Purpose: This research aims to explore the phenomenon of job-hopping in the engineering sector in Penang, Malaysia, focusing on how factors like positive work culture, compensation and benefits, and job satisfaction influence an engineer’s propensity to frequently change jobs. Design/methodology/approach: The study adopted a cross-sectional survey design, targeting 200 engineers in Penang. It was grounded in Herzberg’s Motivation-Hygiene Theory. Data collection was conducted using online questionnaires, which were adaptations of instruments used in previous research. Statistical analysis, including Pearson correlation and multiple linear regression, was performed using SPSS software. Findings: The Pearson correlation analysis revealed significant negative relationships between positive work culture, compensation and benefits, job satisfaction, and the tendency to job-hop. However, in the regression analysis, only job satisfaction emerged as a significant predictor of job-hopping behavior. This finding suggests that while factors like work culture and compensation/benefits contribute to the overall work environment, they do not primarily drive job mobility among engineers in this region. The study indicates that job satisfaction plays a more crucial role in influencing engineers’ decisions to change jobs frequently. Conclusion: The study enriches the field of organizational psychology by applying Herzberg’s theory to understand job-hopping behavior in the engineering sector. For organizations in Penang, the findings highlight the importance of enhancing job satisfaction as a strategy for reducing job-hopping and retaining talent. This insight is valuable for both academic research and practical application in the industry, emphasizing the critical role of job satisfaction in curbing job-hopping tendencies within the engineering field.

Using time series data covering the years 1980 to 2020, this study examines the effects of government spending, population growth, and economic expansion on unemployment in the context of South Africa. The study’s variables include government spending, population growth, and economic growth as independent factors, and unemployment as the dependent variable. To ascertain the study’s outcomes, basic descriptive statistics, the Vector Error Correction Model (VECM), the Johansen Cointegration Procedures, the Augmented Dicky-Fuller Test (ADF), and diagnostic tests were used. Since all the variables are stationary at the first difference, the ADF results show that there isn’t a unit root issue. According to the Johansen cointegration estimation, there is a long-term relationship amongst the variables. Hence the choice of VECM to estimate the outcomes. Our results suggests that a rise in government spending will result in a rise in South Africa’s unemployment rate. The findings also suggest that there is a negative correlation between unemployment and population growth. This implies that as the overall population grows, unemployment will decline. Additionally, the findings suggest that unemployment and economic growth in South Africa are positively correlated. This contradicts a number of economic theories, including Keynesian and Okuns Law, which hold that unemployment and economic growth are inversely correlated.