Distributed Ledger Technology: The International Evolution of Blockchain and Economic Management Research

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Distributed ledger technology (DLT), commonly known as blockchain, has emerged as a transformative force across data management, financial systems, accounting, and economic governance. As industries seek greater transparency, security, and decentralization, the integration of blockchain into economic management practices continues to expand globally. This article leverages advanced analytical tools—CiteSpaceV and NVivo11—to conduct a comprehensive, data-driven examination of international and domestic research trends from 1991 to mid-2017. By analyzing academic literature from Web of Science (WoS), Scopus, and CNKI, along with global patent records, this study reveals key insights into the evolution, thematic focus, institutional leadership, and knowledge structure shaping blockchain research.

The findings underscore a critical divergence between international and Chinese research trajectories: while global scholarship emphasizes foundational technologies such as algorithms, supply chain systems, and network architecture, Chinese research concentrates on applied domains including fintech, digital currency, auditing, and financial regulation. These patterns reflect broader strategic priorities and developmental stages within each region’s innovation ecosystem.


Data Sources and Descriptive Analysis

To ensure robust comparative analysis, three primary data sets were curated:

International Research Data

Domestic Research Data

💡 Notably, CSSCI database results were excluded due to insufficient sample size (<5 entries pre-2017), highlighting a gap in high-quality theoretical output in China during the early phase of blockchain adoption.

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A comparative timeline (2009–2017) reveals pivotal milestones:

This delay suggests China’s transition from imitation to innovation, consistent with the technology追赶 (catch-up) theory. However, the dominance of economic management topics (over 77% of CNKI outputs in 2016) also raises concerns about over-specialization and shallow technical grounding.


Core Research Themes: Global vs. Domestic Focus

Using CiteSpaceV, keyword co-occurrence networks were mapped to identify dominant research themes.

International Research Hotspots

In both WoS and Scopus datasets, recurring keywords include:

These clusters reveal a strong emphasis on technical infrastructure, system modeling, and operational optimization. Central nodes like “system” and “algorithm” indicate deep engagement with computational methods and process efficiency.

Moreover, Scopus data extracted five burst terms—supply chain management, blockchain, Bitcoin, block chain, and cryptocurrency—all peaking around 2015. Their high Sigma scores confirm their dual significance in network centrality and temporal relevance.

Chinese Research Priorities

In contrast, CNKI keyword analysis highlights application-centric themes:

This concentration reflects China’s strategic interest in leveraging DLT for financial modernization, regulatory oversight, and monetary innovation—particularly in digital RMB development.

DimensionInternational FocusChinese Focus
Primary ThemesAlgorithms, supply chains, system modelingFinancial services, audit, digital currency
Methodological ToolsSimulation, Markov models, queuing theoryConceptual frameworks, policy analysis
Innovation StageFoundational researchApplied implementation

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The absence of technical keywords like “cryptography” or “distributed systems” in Chinese literature suggests limited cross-disciplinary integration—a vulnerability that could hinder long-term competitiveness.


Evolution Pathway of Blockchain Research

Timezone mapping via CiteSpaceV uncovers a clear evolutionary arc spanning nearly three decades:

  1. 1991–1996: Emergence of “block” concept focused on queuing systems and buffering mechanisms.
  2. 1997–2002: Algorithmic development using Markov chains and matrix geometry; applications in supply chain logistics.
  3. 2003–2008: Expansion into network design, simulation, performance evaluation—laying groundwork for decentralized systems.
  4. 2008–2015: Bitcoin’s debut catalyzes exploration of peer-to-peer transactions, cryptographic security, and digital ledgers.
  5. 2015–2017: Full conceptual consolidation of “blockchain,” with increasing integration into economic management domains like investment, economics, and global value chains.

This trajectory confirms a maturation path from technical abstractionsystem integrationeconomic application. China bypassed the first two phases by importing mature concepts post-2015, enabling rapid scaling but risking technological dependency and implementation fragility.


Leading Nations and Institutional Collaboration

Geospatial analysis identifies clear hierarchies in global research leadership:

Top Countries by Output and Centrality

RankCountryWoS FrequencyCentrality
1USA580.42
2China390.68
3Canada180.13
4Germany150.17
5Japan140.11

Despite high publication volume, China ranks only fifth in Scopus-based centrality (0.0)—indicating limited international collaboration. Similarly, Japan appears isolated in both datasets, suggesting regional research silos.

Network visualizations confirm that the U.S. anchors a dense collaborative cluster with Canada, the UK, and India. In contrast, Chinese institutions operate largely in isolation—a pattern mirrored in patent origin analysis where the U.S. leads in volume and diversity.

✅ Key Insight: Technological leadership is not just about output volume—it's about connectivity. The U.S. remains the central hub in the global blockchain knowledge network.

Interdisciplinary Knowledge Structure

Blockchain is inherently multidisciplinary. CiteSpaceV category analysis identifies four core foundational disciplines:

  1. Engineering & Industrial Engineering (centrality: 0.69)
  2. Operations Research & Management Science (0.53)
  3. Business & Economics (0.34)
  4. Management (0.34)

These anchor a broader web of supporting fields:

Chinese research teams often lack this interdisciplinary depth, favoring domain experts in finance over technologists—an imbalance that may constrain innovation at the protocol level.


Frequently Asked Questions (FAQ)

Q: What is distributed ledger technology?

A: Distributed ledger technology (DLT) is a decentralized system for recording transactions across multiple locations. Unlike traditional databases controlled by a central authority, DLT ensures data consistency through consensus mechanisms—blockchain being the most widely adopted form.

Q: How does blockchain differ from traditional databases?

A: Traditional databases rely on centralized control and trust in administrators. Blockchain eliminates intermediaries by using cryptographic verification and distributed consensus, enhancing transparency, auditability, and resistance to tampering.

Q: Why is supply chain a major application area for blockchain?

A: Supply chains involve numerous stakeholders across geographies. Blockchain provides immutable tracking of goods, reduces fraud, improves traceability (e.g., food safety), and streamlines documentation—all critical for complex global operations.

Q: Is China leading in blockchain innovation?

A: China leads in applied implementation, especially in digital currency and financial services. However, it lags in core protocol development and international collaboration. True leadership requires deeper investment in foundational research and cross-border partnerships.

Q: Can blockchain function without cryptocurrencies?

A: Yes. While Bitcoin popularized blockchain, the technology can operate independently—especially in private or consortium blockchains used by enterprises for secure recordkeeping, identity verification, and automated contracts.

Q: What risks does rapid blockchain adoption pose?

A: Bypassing foundational research increases technical debt and systemic vulnerabilities. Without robust cybersecurity frameworks and ethical guidelines, poorly implemented DLT systems may introduce new risks in privacy, scalability, and regulatory compliance.

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Conclusion and Strategic Implications

This study confirms that distributed ledger technology remains an evolving field without a fully consolidated theoretical framework—offering significant opportunities for innovation.

Key takeaways:

For China to become a true leader in blockchain innovation, it must:

As blockchain transitions from hype to reality, long-term success will belong not to those who chase trends—but to those who build wisely upon solid scientific foundations.


Core Keywords:
distributed ledger technology, blockchain, CiteSpace, NVivo, economic management, technology innovation, research evolution, interdisciplinary knowledge