TRENDS, CONCEPTUAL STRUCTURE, AND THEMATIC EVOLUTION IN FRAUD AND CORPORATE GOVERNANCE: A BIBLIOMETRIC ANALYSIS
DOI:
https://doi.org/10.70248/jakpt.v4i1.4748Abstract
This study aims to map publication growth, scientific impact, leading contributors, conceptual structure, and thematic evolution in fraud and corporate governance research. A bibliometric analysis was conducted on 500 journal articles indexed in Dimensions and published between 2021 and 2026. The metadata were analysed using RStudio and the bibliometrix package through annual scientific production, citation, source, author, affiliation, country, influential document, keyword co-occurrence, thematic map, and thematic evolution analyses. The results show that annual publications increased from 57 articles in 2021 to a temporary peak of 123 articles in 2024. Earlier publications received higher average citations because of their longer citation windows. PLOS ONE and Heliyon were the most productive sources, Wang Y and Zhang Y were the most productive author names and China made the largest national contribution. However, the dominance of multidisciplinary and environmental journals among the most productive sources suggests that the corpus retrieved is broader than the traditional accounting, finance and corporate governance outlets. This condition may influence the interpretation of thematic patterns, indicating that the results should be interpreted as representing a wider interdisciplinary corpus rather than a narrowly specialised fraud–corporate governance literature. The conceptual structure connects investment, organisational behaviour, auditing, risk management, and technology, while fraud is associated with financial auditing, artificial intelligence, and neural networks. However, corporate governance has not yet emerged as a central theme, while the thematic evolution remains influenced by environmental and health-related issues. Future research should integrate governance mechanisms with artificial intelligence, machine learning, digital auditing, and fraud early-warning systems, while expanding cross-country comparisons and distinguishing among different forms of fraud.
References
Abbott, L. A., Park, Y., & Parker, S. (2000). The effects of audit committee activity and independence on corporate fraud. Managerial Finance, 26(11), 55–68. https://doi.org/10.1108/03074350010766990
Agrawal, A., & Chadha, S. (2005). Corporate governance and accounting scandals. Journal of Law and Economics, 48(2), 371–406. https://doi.org/10.1086/430808
Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
Bao, Y., Ke, B., Li, B., Yu, Y. J., & Zhang, J. (2020). Detecting accounting fraud in publicly traded U.S. firms using a machine learning approach. Journal of Accounting Research, 58(1), 199–235. https://doi.org/10.1111/1475-679X.12292
Broadstock, D. C., & Chen, X. (2021). Corporate site visits, private monitoring and fraud: Evidence from China. Finance Research Letters, 40, 101780. https://doi.org/10.1016/j.frl.2020.101780
Chen, G., Firth, M., Gao, D. N., & Rui, O. M. (2006). Ownership structure, corporate governance, and fraud: Evidence from China. Journal of Corporate Finance, 12(3), 424–448. https://doi.org/10.1016/j.jcorpfin.2005.09.002
Chen, J., Ezzamel, M., & Cai, Z. (2020). Corporate governance in China: A survey. Review of Finance, 24(4), 733–772. https://doi.org/10.1093/rof/rfaa012
Christensen, H. B., Hail, L., & Leuz, C. (2021). Mandatory CSR and sustainability reporting: Economic analysis and literature review. Review of Accounting Studies, 26(3), 1176–1248. https://doi.org/10.1007/s11142-021-09609-5
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002
Cohen, S., Eimicke, W., & Heikkila, T. (2019). Board committees in corporate governance: A cross-disciplinary review and agenda for the future. Journal of Management Studies, 56(6), 1138–1193. https://doi.org/10.1111/joms.12444
Craja, P., Kim, A., & Lessmann, S. (2020). Deep learning for detecting financial statement fraud. Decision Support Systems, 139, 113421. https://doi.org/10.1016/j.dss.2020.113421
Dechow, P. M., Ge, W., Larson, C. R., & Sloan, R. G. (2011). Predicting material accounting misstatements. Contemporary Accounting Research, 28(1), 17–82. https://doi.org/10.1111/j.1911-3846.2010.01041.x
Devi, P. V. S. (2024). Corporate governance as a detector of financial statement fraud: Systematic literature review. Asia Pacific Fraud Journal, 9(1). https://doi.org/10.21532/apfjournal.v9i1.342
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
Dorminey, J., Fleming, A. S., Kranacher, M.-J., & Riley, R. A. (2012). The evolution of fraud theory. Issues in Accounting Education, 27(2), 555–579. https://doi.org/10.2308/iace-50131
Du, X. (2020). Corporate governance: Five-factor theory-based financial fraud identification. Journal of Chinese Governance, 6(4), 456–482. https://doi.org/10.1080/23812346.2020.1803036
Eugster, F., Isakov, D., & Weisskopf, J.-P. (2024). Corporate governance and corporate misconduct: A meta-analytic review. International Review of Financial Analysis, 92, 103109. https://doi.org/10.1016/j.irfa.2024.103109
Farber, D. B. (2005). Restoring trust after fraud: Does corporate governance matter? The Accounting Review, 80(2), 539–561. https://doi.org/10.2308/accr.2005.80.2.539
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27, 938–985. https://doi.org/10.1007/s11142-022-09697-x
Files, R., & Liu, X. (2022). Unraveling financial fraud: The role of the board of directors and external advisors in conducting independent internal investigations. Contemporary Accounting Research, 39(3), 1907–1944. https://doi.org/10.1111/1911-3846.12784
Free, C. (2015). Looking through the fraud triangle: A review and call for new directions. Meditari Accountancy Research, 23(2), 175–196. https://doi.org/10.1108/MEDAR-02-2015-0009
He, L., Conyon, M. J., & Chen, J. (2020). Signaling via earnings downgrades: How reputational concerns shape analyst responses to corporate fraud. Corporate Governance: An International Review, 28(5), 327–348. https://doi.org/10.1111/corg.12322
Hogan, C. E., Rezaee, Z., Riley, R. A., & Velury, U. K. (2008). Financial statement fraud: Insights from the academic literature. Auditing: A Journal of Practice & Theory, 27(2), 231–252. https://doi.org/10.2308/aud.2008.27.2.231
Kassem, R. (2022). Elucidating corporate governance’s impact and role in countering fraud. Corporate Governance, 22(7), 1523–1546. https://doi.org/10.1108/CG-08-2021-0279
Li, J. (2025). Corporate governance, fraud learning cycles, and financial fraud detection in China. Research in International Business and Finance, 102832. https://doi.org/10.1016/j.ribaf.2025.102832
Lim, W. M., Kumar, S., & Donthu, N. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182, 114760. https://doi.org/10.1016/j.jbusres.2024.114760
Lokanan, M. E. (2015). Challenges to the fraud triangle: Questions on its usefulness. Accounting Forum, 39(3), 201–224. https://doi.org/10.1016/j.accfor.2015.05.002
Md Nasir, N. A., & Hashim, H. A. (2021). Corporate governance performance and financial statement fraud: Evidence from Malaysia. Journal of Financial Crime, 28(3), 797–809. https://doi.org/10.1108/JFC-09-2020-0182
Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de La Información, 29(1), e290103. https://doi.org/10.3145/epi.2020.ene.03
Mousavi, M., Zimon, G., Salehi, M., & Stępnicka, N. (2022). The effect of corporate governance structure on fraud and money laundering. Risks, 10(9), 176. https://doi.org/10.3390/risks10090176
Mukherjee, D., Lim, W. M., Kumar, S., & Donthu, N. (2022). Guidelines for advancing theory and practice through bibliometric research. Journal of Business Research, 148, 101–115. https://doi.org/10.1016/j.jbusres.2022.04.042
Öztürk, O. (2024). How to design bibliometric research: An overview and a framework proposal. Review of Managerial Science. https://doi.org/10.1007/s11846-024-00738-0
Rezaee, Z. (2005). Causes, consequences, and deterrence of financial statement fraud. Critical Perspectives on Accounting, 16(3), 277–298. https://doi.org/10.1016/S1045-2354(03)00072-8
Schmidt, J., & Wilkins, M. S. (2020). Does audit committee accounting expertise help to promote audit quality? Evidence from auditor reporting of internal control weaknesses. Contemporary Accounting Research, 37(2), 1063–1098. https://doi.org/10.1111/1911-3846.12517
Shi, W., Aguilera, R. V, & Wang, K. (2020). State ownership and securities fraud: A political governance perspective. Corporate Governance: An International Review, 28(2), 157–176. https://doi.org/10.1111/corg.12313
Siala, H., & Wang, Y. (2022). SHIFTing artificial intelligence to be responsible in healthcare: A systematic review. Social Science & Medicine, 296, 114782. https://doi.org/10.1016/j.socscimed.2022.114782
Skousen, C. J., Smith, K. R., & Wright, C. J. (2009). Detecting and predicting financial statement fraud: The effectiveness of the fraud triangle and SAS No. 99. International Journal of Quality & Reliability Management, 26(1), 53–81. https://doi.org/10.1108/02656710910928393
Trompeter, G. M., Carpenter, T. D., Desai, N., Jones, K. L., & Riley, R. A. (2013). A synthesis of fraud-related research. Auditing: A Journal of Practice & Theory, 32(Suppl. 1), 287–321. https://doi.org/10.2308/ajpt-50360
Vousinas, G. L. (2019). Advancing theory of fraud: The S.C.O.R.E. model. Journal of Financial Crime, 26(1), 372–381. https://doi.org/10.1108/JFC-12-2017-0128
Wang, Y., Yu, L., & Gao, S. (2022). Gender diversity and financial statement fraud. Journal of Accounting and Public Policy, 41(2), 106903. https://doi.org/10.1016/j.jaccpubpol.2021.106903
Wirba, A. V. (2024). Corporate social responsibility and the Sustainable Development Goals: What is the relationship? Journal of the Knowledge Economy, 15, 7428–7454. https://doi.org/10.1007/s13132-023-01185-0
Wu, W., Cao, J., & Zhang, W. (2023). Non-executive employee stock ownership plans and corporate financial fraud. Journal of Business Research, 163, 113922. https://doi.org/10.1016/j.jbusres.2023.113922
Xu, Y., Xiong, X., & An, Z. (2023). Using machine learning to predict corporate fraud: Evidence based on the GONE framework. Journal of Business Ethics, 186(1), 137–158. https://doi.org/10.1007/s10551-022-05120-2
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Jurnal Akuntansi, Keuangan, Perpajakan dan Tata Kelola Perusahaan
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
