Big Data-driven Algorithmic Decision-Making in Selecting and Managing Employees: Advanced Predictive Analytics, Workforce Metrics, and Digital Innovations for Enhancing Organizational Human Capital
Thomas D. Meyers et al.ABSTRACT. Employing recent research results covering big data-driven algorithmic decision-making in selecting and managing employees, and building our argument by drawing on data collected from Bright & Company, Corporate Research Forum, Deloitte, Management Events, McKinsey, and Top Employers Institute, we performed analyses and made estimates regarding data-driven approaches in organizations. Structural equation modeling was used to analyze the collected data.
JEL codes: E24; J21; J54; J64
Keywords: predictive analytics; workforce metrics; organizational human capital
How to cite: Meyers, Thomas D., Ladislav Vagner, Katarina Janoskova, Iulia Grecu, and Gheorghe Grecu (2019). “Big Data-driven Algorithmic Decision-Making in Selecting and Managing Employees: Advanced Predictive Analytics, Workforce Metrics, and Digital Innovations for Enhancing Organizational Human Capital,” Psychosociological Issues in Human Resource Management 7(2): 49–54. doi:10.22381/PIHRM7220198
Received 8 July 2019 • Received in revised form 13 September 2019
Accepted 15 September 2019 • Available online 11 October 2019
