Addressing Voluntary Turnover in Manufacturing Sectors: An Empirical Study

Main objectives. Voluntary turnover of employees are increasingly becoming serious problems in manufacturing sectors. Turnover creates a hindrance to practical access to ensure a continuous production process. That is why, turnover prediction model was proposed to add resssuch problem in manufacturing organizations. Background problems. Despite the introduction of automation in manufacturing-based organizations across the world, Human resources are still one of the key determinants of production and Voluntary employee turnover still remain the barrier to remove such problem. Novelty. The study took broad aspects resulting in voluntary turnover firstly and applied the multinomial regression and multilayer perceptron model for analyzing categorical data. Research method. Along with the descriptive analysis, the research applied multinomial regression and multilayer perceptron model to analyze data. Besides,Secondary data of manufacturing-based organization was collected from kaggle.com archive for the study purpose. Findings:Table 2 to 8 display the empirical findings of the study. Table 5 explained correlation and table 6 showed regression results of the study. Correlations showed that performance score and complaints directly contribute to the turnover decision, while multinomial regression proved that error, performance score, pay, complaints, abutments lead to the voluntary turnover decision. Contribution. The findings contribute to the literature by identifying different causes of voluntary turnover in manufacturing organizations. The study will help the manufacturing organizations to address the voluntary turnover. Conclusions. The different independent variables (the reason for termination, performance score, pay, error, and _90_days, etc.)are identified to suggest the possible action to be taken by the organization to minimize the influence of voluntary turnover. Manufacturing organizations may be able to take necessary actions to recruit or retain the existing workers with the identification of workers who may leave the organizations.