Mohamad, Azhar
(2025)
Mapping the intellectual landscape of big data in accounting and finance: a decade of bibliometric analysis (2013-2023).
Journal of Scientometric Research, 14 (1).
pp. 201-220.
ISSN 2321-6654
E-ISSN 2320-0057
Abstract
This study examines the intellectual structure and research trends at the intersection of big data, accounting, and finance using a bibliometric analysis of 295 Scopus-indexed papers from 2013 to 2023. The study tackles the need to understand collaboration networks and topic evolutions in this dynamic environment. We discovered dominating research clusters, essential contributors, and topic trajectories before and after COVID-19 using co-authorship and keyword co-occurrence analyses. The methodology uses tools like VOSviewer and Biblioshiny to map collaboration patterns and thematic map concentrations. The findings show that international collaboration, notably amongst scholars from China, the United States, and the United Kingdom, is critical to advance the discipline. Traditional subjects such as “big data”, “finance”, and “accounting” dominate keyword research, while emergent topics such as “artificial intelligence”, “cloud computing”, and “risk assessment” represent technological improvements. The COVID-19 pandemic sparked new research avenues, introducing concepts like “neural networks” and “sustainable development goals”. The findings emphasise big data’s disruptive impact on financial and accounting procedures and the need for future studies to address regulatory, ethical, and transdisciplinary issues. This study adds to the literature by providing a complete analysis of big data research trends and a road map for scholars and practitioners to navigate the changing academic and industrial settings
Actions (login required)
 |
View Item |
Download Statistics
Download Statistics