Big Data-driven Algorithmic Decision-Making in Selecting and Managing Employees: Advanced Predictive Analytics, Workforce Metrics, and Digital Innovations for Enhancing Organizational Human Capital

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 per...

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Bibliographic Details
Published in:Psychosociological issues in human resource management 2019-01, Vol.7 (2), p.49-54
Main Authors: Meyers, Thomas D, Vagner, Ladislav, Janoskova, Katarina, Grecu, Iulia, Grecu, Gheorghe
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Conflicts of interest
Customer relationship management
Decision making
Educational philosophy
Employees
Employers
Executives
Human capital
Human resource management
Innovations
Land use
Management and complex organizations
Multiculturalism & pluralism
Petroleum services industry
Postmodernism
Predictive analytics
Structural equation modeling
Technological change
Workforce
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Summary: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.
ISSN:2332-399X
2377-0716
DOI:10.22381/PIHRM7120198