patrícia Bernardes & Petr Ekel, 2020. "Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    12. Boggia, Antonio & Massei, Gianluca & Pace, Elaine & Rocchi, Lucia & Paolotti, Luisa & Attard, Maria, 2018. "Spatial multicriteria analysis for sustainability assessment: A new model for decision making," Land Use Policy, Elsevier, vol. 71(C), pages 281-292.
    13. Marco Cinelli & Matteo Spada & Wansub Kim & Yiwen Zhang & Peter Burgherr, 2021. "MCDA Index Tool: an interactive software to develop indices and rankings," Environment Systems and Decisions, Springer, vol. 41(1), pages 82-109, March.
    14. Hasan Ture & Seyyide Dogan & Deniz Kocak, 2019. "Assessing Euro 2020 Strategy Using Multi-criteria Decision Making Methods: VIKOR and TOPSIS," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 645-665, April.
    15. José-María Montero & Coro Chasco & Beatriz Larraz, 2010. "Building an environmental quality index for a big city: a spatial interpolation approach combined with a distance indicator," Journal of Geographical Systems, Springer, vol. 12(4), pages 435-459, December.
    16. Matheus Pereira Libório & Petr Yakovlevitch Ekel & Oseias da Silva Martinuci & Letícia Ribeiro Figueiredo & Renato Moreira Hadad & Renata de Mello Lyrio & Patrícia Bernardes, 2022. "Fuzzy set based intra-urban inequality indicator," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(2), pages 667-687, April.
    17. 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.
    18. Samira El Gibari & Trinidad Gómez & Francisco Ruiz, 2019. "Building composite indicators using multicriteria methods: a review," Journal of Business Economics, Springer, vol. 89(1), pages 1-24, February.
    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. Matheus Pereira Libório & João Francisco Abreu & Petr Iakovlevitch Ekel & Alexei Manso Correa Machado, 2023. "Effect of sub-indicator weighting schemes on the spatial dependence of multidimensional phenomena," Journal of Geographical Systems, Springer, vol. 25(2), pages 185-211, April.
    2. Matheus Pereira Libório & Elisa Fusco & Alexandre Magno Alves Diniz & Oséias da Silva Martinuci & Petr Iakovlevitch Ekel, 2024. "A Novel Approach for Multispatial and Multitemporal Analysis of Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 173(3), pages 783-800, July.
    3. Cantone, Giulio Giacomo & Tomaselli, Venera, 2024. "On the Coherence of Composite Indexes: Multiversal Model and Specification Analysis for an Index of Well-Being," MetaArXiv d5y26, Center for Open Science.
    4. Ana Garcia-Bernabeu & Adolfo Hilario-Caballero, 2021. "Monitoring multidimensional phenomena with a multicriteria composite performance interval approach," Papers 2107.08393, arXiv.org.
    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. Matheus Pereira Libório & Petr Yakovlevitch Ekel & Oseias da Silva Martinuci & Letícia Ribeiro Figueiredo & Renato Moreira Hadad & Renata de Mello Lyrio & Patrícia Bernardes, 2022. "Fuzzy set based intra-urban inequality indicator," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(2), pages 667-687, April.
    7. 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.
    8. Matheus Pereira Libório & Oseias da Silva Martinuci & Alexei Manso Correa Machado & Renata de Mello Lyrio & Patrícia Bernardes, 2022. "Time–Space Analysis of Multidimensional Phenomena: A Composite Indicator of Social Exclusion Through k-Means," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 569-591, January.
    9. 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).
    10. Jie Yang & Yanan Ding & Lin Zhang, 2022. "Conceptualizing and Measuring Megacity Resilience with an Integrated Approach: The Case of China," Sustainability, MDPI, vol. 14(18), pages 1-26, September.
    11. 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.
    12. Matheus Pereira Libório & Alexandre Magno Alvez Diniz & Angélica Cidália Gouveia Santos & Cristiane Neri Nobre & Douglas Alexandre Gomes Vieira & Hasheem Mannan & Marcos Flávio Silveira Vasconcelos Da, 2024. "Benefit-of-the-Doubt in the Spatial Analysis of Child Well-Being in European Countries," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 17(4), pages 1851-1870, August.
    13. Olga Bogdanov & Veljko Jeremiæ & Sandra Jednak & Mladen Èudanov, 2019. "Scrutinizing the Smart City Index: a multivariate statistical approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(2), pages 777-799.
    14. 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.
    15. 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.
    16. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2018. "σ-µ efficiency analysis: A new methodology for evaluating units through composite indices," MPRA Paper 83569, University Library of Munich, Germany.
    17. Khatab Alqararah, 2023. "Assessing the robustness of composite indicators: the case of the Global Innovation Index," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-22, December.
    18. Carayannis, Elias G. & Goletsis, Yorgos & Grigoroudis, Evangelos, 2018. "Composite innovation metrics: MCDA and the Quadruple Innovation Helix framework," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 4-17.
    19. Ying Zhou & Weiwei Li & Pingtao Yi & Chengju Gong, 2019. "Evaluation of City Sustainability from the Perspective of Behavioral Guidance," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    20. Carmen García-Peña & Moneyba González-Medina & Jose Manuel Diaz-Sarachaga, 2021. "Assessment of the Governance Dimension in the Frame of the 2030 Agenda: Evidence from 100 Spanish Cities," Sustainability, MDPI, vol. 13(10), pages 1-21, May.

    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:spr:qualqt:v:57:y:2023:i:5:d:10.1007_s11135-022-01546-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.