Over the last few years, many activities conducted by university employees have contributed greatly to the global rise of greenhouse gases responsible for the warming of the planet. This phenomenon can be attributed primarily to altering lifestyle, consumption, and portability patterns. Even though there is a significant applicability, understanding the factors determining the pro-environmental behavior (PEB) of university employees is lacking. Thus, this study extended the theory of planned behavior (TPB) to explain PEB among university employees. Ten hypotheses were suggested regarding the relations between the initial TPB constructs, environmental ethics, and emotional intelligence. A self-reported questionnaire was used to collect data from a randomly selected sample of 302 university employees from six Malaysian higher educational institutions listed in the UI Green Matrix 2016. The findings revealed that environmental ethics significantly affected attitudes, perceived behavioral control, and subjective norms. Furthermore, pro-environmental behavioral intentions (PEIs) were directly influenced by attitude and perceived behavioral control, while emotional intelligence mediated the relationship between PEIs and PEB. Moving forward, this study will provide new insights into the literature of university employees’ PEB using an expanded TPB model.

This research aims to analyze studies that have investigated the effects of teacher empowerment on job satisfaction. From the results obtained from the meta-analytic structural equation modeling of 11 studies (N = 19,462), it has been found that the teacher empowerment model and job satisfaction are meaningfully correlated. The findings have also revealed that decision-making and self-efficacy among teachers had a significant impact on job satisfaction, followed by professional growth. Conversely, autonomy, impact, and status among teachers were negatively linked to job satisfaction. The findings confirm the significant effects of teacher empowerment on job satisfaction.

(1) Background: Tertiary institutions are facing increasing pressure to produce employable undergraduates who can drive the sustainability of strong economic growth and development. As such, responsibility lies with the higher education sector in ensuring undergraduates’ readiness for entry to the labor market, thus joining the ranks of those already employable. Thus, this study applied the CareerEDGE model as a theoretical basis to investigate the factors associated with undergraduate employability. The mediating effect of self-efficacy on the predictive relationships was also examined. (2) Methods: Data were collected from a sample of 264 from six universities in the North-East region of Nigeria. Partial least squares structural equation modeling was used to perform the data analysis in this study. (3) Results: Results revealed that the five constructs of the CareerEDGE model (career development learning; work experience; degree subject knowledge, skills, and understanding; generic skills; and emotional intelligence) are positively associated with undergraduate employability. Self-efficacy was found to mediate this relationship. Altogether, these results signal that the CareerEDGE model contributes to undergraduate employability and that self-efficacy is instrumental in elucidating this relationship. The results add to the extant knowledge on the impact of the CareerEDGE constructs on students’ approaches to careers. (4) Conclusions: The findings have significant implications for higher education institutions and career practitioners in identifying ways of enhancing undergraduates’ career planning strategies within a more challenging labor market context.

(1) Background: Due to the rapid growth of Massive Online Open Courses (MOOCs), higher educational institutions across the world are investing heavily in MOOCs to support their traditional teaching, their students’ learning experience, and their performance. However, the success of MOOCs highly depends on several factors that influence their success in higher education. Prior studies have attempted to investigate and predict user acceptance of MOOCs in higher education by using a variety of theoretical viewpoints. Nonetheless, these studies have yielded conflicting findings and are inconclusive. (2) Purpose: This study aims to develop a model that integrates the Theory of Planned Behavior (TPB), the Unified Theory of Acceptance and Use of Technology (UTAUT), as well as the Task-Technology Fit (TTF) to explore the factors that influence the acceptance and use of MOOCs in higher education institutions, while synthesizing previous empirical findings in the field. (3) Methods: The model was tested using Meta-analytic Structural Equation Modelling (MASEM) based on the data gathered from 43 studies (k = 45 samples, n = 16,774). (4) Results: Effort expectancy (EE), attitude (ATT), performance expectancy (PE), and TTF—determined by several task and technology characteristics—were identified as the direct predictors of behavioral intention (BI) to continue using MOOCs. (5) Conclusions: This model provides a cohesive view of MOOCs’ acceptance in higher educational institutions, and it helps to identify potential research opportunities in this area. (6) Implications: Results from MASEM offer managerial guidance for the effective implementation of MOOCs and provide directions for further research, to augment current knowledge of MOOCs’ adoption, by higher education institutions.