Research Article
Modeling of Job Tenure: Insights from Russia
@INPROCEEDINGS{10.4108/eai.2-12-2022.2327918, author={Fengchen Wang and William Attatsitsey and Romie F. Littrell and Natalia Volkova}, title={Modeling of Job Tenure: Insights from Russia}, proceedings={Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqing, China}, publisher={EAI}, proceedings_a={ICICA}, year={2023}, month={3}, keywords={job tenure employee retention categorical regression model (catreg) demographic variables people analytics digital hrm job board russia}, doi={10.4108/eai.2-12-2022.2327918} }
- Fengchen Wang
William Attatsitsey
Romie F. Littrell
Natalia Volkova
Year: 2023
Modeling of Job Tenure: Insights from Russia
ICICA
EAI
DOI: 10.4108/eai.2-12-2022.2327918
Abstract
Over the years, both business practitioners and social scientists have been concerned about employee turnover. Several attempts to estimate the job tenure of an individual given specific criteria have been made as a result of this. An index called "job tenure" shows how stable a person's employment is over time. One measure of loyalty in the workplace is length of employment. Employee pleasure is reflected in loyalty, which raises productivity and, in turn, increases business profitability. With the aid of the categorical regression model with optimal scaling technique (CATREG) and CV data from HeadHunter, the largest job board in Russia, this study uses data from Russia and takes into account the employee's age, gender, and educational levels to build a model that anticipates their employment tenure. Our findings make it abundantly evident that, in the case of the Russian labor market, the older the job seeker or an employee is and the better educational level they possess, the longer employment duration may be anticipated within an organization.