Work-Life Balance for Sustainable Development in Malaysian Higher Education Institutions: Fad or Fact?

Abstract

The mainstream literature abounds with the challenges and effects of lack of worklife balance (WLB), but little is known about WLB experience and coping strategies that may be unique to women in academe. Knowledge in this area assumes significance amid the increased work intensification experienced by academics in recent years. Premised on the notion that WLB is not a passing fad but a catalyst for sustainable development, this article documents the findings of a qualitative study of 11 full-time women academic staff in Malaysian universities. Majority of the women perceived their WLB to be reasonable despite experiencing increased work intensification. The findings imply that how they cope with work and family situations are important to a healthy WLB. Research and policy implications for sustainable work and growth are discussed.

Turnover intention and its antecedents: The mediating role of work–life balance and the moderating role of job opportunity

“…Furthermore, empirical studies revealed that WLB is a significant predictor of employee well-being and job commitment ( Lestari and Margarethaa, 2021 ), productivity and performance ( Aman-Ullah et al, 2022 ), which are essential for long-term organisational viability and growth ( Ang, 2020 ). While the literature highlighted the significance of WLB practises, few studies examined WLB practises from the employees’ perspectives ( Kakar et al, 2021 ; Ozioma et al, 2022 ).…”

Academic managerial competency in Australia, New Zealand, and Malaysia: validity and factorial invariance of an Australian Scale in the Malaysian context

“…We then moved one step further and assessed the factorial invariance of our validated secondorder three-factor model across male and female groups. Notably, gender is one of the main covariates in social sciences research (Bernerth and Aguinis 2016) and its effect on various organizational outcomes in applied higher education research has been scrutinized [e.g., Ghasemy et al (2021b, c), and Ang (2020)]. For this purpose, we created two datasets-one for the male leaders, with a sample size of N = 219, and the other one for female leaders (N = 148).…”

A Systematic Review: Do the Use of Machine Learning, Deep Learning, and Artificial Intelligence Improve Patient Outcomes in Acute Myocardial Ischemia Compared to Clinician-Only Approaches?

“…Multiple factors can contribute to AMI, including smoking, hypertension, high BMI, hyperglycemia, an unhealthy diet, and genetic predispositions, leading to dyslipidemia, and the harmful use of substances such as alcohol and drugs, as well as physical inactivity [ 5 ]. Post-MI patients can be affected by various factors, including non-communicable diseases, demographics, and environmental factors, which can impact AMI mortality [ 6 , 7 ]. AMI often comes with chest pain, a common symptom often reported [ 8 ].…”