Artificial intelligence and machine learning in corporate governance: A bibliometric analysis

BACKGROUND: The study deeply explores the thriving domains of artificial intelligence (AI) and machine learning (ML) in corporate governance. OBJECTIVE: The study aims to thoroughly examine the rapidly developing fields of artificial intelligence (AI) and machine learning (ML) in corporate governance. METHODS: After completing an in-depth analysis of 229 research studies published between 2008 and 2023 (using software tools such as RStudio, VOSviewer, and Excel),), the study reveals a notable increase in publications since 2022. Corporate social responsibility (CSR), environmental, social, and governance (ESG) issues, executive remuneration, and sustainability are all considered as important key focal areas of focus. Scholars in this field are notably at the forefront from Taiwan, the United States, and China. IMPLICATIONS: However, the study stress the necessity for further researches to estimate the efficacy of different AI and ML methodologies. This may guide evidence-based governance practices various industries and geographical areas.

Authors

Institutions

Publication Details

Journal
Human Systems Management
Published
2024-09-21
DOI
https://doi.org/10.3233/hsm-240114
Citations
35
Primary Topic
Innovation, Sustainability, Human-Machine Systems
Type
article
Field-Weighted Citation Impact
39.62
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence and machine learning in corporate governance: A bibliometric analysis

Husni Samara, Hanan Ahmad Qudah, Hayder Jerri Mohsin, Mohammad Zakaria AlQudah et al.
35 citations
Human Systems Management
Innovation, Sustainability, Human-Machine Systems
39.62
article

Artificial intelligence and machine learning in corporate governance: A bibliometric analysis

Husni Samara, Hanan Ahmad Qudah, Hayder Jerri Mohsin, Mohammad Zakaria AlQudah, Laith Yousef Bani Hani, Seba Abualhijad, Samer Al rahamneh
article en
35 citations

Abstract

BACKGROUND: The study deeply explores the thriving domains of artificial intelligence (AI) and machine learning (ML) in corporate governance. OBJECTIVE: The study aims to thoroughly examine the rapidly developing fields of artificial intelligence (AI) and machine learning (ML) in corporate governance. METHODS: After completing an in-depth analysis of 229 research studies published between 2008 and 2023 (using software tools such as RStudio, VOSviewer, and Excel),), the study reveals a notable increase in publications since 2022. Corporate social responsibility (CSR), environmental, social, and governance (ESG) issues, executive remuneration, and sustainability are all considered as important key focal areas of focus. Scholars in this field are notably at the forefront from Taiwan, the United States, and China. IMPLICATIONS: However, the study stress the necessity for further researches to estimate the efficacy of different AI and ML methodologies. This may guide evidence-based governance practices various industries and geographical areas.

Human Systems Management
Andhra University (IN), Princess Sumaya University for Technology (JO), Universitat de València (ES), Al-Balqa Applied University (JO), Southern Technical University (IQ), Universidad de Extremadura (ES)
Openalex Percentile: Top 0%
Innovation, Sustainability, Human-Machine Systems
39.62
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.