Exploring the Intersection of Artificial Intelligence and Human Resource Management: A Bibliometric Study

Artificial Intelligence presents promising opportunities to improve efficiency, enhance decision-making, and boost employee engagement within human resource management. This study explores the intersection of Artificial Intelligence and Human Resource Management through an in-depth bibliometric analysis, offering a comprehensive overview of research trends and advancements over the past decade. Drawing from the Web of Science database, this research examined 491 journal articles published from 2014 to 2023. AI applications in Human Resource Management have been particularly valuable during the COVID-19 pandemic, aiding healthcare professionals, facilitating remote work, and optimizing workforce management under challenging conditions. Implementing Artificial Intelligence in Human Resource Management leadership management and information management has significantly improved organizational processes and outcomes. The study concludes that ongoing advancements in Artificial Intelligence technology will continue to enhance Artificial Intelligence practices, leading to a more adaptable, responsive, and efficient workforce capable of addressing future challenges.

Authors

Institutions

Publication Details

Journal
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE
Published
2024-12-03
DOI
https://doi.org/10.70594/brain/15.4/15
Citations
2
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.69
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the Intersection of Artificial Intelligence and Human Resource Management: A Bibliometric Study

Betül Yıkıcı, Gökmen Dağlı, Rustam Shadiev, Zehra Altınay et al.
2 citations
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE
Organizational and Employee Performance
0.69
article

Exploring the Intersection of Artificial Intelligence and Human Resource Management: A Bibliometric Study

Betül Yıkıcı, Gökmen Dağlı, Rustam Shadiev, Zehra Altınay, Fahriye Altınay, Phillip Benachour, Muhammet Berigel, Ahmet Ayaz, Ebba Ossiannilsson
article en
2 citations

Abstract

Artificial Intelligence presents promising opportunities to improve efficiency, enhance decision-making, and boost employee engagement within human resource management. This study explores the intersection of Artificial Intelligence and Human Resource Management through an in-depth bibliometric analysis, offering a comprehensive overview of research trends and advancements over the past decade. Drawing from the Web of Science database, this research examined 491 journal articles published from 2014 to 2023. AI applications in Human Resource Management have been particularly valuable during the COVID-19 pandemic, aiding healthcare professionals, facilitating remote work, and optimizing workforce management under challenging conditions. Implementing Artificial Intelligence in Human Resource Management leadership management and information management has significantly improved organizational processes and outcomes. The study concludes that ongoing advancements in Artificial Intelligence technology will continue to enhance Artificial Intelligence practices, leading to a more adaptable, responsive, and efficient workforce capable of addressing future challenges.

BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCEVol. 15(4)
Karadeniz Technical University (TR), IQ Samhällsbyggnad (SE), University of Kyrenia (CY), Lancaster University (GB), Near East University (CY), Zhejiang University (CN)
Openalex Percentile: Top 23%
Organizational and Employee Performance
0.69
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.