Addressing Voluntary Turnover in Manufacturing Sectors: An Empirical Study
DOI:
https://doi.org/10.5281/zenodo.4468529Keywords:
Human resource management,, Employee turnover, Multilayer perceptron, Multinomial regression, Turnover predictionAbstract
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 address such 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.
References
Aharon Tziner, Edna Rabenu, Ruth Radomski, Alexander Belkin. (2015). Work stress and turnover intentions among hospital physicians: The mediating role of burnout and work satisfaction. Journal of Work and Organizational Psychology, 31(2015), 207-213. https://doi.org/10.1016/j.rpto.2015.05.001
Baron, J.N., Hannan, M. T., Burton, M.D.,. (2001). Labor pains: change in organizational models and employee turnover in young, high-tech firms. Am. J. Social, 106(4, Rev. 44 (3)), 8-36. https://doi.org/10.1086/320296
Bontis, M. Stoval and N. (2002). “Voluntary turnover: Knowledge management – Friend or foe? Journal of Intellectual Capital, 3(3), 303-322. https://doi.org/10.1108/14691930210435633
Boundless. (2015, 08 21). Herzberg's two-factor theory. Boundless Management. Retrieved from https://www.boundless.com/management/textbooks/boundless-management-textbook/ organizational behavior-5/employee-needs-and-motivation-46/herzberg-s-two-factor-theory-239-6609.
Boyne, G. A., O. James, P. John, and N. Petrovsky. (2010). Does Public Service Performance Affect Top Management Turnover? Journal of Public Administration Research and Theory, 20(2), i261-i279.https://doi.org/10.1093/jopart/muq024
Boyne, G., and J. Dahya. (2002). Executive Succession and the Performance of Public organizations. Public Administration, 80(1), 179-200. https://doi.org/10.1111/1467-9299.00299
Burbeck, R., Coomber, S., Robinson, S.M., & Todd, C. (2002). Occupational stress in Consultants in accidient and emergency medicine: A national survey of levels of stress at work. Emergency Medicine Journal, 19, 234-238. https://doi.org/10.1136/emj.19.3.234
Clinton, M.E. & Guest, D.E. (2014). Psychological contract breach and voluntary turnover: Testing a multiple mediation model. Journal of Occupational and Organizational Psychology, 87, 200-207. https://doi.org/10.1111/joop.12033
Coad, A., Daunfeldt, S. O., Johansson, D., Wennberg, K.,. (2014). Who do high-growth firms hire? Ind. Corp. Change, 23(1), 293-327. https://doi.org/10.1093/icc/dtt051
Cooke, F. (2013). Human resource development and innovation in China: state HRD policies, organizational practices, and research opportunities. J. Chinese Hum. Resource Mgt., 2, 144-150.
Demier, R., Wennberg, K., Mckelvie, A.,. (2017). The strategic management of high-growth firms: a review and theoreitical conceptualization. Long Range Plan, 50, 431-456. https://doi.org/10.1016/j.lrp.2016.09.004
Denis Enaˇchescu (2004). Multilayer perceptron model for prostate cancer prediction, International Journal of Computer Mathematics, 81:4, 407-415, DOI: 10.1080/00207160410001661302
DeTienne, K.B., Agle, B.R., Phillips, J.C. & Ingerson, M.C. (2012). The impact of moral stress compared to other stressors on employee fatigue, job satisfaction, and turnover: An empirical investigation. Journal of Business Ethics, 110(3), 377-391. https://doi.org/10.1007/s10551-011-1197-y
Direnzo, M.S. & Greenhaus, J.H. (2011). Job search and voluntary turnover in a boundaryless world: A control theory perspective. Academy of Management Review, 36(3), 567–589. https://doi.org/10.5465/amr.2009.0333
Dunford, B. B., Shipp, A.J., Boss, R.W., Angemeier, I. & Boss, A.D. (2012). Is burnout statis or dynamic? A career transition perspective of employee burnout trajectories. Journal of Applied Psychology, 97, 637-650. https://doi.org/10.1037/a0027060
Fullerton, A. S. (2009). A conceptual framework for ordered logistic regression models. Sociological Methods & Research, 38(2), 306–347. https://doi.org/10.1177/0049124109346162 .
García-Altés, A., Santín, D., & Barenys, M. (2007). Applying artificial neural networks to the diagnosis of organic dyspepsia. Statistical methods in medical research, 16(4), 331-346. https://doi.org/10.1177/0962280206071839
Gogia, P. (2010, 09 14). Equity theory of motivation. Retrieved from Retrieved from http://www.businessihub.com/equity-theory-of-motivation/
Goodman, E. A., & Boss, R. W. (2002). The phase model of burnout and employee turnover. Journal of Health and Human Services Administration, 25(1), 33-47.
Luis R. Gomez-Mejia, Manuel Nuñez-Nickel, Isabel Gutierrez (2001). The role of falimy ties in agency contracts. Academy of management journal, 23(1), 35-55. https://doi.org/10.5465/3069338
Griffeth, R.W., Hom, P.W. & Gaertner, S. (2000). A metaanalysis of antecedents and correlates of employee turnover: Update, moderator tests, and research implications for the next millennium. Journal of Management, 26(3), 463–488. doi.org/10.1177/014920630002600305
Hamzah Abdul Hamid, Y. B.-J. (2018). Investigating the power of goodness-of-fit tests for multinomial logistic regression. Communications in Statistics - Simulation and Computation, 47(4), 1039-1055. doi:10.1080/03610918.2017.1303727
Hausknecht, J. P., and C. O. Trevor. (2011). Collective Turnover at the Group, Unit, and Organizational Levels: Evidence, Issues and Implications. Journal of Management, 37(1), 352-388. https://doi.org/10.1177/0149206310383910
David W. Hosmer, Stanley Lemeshow, Rodney X. Sturdivant (2013). Applied Logistic Regression (Vol. 398). Hoboken: NJ: John Wiley & Sons, Inc. https://doi.org/10.1002/9781118548387
Klein. J., Frie, K.G., Blum, K., & Von dem Knesebeck, O. (2011). Phychological stress at work and perceived quality of care among clinicans in surgery. BMC Health services research, 11, 109-117. https://doi.org/10.1186/1472-6963-11-109
Kurt, I., Ture, M., & Kurum, A. T. (2008). Comparing performances of logistic regression, classification and regression tree, and neural networks. Expert systems with applications, 34(1), 366-374. https://doi.org/10.1016/j.eswa.2006.09.004
Lee, S.-Y., and A. B. Whitford. (2013). “Assessing the Effects of Organizational Resources on Public Agency Performance: Evidence from the US Federal Government. Journal of Public Administration Research and Theory, 23(3), 687-712. https://doi.org/10.1093/jopart/mus050
Maltarich, M.A., Nyberg, A.J. & Reilly, G. (2010). A conceptual and empirical analysis of the cognitive ability– voluntary turnover relationship. Journal of Applied Psychology, 95(6), 1058–1070. https://doi.org/10.1037/a0020331
MartinˇCecha, W. Y. (2016). Human Resource Management in Chinesemanufacturing companies. Perspectives in Science, 6-9.
Md. Habibur Rahman, Mst. Rinu Fatema and Md. Hazrat Ali. (2019). Impact of Motivation and Job Satisfaction on Employee’s Performance: An Empirical Study. Asian Journal of Economics, Business and Accounting, 10(4), 1-10. https://doi.org/10.9734/ajeba/2019/v10i430112
Messersmith, Jake G., Jeong-Yeon Lee, James P. Guthrie, and Yong-Yeon Ji. (2014). Turnover at the Top: Executive Team Departures and Firm Performance. Organization Science, 25(3), 776-793. https://doi.org/10.1287/orsc.2013.0864
Mitchell, R. K., Morse, E. A., & Sharma, P. (2003). The transacting conditions of nonfamily employees in the family business setting. Journal of Business Venturing, 18(4), 533-551. https://doi.org/10.1016/s0883-9026(03)00059-4
Morrow-Howell, N. P. (2008). The use of logistic regression in social work research. Journal of Social Service Research, 16(1–2), 87–104. https://doi.org/10.1300/j079v16n01_05
Nyberg, A. J., & Ployhart, R. E. (2013). Context-emergent turnover (cet) theory: A theory of collective turnover. Academy of Management Review, 38(1), 109–131. https://doi.org/10.5465/amr.2011.0201
Peter W. Hom, David G. Allen, Rodger W. Griffeth. (2019). Causes and Correlates of Turnover. In D. G. Peter W. Hom, Employee Retention and Turnover: Why Employees Stay or Leave (1st Edition ed., p. 25). New York: Routledge. doi:https://doi.org/10.4324/9781315145587
Pfeffer, J. (2005). Changing mental models: HR’s most important task’. Human Resource Management, 44(2), 123-128. https://doi.org/10.1002/hrm.20053
Pines, A. M. & Keinan, G. (2005). Stress and Burnout: The significance difference. Personality and Individual Differences, 39, 625-635. https://doi.org/10.1016/j.paid.2005.02.009
Principe, J. C., Euliano, N. R., & Lefebvre, W. C. (2000). Innovating adaptive and neural systems instruction with interactive electronic books , 88 (1), 81-95. https://doi.org/10.1109/5.811604
Quezada-Sarmiento, P. A., Macas-Romero, J. D. C., Roman, C., & Martin, J. C. (2018). A body of knowledge representation model of ecotourism products in southeastern ecuador. Heliyon, 4(12). https://doi.org/10.1016/j.heliyon.2018.e01063
Rappaport, A., Bancroft, E., & Okum, I. (2003). The Aiging workforce raises new talent management issues for employeers. Journal of Organizational Excellence, 23(1), 55-66. https://doi.org/10.1002/npr.10101
Shaw, J. D. (2011). Turnover rates and organizational performance: Review, critique, and research agenda. Organizational Psychology Review, 1(3), 187–213. doi.org/10.1177/2041386610382152
Seung-HoAn. (2019). Employee Voluntary and Involuntary Turnover and Organizational Performance: Revisiting the Hypothesis from Classical Public Administration. International Public Management Journal, 1-26. https://doi.org/10.1080/10967494.2018.1549629
Shamika Almeida, Mario Fernando, Zeenobiyah Hannif & Shyamali C. Dharmage (2015) Fitting the mould: the role of employer perceptions in immigrant recruitment decision-making, The International Journal of Human Resource Management, 26:22, 28112832, DOI: 10.1080/09585192.2014.1003087
Shamsuzzoha, A. H. M., &Shumon, R. H. (2010). Employee turnover: A study of its causes and effects to different industries in Bangladesh. International Journal of Humanities and Social Science(Special Issue), 64-68.
Shukla, S., & Sinha, A. (2013). Employees’ turnover in banking sector: Empirical evidence. IOSR Journal of Humanities and Social Science,, 11(5), 57-61. https://doi.org/10.9790/0837-1155761
Sieger, P., Bernhard, F., & Vellella, R.F. (2011). Affective commitment and job satisfaction among non-family employees: investigating the roles of justice perceptions and psychological ownership. Journal of Family Business Strategy, 2(2), 79-89. https://doi.org/10.1016/j.jfbs.2011.03.003
Sincero, S. M. (2008). Two-factor theory of motivation. Retrieved from https://explorable.com/two-factor-theory-of-motivation.
Tseng, W.-T., Chiang, W.-F., Liu, S.-Y., Roan, J., & Lin, C.-N. (2015). The application of data mining techniques to oral cancer prognosis. Journal of medical systems, 39(5), 59. https://doi.org/10.1007/s10916-015-0241-3
Nikolaos Tsigilis, Athanasios Gregoriadis, Vasilis Grammatikopoulos, Evridiki Zachopoulou. (2018). Job satisfaction and burnout among Greek early educators. A comparison between public and private sector employees. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.00733
Watlington, E., R. Shockley, P. Guglielmino, and R. Felsher. (2010). The High Cost of Leaving: An Analysis of the Cost of Teacher Turnover. Journal of Education Finance, 36(1), 22-37. https://doi.org/10.1353/jef.0.0028
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 International Fellowship Journal of Interdisciplinary Research
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
