A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making


Karaoğlu N. B., ÜNVER M., OLGUN M.

Turkish Journal of Mathematics and Computer Science, cilt.17, sa.1, ss.243-263, 2025 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 1
  • Basım Tarihi: 2025
  • Doi Numarası: 10.47000/tjmcs.1677588
  • Dergi Adı: Turkish Journal of Mathematics and Computer Science
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.243-263
  • Anahtar Kelimeler: income, Interval-valued intuitionistic fuzzy neutrosophic set, multi-criteria decision-making, WASPAS
  • Ankara Üniversitesi Adresli: Evet

Özet

Income equality plays a fundamental role in ensuring sustainable development and social welfare globally. The increase in economic inequality threatens not only the living standards between individuals but also societal harmony and economic stability. In many developed and developing countries, injustices in income distribution exacerbate social tensions and negatively affect long-term economic growth. This study introduces a novel multi-criteria decision-making framework based on interval-valued intuitionistic fuzzy neutrosophic sets (IVIFNSs) to evaluate and compare income equality across selected Organisation for Economic Co-operation and Development (OECD) countries. The IVIFNS model improves traditional fuzzy systems by representing truth, indeterminacy, and falsity degrees with interval-valued intuitionistic fuzzy values, offering a more nuanced approach to uncertainty. Algebraic operations are defined using triangular-norms and triangular-conorms, and new aggregation operators are developed. The proposed theory is applied to rank 25 OECD countries based on key income inequality indicators: Gini coefficient, Palma ratio, P90/P10, and P90/P50, using the Weighted Aggregated Sum Product Assessment (WASPAS) method. A comparative analysis demonstrates the method’s effectiveness in capturing complex, uncertain data and producing robust country rankings for policy evaluation.