Use of Big Data in Human Resource Management to Strengthen Human Capital Management?
HR Big Data represents an innovative approach to managing large-scale employee-related data, offering significant opportunities for Human Resource Management (HRM). It enables companies to better understand their employees, make more informed decisions, and predict HR-related risks and opportunities. This new approach allows the processing of large volumes of data and the identification of relevant correlations for businesses, particularly in the HR field. However, the challenge lies in identifying relevant data and using it wisely to solve specific HR problems. Although widely regarded as a revolution in management press, academic research on HR Big Data remains limited, largely due to the difficulty of collecting and analyzing massive data sets. This article aims to increase the visibility and understanding of the potential contributions of HR Big Data to Human Resource Management from both a scientific and managerial perspective. The study seeks to propose an exhaustive classification of the HR Big Data literature, complemented by a comprehensive bibliography and a prospective research agenda. To achieve this, a systematic literature review methodology was adopted, based on a database of articles and books published in prestigious journals between 2010 and 2018. The results of this analysis reveal the main advances in HR analytics research. Major findings, as well as gaps in the existing literature, are also highlighted. This study has the potential to inspire new research directions.
Authors
- Hamza KATFI
- Ayoub Katfi (ORCID: https://orcid.org/0000-0002-6090-6643)
- Oumaima El Mnouer
- Sabrina GHALLAL
- Thierry Côme
- Fetta BOUDRICHE
Institutions
- Mohammed V University (MA)
- Université Paris-Saclay (FR)
- Université Hassan II Mohammedia (MA)
Publication Details
- Journal
- RMd Economics Management & Social Sciences
- Published
- 2024-10-28
- DOI
- https://doi.org/10.23882/emss25115
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00