The turnover literature is expansive, however empirical evidence on turnover using data science tools remains limited. We propose a novel examination of turnover antecedents-competencies, commitment, trust and values-using big data tools to develop a granular, case-dependent measure of turnover. Using archival data from 700,000 employees of a large organization collected over a decade, we find that turnover changes according to its antecedents' levels. However, in more fine-grained analysis, their effect on turnover is contingent upon role, person and cultural background. We discuss turnover implications and the potential of data science methods in the implementation of managerial and HR initiatives.
|State||Published - 2021|
|Event||81st Annual Meeting of the Academy of Management 2021: Bringing the Manager Back in Management, AoM 2021 - Virtual, Online|
Duration: 29 Jul 2021 → 4 Aug 2021
|Conference||81st Annual Meeting of the Academy of Management 2021: Bringing the Manager Back in Management, AoM 2021|
|Period||29/07/21 → 4/08/21|