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This article aims to propose a model to support the assessment and prioritization of risk in manufacturing processes.

The model integrates the failure modes and effects analysis (FMEA) criteria with the evaluation procedures of a new hesitant fuzzy linguistic-technique for Order of Preference by Similarity to Ideal Solution (HFL-TOPSIS) variation. A case study evaluating failure risk in a wiring harness assembly process demonstrated the model's applicability. A sensitivity analysis was performed to verify the effect of the variation in the weights assigned to the decision-makers (DMs).

The failure mode (FM) ranking was FM4 > FM9 > FM17 > FM2>FM8>FM12 > FM16 > FM19 > FM11 > FM3>FM18 > FM15 > FM13 > FM10 > FM14 > FM7 > FM1 > FM5 > FM6. These outcomes suggest that “stripping length less than specified” was the top priority among the 19 FMs evaluated. Sensitivity tests demonstrated the effect of the DMs’ weights on the ranking of FMs. A comparison with FMEA and HFL-TOPSIS demonstrates the model's greater capacity to discriminate levels of risk priority, as it identifies a total of 19 risk levels compared with 9 levels in the other approaches.

The adoption of the proposed model can drive substantial improvements in risk management practices across industries, provided that the organization has a decision-making team experienced with FMEA. Therefore, this approach promotes the continuous improvement of operations and ensures that mitigation actions effectively address critical FMs.

This is the first study to propose a risk evaluation model that accounts for DMs' hesitation in defining criteria weights through linguistic expressions. Additionally, it addresses uncertainty when assessing weights for the DMs’ opinions and considers multiple factors that affect these weights in decision-making for risk prioritization.

Neglected communities, such as transgender individuals in developing nations like Pakistan, face substantial barriers to economic participation due to diverse economic and social conditions. This study aims to explore the role of inclusive entrepreneurial ecosystems in enhancing entrepreneurial intentions among these communities, emphasizing the mediating role of psychological capital and the moderating effect of entrepreneurial education.

Using social cognitive theory and the theory of planned behavior, the research adopts a questionnaire survey methodology with a sample size of 308 to gather data from transgender individuals engaged in or interested in entrepreneurship. The analysis was conducted using AMOS and SPSS software.

The results show that inclusive entrepreneurial ecosystems directly enhance psychological capital but do not significantly affect entrepreneurial intentions unless psychological capital acts as a mediator. Entrepreneurial education does not illustrate a significant moderating effect on the connection between inclusive entrepreneurial ecosystems and entrepreneurial intentions.

These findings highlight the significance of psychological resources in transforming environmental supports into entrepreneurial action, proposing significant insights for policymakers and educators to foster more inclusive entrepreneurial ecosystems aligned with sustainable development goals. This study contributes to the discussion on entrepreneurship among underserved populations and demonstrates the vital role of personalized educational and environmental supports in developing economic participation.