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Hot spot mining and trend analysis of Economic Responsibility Audit based on knowledge graph

Author

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  • Zhu, Jingjuan
  • Zhang, Wenjie
  • Lu, Lingyun
  • Lu, Yi
  • Wang, Duo

Abstract

Economic Responsibility Audit (ERA) of China is a unique audit system in the world. To explore and predict the Chinese economy responsibility audit, this study conducts a multi-dimensional analysis of research literature on ERA from 1986 to 2022 based on knowledge graph. Using Citespace software, we established a sound theoretical and a scientific evaluation system of ERA, which carry out an effective data application. This analysis unveils the intricate tapestry of research themes within the realm of ERA, with particular emphasis on the establishment of a robust theoretical foundation, the identification of pivotal audit focal points, the construction of a rigorous evaluation framework, and the adept utilization of data for effective decision-making. The research concluded that the trend of ERA is deeply integrated with performance management, national governance, Big data, etc.​ In addition, we also point out that applying interdisciplinary knowledge system to establish an innovative thinking system is the key point to the ERA’s future research. The research results also demonstrate that learning from the mature experience of international audit field and the forefront of theoretical research can effectively promote relevant empirical research.

Suggested Citation

  • Zhu, Jingjuan & Zhang, Wenjie & Lu, Lingyun & Lu, Yi & Wang, Duo, 2024. "Hot spot mining and trend analysis of Economic Responsibility Audit based on knowledge graph," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 222(C), pages 38-49.
  • Handle: RePEc:eee:matcom:v:222:y:2024:i:c:p:38-49
    DOI: 10.1016/j.matcom.2023.08.029
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    References listed on IDEAS

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    1. Rania Beji & Ouidad Yousfi & Nadia Loukil & Abdelwahed Omri, 2021. "Board Diversity and Corporate Social Responsibility: Empirical Evidence from France," Journal of Business Ethics, Springer, vol. 173(1), pages 133-155, September.
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