Corporate Finance & Governance
Knowledge Mapping of Corporate Related Party Transactions Research: An Analysis Using CiteSpace Visual Analytics
This study leverages CiteSpace and bibliometric techniques to analyze 364 CSSCI documents (1998-2024) on corporate related-party transactions. It reveals a predominant focus on debt transfer, with digital-era transactions intensifying tax risks and regulatory complexities due to their clandestine nature, linking them to tax avoidance and market fairness. Post-2020, the emphasis shifted to managing systemic risks from irregular transactions, where governance structures significantly impact economic performance. The study advocates for intelligent identification technologies in auditing for the digital economy, integrating transaction pricing and information disclosure for accurate related-party transaction determination in corporate governance.
Executive Impact & Key Metrics
Understand the quantifiable implications and strategic insights derived from the research on related-party transactions for enterprise leaders.
364
Documents Analyzed
2020+
Shift in Focus Year
0.96
Clustering Quality (S-value)
0.71
Modularity (Q-value)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Phase I: Development (1998-2014)
This phase primarily centered on the theory and policy of related-party transactions, related guarantees, and their legal implications. Key topics included concepts, motives, and legal regulatory measures. Research highlighted how market competition can negatively affect internal decentralization and how firms cut internal transactions to boost price competitiveness.
Phase II: Maturity (2014-2020)
This stage marked a "theory-practice" transition, emphasizing empirical analysis and governance strategies. Key issues included internal control, corporate governance, stakeholders, and risk management. Studies showed related-party transactions boosting corporate value through tax avoidance, internal financing, interest transfer, and surplus management.
Phase III: Expansion (2020-2024)
Current research focuses on regulatory technology and governance innovation. Key areas include financial regulation, tax auditing, entrusted lending, equity governance, social responsibility, and transaction transparency. Researchers are examining smart auditing tools and blockchain technology for compliance and benefit transfer issues in digital contexts, with systems like "Golden Tax III" restraining connected transactions.
Debt Transfer
Predominant Focus of Existing Literature on Corporate Transactions
Digital Economy
Intensifies Tax Risks and Regulatory Complexities Due to Clandestine Transactions
Enterprise Process Flow
Identify Abnormal RPTs
→
Integrate Pricing & Disclosure
→
Deploy Smart Tech (AI/Blockchain)
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Strengthen Governance
→
Improve Economic Performance
Post-2020
Focus Redirected to Managing Systemic Risks from Irregular RPTs
Case Study: Golden Tax III System
The implementation of the "Golden Tax III" system significantly restrains enterprise connected transactions. This digital reform of tax administration reduces the scale of non-essential connected transactions in purchasing and sales processes, thereby enhancing the tax department's supervisory capabilities through big data technology. It demonstrates how intelligent systems can detect unusual transactions and strengthen tax governance.
Comparison: Traditional vs. Modern RPT Oversight
| Feature | Traditional Approach | Modern (Digital Economy) |
|---|---|---|
| Risk Identification |
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| Regulatory Efficacy |
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| Governance Focus |
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Calculate Your Potential AI-Driven ROI
Estimate the efficiency gains and cost savings your enterprise could realize by implementing advanced AI solutions for transaction monitoring and governance.
Estimated Annual Savings
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Annual Hours Reclaimed
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Your AI Implementation Roadmap for Enhanced RPT Oversight
A phased approach to integrate intelligent identification and governance solutions for corporate related-party transactions.
Phase 1: Diagnostic & Data Integration
Conduct a comprehensive audit of existing RPT monitoring processes. Integrate diverse data sources (financial, legal, operational) into a unified platform. Establish baseline metrics for current RPT risk exposure and compliance.
Phase 2: Intelligent Identification System Deployment
Implement AI-powered anomaly detection for RPTs, focusing on transaction pricing deviations and hidden relationships. Develop and deploy intelligent identification technologies for real-time monitoring and early warning of irregular transactions.
Phase 3: Governance Structure Enhancement & Automation
Refine corporate governance structures to support AI-driven insights, ensuring board independence and specialized review mechanisms. Automate reporting and compliance checks, transitioning from reactive auditing to proactive risk management.
Phase 4: Continuous Improvement & Strategic Value Creation
Regularly update AI models with new regulatory changes and transaction patterns. Expand AI capabilities to support strategic decision-making, transforming RPT oversight from a cost center to a value creation driver for the enterprise.
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