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Article

Tokenomics and Digital Economy in China: Analyzing the Influence of Blockchain Technology Integration on Traditional Business Models

by
Fadi Ghosn
1,
Mohamad Zreik
2,*,
Hala Koleilat Al Dilby
3,
Caroline Dib Kassably Fakhry
4 and
Fida Ragheb Hassanein
5
1
Banking and Finance Department, Lebanese International University, Bekaa 1803, Lebanon
2
Institute of International and Regional Studies, Sun Yat-sen University, No. 2 Daxue Road, Xiangzhou District, Zhuhai 519082, China
3
Marketing Department, Lebanese International University, Beirut 146404, Lebanon
4
School of Business, Lebanese International University, Bekaa 1803, Lebanon
5
School of Business, Lebanese International University, Beirut 146404, Lebanon
*
Author to whom correspondence should be addressed.
Economies 2025, 13(7), 189; https://doi.org/10.3390/economies13070189
Submission received: 24 May 2025 / Revised: 20 June 2025 / Accepted: 24 June 2025 / Published: 2 July 2025
(This article belongs to the Special Issue Economic Development in the Digital Economy Era)
Versions Notes

Abstract

This study investigates the impact of tokenomics and the integration of blockchain technology on China’s digital economy, focusing on how blockchain adoption influences traditional business models. As China becomes a global leader in digital transformation, understanding the role of the blockchain in economic modernization is critical. The aim of this research is to quantify the effects of blockchain adoption on key economic indicators such as GDP growth, investment levels, and business innovation. Using panel data analysis and regression models, this study provides empirical evidence on the positive correlation between blockchain integration and improved economic performance. Key results reveal that a 1% increase in blockchain adoption is associated with a 0.3% rise in GDP growth, while tokenization contributes significantly to investment levels and business innovation. These findings emphasize the transformative potential of the blockchain in enhancing economic stability, increasing liquidity, and fostering new business opportunities. In conclusion, this research highlights the critical role of the blockchain and tokenomics in driving economic modernization in China, offering valuable insights for policymakers, business leaders, and investors aiming to leverage digital technologies for sustainable growth. Future research should explore the broader global implications of blockchain adoption and tokenomics in emerging markets.

1. Introduction

The advent of blockchain technology and its associated economic principles, commonly referred to as tokenomics, has introduced a transformative potential for economies worldwide (Freni et al., 2022; Kher et al., 2021). In particular, China has been at the forefront of integrating blockchain technology into its digital economy, driven by the need for innovation and enhanced economic performance (Tseng et al., 2023). While many studies have examined the blockchain’s impact on global economies, the specific role of tokenomics in China’s digital transformation has not been sufficiently explored. The concept of tokenomics encompasses the creation, distribution, and management of digital tokens, which represent various assets and can be used in numerous applications, from cryptocurrencies to tokenized physical assets (Lo & Medda, 2020; Blemus & Guégan, 2020; Sazandrishvili, 2020). As China continues to evolve into a digital powerhouse, understanding the role of tokenomics in its economic landscape becomes increasingly critical.
This paper aims to explore the influence of tokenomics on China’s digital economy and the integration of blockchain technology into traditional business models. The primary objectives are to quantify the effects of blockchain adoption on key economic performance metrics, such as GDP growth, investment levels, and business innovation, and to provide empirical evidence on how digital tokens can reshape traditional business practices. What is novel about this research is the use of econometric analysis to provide evidence-based insights on how blockchain adoption directly impacts China’s economy, beyond the conceptual or theoretical discussion. By employing econometric analysis, this study seeks to identify the underlying factors that contribute to the successful integration of blockchain technology and its potential to drive economic modernization in China.
The significance of this study lies in its potential to offer a comprehensive understanding of the economic implications of blockchain technology in one of the world’s largest economies. This paper rigorously quantifies the impact of blockchain adoption in China’s diverse sectors, providing policymakers, business leaders, and investors with actionable insights on how to harness blockchain technology for sustainable growth. By emphasizing the economic outcomes of the blockchain, this research uniquely focuses on the integration of digital tokens in traditional sectors, a novel contribution to the discourse on digital innovation. Moreover, the empirical evidence presented in this paper will serve as a foundation for future research and policy formulation, aimed at leveraging blockchain technology to achieve sustainable economic growth in China and beyond.

2. Literature Review

Tokenomics, a portmanteau of “token” and “economics,” refers to the economic systems and models that underpin the creation, distribution, and utilization of digital tokens. According to Freni et al. (2022), tokenomics represents a paradigm shift in the digital economy, enabling new forms of value exchange and economic interaction. Tokens can be categorized into utility tokens, security tokens, and asset-backed tokens, each serving different purposes within the blockchain ecosystem. Utility tokens, as discussed by Lee (2019), provide access to specific services or products within a blockchain network, while security tokens represent ownership in an underlying asset, akin to traditional securities. Asset-backed tokens, highlighted by Hines (2020), are pegged to real-world assets such as commodities, real estate, or precious metals, providing a stable value base and reducing the volatility commonly associated with cryptocurrencies.
The rise of tokenomics has facilitated the development of decentralized finance (DeFi) platforms, which leverage blockchain technology to offer financial services without intermediaries. This democratization of finance, noted by Blemus and Guégan (2020), has opened up new investment opportunities and has the potential to enhance financial inclusion globally. The tokenization of assets, as explored by Nestarcova (2018), allows for fractional ownership and the increased liquidity of traditionally illiquid assets, such as real estate or fine art. This innovation has profound implications for investment strategies and asset management.
China has emerged as a global leader in blockchain technology, driven by strong governmental support and significant investments in research and development. In 2019, the Chinese government formally recognized the blockchain as a critical component of its national strategy for technological innovation. The People’s Bank of China (PBOC) has been at the forefront of this initiative, developing the Digital Currency Electronic Payment (DCEP) system, which aims to digitize the Chinese yuan (Kshetri, 2023). This state-backed digital currency is designed to enhance the efficiency and security of the financial system, reduce transaction costs, and combat money laundering and tax evasion.
Chinese enterprises have also been proactive in adopting blockchain technology across various industries. Alibaba and Tencent, two of China’s largest tech companies, have implemented blockchain solutions in supply chain management, healthcare, and finance (Hasan et al., 2021). Alibaba’s Ant Financial, for example, has developed a blockchain-based platform for tracking the provenance of goods, ensuring transparency and authenticity in supply chains (Balzarova, 2021). Tencent has launched blockchain applications in areas such as digital identity verification and intellectual property protection (Chen et al., 2020).
The integration of blockchain technology in China’s public and private sectors underscores its potential to transform the economic landscape. However, this rapid adoption has also raised concerns about regulatory oversight and data privacy. According to Sigley and Powell (2023), the Chinese government has implemented strict regulations to ensure that blockchain applications comply with national security standards and protect user data. These regulatory measures aim to balance innovation with security, fostering a stable environment for blockchain development.
The integration of blockchain technology into traditional business models has been a significant area of research and practice. The blockchain’s decentralized, immutable ledger offers numerous advantages, including enhanced transparency, reduced fraud, and improved efficiency. As noted by Werbach (2018), the core principle of the blockchain is to provide a trustless system where transactions can be verified without the need for intermediaries. This capability has profound implications for industries that rely on trust and verification, such as finance, supply chain management, and healthcare.
In the finance sector, the blockchain has been used to streamline processes such as cross-border payments, trade finance, and securities settlement. According to Tsai et al. (2020), the blockchain can significantly reduce the time and cost associated with these processes by eliminating the need for intermediaries and enabling real-time settlement. For example, the use of smart contracts—self-executing contracts with the terms directly written into code—can automate and enforce contract conditions without the need for manual intervention (Mik, 2017).
Supply chain management is another area where the blockchain has shown substantial promise. By providing a transparent and immutable record of transactions, the blockchain can enhance the traceability and accountability of goods as they move through the supply chain. As highlighted by Azzi et al. (2019), this capability is particularly valuable in industries such as food and pharmaceuticals, where ensuring the authenticity and safety of products is critical. The blockchain can help track the origin and journey of products, reducing the risk of counterfeit goods and improving consumer trust.
In healthcare, blockchain technology has been used to secure patient data, streamline medical records, and enhance interoperability between different healthcare providers. According to Zaabar et al. (2021), the blockchain can address many of the challenges associated with data privacy and security in healthcare by providing a decentralized and secure platform for storing and sharing medical information. This capability can improve the efficiency and accuracy of medical care, reducing the risk of errors and enhancing patient outcomes.
Empirical studies on the digital economy and blockchain technology have provided valuable insights into their impact on various economic and business outcomes. According to Javaid et al. (2022), the adoption of blockchain technology has been associated with increased efficiency and reduced costs in financial transactions. This finding is supported by empirical evidence from case studies of blockchain implementations in banking and finance, which have shown significant reductions in transaction times and costs (Patki & Sople, 2020).
In the context of supply chain management, empirical research by Centobelli et al. (2022) has demonstrated that blockchain technology can enhance the transparency and traceability of supply chains, leading to improved operational efficiency and reduced fraud. These benefits have been observed in various industries, including food, pharmaceuticals, and luxury goods. For example, a study by Li et al. (2023) found that blockchain implementation in the food supply chain resulted in the faster and more accurate traceability of products, reducing the risk of contamination and enhancing consumer trust.
In healthcare, empirical studies have highlighted the potential of the blockchain to improve data security and interoperability. According to Attaran (2022), blockchain technology can provide a secure and decentralized platform for storing and sharing patient data, addressing many of the challenges associated with data privacy and security. Empirical evidence from pilot projects in healthcare has shown that the blockchain can improve the accuracy and efficiency of medical records, enhancing patient care and outcomes (Tanwar et al., 2020).
The impact of tokenomics on the digital economy has also been a focus of empirical research. According to Nestarcova (2018), the tokenization of assets can increase liquidity and provide new investment opportunities, particularly for traditionally illiquid assets such as real estate and fine art. This finding is supported by empirical evidence from studies of tokenized asset platforms, which have shown increased liquidity and reduced transaction costs compared to traditional asset markets (Ciriello, 2021).
Although previous research has highlighted the potential of blockchain technology to transform industries such as finance, supply chain, and healthcare, much of the existing literature has focused on theoretical frameworks and isolated sectoral applications. While the blockchain’s advantages in enhancing transparency, reducing costs, and improving efficiency have been well documented (e.g., Tsai et al., 2020; Azzi et al., 2019), there is a notable gap in empirical studies that examine the comprehensive economic impact of blockchain adoption, particularly in the context of emerging economies like China. Furthermore, while tokenomics has gained significant attention as a driver of innovation, there remains a lack of research on how the integration of digital tokens affects broader economic performance metrics, such as GDP growth, investment levels, and business innovation. This study aims to fill these gaps by providing a comprehensive empirical analysis of the role of blockchain technology and tokenomics in driving China’s digital economy, offering new insights into the transformation of traditional business models in this rapidly developing market.

3. Methodology

The data for this study were collected from a combination of sources to ensure a comprehensive analysis of the impact of tokenomics on China’s digital economy and the integration of blockchain technology into traditional business models. Data were mainly sourced from reputable databases, government reports, industry publications, and academic journals. Key indicators such as GDP growth, investment levels, blockchain adoption rates, and business innovation metrics were extracted for analysis. Data for blockchain adoption rates were primarily sourced from the China Blockchain Application Research Center (CBARC) and industry reports published by organizations such as Deloitte and PwC. Tokenization metrics were obtained from blockchain-specific financial databases such as CoinMarketCap (CoinMarketCap LLC, Dover, Delaware, USA), TokenAnalyst (TokenAnalyst Ltd., London, United Kingdom), and Blockchain.info (Blockchain Luxembourg S.A., Luxembourg City, Luxembourg).
Panel data analysis is particularly suited for this study as it allows for the examination of multiple entities over time, capturing both cross-sectional and time-series dimensions. This approach enables the analysis of the dynamic effects of blockchain adoption and tokenomics on economic performance in China. The panel data will consist of annual observations from various sectors within the Chinese economy over a period of 10 years, from 2013 to 2023. The sectors included in the analysis were selected based on their relevance to the digital economy in China, including finance, supply chain management, healthcare, real estate, and manufacturing, which were chosen to represent both traditional and emerging industries impacted by blockchain technology. This timeframe captures the period of significant blockchain innovation and adoption in China.
The panel data model will be specified as follows:
Yit = α + βXit + γZit + μi + λt + ϵit
where the variables are defined as follows:
  • Yit is the dependent variable representing economic performance metrics (e.g., GDP growth, investment levels) for sector i at time t.
  • Xit represents the main independent variables of interest, including blockchain adoption rate and tokenization metrics.
  • Zit includes control variables such as labor force, capital investment, and technological infrastructure.
  • μi captures the unobserved individual effects (e.g., year dummies), which account for events or factors affecting all sectors in the same year, such as national policy changes or economic crises.
  • λt captures the time-specific effects.
  • ϵit is the error term.
To estimate the effects of blockchain technology and tokenomics on China’s digital economy, multiple regression models will be employed. The primary model will be a fixed effects regression, which controls for time-invariant unobserved heterogeneity across sectors. The fixed effects model is specified as follows:
Yit = α + βXit + γZit + μi + ϵit
Additionally, a random effects model will be estimated to account for both within-entity and between-entity variations. The Hausman test will be conducted to determine which model is more appropriate, as the test compares the consistency of the fixed and random effects models.
For robustness checks, this study will also utilize dynamic panel data models, such as the Generalized Method of Moments (GMM) estimator, to address potential endogeneity issues arising from the inclusion of lagged dependent variables and other endogenous regressors. The instruments used in the GMM model include lagged values of blockchain adoption rates and tokenization metrics, as well as sectoral lagged GDP and investment levels. The GMM model is specified as follows:
ΔYit = α + βΔXit + γΔZit + ϵit
The dependent variable in this study is the economic performance of China’s digital economy, measured through various indicators such as GDP growth rate, investment levels, and business innovation indices. These indicators provide a comprehensive view of the economic impact of blockchain technology and tokenomics.
The key independent variables include the following:
  • Blockchain Adoption Rate: measured as the percentage of businesses and sectors adopting blockchain technology, sourced from industry reports and surveys.
  • Tokenization Metrics: measured through the number of tokenized assets, the market value of these assets, and the volume of transactions involving digital tokens, obtained from blockchain databases and financial reports.
Control variables include the following:
  • Labor Force: measured as the total number of employed individuals in each sector, sourced from national labor statistics.
  • Capital Investment: measured as the total capital expenditure in each sector, sourced from financial reports and investment databases.
  • Technological Infrastructure: measured through indicators such as internet penetration rate, availability of high-speed broadband, and technological readiness index, obtained from government and industry reports.
To ensure comparability across sectors, the data were standardized by adjusting for the sector-specific economic output and scale. For example, GDP growth was normalized by sector-specific growth rates, and investment levels were adjusted for capital intensity in each sector.
To ensure the accuracy and reliability of the data, rigorous data cleaning and preprocessing steps were undertaken. Missing values were addressed through appropriate imputation methods, and outliers were identified and managed using statistical techniques. Missing data were handled using the Multiple Imputation by Chained Equations (MICE) method, which is appropriate for panel data. The percentage of missing data was found to be low (approximately 3–5%) across key variables. Descriptive statistics and correlation analysis were performed to understand the data distribution and relationships among variables. Multicollinearity was assessed using the Variance Inflation Factor (VIF), and no variables showed problematic multicollinearity (VIF > 10). Heteroskedasticity was addressed by using robust standard errors, and serial correlation was tested using the Wooldridge test for autocorrelation in panel data.

4. Results

4.1. Descriptive Statistics

The descriptive statistics provide an initial understanding of the data distribution and the central tendencies of the key variables used in this study. The analysis covers the period from 2013 to 2023, encompassing various sectors within China’s digital economy. The panel data in this study are based on sectors within China’s digital economy, rather than individual firms. This approach allows for an analysis of sector-level economic performance and the integration of blockchain technology across different industries.
The mean GDP growth rate for the sectors under study was found to be 6.5%, with a standard deviation of 1.2%, indicating moderate variability around the average growth rate. The minimum GDP growth rate observed was 3.2%, while the maximum was 9.1%, reflecting the diverse economic performance across different sectors during the study period.
The blockchain adoption rate, measured as the percentage of businesses integrating blockchain technology, had a mean value of 15%, with a significant standard deviation of 10%. This high variability suggests that while some sectors have rapidly embraced blockchain technology, others are still in the early stages of adoption. The adoption rate ranged from a low of 2% to a high of 45%.
Tokenization metrics, including the number of tokenized assets and the volume of transactions, also exhibited considerable variation. The mean number of tokenized assets was 120 per sector, with a standard deviation of 50. The minimum number of tokenized assets recorded was 30, and the maximum was 300. The volume of transactions involving digital tokens had a mean value of USD 2 billion, with a standard deviation of USD 1 billion, ranging from USD 500 million to USD 4.5 billion.
Control variables such as labor force, capital investment, and technological infrastructure were also analyzed. The average labor force size was 1.2 million individuals per sector, with a standard deviation of 200,000. Capital investment averaged USD 500 million per sector, with a standard deviation of USD 100 million. Technological infrastructure, measured by the technological readiness index, had a mean value of 70, with a standard deviation of 10.
The correlation analysis revealed significant positive correlations between the blockchain adoption rate and GDP growth rate (r = 0.45), indicating that sectors with higher blockchain adoption tended to experience greater economic growth. Tokenization metrics also showed positive correlations with investment levels and business innovation indices, supporting the hypothesis that tokenomics contributes to enhanced economic performance. The descriptive statistics for the key variables are summarized in Table 1.
As shown in Table 1, the mean GDP growth rate for the sectors was 6.5%, with a standard deviation of 1.2%. These descriptive statistics provide a foundational understanding of the data and set the stage for more advanced econometric analyses to further explore the relationships between tokenomics, blockchain technology, and economic outcomes in China’s digital economy.

4.2. Econometric Analysis

The econometric analysis utilizes panel data regression models to examine the impact of blockchain adoption and tokenomics on economic performance indicators across various sectors in China from 2013 to 2023. Both fixed effects and random effects models were estimated to capture the effects while controlling for unobserved heterogeneity. The panel data for this study are aggregated at the sector level, not at the individual firm level. This allows for the exploration of blockchain adoption and tokenomics’ impact on economic performance at a broader industry scale, rather than focusing on firm-specific outcomes.
The fixed effects regression model results indicate a significant positive relationship between blockchain adoption and GDP growth rate. Specifically, a 1% increase in the blockchain adoption rate is associated with a 0.3% increase in GDP growth (β = 0.003, p < 0.01). This finding underscores the transformative potential of blockchain technology in driving economic growth by enhancing efficiency and innovation in traditional business models.
The random effects model, confirmed by the Hausman test as appropriate for this analysis (χ2 = 12.34, p < 0.05), also supports these findings, showing a consistent positive impact of blockchain adoption on GDP growth. Additionally, the random effects model highlights the significant influence of tokenization metrics on investment levels. A higher volume of transactions involving digital tokens is associated with increased sectoral investments (β = 0.25, p < 0.05), suggesting that tokenization enhances liquidity and attracts more capital into the economy.
Dynamic panel data models using the GMM were employed to address potential endogeneity issues. The GMM results confirm the robustness of the previous findings, indicating that blockchain adoption and tokenization significantly contribute to economic performance. The coefficient for blockchain adoption remains positive and significant (β = 0.004, p < 0.01), while tokenization metrics show a strong positive effect on business innovation indices (β = 0.45, p < 0.01).
Control variables such as labor force, capital investment, and technological infrastructure were also significant in the models, demonstrating their importance in driving economic outcomes. For instance, capital investment showed a positive relationship with GDP growth (β = 0.002, p < 0.05), emphasizing the role of financial resources in fostering economic development.

4.3. Regression Results

The regression analysis, employing both fixed effects and random effects models, reveals significant insights into the impact of blockchain adoption and tokenomics on economic performance indicators across various sectors in China from 2013 to 2023.
The fixed effects regression model results indicate a significant positive relationship between blockchain adoption and GDP growth rate. Specifically, a 1% increase in the blockchain adoption rate is associated with a 0.3% increase in GDP growth (β = 0.003, p < 0.01). This suggests that sectors with higher levels of blockchain adoption experience greater economic growth, likely due to improved efficiency, reduced transaction costs, and enhanced transparency.
Additionally, the fixed effects model shows that tokenization metrics, such as the volume of transactions involving digital tokens, positively impact investment levels. A higher transaction volume is associated with a 0.2% increase in sectoral investments (β = 0.002, p < 0.05), indicating that tokenization enhances liquidity and attracts more capital.
The random effects model, validated by the Hausman test (χ2 = 12.34, p < 0.05), corroborates these findings. The model confirms the positive impact of blockchain adoption on GDP growth (β = 0.003, p < 0.01) and highlights the significant influence of tokenization on investment levels (β = 0.25, p < 0.05). The random effects model also reveals that blockchain adoption significantly improves business innovation indices (β = 0.35, p < 0.05), suggesting that blockchain technology fosters innovative business practices.
The GMM estimator addresses potential endogeneity issues and further supports the robustness of the results. The GMM results show that blockchain adoption has a significant positive effect on GDP growth (β = 0.004, p < 0.01) and business innovation indices (β = 0.45, p < 0.01). This confirms that blockchain technology and tokenomics drive economic performance and innovation.
Control variables such as labor force, capital investment, and technological infrastructure were significant in the models. For example, capital investment showed a positive relationship with GDP growth (β = 0.002, p < 0.05), highlighting the importance of financial resources in economic development.
The econometric analysis reveals significant insights into the impact of blockchain adoption and tokenomics on economic performance in China. The fixed effects regression model shows that a 1% increase in blockchain adoption rate is associated with a 0.3% increase in GDP growth, indicating that sectors with higher blockchain integration experience enhanced economic performance. This positive relationship suggests that blockchain technology improves efficiency, reduces transaction costs, and increases transparency, thereby driving economic growth.
The results of the fixed effects regression model in Table 2 show that blockchain adoption significantly impacts GDP growth.
The random effects model further validates these findings, highlighting the substantial influence of tokenization metrics on investment levels. A higher volume of transactions involving digital tokens correlates with increased sectoral investments, demonstrating that tokenization enhances liquidity and attracts more capital into the economy. This effect underscores the role of digital tokens in providing new investment opportunities and improving asset liquidity.
Dynamic panel data models, using the GMM estimator, address potential endogeneity issues and confirm the robustness of the results. The GMM analysis reveals that blockchain adoption has a significant positive effect on both GDP growth and business innovation indices. This indicates that blockchain technology not only boosts economic performance but also fosters innovative business practices. The empirical evidence from the GMM model underscores the transformative potential of blockchain and tokenomics in driving economic modernization in China.
Control variables, such as labor force, capital investment, and technological infrastructure, also play crucial roles in determining economic outcomes. Capital investment shows a positive relationship with GDP growth, emphasizing the importance of financial resources in fostering economic development. These findings collectively highlight the significant impact of blockchain technology and tokenomics on enhancing economic stability, investment levels, and business innovation in China’s digital economy. The results provide valuable insights for policymakers, business leaders, and investors aiming to leverage blockchain technology for sustainable economic growth.

5. Discussion

5.1. Implications for China’s Digital Economy

The findings from the econometric analysis underscore the transformative potential of blockchain technology and tokenomics in shaping China’s digital economy. The positive relationship between blockchain adoption and GDP growth indicates that integrating blockchain technology can significantly enhance economic performance. This enhancement is attributed to blockchain’s ability to improve efficiency, reduce transaction costs, and increase transparency across various sectors (Javaid et al., 2022). As China continues to position itself as a leader in digital innovation, the widespread adoption of blockchain technology could further solidify its status in the global digital economy.
Moreover, the significant impact of tokenization metrics on investment levels highlights the crucial role of digital tokens in fostering new investment opportunities. By increasing liquidity and providing fractional ownership, tokenization allows for greater capital influx into the economy, particularly in traditionally illiquid asset classes such as real estate and fine art (Nestarcova, 2018). This increased liquidity can stimulate economic activity and drive further innovation.
The implications extend to the democratization of finance through decentralized finance (DeFi) platforms. Blockchain technology, by eliminating intermediaries, opens up financial services to a broader population, promoting financial inclusion. This democratization can lead to a more inclusive and resilient economy, where access to financial services is not limited by traditional barriers.

5.2. Impact on Traditional Business Models

Blockchain technology’s integration into traditional business models has far-reaching implications. The decentralized and immutable nature of the blockchain can fundamentally alter how businesses operate, ensuring greater transparency and trust in transactions. In supply chain management, for example, blockchain can provide an immutable record of a product’s journey from origin to consumer, reducing fraud and ensuring authenticity (Azzi et al., 2019). This capability is particularly valuable in industries such as food and pharmaceuticals, where the integrity of the supply chain is critical.
In the financial sector, blockchain technology can streamline processes such as cross-border payments, trade finance, and securities settlement. By reducing the need for intermediaries, the blockchain can lower costs and expedite transactions (Javaid et al., 2022). Smart contracts, which are self-executing contracts with terms directly written into code, can automate and enforce contractual agreements without manual intervention (Mik, 2017). This automation can significantly reduce the time and cost associated with traditional contract management.
The healthcare sector can also benefit from blockchain technology through improved data security and interoperability. By providing a secure platform for storing and sharing patient data, the blockchain can address many of the challenges associated with data privacy and security. This capability can enhance the accuracy and efficiency of medical care, reducing errors and improving patient outcomes.

5.3. Comparison with the Existing Literature

The findings of this study align with and expand upon the existing literature on the economic implications of blockchain technology and tokenomics. Previous research has highlighted the blockchain’s potential to increase efficiency and reduce costs in financial transactions (Javaid et al., 2022; Patki & Sople, 2020). This study corroborates these findings, showing that blockchain adoption is significantly associated with GDP growth and investment levels.
In the context of supply chain management, prior studies have demonstrated the blockchain’s ability to enhance transparency and traceability (Centobelli et al., 2022; Li et al., 2023). The present research supports these conclusions, providing empirical evidence that blockchain integration can improve operational efficiency and reduce fraud in supply chains.
The healthcare sector has also been a focal point of blockchain research, with studies indicating its potential to improve data security and interoperability (Attaran, 2022; Tanwar et al., 2020). This study reinforces these findings, showing that blockchain technology can significantly enhance business innovation indices, which include measures of technological advancement and efficiency improvements in healthcare.
This research also contributes to the literature on tokenomics by empirically demonstrating the positive impact of tokenization on investment levels and business innovation. While previous studies have explored the theoretical benefits of tokenomics (Nestarcova, 2018; Ciriello, 2021), this study provides concrete evidence of its economic impact, particularly in the context of China’s digital economy.

5.4. Policy Recommendations

Based on the findings, several policy recommendations can be made to further leverage blockchain technology and tokenomics for sustainable economic growth in China. Policymakers should continue to encourage the adoption of blockchain technology across various sectors. This can be achieved through incentives such as tax breaks, grants, and subsidies for businesses implementing blockchain solutions. Additionally, public awareness campaigns highlighting the benefits of blockchain technology can help accelerate its adoption. Establishing clear and supportive regulatory frameworks is crucial for fostering innovation while ensuring security and compliance. Regulations should address issues such as data privacy, security standards, and anti-money laundering measures. A balanced approach that promotes innovation while mitigating risks will be essential.
Supporting the development of tokenization platforms and initiatives is another critical area. The government should create legal frameworks for tokenized assets and ensure the protection of investors. By facilitating the tokenization of traditionally illiquid assets, policymakers can enhance liquidity and attract more investment into the economy (Tian et al., 2020). Investing in technological infrastructure, such as high-speed internet and blockchain research and development, is also vital. Improving technological readiness will ensure that businesses and consumers can fully leverage the benefits of blockchain technology.
Fostering public–private partnerships can drive blockchain innovation and adoption (Toufaily et al., 2021). Collaboration between the public and private sectors can facilitate the sharing of resources, expertise, and best practices, accelerating the integration of blockchain technology into traditional business models. Additionally, developing a skilled workforce capable of understanding and implementing blockchain technology is essential. Policymakers should support educational programs and training initiatives focused on blockchain and digital economy skills. This will ensure a steady supply of talent to drive the digital transformation.
The continuous monitoring and evaluation of blockchain initiatives will be important to understand their impact and make necessary adjustments. Policymakers should establish mechanisms for tracking the adoption and performance of blockchain technology, gathering data to inform future policy decisions. Engaging in international collaboration and knowledge exchange can enhance China’s blockchain ecosystem. By participating in global blockchain initiatives and sharing insights with other countries, China can stay at the forefront of blockchain innovation and adoption.

5.5. Limitations of This Study

While this research provides valuable insights into the impact of blockchain adoption and tokenomics on China’s digital economy, there are several limitations to consider.
The data used in this study, particularly for blockchain adoption and tokenization metrics, were obtained from industry reports and blockchain-specific databases, which may not always be comprehensive or entirely accurate. The reliance on publicly available data means that certain sectors or regions may be underrepresented, potentially affecting the generalizability of the findings.
The analysis is based on sector-level data, not firm-level data, which may limit the ability to draw conclusions about how individual firms are affected by blockchain adoption. Sector-level analysis aggregates heterogeneity within each sector, which could overlook variations in blockchain adoption at the firm level.
Although dynamic panel data models, such as the GMM, were employed to address potential endogeneity, there may still be unobserved factors influencing both blockchain adoption and economic performance that were not captured in the models. This could potentially introduce bias into the estimates.
This study covers the period from 2013 to 2023, which captures a phase of significant blockchain adoption in China. However, blockchain technology is still evolving, and the long-term effects of blockchain adoption on the digital economy may differ from the short-term effects observed in this study.
The results may also be influenced by external factors such as government policies, global economic conditions, and technological advancements unrelated to the blockchain. Although time fixed effects were included to control for some of these factors, there may still be other unaccounted-for variables that influence the results.
Despite these limitations, this study provides valuable insights into the role of blockchain technology in reshaping China’s digital economy, offering directions for future research to explore these issues in greater depth.

6. Conclusions

This paper provides a comprehensive analysis of the impact of blockchain technology and tokenomics on China’s digital economy and traditional business models. Through advanced econometric techniques, including fixed effects and random effects models, as well as the GMM estimator, this study quantifies the significant positive effects of blockchain adoption on GDP growth, investment levels, and business innovation. The empirical evidence demonstrates that integrating blockchain technology enhances economic performance by improving efficiency, reducing transaction costs, and increasing transparency across various sectors.
This research highlights the transformative potential of digital tokens in fostering new investment opportunities and increasing liquidity in traditionally illiquid asset classes. Tokenization, by allowing fractional ownership and facilitating smoother transactions, plays a critical role in attracting more capital into the economy. These findings underscore the importance of blockchain and tokenomics in driving economic modernization and innovation, positioning China as a global leader in the digital economy.
Policy recommendations derived from this study emphasize the need for continued promotion of blockchain adoption through incentives and public awareness campaigns. Establishing clear regulatory frameworks that balance innovation with security, supporting tokenization initiatives, investing in technological infrastructure, and fostering public–private partnerships are crucial steps to leverage the full potential of blockchain technology. Additionally, developing a skilled workforce through education and training programs, the continuous monitoring and evaluation of blockchain initiatives, and engaging in international collaboration will further enhance China’s blockchain ecosystem.
The integration of blockchain technology and tokenomics offers significant opportunities for economic growth and innovation in China. By adopting supportive policies and strategic investments, China can harness the transformative power of the blockchain to achieve sustainable economic development and maintain its competitive edge in the global digital landscape. The insights from this study provide a valuable foundation for future research and policy formulation aimed at leveraging blockchain technology for long-term economic prosperity.

Author Contributions

Conceptualization: F.G. and M.Z.; methodology: M.Z.; software: M.Z.; validation: F.G., M.Z. and H.K.A.D.; formal analysis: M.Z.; investigation: M.Z.; resources: F.G.; data curation: C.D.K.F.; writing—original draft preparation: F.G.; writing—review and editing: H.K.A.D., F.G. and M.Z.; visualization: F.G.; supervision: H.K.A.D. and F.R.H.; project administration: H.K.A.D.; funding acquisition: H.K.A.D. All authors contributed equally to this work. All authors have read and agreed to the published version of the manuscript.

Funding

This research has received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Descriptive statistics for key variables.
Table 1. Descriptive statistics for key variables.
VariableMeanStandard DeviationMinMax
GDP Growth Rate6.5%1.2%3.2%9.1%
Blockchain Adoption Rate15%10%2%45%
Tokenized Assets (per sector)1205030300
Volume of Digital Token Transactions (USD)USD 2 BUSD 1 BUSD 500 MUSD 4.5 B
Labor Force (per sector, millions)1.20.2 million0.91.6
Capital Investment (USD million)500100300700
Source: Authors’ work.
Table 2. Regression results for fixed effects model.
Table 2. Regression results for fixed effects model.
VariableCoefficientStandard Errorp-Value
Blockchain Adoption Rate0.0030.001<0.01
Tokenization Metrics (Volume)0.0020.001<0.05
Labor Force0.00020.0001<0.05
Capital Investment0.0020.001<0.05
Technological Infrastructure0.0010.0005<0.10
Source: Authors’ work.
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MDPI and ACS Style

Ghosn, F.; Zreik, M.; Al Dilby, H.K.; Kassably Fakhry, C.D.; Hassanein, F.R. Tokenomics and Digital Economy in China: Analyzing the Influence of Blockchain Technology Integration on Traditional Business Models. Economies 2025, 13, 189. https://doi.org/10.3390/economies13070189

AMA Style

Ghosn F, Zreik M, Al Dilby HK, Kassably Fakhry CD, Hassanein FR. Tokenomics and Digital Economy in China: Analyzing the Influence of Blockchain Technology Integration on Traditional Business Models. Economies. 2025; 13(7):189. https://doi.org/10.3390/economies13070189

Chicago/Turabian Style

Ghosn, Fadi, Mohamad Zreik, Hala Koleilat Al Dilby, Caroline Dib Kassably Fakhry, and Fida Ragheb Hassanein. 2025. "Tokenomics and Digital Economy in China: Analyzing the Influence of Blockchain Technology Integration on Traditional Business Models" Economies 13, no. 7: 189. https://doi.org/10.3390/economies13070189

APA Style

Ghosn, F., Zreik, M., Al Dilby, H. K., Kassably Fakhry, C. D., & Hassanein, F. R. (2025). Tokenomics and Digital Economy in China: Analyzing the Influence of Blockchain Technology Integration on Traditional Business Models. Economies, 13(7), 189. https://doi.org/10.3390/economies13070189

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