Analysis of the Effect of Skills-Based Hiring and AI Application in the Selection Process on Employee Turnover Intention
Keywords:
skills-based hiring, artificial intelligence, turnover intention, SmartPLS 3.0, PLS SEMAbstract
This study aims to analyze the effect of skills-based hiring on the use of AI in the selection process and employee turnover intention, as well as the effect of the use of AI in the selection process on employee turnover intention. The study employed a quantitative approach with 102 respondents selected using purposive sampling. Data were collected via a questionnaire using a 5-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the assistance of SmartPLS 3.0. The results indicate that Skills-Based Hiring has a positive and significant effect on the use of AI in the selection process, with a path coefficient of 0.424, a t-statistic of 5.063, and a p-value of 0.000. Skills-Based Hiring also has a positive and significant effect on Employee Turnover Intention, with a path coefficient of 0.270, a t-statistic of 2.831, and a p-value of 0.00482. Furthermore, the use of AI in the selection process has a positive and significant effect on employee turnover intention, with a path coefficient of 0.466, a t-statistic of 5.178, and a p-value of 0.000. The R-Square value indicates that Skills-Based Hiring explains 18.0% of the variation in AI Application in the Selection Process, while Skills-Based Hiring and AI Application in the Selection Process together explain 39.6% of the variation in Employee Turnover Intention. These findings indicate a significant relationship between skills-based hiring approaches, the application of AI in the selection process, and employee turnover intention.
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