Implementation of Digital Human Resource Management (E-HRM) to Improve Organizational Efficiency in the Industry 4.0 Era

Technological developments in the Industry 4.0 era have driven significant digital transformation in various sectors, including human resource management. Electronic Human Resource Management (E-HRM) is a crucial innovation that enables integrated, digital-based HR management processes. This study aims to analyze the benefits, barriers, and optimization strategies for implementing E-HRM to improve organizational efficiency. The method used was a Systematic Literature Review (SLR) of 70 selected articles from the Scopus, Web of Science, and Google Scholar databases, with the PRISMA protocol applied in the literature selection process. The results show that implementing E-HRM can have a positive impact on organizational efficiency by accelerating administrative processes, saving operational costs, increasing data accuracy, and enabling faster, data-driven decision-making. However, several obstacles such as organizational cultural resistance, low digital literacy, limited technological infrastructure, and high initial implementation costs are challenges that need to be overcome. Recommended optimization strategies include ongoing digital literacy training, top management support, and the integration of artificial intelligence-based technology. These findings confirm that E-HRM can be a major catalyst in improving organizational efficiency and competitiveness in the era of digital transformation.

Authors

Publication Details

Journal
Maneggio
Published
2025-08-22
DOI
https://doi.org/10.62872/3qy9km17
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Implementation of Digital Human Resource Management (E-HRM) to Improve Organizational Efficiency in the Industry 4.0 Era

Prastiyo Diatmono
Maneggio
Digital Transformation in Industry
article

Implementation of Digital Human Resource Management (E-HRM) to Improve Organizational Efficiency in the Industry 4.0 Era

Prastiyo Diatmono
article en

Abstract

Technological developments in the Industry 4.0 era have driven significant digital transformation in various sectors, including human resource management. Electronic Human Resource Management (E-HRM) is a crucial innovation that enables integrated, digital-based HR management processes. This study aims to analyze the benefits, barriers, and optimization strategies for implementing E-HRM to improve organizational efficiency. The method used was a Systematic Literature Review (SLR) of 70 selected articles from the Scopus, Web of Science, and Google Scholar databases, with the PRISMA protocol applied in the literature selection process. The results show that implementing E-HRM can have a positive impact on organizational efficiency by accelerating administrative processes, saving operational costs, increasing data accuracy, and enabling faster, data-driven decision-making. However, several obstacles such as organizational cultural resistance, low digital literacy, limited technological infrastructure, and high initial implementation costs are challenges that need to be overcome. Recommended optimization strategies include ongoing digital literacy training, top management support, and the integration of artificial intelligence-based technology. These findings confirm that E-HRM can be a major catalyst in improving organizational efficiency and competitiveness in the era of digital transformation.

ManeggioVol. 2(4)
Openalex Percentile: Top 66%
Digital Transformation in Industry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.