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An Integrated QFD and Common Weight DEA-Based Fuzzy MCDM Framework for Performance Ranking of Countries

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Abstract

United Nations Development Program presented the Human Development Index for ranking the countries with regard to three dimensions, namely being knowledgeable, a long and healthy life, and having a proper standard of living. In order to provide social, economic, and environmental improvement for the countries, 2030 Agenda for Sustainable Development was presented with seventeen sustainable goals. This study proposes a fuzzy multiple criteria group decision making procedure combining quality function deployment and data envelopment analysis (DEA). The developed approach enables to include the interactions among country evaluation criteria via forming a house of quality (HOQ). The lower and upper bounds on country evaluation criteria are determined by utilizing fuzzy weighted average (FWA) technique. A common-weight DEA-based modeling framework, which uses the weights of country attributes calculated by FWA with the data from HOQ, is employed for identifying country ratings with respect to related country attributes. The proposed approach is implemented for ranking Latin American countries in a way to incorporate imprecise data and inner dependence among evaluation criteria. According to the results, Peru ranks first, followed by Chile and Costa Rica. Moreover, rankings obtained from human development index and the proposed formulation are compared via Spearman’s rank correlation. While the obtained rankings of countries according to the proposed approach are positively correlated with those of human development index, the variations in rankings may be due to considering a wider coverage of sustainable development goals as well as interactions among them by the proposed methodology.

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Acknowledgements

This research has been financially supported by Galatasaray University Research Fund.

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Authors and Affiliations

  1. Industrial Engineering Department, Galatasaray University, 34349, Ortakoy, Istanbul, Turkey

    Nazli Goker & E. Ertugrul Karsak

  2. Industrial Engineering Department, Decision Analysis Application and Research Center, Galatasaray University, 34349, Ortakoy, Istanbul, Turkey

    Mehtap Dursun

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  1. Nazli Goker
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  2. E. Ertugrul Karsak
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  3. Mehtap Dursun
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Correspondence to Nazli Goker.

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Goker, N., Karsak, E.E. & Dursun, M. An Integrated QFD and Common Weight DEA-Based Fuzzy MCDM Framework for Performance Ranking of Countries. Soc Indic Res 159, 409–430 (2022). https://doi.org/10.1007/s11205-021-02751-2

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