An integrated type-2 neutrosophic entropy and MCDM framework for women's unemployment evaluation

Abstract Problem: Women's unemployment remains a critical socio-economic challenge in India with substantial variations across states and union territories due to regional, cultural, economic, and policy-related factors. Evaluating these disparities is difficult because data assessment of unemployment-related risk factors involves uncertainty, vagueness and imprecision. Aim: This study aims to develop a robust decision-making framework for assessing and ranking Indian states and union territories according to women's unemployment levels while addressing uncertainty in data evaluations. Methods: To achieve this objective a type-2 neutrosophic fuzzy set (T2NFS) based framework is proposed. A novel entropy-based weighting method is introduced to determine the relative importance of risk factors under uncertain information. Subsequently, three well-established multi-criteria decision-making (MCDM) methods such as the technique for order preference by similarity to ideal solution (TOPSIS), weighted aggregated sum product assessment (WASPAS) and combinative distance-based assessment (CODAS) are employed to rank the states and union territories. Furthermore, sensitivity analysis is conducted to evaluate the stability of the obtained rankings under different parameter settings. Results: The results demonstrate the effectiveness of the proposed framework. The sensitivity analysis confirms that the rankings remain stable across varying parameter values, indicating the robustness of the approach. Among the evaluated alternatives Lakshadweep consistently emerges as the vulnerable region receiving the lowest ranking across all three MCDM methods. In contrast Rajasthan, Haryana and Telangana achieve the highest rankings reflecting comparatively lower levels of women's unemployment. Conclusion: The proposed type-2 neutrosophic entropy-based MCDM framework provides an effective tool for analysing complex socio-economic problems characterised by uncertainty and imprecise information. The findings offer valuable insights into state-level disparities in women's unemployment and can assist policymakers in designing targeted interventions. It can improve women's workforce participation and promote inclusive socio-economic development.