Thematic Evolution and Research Trends in Business Crime: A Bibliometric Study

Objective: This study aims to map the intellectual landscape and thematic evolution of global scientific research on business crime from 2010 to 2025, in response to rapid technological, regulatory, and social transformations. Research Design & Methods: Bibliometric analysis was performed using data obtained from the Scopus database. This study used descriptive statistics, keyword co-occurrence, author and institutional productivity mapping, and trend analysis techniques. Tools such as VOSviewer and Excel were used to visualize collaboration networks and thematic clusters. Findings: The volume of academic publications on business crime increased significantly between 2010 and 2025, driven by new themes such as cybercrime, cryptocurrency fraud, and the use of AI and machine learning in criminal activity and prevention. While classic topics such as corruption and asset misappropriation remain relevant, recent studies increasingly adopt predictive analytics, forensic accounting, and geospatial mapping. The United States and the United Kingdom dominate contributions, reflecting their academic infrastructure and legal influence.Implications and Recommendations: Academically, these findings lay the groundwork for systematic literature reviews and the setting of future research agendas. Practically, these results emphasize the need for evidence-based policymaking and strategic planning in business crime prevention, particularly through technology-driven compliance systems. Contribution and Value Added: This study supports the development of a more cohesive, impactful, and integrated technological approach to tackling business crime in the digital age.

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Publication Details

Journal
Journal of Business Crime
Published
2025-09-30
DOI
https://doi.org/10.70764/gdpu-jbc.2025.1(2)-07
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

Thematic Evolution and Research Trends in Business Crime: A Bibliometric Study

Miftahul Jannah, Andi Afgan Nugraha, Rahmad Masturi, Md. Mokhlesur Rahman
Journal of Business Crime
Computational and Text Analysis Methods
article

Thematic Evolution and Research Trends in Business Crime: A Bibliometric Study

Miftahul Jannah, Andi Afgan Nugraha, Rahmad Masturi, Md. Mokhlesur Rahman
article en

Abstract

Objective: This study aims to map the intellectual landscape and thematic evolution of global scientific research on business crime from 2010 to 2025, in response to rapid technological, regulatory, and social transformations. Research Design & Methods: Bibliometric analysis was performed using data obtained from the Scopus database. This study used descriptive statistics, keyword co-occurrence, author and institutional productivity mapping, and trend analysis techniques. Tools such as VOSviewer and Excel were used to visualize collaboration networks and thematic clusters. Findings: The volume of academic publications on business crime increased significantly between 2010 and 2025, driven by new themes such as cybercrime, cryptocurrency fraud, and the use of AI and machine learning in criminal activity and prevention. While classic topics such as corruption and asset misappropriation remain relevant, recent studies increasingly adopt predictive analytics, forensic accounting, and geospatial mapping. The United States and the United Kingdom dominate contributions, reflecting their academic infrastructure and legal influence.Implications and Recommendations: Academically, these findings lay the groundwork for systematic literature reviews and the setting of future research agendas. Practically, these results emphasize the need for evidence-based policymaking and strategic planning in business crime prevention, particularly through technology-driven compliance systems. Contribution and Value Added: This study supports the development of a more cohesive, impactful, and integrated technological approach to tackling business crime in the digital age.

Journal of Business CrimeVol. 1(2)
Manado State University (ID)
Openalex Percentile: Top 61%
Computational and Text Analysis Methods
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