Higher education institutions (HEI) are uniquely positioned to contribute to sustainable development through education, research, community engagement, and policy influence. In this context, stakeholder engagement is recognised as an important strategy, since involving diverse groups in decision-making processes, HEIs can harness a wealth of perspectives, expertise, and resources, fostering more inclusive, innovative, and effective approaches to sustainability. There is a perceived need for studies that explore the contribution of various stakeholders in higher education, and suggest ways to optimise their participation in processes. Against this background, this paper seeks to bridge the gap between theoretical frameworks of stakeholder engagement and practical applications within the context of sustainable development in higher education. By examining 29 real-world case studies and best practices, this paper provides actionable insights and guidance for HEIs to enhance their sustainability efforts. Findings from the analysis of cases in Europe, Africa, Asia, and North and South America were consolidated into ten guidelines for HEIs seeking to promote sustainable development through stakeholder engagement. The analysis of trends identified three clusters: (i) HEI’s role in sustainable development through stakeholder engagement and Sustainable Development Goals (SDGs); (ii) human-centred sustainability via transformative learning and community empowerment; and (iii) education and interdisciplinary approaches to sustainability. The nature of the work performed, and the scope of the activities of HEIs put them in a key position to drive sustainable development by engaging diverse stakeholders across academic and societal contexts, including students, faculty, administration, industry partners, and the broader community. Inclusive participation and interdisciplinary educational programmes that integrate sustainability across curricula are key to effective stakeholder engagement. In addition, institutional commitment, including strong leadership and strategic policies, is essential for advancing sustainability initiatives, while partnerships with local communities and industries amplify the practical impact of sustainability efforts while addressing real-world challenges.

Although a significant amount of research has already been published, the field of ergonomics/human factors and sustainability (E/HF-S) has not yet been systematically profiled based on recent studies. Conducting a systematic review of the literature, this article aims: (i) to identify the main emergent research themes in this subject area and (ii) to provide future directions for applied research and practice on E/HF-S. Six emergent research themes were identified in this literature allowing for a proposal to synthesise the main concepts related to E/HF-S. However, it was noted that there are still relatively few empirical papers which assess the models being developed or that apply E/HF principles to sustainability challenges. Thus, this paper identifies the opportunities for practical application related to E/HF-S. The last part of the paper explores the E/HF-S opportunities using an external framework; the United Nations’ sustainable development goals. The field of ergonomics/human factors and sustainability (E/HF-S) has not yet been organized by recent studies. Conducting a systematic review of the literature, this article identifies the main emergent research themes in this subject area, and it provides future direction for applied research and practice on E/HF-S.

Purpose: This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.Design/methodology/approach: Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.Findings: The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.Practical implications: This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.Originality/value: This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.