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Intuitionistic Fuzzy Data Envelopment Analysis Model with Variable Returns to Scale using Possibility Mean

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Author Affiliations

  • 1Department of Statistics, MES Abasaheb Garware College (Autonomous), Savitribai Phule Pune University, Pune, India
  • 2Department of Statistics, MES Abasaheb Garware College (Autonomous), Savitribai Phule Pune University, Pune, India

Res. J. Mathematical & Statistical Sci., Volume 14, Issue (2), Pages 1-9, May,12 (2026)

Abstract

Evaluating efficiency in the banking sector is essential, as banks are key drivers of economic growth and must utilize resources effectively to remain competitive. While Data Envelopment Analysis (DEA) offers a framework for assessing efficiency without rigid functional assumptions, its application is constrained when data is uncertain, imprecise, or subjective. To address these challenges, this study develops a triangular intuitionistic fuzzy DEA model integrated with a weighted possibility mean technique for BCC model, incorporating membership, non-membership, and hesitation degrees simultaneously. This approach more accurately reflects ambiguity and data vagueness, providing a realistic assessment of bank performance. A case study of Indian banks demonstrates that the model delivers reliable, interpretable, and actionable efficiency results. By extending existing intuitionistic fuzzy DEA methodologies, this framework presents a robust and practical tool for performance evaluation under complex and uncertain conditions, facilitating informed decision-making and effective resource allocation.

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