Geodesic
Predictors of Employees’ Voluntary Turnover Intentions: Analytic Hierarchy Process Approach
Yugoslav journal of operations research, Tome 34 (2024) no. 3, p. 587 .

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The possibility to prevent employees` turnover intentions are important issue for organizations but it is not easy without identifying risk factors. HR analytic methods are seen as the valuable tools for extracting and weighting predictors of employees` withdrawal behavior. This paper ilustrates the potential of analytic hierarchy process method for identifying key predictors of voluntary turnover intentions. The analysis is conducted on 665 production employees using five criteria: work satisfaction, work characteristics (job motivating potential), intrinsic motivation, life aspirations and needs, from the most to the least weighted. Two parementers were included, sector where employees work and their shift. Results indicate the sectors and shift employing people with highest risk of turnover demonstrating the effectivness of using AHP method for the purpose. As previous studies that uses HR analytics tools in the domain mainly operated with demographic and general employees` data, while more orthodox HR approaches focus on direct effect of job satisfaction, we offered the combination of those two. We imply that the integration of more subjective data collected directly from employee, might be integrated in the overal personnel database and available for processing with HR analytic tools.
Keywords: Analytic hierarchy process, turnover intentions, employees, predictors 
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Ivana Kovačević; Ognjen Pantelić; Jelena Anđelković Labrović. Predictors of Employees’ Voluntary Turnover Intentions: Analytic Hierarchy Process Approach. Yugoslav journal of operations research, Tome 34 (2024) no. 3, p. 587 . http://geodesic.mathdoc.fr/item/YJOR_2024_34_3_a10/