Previous studies have acknowledged the importance of resilience in enabling individuals to cope and bounce back from crises and unexpected situations like the COVID-19 pandemic. Thus, this study advances conservation of resources theory by investigating the job, social, and personal resources underlying employees’ resilience, and the impact of resilience in stimulating job engagement amid the COVID-19 pandemic. The model was tested using data collected from 259 employees in Malaysia. Results of path modeling analysis revealed significant impacts of self-efficacy, facilitating conditions, and family and friends’ support on employees’ resilience. Besides, resilience was significantly associated with job engagement. Our findings suggest that management concerns for employees may not enhance employees’ resilience amid the COVID-19 pandemic. Nevertheless, management could stimulate their employees’ resilience by providing them with the flexibility to spend quality time with their loved ones and adequate support for enabling working conditions.

Purpose: This study aims to investigate the factors, which may potentially influence green product buying decision among young consumers in Malaysia. Design/methodology/approach: A perceived lack of intention to buy green products observed among the Malaysian Generation Young consumers has sparked the interest to carry out this study. With the aid of structured questionnaires, data were collected from a total of 217 respondents, between 18 and 25 years of age. Findings: The results of data analysis indicated that environmental consciousness, eco-label, price and advertising were significant predictors of green product buying behaviour. Contrary to the hypothesis, attitude was not a significant predictor of green buying behaviour among young consumers. The implications of these findings and directions for future research are outlined at the end of this paper. Originality/value: This study offers empirical insights from the perspective of an emerging economy on the determinants of green products buying behaviour among young consumers.

Purpose: Academics research productivity is the pinnacle issue of higher learning institution (HLI) quest for providing the best service for the community and a country’s as a whole. Being productive in their area of expertise will determine how far HLI can challenge for the best education in the world. In lieu of this, knowledge sharing (KS) behavior determinants are assessed to determine what factors that can contribute to academic’s research productivity. Design/methodology/approach: A quota sampling method was applied in selecting academics from public and private universities in Malaysia. A partial least square structural equation modelling (PLS-SEM) was used for analysis. Findings: The results show that academics productivity explained variance is 22.6 per cent. This suggests that academics KS behavior has substantial impact on research productivity. As for determinants of academic’s attitude, academics commitment, trust and social network constituted an explained variance of 36.4 per cent. Management support has an explained variance of 38.7 per cent towards subjective norm, while facilitating condition and social media has an explained variance of 26.5 per cent towards perceived behavioral control (PBC). Academics KS intention and KS behavior explained variance were 62.1 and 47.1 per cent, respectively. Research limitations/implications: All the hypotheses result in significant relationship except for H1, commitment toward attitude. The impact of this study will be discussed in term of its theoretical and managerial perspectives. Originality/value: The KS behavior in a multiracial and multinational country in Malaysia can be a benchmark for Asian countries in general.

The healthcare industry is increasingly becoming more competitive, with patients now demanding a higher level of service quality. This study aims to model the impact of service quality (medical care procedures, administrative practices, hospital image, trustworthiness, patient safety, infrastructure, personnel quality, and social responsibility) on patient satisfaction. Using a structured questionnaire, data were gathered from 194 patients from public and private hospitals in Melaka and Johor. The data were analyzed using a second-generation analytical software, SmartPLS. The results suggest the model can explain 58 percent of the variance in patient satisfaction. Hospital image, patient safety, personnel quality, and social responsibility were the significant predictors of patient satisfaction. Personnel quality was the most important predictor. The implication is that to keep patients satisfied and willing to return for subsequent treatments, the hospitals should invest more on training their personnel.