This study aimed to determine the effect of overtime, job stress, and workload on turnover intention. This is a quantitative study with a sample collection method using a purposive sampling in PT. Ungaran Sari Garmen, Indonesia. Data collection was carried out by the method of observation, documentation, and questionnaires. The data obtained were then processed and analyzed with ordinary least square regression model. The results show that overtime, job stress, and workload significantly affected the turnover intention. Adjusted R2 value of this study was 0.776, which means overtime, job stress, and workload explained the turnover intention of 77.6%, and 22.4% was influenced by other variables.

This study aims to examine and analyze the influence of Workload, Demographic Factors, Locus of Control, Self Esteem and Workstress on Burnout in the Senior Masinists. The research method used in this research is descriptive method. Questionnaires were distributed to 43 respondent employees of The Indonesia Railway Industry. The approach used in this research is a Variance-based Model or Structural Equation Model with a Smart-PLS analysis tool. The results show that the four variables namely Workload, Demography, Locus of Control and Work Stress had positive and significant effects on Burnout on Machinists while the Self-Esteem Variable did not have a significant effect on Burnout.

A workload is one of contradictive variables, whether it influences the performance of employees or not. The purpose of this study is to analyze whether or not the workload influences the performance of bank employees. It employs quantitative approach and path analysis is employed to analyze the effect of workload on the performance of bank employees. The research samples include 74 bank employees around the City of Blitar, East Java, Indonesia. The result shows that a workload had a significant positive effect on the performance of bank employees. It also has greater influence on employee performance through motivation variables. The managerial implication of the current research is that the provision of workload which is in accordance with the competence and comfort of employees may improve their performance. In addition, employees who have higher education level are able to adjust more on the workload because they have higher-achievement motivation.

This study set out to find out on how big data analytics, workload, work wages, and organizational structure pressures affect employee job performance and overall business performance in the Jordan banking sector in the context of that country's banking sector. 292 samples from the research study were collected, analyzed, and debated to test the study's hypotheses. Employee and company success were found to be affected by workload, compensation, and organizational structure. Workload was reflected by job completion rate, average daily issues, and work completion time, while big data was reflected by external and internal, unique application, indexing, and source correctness. Work compensation, including employee compensation, employee experience and skill, and employee incentives and rewards, is the third primary factor. Communities of practice, group work, and physical infrastructure make up the fourth and last important factor, the organization's structure. The study finds that when dealing with large amounts of data, reducing the workload can improve employee performance, increasing employee motivation through higher wages and bonuses can improve performance, and having an organizational structure that promotes teamwork and work teams can improve employees' abilities to solve problems and improve work performance, which in turn affects overall productivity. This study contributes fresh information to an emerging field that requires more investigation to fully understand the interplay between big data, workload, work wages, and organizational structure pressures. The topic of this study, the Jordan banking sector, is both innovative and highly relevant because it may help financial institutions enhance their operations and provide superior customer service.