Abstract
Business organizations have introduced data analytics to human resource management (HRM) to predict employee behavior in recent years. This practice is called HR analytics, and uses the various properties of employees, including their personal values, as inputs. Personal values are conceptualized as stable personal traits that represent the relevant employee. Previous studies in the area have shown that the personal values of employees influence their attitudes and behaviors as well as the performance of their group. Assessing these values is thus important in HRM. Although most previous studies have measured personal values based on self-reported questionnaires, this method encounters many problems, such as the social desirability bias. Accordingly, more recent studies have proposed alternative methods that apply machine learning algorithms to linguistic or visual data. This study reviews research on personal values by focusing on the methods used to measure them, and discusses the usefulness of and the challenges to the measurement of personal values. We also discuss future directions of research on the assessment of personal values.