Education 4.0 (EDUC4) was driven by the onset of the Fourth Industrial Revolution (4IR) to meet labor market requirements resulting from learning that is customized, flexible, accessible, and skills-based. As the concept of EDUC4 develops popularity in the education and innovation research domains, various challenges about its implementation have emerged, especially in developing economies. Thus, there is a need to investigate the existing barriers to EDUC4 implementation. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature review of journal articles in the Scopus database was conducted. Of the 299 journal articles generated from the initial search on Scopus, 30 met the inclusion criteria and were included in the review. The content analysis yielded 12 barriers which include cybersecurity threat, costly, skills gap of human capital, apprehensive stakeholders, lack of training resources, lack of collaboration, knowledge gap for the customization of curriculum design, insufficient available technologies, health issues, time constraint for material preparation, complexity of learning platforms, and insufficient foundation of basic education. They were then associated with seven themes for better operationalization in Higher Education Institutions (HEIs): (1) human resources, (2) infrastructure, (3) financial, (4) linkages, (5) educational management, (6) learners, and (7) health and environment. Finally, a theoretical predictive model was constructed to present the causal relationships in modeling the problems associated with implementing EDUC4. The insights generated from this work offer both theoretical and practical perspectives for stakeholders of HEIs in the implementation of EDUC4 in developing economies.

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.

Due to workers’ vulnerability in construction sites, workplace safety has become of particular interest, and the current literature offers myriad approaches to dealing with it. From a social and organizational lens, this study explores an empirical model that integrates the dimensions of social capital theory (SCT) and leader-member exchange (LMX) in modelling the safety behavior of construction workers, particularly relevant in small-medium construction firms. The data were collected from 232 construction workers in the central Philippines. The responses were analyzed using partial least squares—structural equation modeling to investigate five hypothesized paths, including the influence of SCT dimensions (e.g., structural, relational, and cognitive) on LMX and LMX on safety behaviors (i.e., compliance and participation). We also tested whether the relationship of LMX to safety behaviors is moderated by age. The results indicate that the three dimensions of SCT have a significant and direct influence on LMX. In addition, LMX directly affects safety participation but does not significantly affect safety compliance. Particularly in small and medium construction firms with relatively flat organizational structures and supervisors displaying diverse roles, these findings suggest that the social relationships of workers tend to promote their trust and professional respect for supervisors who can leverage their position to encourage them participate in safety initiatives. On the other hand, age negatively influences the relationship of LMX to safety participation, indicating that younger workers tend to better translate high quality LMX into initiatives that promote overall workplace safety. Our findings offer the first evidence of the positive relationship between SCT and LMX in advancing the safety participation of construction workers. From these insights, practical inputs to the design of relevant measures and future research works are outlined.

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