Current literature merely identifies the driving factors of research productivity in higher education institutions without directly examining their interrelationships that would offer some fundamental insights into the nature of these factors. Thus, this work intends to identify those driving factors and establish their structural relationships to determine those factors with crucial roles in advancing research productivity. Due to the subjectivity of the identified driving factors and the notion that the evaluation of their relationships reflects an expert judgment, an interpretive structural modeling (ISM) approach and the Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis were adopted. Results show that institutional support, reward system, research funding, mentoring, and electronic information resources are the most crucial factors influencing research productivity. When addressed, these driving factors would motivate other driving factors, contributing to higher research productivity. In particular, these findings encourage higher education institutions to (1) efficiently allocate research funds and design mentoring programs, (2) offer efficient research incentive schemes, (3) develop initiatives that would support promising research proposals beneficial to the institution, and (4) collaborate with external organizations to grant funding for research proposals. These results contribute significantly to the literature as it provides meaningful insights that aid decision-makers in higher education institutions in resource allocation decisions, policy-making, and the design of efficient initiatives for augmenting their innovation potential.

Technological transitions in the education sector of developing economies are faced with a range of barriers, involving resource scarcity, socio-cultural concerns, and issues related to management and policy. The popularity of Industry 4.0 has prompted Education 4.0 (EDUC4), an approach to learning that involves transformation using advanced technologies. While a recent work reported a comprehensive list of barriers to EDUC4 implementation, particularly in developing economies, further analysis to identify those priority barriers remains a gap. Thus, this work addresses this gap by introducing a novel methodological extension of the decision-making trial and evaluation laboratory (DEMATEL) method following the integration of Fermatean fuzzy sets (FFS). The FFS, compared to other fuzzy environments, could capture higher levels of uncertainties that are associated when eliciting judgments necessary for the DEMATEL. Such integration is aided by the maximum mean de-entropy (MMDE) algorithm, which analytically determines the threshold value crucial for constructing the prominence-relation map of the DEMATEL. Following its application in evaluating the implementation of EDUC4 in Philippine universities, the critical barriers are the lack of training resources, costs, insufficiency of available technologies, skills gap of human resources, knowledge gap, and the complexity of the learning platforms. Among this set, barriers related to cost and lack of training resources are deemed the most prominent ones. The statistical test on the impact of addressing the two prominent barriers shows that addressing the barrier related to costs yields statistically more favorable results regarding the mitigation of other EDUC4 implementation barriers. Although these insights may contain idiosyncrasies, they can serve as starting points of discussion in other relevant developing economies. These methodological and practical contributions advance the development of analytical tools under uncertainty that can handle pressing problems such as the EDUC4 implementation.

While teaching quality has been widely studied, this work advances the domain literature by evaluating the factors influencing teaching quality in order to determine their causal relationships and eventually identify those crucial factors. With ten factors obtained from a comprehensive review of literature, the neutrosophic decision-making trial and evaluation laboratory (DEMATEL) method is used to model these factors in the case of public universities in the Philippines. The DEMATEL handles the causal relationships among factors of teaching quality, while the vagueness associated with domain experts eliciting judgments within the DEMATEL is modeled in single-valued neutrosophic numbers. Findings reveal that individual characteristics, psychological characteristics, and institutional culture are key factors of teaching quality, while institutional resources and student composition are minor key factors. Higher education institutions (HEIs) must pay more attention to these factors in designing different initiatives, as they are crucial in shaping teaching quality. These findings offer important insights for HEIs in their recruitment and hiring decisions, strategic road mapping for building an institutional culture that values teaching quality, establishing student composition schemes, and resource allocation decisions for promoting institutional resources that drive teaching quality initiatives. Some policy takeaways and avenues for future works are also discussed.

The barriers to implementing circular supply chains are well explored, but very little is provided to understand how these barriers play in public sector supply chains. Consequently, the role of digital technologies in addressing these barriers in the circularity of supply chains in the public sector remains a gap. Thus, this study bridges these gaps by evaluating digital technologies according to their relevance in addressing the identified barriers. In particular, eight domain experts who have sufficient knowledge and expertise in the domains of the public sector and circular economy were asked to elicit judgments in order to (1) set a threshold that defines the list of barriers that are significant to supply chains in the public sector, (2) obtain the priority weights of these barriers through the criteria importance through intercriteria correlation (CRITIC), and (3) rank the identified digital technologies based on their relevance in addressing the identified barriers in public sector supply chains using combinative distance-based assessment (CODAS) method, all under a Fermatean fuzzy set environment to account for epistemic uncertainties in judgment elicitation processes. This novel integration of the CRITIC and CODAS methods augmented by Fermatean fuzzy sets forms the methodological contribution of this work. Findings show that barriers associated with regulations restricting the collection of wastes, poor demand or acceptance for environmentally superior technologies, lack of expertise, technology, and information, operational risk, immature recycling technologies, and information sharing and communication were considered critical in managing circular public sector supply chains. The analysis also revealed that ripple effect modeling, simulation, and artificial intelligence are the priority digital technologies. These digital technologies offer efficiency and flexibility to decision-makers in analyzing complex and dynamic scenarios before the deployment of any circularity initiative, providing crucial information in its design and implementation. This paper outlines several managerial insights and offers possible agenda for future research.

This work defines various stakeholder roles (or strategies) to overcome the barriers to implementing Education 4.0 (EDUC4), which were recently identified in the domain literature. The stakeholder roles are evaluated against these barriers, and such evaluation is structured as a multicriteria sorting problem. To this end, an integrated entropy‐based CRITIC‐CODAS‐SORT under a Fermatean fuzzy (FF) environment addresses epistemic uncertainties inherent in decision‐making. The FF CRITIC assigns the priority weights of the barriers, while the FF CODAS‐SORT determines the high‐priority stakeholder roles. A case of an HEI evaluating 57 possible roles of 5 stakeholders is demonstrated here. Findings suggest the lack of collaboration, apprehensive stakeholders, cybersecurity threats, health issues, and cost as crucial barriers to the HEI. The sorting process yields 13 high‐priority roles, encompassing those within the influence of the government (i.e., cybersecurity awareness, allocation of necessary funds, designing more aligned curricula, and streamlining the basic education agenda), university management (i.e., investing in efficient technologies and forging extensive stakeholder collaboration), human resource function (i.e., implementing periodic skills training for educators), and educators (i.e., engaging in continuous learning about cybersecurity threats, integrating awareness of applicable laws against cyberbullying, devising alternative cost‐efficient teaching strategies, taking part in initiatives to improve curricula, efficient preparation of learning materials, and participating in skills development initiatives). Various managerial insights are offered as inputs to the design of initiatives in EDUC4 implementation.

This work develops a computational platform to evaluate the ecotourism potential of tourist sites (alternatives) under multiple indicators (criteria). Such a platform is a generalized multi-attribute decision-making approach based on the integration of Criteria Importance Through Intercriteria Correlation (CRITIC) and the weighted sum method (WSM) under a stochastic environment. In this proposed approach, a randomly generated decision matrix is formed, derived from the initial judgments of decision-makers. Then, the priority weights of the criteria are obtained through CRITIC, while the WSM generates the global priority vector of alternatives. A stochastic process based on Monte Carlo simulation generates a large set of global priority vectors. The aggregation of these vectors yields the final priorities of the alternatives. Contextually, it generates a single-valued composite ecotourism potential index which provides the overall performance of the potential ecotourism sites. Evaluating 47 tourist sites under eight indicators demonstrates the proposed approach. Findings and insights are discussed.