TECHNOLOGICAL ADAPTABILITY AS A MODERATING VARIABLE OF THE INFLUENCE OF DIGITAL TECHNOLOGY-ORIENTED EMPLOYEE SELECTION PROCESSES ON EMPLOYEE PERFORMANCE

Abstrak

In the era of modern industrial transformation, the integration of digital instruments in human resource management has become a crucial determinant of operational efficiency. This study aims to analyze and empirically prove the influence of a digital technology-oriented employee selection process on employee performance, position technological adaptability as a moderating variable. Employing a causal quantitative approach, data were gathered through structured questionnaires from a sample of employees recruited via artificial intelligence (AI)-based selection systems and other digital platforms. Data analysis was executed using the Moderated Regression Analysis (MRA) framework to examine the interactions between components. The analytical results indicate that digital technology-oriented employee selection has a partially positive and significant impact on individual workplace performance. Furthermore, technological adaptability is proven to act as a quasi-moderator that strengthens this causal relationship. These adaptation findings emphasize that the effectiveness of sophisticated digital recruitment systems will only be optimized in generating superior performance if aligned with the candidates' inherent capacity for technology. Practical implications for organizations highlight the importance of revising selection criteria to focus not only on concurrent technical competencies but also on the cognitive flexibility of employees toward future technological updates.

Keywords: Digital Employee Selection, Employee Performance, Technological Adaptability, Moderating Variables, Human Resource Management