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
- Husni Samara (ORCID: https://orcid.org/0009-0002-8807-8349)
- Hanan Ahmad Qudah (ORCID: https://orcid.org/0000-0002-4611-4244)
- Hayder Jerri Mohsin (ORCID: https://orcid.org/0009-0007-6743-9826)
- Mohammad Zakaria AlQudah (ORCID: https://orcid.org/0000-0002-2781-1028)
- Laith Yousef Bani Hani (ORCID: https://orcid.org/0000-0002-4233-1516)
- Seba Abualhijad
- Samer Al rahamneh
Institutions
- 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)
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