New Development of Anti-Monopoly Regulation on Data in China

1. The Status of Data Monopoly Regulation in China

1.1. The Rising Status of Data Elements

Digital data have increasingly become a strategic production factor in the global digital economy, fundamentally reshaping innovation, competition, and industrial organization. Against this background, China has also accelerated the institutional construction of the data factor market (OECD 2024). The 2025 Government Work Report explicitly calls for “developing new productive forces tailored to local conditions and accelerating the construction of a modern industrial system.” It also underscores the importance of “speeding up the improvement of foundational data systems, deepening data resource development and utilization, and promoting and regulating cross-border data flows.” This policy reflects China’s attempt to institutionalize data circulation as a driver of digital economic growth. Facilitating a reasonable degree of data flow and sharing can significantly boost the growth of the digital economy. China has gradually established a regulatory framework governing data elements through a series of legislative and policy reforms. The Fourth Plenary Session of the 19th CPC Central Committee made it clear for the first time that data could be distributed as a production factor according to their contributions (China Academy of Information and Communications Technology 2022), which means that the State Council formally designated data as a factor of production such as joining land, labor, capital, and technology in China. Data elements have become one of the most important factors of production in digital economy, and the accumulation of data helps market entities to gain competitive advantages and market power (Xu 2020; Zhou 2023). New technologies, new industries, and new markets continue to emerge. As a result, the collection, use, trading and sharing of data have become the most common behaviors in the market. At the same time, data-related competitive behavior has gradually attracted great attention from competition enforcement agencies around the world.

While the concept of “data monopoly” in the context of the digital economy has not reached a unanimous viewpoint in theory and practice (Crémer et al. 2019), many countries have responded to data-related competition with concrete supervisory actions (European Parliament and Council 2022). As the second largest economy in the world, the Chinese government has also strengthened the regulation of data monopolies and has formulated and issued a series of laws and regulations to supervise data-related monopolies. China’s concern over data-related monopolistic practices emerged alongside the rapid expansion of platform economy enterprises, particularly after a series of investigations involving major digital platforms such as Ant Group. In August 2024, the Shanghai Municipal Administration for Market Regulation investigated Ningbo Senpu Information Technology Co., Ltd. for abusing its dominant market position, ordering it to cease its illegal activities and imposing a hefty fine. This case, the first financial data monopoly case in China, aims to break the monopoly barriers in the financial data sector and set a precedent for fair competition in the data element market.

In contemporary society, digitalization is becoming a significant factor in restructuring the allocation of resources, reshaping industrial development, changing competitive landscape, and emerging new industrial forms. However, in practice, certain behaviors that exclude or restrict competition have emerged, hindering the orderly flow of data elements. Data-related monopolies are gradually spreading among various digital industries from fintech industry. Accordingly, removing barriers to data circulation and overcoming “data silos” have become central objectives of contemporary digital economy governance, as efficient data sharing is increasingly regarded as a prerequisite for innovation and fair competition (OECD 2015). As far as the development of the digital industry is concerned, the key lies in the co-enhancement of the sharing level and governance capacity, and the key to realizing fair competition lies in the adoption of effective means to regulate highly data-concentrated markets (World Bank 2021). In practice, China has responded relatively early to the need for regulating data monopolies at the legislative level. On February 7, 2021, the State Council Anti-Monopoly Commission issued the Anti-Monopoly Guidelines for the Platform Economy Sector (hereinafter referred to as the Anti-Monopoly Guidelines) and promptly amended the Anti-Monopoly Law and related supporting regulations. The newly revised Anti-Monopoly Law, effective since August 2022, adds Article 9, which explicitly prohibits monopolistic conduct involving the use of data.

However, data monopolization is a complex and systemic issue, with its regulation involving multiple dimensions such as antitrust, anti-unfair competition, data security, cybersecurity, consumer rights protection, and personal information protection (Stucke and Grunes 2016). The digital economy is still in a phase of rapid development, and the existing antitrust legal framework faces shortcomings or ineffectiveness when addressing new business models, new technologies, and emerging practices within the digital economy. In practice, due to the special nature of monopolistic behavior using data as a production factor. Traditional antitrust analytical tools—including relevant market definition, market power assessment, and competitive effects analysis—cannot always be directly applied to digital markets because data-driven platforms frequently exhibit zero-price services, multi-sided market structures, and strong network effects (Sun and Wei 2023). Additionally, due to a lack of regulatory experience, enforcement agencies may intervene untimely or apply enforcement with inappropriate intensity, resulting in some anti-competitive behaviors not being promptly or effectively regulated, or excessive enforcement undermining the incentives of market participants. Therefore, it is urgently necessary to systematically clarify the specific objectives and implementation pathways of anti-data monopolization, and to promote the normalized and systematic regulation of data monopolistic behaviors in a scientific and prudent manner, ensuring the standardized and healthy development of the digital economy.

1.2. Data Monopoly Has Been Taken Seriously

China’s Anti-Monopoly Law (AML) constitutes the cornerstone of the country’s competition law regime and provides the principal legal basis for regulating data-related monopolistic conduct. Unlike traditional competition legislation that focuses primarily on economic efficiency, the AML pursues multiple legislative objectives, including maintaining fair market competition, improving economic efficiency, protecting consumer interests, and promoting the healthy development of the socialist market economy. This multi-objective legislative structure enables the AML to respond more effectively to emerging competition issues arising from the digital economy (Zhang 2021). The issue of whether data constituted an essential facility is extremely controversial (Wang 2022; Liu et al. 2023). In practice, data-related monopolistic conduct has become an increasingly important focus of antitrust enforcement in China, and the existing AML framework already provides a sufficient legal basis for regulatory intervention.

The 2022 revision of the AML explicitly incorporated “data, algorithms, technology, capital advantages, and platform rules” into the statutory framework governing monopolistic conduct. By expressly recognizing data-related market power, the revised AML significantly strengthened the legal basis for regulating data-driven monopolistic practices.

The enactment and revision of supporting laws and regulations also play a complementary role in improving China’s Anti-Monopoly Law and regulations, enabling China’s Anti-Monopoly Law enforcement authorities to have a complete legal basis for data monopolization and to carry out timely and effective supervision. In fact, prior to the revised Anti-Monopoly Law, the Chinese legislature had imposed restrictions on an e-commerce business with dominant market position on account of its technological advantage, number of users, control of the relevant industries and other factors, may not abuse the dominant market position to exclude or restrict competition e-commerce data dominance in Articles 22 and 35 of the E-Commerce Law enacted in 2019, businesses are prohibited from abusing their dominant market position in e-commerce data by excluding or restricting competition. This includes factors such as the number of users, control of relevant industries, and other relevant considerations.

In the same year, Parts II, IV, and V of the Guiding Opinions on Promoting the Healthy Development of the Platform Economy (2019) and Chapters II, III, and IV of the ‘Guidelines’ issued in 2021 provide relatively detailed provisions on monopoly agreements, abuse of dominant market position and operator concentration in the new context. These provisions have expanded the field of platform competition regulation for digital governance, and constitute the prototype of China’s regulation of data-related monopoly behaviors, but the enforcement framework of the above laws and regulations is still based on the traditional concepts of “monopoly agreement”, “dominant position”, “concentration of operators” and so on.

In March 2022, Opinions of the CPC Central Committee and the State Council on Accelerating the Construction of a Unified National Market that “Focusing on increasing anti-monopoly efforts. We will improve legal rules for identifying monopolies and a category-and class-based system for anti-monopoly review of concentrations between undertakings. We will address issues such as platform enterprises’ monopoly of data to avoid eliminating and restricting competition by data, algorithms, technology, and other measures”. This policy explicitly calls for strengthening the regulation of data monopolization, providing important guidance for further improving the legal framework of the data factor market. It also demonstrates China’s increasingly deepened focus on data competition in the field of antitrust regulation.

In addition to the counteracting effect on data abuse that can be reflected in economic laws, the rules about data-related monopolistic behaviors provided for in legal provisions on the rights of the individual and property interests, such as Article 127 of the Civil Code, Article 45 of the Personal Information Protection Law and Article 51 of the Data Security Law. These provisions, from the perspective of personal rights protection, set limitations on the collection, use, and processing of personal information, aiming to prevent the misuse of data that could infringe upon personal rights. Although these regulations need further refinement and clarification in areas such as balancing data circulation with protection and preventing data monopolies by large platform companies, they still hold value in fostering competition.

Overall, China’s regulatory approach demonstrates an increasingly integrated legal framework in which competition law, data governance legislation, and civil law jointly address the competitive risks arising from data concentration. Rather than relying solely on traditional antitrust enforcement, China has gradually developed a multi-layered regulatory system capable of responding to the distinctive challenges posed by data-driven market power.

2. China’s Data Monopoly Supervision Status and Practice

2.1. The Necessity of Regulating Platform Data Monopolies

The Organization for Economic Co-operation and Development (OECD) maintains that data-driven markets are more concentrated than others, and more susceptible to being monopolized (OECD 2015). In September 2020, the inspection team of the National People’s Congress Standing Committee carried out by the implementation of the anti-unfair competition law, it was highlighted in the inspection report, pointed out that in recent years, Alibaba, Tencent and other digital enterprise mergers and acquisition are frequent, suffered from mergers and acquisitions of innovative small and medium-sized enterprises, although they do not reach the current standard of notification prescribed by the State Council and are not subject to the supervision of anti-monopoly law enforcement agencies, but many scholars argue that these concentrations between undertakings have produced a monopoly effect of restricting competition and inhibiting innovation (National People’s Congress Standing Committee Inspection Team 2020). Internet enterprises, especially digital platforms, have become the key target in China’s data-related antitrust supervisory practice (Zhang 2021).

In fact, China has a large number of digital platform enterprises, whose industry scale has exceeded 50 trillion dollars as of 2022 (China Academy of Information and Communications Technology 2022). Existing studies suggest that the rapid decline in data collection costs and continuous improvements in computing power have substantially increased the economic value of data. Other scholars further argue that moderate data concentration may generate economies of scale and improve data quality, thereby promoting innovation (Su 2022).

However, data is often concentrated in the hands of large digital platforms, and such concentration may reinforce market power through data-driven network effects and economies of scale. Reliance on platform self-regulation alone may be insufficient to prevent the abusive use of concentrated data, particularly where user feedback loops and control over personal data contribute to market tipping and consumer harm (Cao 2025). Improper use of data not only poses a risk of damage to consumer rights but also jeopardizes social governance and national security. The risk of data-related monopolization posed by digital platforms has already emerged during the development of the digital economy. Consequently, Chinese competition authorities have increasingly regarded data-related monopolistic conduct as a regulatory priority, reflecting the growing importance of competition policy in the governance of the digital economy.

2.2. Enforcement Practices for Regulating Data Monopolies

Before data-related provisions were formally incorporated into China’s Anti-Monopoly Law, several mergers involving substantial data assets had already attracted significant public and regulatory attention. In the case of the DiDi-Uber merger, Uber (China) sold its China business to Didi Chuxing (DiDi) for US$35 billion. DiDi which has more than 15 million drivers and 300 million registered users, the takeover, which solidified Didi’s market dominance, prompted an investigation by the Chinese Ministry of Commerce that ultimately failed to find Didi in violation of any regulations, because the acquisition did not meet the relevant market turnover standards under China’s existing antitrust laws. Although the transaction was ultimately cleared under the turnover thresholds applicable at the time, the case exposed a structural limitation of traditional merger control in digital markets. It demonstrated that transactions involving substantial data accumulation and ecosystem expansion may escape regulatory scrutiny despite their significant competitive implications. The Didi–Uber case therefore became an important catalyst for subsequent reforms of China’s antitrust regime concerning data and digital platforms.

In terms of the current development of the domestic digital market, it is again true that platform operators use a large amount of concentrated data to gain a dominant position in the market (Li and Xia 2020), and it is indeed an observable phenomenon, especially for operators to track users’ preferences and daily lives in real time by providing them with free basic services, treating users’ personal data as a key input variable, adjusting and optimizing their services in a timely manner, and providing a basis for merchants to place online targeted advertisements based on users’ consumption portraits, so as to realize the digital industrialization. This phenomenon has become the main profit model and competitive advantage for many digital platforms (Su 2022), while exacerbating the excessive collection and misuse of data by platform enterprises. This significantly reduces the participation of users and third-party vendors in the digital economy (Liu 2023), further leading to the potential risk of “data monopolies” among some leading platforms.

These phenomena are particularly evident in the series of cases handled by China’s Anti-Monopoly law enforcement institutions, which has investigated and dealt with cases of abuse of dominant market positions such as the Alibaba group required platform-based operators to choose “one out of two” and Meituan required platform-based operators to choose “one out of two”, as well as a number of cases of unlawful concentration of business operators. The case is particularly evident in the number of cases in which operators have on illegal concentration of undertakings in the field of platform economy. In response, the Supreme People’s Court issued the “Opinions on Ensuring Technological Innovation through High-Quality Judicial Services” in January 2025. By releasing typical cases, it explicitly calls for severe punishment of platform practices such as “choose one of two”. It emphasizes strengthening judicial deterrence through punitive damages, preservation measures, and other means, and promotes the coordination between judicial and law enforcement actions. These cases illustrate that China’s enforcement authorities have gradually shifted from focusing solely on price-based competition towards addressing platform conduct that strengthens market power through data accumulation, platform rules and algorithmic coordination. They also demonstrate the transition of Chinese antitrust enforcement from ex post intervention to a more proactive regulatory approach in the platform economy.

While the crux of the matter for solving data-related monopoly lies in the existence or non-existence of data monopoly. In China’s laws and regulations, the word ‘data monopoly’ is seldom explicitly mentioned but rather expressed in terms of the use of data monopoly advantage, data advantage, and so on. On the one hand, due to the theoretical system involving data has not been fully established, and there is a great deal of controversy surrounding the data monopoly at the theory level, because some scholars argue that the data itself has a non-competitive, instantaneous and other characteristics are not sufficient to determine the existence of data monopoly; On the other hand, the data is difficult to constitute an essential facility, whether the access restrictions on the data constitutes an impenetrable barrier to entry into the market, or the data holding capacity of the market power. Therefore, it is difficult for data to constitute a necessary facility in the sense of monopoly, whether data access restrictions constitute an impenetrable market entry barrier, or whether data holdings can be equated with monopoly power (Li 2011).

2.3. Establishing Data-Specific Supervisory Measures

Data is easily concentrated and exhibits significant economies of scale and scope. This characteristic has been widely recognised in competition economics, which considers data to exhibit strong economies of scale and scope, thereby reinforcing cumulative competitive advantages for incumbent digital platforms (OECD 2021). Although the initial fixed costs of data are often high, it can generate a positive feedback loop once utilized. In the context of the digital economy, data not only serves as the product itself or the content for providing services, but also plays an important role in business decision-making and strategic implementation. It helps businesses accurately and comprehensively understand and analyze industry and market development trends, effectively assisting in their competitive positioning (Ding 2023).

From a competition law perspective, the competitive significance of data does not arise from data ownership alone, but from an undertaking’s ability to transform large-scale datasets into sustainable competitive advantages through algorithms, computing capacity and platform ecosystems (Sun and Zhou 2023). In respect of platform operators involving data monopoly, the root cause of the monopoly lies in the fact that the platform operators have collected a large amount of data far exceeding that of ordinary operators, and restricting other trading conditions by data, platform rules and other methods to eliminate and restrict market competition. However, the main questions are whether the data itself is non-exclusive and cannot be monopolized by other operators, whether the data itself is sufficient to constitute a market controlling force that restricts competition, and whether it is easy to understand data in isolation from the platform’s economic structure of the platform and create a bias in understanding. Theoretically, the scale of data does not necessarily constitute dominant market positions, and it is necessary to examine the market power of operators based on their data advantages in the context of multiple dimensions, such as the value, type and validity of data.

In addition to Chinese market regulatory authorities regulating and supervising the competitive behavior of platform operators, China’s anti-monopoly authorities also focus on industry supervisory to regulate the platform economy, such as the Cyberspace Administration of China, Ministry of Industry and Information Technology, Ministry of Transport and other departments, which also regulate and supervise the characteristics of the industry, safety risks, and quality of services of the platform operators, for the purposes of promoting standardized, orderly, innovative and sound development of the platform economy, and safeguarding consumers’ interests and public interests. During China’s anti-monopoly supervisory practice, China’s legislature will on the basis of the development status and characteristics of the platform economy, continuously strengthen and improve the regulation, and enhance the pertinence and scientificity of anti-monopoly law enforcement.

Overall, China’s regulatory practice demonstrates a gradual transition from regulating traditional market dominance towards supervising data-enabled market power. Rather than establishing an entirely new legal regime for data monopolies, Chinese authorities have sought to adapt existing antitrust, data governance and platform regulatory frameworks to address emerging challenges in the digital economy. This incremental approach provides an important institutional foundation for the future development of data-specific competition rules.

3. Practical Challenges in China’s Data-Related Anti-Monopoly Supervision

3.1. The Relationship Between Data and Competition Becomes Ambiguous

Data has become an increasingly important competitive asset in the digital economy. With the rapid development of algorithms, artificial intelligence and computing power, the competitive functions of data have expanded significantly across different markets and business models. Competition in the digital economy is no longer determined solely by conventional factors such as price, output and market share. Instead, competitive dynamics increasingly arise from the interaction among digital platforms, data resources and algorithmic capabilities (Cheng and Yu 2023). In this structure, the competitive model of data monopoly is not solely caused by data itself but results from the synergistic effects of multiple factors, including platforms, capital, data, computing power, and algorithms. Data-related competitive advantages may also extend across interconnected markets and business ecosystems, allowing market power acquired in one service to reinforce competitive advantages in another. Consequently, data-related monopoly should not be understood as an isolated competition issue, but as a systemic governance challenge involving market competition, technological innovation and data governance simultaneously.

The relationship between data and competition dynamic and depends on the technological, commercial and institutional context in which the data is collected and used. As digital technologies evolved, data became one of the core elements of competition for enterprises. Data was once regarded primarily as an operational resource used to improve efficiency and service quality. With the development of digital platforms, machine learning and data analytics, however, it has increasingly become a strategic input capable of shaping innovation, entry barriers and market power (Barker 2021). However, data monopolies can distort market competition, becoming a tool for a few companies to exclude competitors and raise market barriers. Therefore, it is necessary to correctly examine the relationship between data and competition. In terms of data protection and openness, the two are not opposing forces. Combating data monopolies does not mean restricting data protection but rather aims to achieve healthy data competition and utilization through scientific, standardized, and effective data flow and sharing (Chen 2021).

Given that data plays different roles in various industries and technologies, it is necessary to establish appropriate regulatory measures to address potential anti-competitive effects. Generative artificial intelligence provides a useful example. Article 4 of China’s Interim Measures for the Management of Generative Artificial Intelligence Services prohibits providers and users from exploiting advantages in algorithms, data or platforms to engage in monopolistic or unfair competitive conduct. The training cost of data in generative AI technology is extremely high, making the role of data in such emerging technologies even more critical. Exclusionary control over essential data inputs may therefore restrict market entry, weaken downstream innovation and reinforce the position of incumbent digital firms. Therefore, in the development of the data industry, it is essential to adopt targeted regulatory approaches, taking into account the role of data as a competitive element in the market.

3.2. Difficulty in Effectively Regulating Data-Related Monopoly Behaviors by Traditional Standards

Under the traditional anti-monopoly supervision model, for example, the standard of assessing market shares of operators in the relevant markets based on the proportions of trading amount seems to be not feasible in the digital economy. The DiDi–Uber merger demonstrates the limitations of China’s current merger control regime in addressing data-driven concentrations. Existing notification thresholds, which are primarily based on turnover, may fail to capture transactions involving strategically valuable data assets and network effects. The DiDi–Uber transaction illustrates that turnover-based merger notification thresholds may fail to capture acquisitions involving strategically valuable data assets. Although the transaction significantly strengthened DiDi’s data accumulation and network effects, it escaped substantive merger review because the statutory turnover thresholds were not triggered. This case exposed the structural limitations of traditional merger control in digital markets (Crémer et al. 2019). For example, in terms of analysis methods of internet-related market definition and abuse of dominant market position, Hypothetical Monopolist Testing (HMT) is a generally applicable analytical method that defines the relevant market. In practice, it is assumed that HMT can be conducted through methods such as Small but Significant and Non-transitory Increase in Price (SSNIP) or Small but Significant and Non-transitory Decrease in Quality (SSNDQ). However, in judicial practice, market share in the platform economy is a relatively crude and potentially misleading indicator for evaluating dominant market position (Cheng 2023). Its position and role in determining dominant market position must be determined based on the circumstances of specific cases.

China has revised a number of competition regulations to reflect the characteristics of the platform economy, including the Anti-Monopoly Guidelines for the Platform Economy Sector and the Provisions on the Review of Concentrations of Undertakings. These instruments recognize the growing competitive significance of data and algorithms. However, they still lack clear legal standards for identifying data concentration, evaluating data-driven market power and determining data-related monopolistic conduct. Moreover, due to the strict criteria based on the “relevant market → dominance → abuse” paradigm, the post-regulation of many monopoly cases is often time-consuming and difficult, with challenges in determining the relevant elements, and it lacks universality (Furman 2019). Furthermore, uniform enforcement standards cannot adequately distinguish between different platform business models, resulting in either under-enforcement against high-risk platforms or excessive intervention in low-risk markets (National People’s Congress Standing Committee Inspection Team 2020).

In the context of the digital economy, as new technologies such as algorithms and artificial intelligence are widely applied in market operations, supported by factors like platforms, capital, algorithms, and computing power, the manifestations of data monopoly behavior have become more diverse and covert, further complicating the difficulty of determining their illegality (Chen 2024). Due to the characteristics of data, the regulatory model for data-related monopolistic behavior must differ from traditional regulatory methods. Although traditional anti-monopoly measures and relevant market definition methods still have some applicability, they are difficult to apply directly and need to be updated and adjusted according to the characteristics of the internet platform’s bilateral market structure, network effects, and lock-in effects (Li and Yuan 2023).

China’s current enforcement model remains predominantly ex post, relying mainly on administrative penalties imposed after anti-competitive conduct has occurred. However, financial penalties alone may not provide sufficient deterrence for dominant digital platforms when expected monopoly profits substantially exceed the cost of regulatory sanctions. For example, in the case of China’s anti-monopoly authorities imposed a fine of more than 20 billions on Alibaba and Meituan for their ‘choose one from two’ monopoly behaviors, the market capitalization of the two companies has not fallen but risen, and the extent of the increase in their market capitalization is higher than the amount of the fines imposed by the anti-monopoly institutions. Therefore, it is difficult to effectively regulate data-related monopoly behaviors purely by ex-post regulations for antitrust regulation.

Traditional antitrust law has strong policy rigidity, making it difficult to adapt to the rapid and innovative development of the platform economy. It lacks the flexibility to respond to new forms of data monopolistic behavior arising from business model innovations on digital platforms. In particular, its post facto prohibitions on specific behaviors may unintentionally harm non-involved companies, leading to significant adjustments in existing business models and increasing uncertainty in innovation and development. Meanwhile, post facto antitrust enforcement is also ineffective in addressing the non-economic harms caused by data monopolies and fails to achieve social value goals effectively. The goal of antitrust law is to maintain market competition; however, post facto enforcement typically only halts specific data monopolistic behaviors and cannot effectively restore market competition or fundamentally resolve the problem of insufficient competition in the market. Under such circumstances, moderate ex ante supervision should be an important supplement, and eventually regulation should be carried out by a combination of ex ante and ex-post regulation. The limitations of traditional antitrust enforcement demonstrate that effective governance of data-related monopolies cannot rely solely on market regulators. A coordinated regulatory framework involving both competition authorities and sector-specific regulators is therefore required.

3.3. Strengthening Coordination Between Sectoral Regulation and Competition Law Enforcement

China’s supervision of data-related competition conduct not only involves the participation of market regulators, but also involves the needs and development of the relevant industry based on the needs of the industry’s development of intra-industry competition regulation (Chen 2023a). Platform interoperability policies illustrate the growing interaction between industrial regulation and competition enforcement. For example, since July 2021, the Ministry of Industry and Information Technology initiated the issue of platform inter-connectivity, which later also affected the Chinese market regulatory authorities’ attention to the refusing to deal with the other transactional parties without any justifiable cause or self-preferential treatment based on the data. However, industry regulations are influenced by industrial policies and often focus on aspects such as consumer rights protection, personal privacy protection, or trade secret protection. As a consequence, overlapping regulatory responsibilities may generate inconsistent compliance requirements, duplicate enforcement efforts and regulatory uncertainty for digital platform operators.

For example, the phenomenon of overlapping regulation involving industry regulators and market regulators also occurs in the online car-hailing industry and market. Between 2021 and 2023, several ministries successively introduced regulatory measures governing competition, pricing practices and platform governance in the ride-hailing industry. These policy documents collectively sought to strengthen fair competition while promoting the compliant development of digital transportation platforms. These documents explicitly outline anti-monopoly regulations within the regulatory framework, aiming to limit the market dominance of platform companies and prevent the abuse of market power. However, due to the dispersed functions of various departments, regulatory measures often overlap and contradict each other, lacking a unified and coordinated regulatory framework. The aforementioned industry regulations have not fully connected with market regulation, leading to overlaps in supervision and difficulties in enforcement. So it is a challenge to set up the powers and responsibilities between departments so that they can better cooperate with each other (Chen 2023b). Similar institutional coordination mechanisms have also been developed in other jurisdictions. For example, the European Union has strengthened coordination between competition authorities and digital regulators through the Digital Markets Act (DMA) (European Parliament and Council 2022), while the United Kingdom established the Digital Regulation Cooperation Forum (DRCF) to facilitate cooperation among competition, communications, data protection and financial regulators (Digital Regulation Cooperation Forum 2024). These experiences demonstrate that effective governance of digital markets increasingly depends on institutional coordination rather than isolated regulatory actions by individual authorities.

4. Emphasizing and Improving Data Monopoly Supervision

4.1. Establishing Regular, Adaptive and Risk-Based Regulatory Mechanisms

The Chinese government has repeatedly emphasized the regular regulation of the digital economy, raised the level of regulation and supported platform companies to lead development, create jobs, and better compete internationally. During the annual sessions of the National People’s Congress (NPC) and the National Committee of the Chinese People’s Political Consultative Conference (CPPCC) of the State Administration of Market Regulation (SAMR), in 2023 Luo Wen, head of the State Administration for Market Regulation, during an interview on the “Ministers’ Passage” said “we need to ensure clarity of rules and process for enforcement and inspections conducive to improve a business environment, and strengthen the regular supervision, especially in key areas such as the digital economy and livelihood protection, and strengthen agile supervision to help strengthen compliance management and provide assistance for enterprise development.” The 2025 Government Work Report stated, “Promote the standardized and healthy development of the platform economy, and better leverage its positive role in driving innovation, expanding consumption, and stabilizing employment.” Regular and agile supervision has become a regulatory measure adopted by China’s anti-monopoly authorities to cope with the context of the digital economy development.

An effective regulatory framework should incorporate at least three complementary dimensions. Firstly, antimonopoly supervision in the field of digital platform economy should be broadened, emphasizing the balance of multiple values and objectives, and paying special attention to innovation in data monopoly supervision. Secondly, antitrust supervisory measures should be innovated, and scientific and technological supervisory means should be introduced to promote compliance governance and precise regulation of anti-competitive risks of digital economy platform enterprises with scientific supervision, to promote the healthy development of the platform economy. Finally, the rule of platform classification and platform grading should be optimized, and the interconnection regulatory framework can be improved, focusing on perfecting the governmental supervisory system, supplemented by the construction of a diversified regulatory pattern, which will help data monopoly supervision.

4.2. Implementing Interdepartmental Comprehensive Supervision

Because data simultaneously possesses economic, personal, social and security attributes, data-related monopolistic conduct cannot be effectively addressed through competition law alone. Instead, it requires coordinated regulatory intervention from multiple government authorities responsible for competition, data governance, cybersecurity and consumer protection (OECD 2022). For example, Data Security Law, Personal Information Protection Law and other laws and regulations also contain provisions on the use of data advantages and platform advantages to implement monopolistic behavior. At the same time, combined with the multiple attributes of data, multi-dimensional and multi-level regulation also helps to clarify the theoretical basis of data, and perfecting the theoretical basis of data is a prerequisite for clarifying how to regulate data monopoly behavior.

Accordingly, closer institutional coordination between sectoral regulators and competition authorities should be established to create an integrated governance framework covering the entire data lifecycle.

First, the boundaries between government and market should be clarified. From the perspective of market regulation, the focus is on protecting competition. Improper industry regulations may hinder the cross-industry or cross-domain circulation of data elements, leading to industry data monopolies and restricting market competition. In this case, the coordination between industry regulation and market regulation is crucial. It is important to balance the relationship between competition protection and data value sharing, better protect competition, encourage innovation, and achieve co-creation and sharing of data value.

Second, the responsibilities and division of labor among different departments within the government should be clarified. Industry regulatory departments should formulate corresponding data rules based on the characteristics of each industry, while market regulatory departments should be responsible for the formation of a unified national market for data elements. The National Data Administration (NDA) should take the lead in coordinating the construction of data infrastructure, managing the construction of local data trading platforms, and establishing unified and reasonable data trading rules, as well as formulating fair data pricing mechanisms.

Finally, communication and collaboration between different departments should be further strengthened. Based on the “Guiding Opinions on Deepening the Promotion of Cross-departmental Comprehensive Regulation” issued by the General Office of the State Council, a comprehensive regulatory system for data circulation governance should be improved, enhancing the effectiveness of cross-departmental regulatory coordination.

4.3. Improvement of the Basic Theoretical System of Data

According to the characteristics of data, it really could hardly constitute an element of monopoly, because of its non-rivalrous and replicable nature, data itself does not necessarily constitute a source of monopoly power. Nevertheless, data-related monopolistic conduct may still emerge through the accumulation of data advantages, network effects and platform ecosystems, thereby requiring an appropriate legal governance framework. In 2020, the Chinese government has explicitly stated that it would link anti-monopoly regulation to the regulation of data collection and use behaviors, especially in relation to innovations in the financial sector. The Chinese government’s governance of data monopoly emphasizes more on governance at the source. The Chinese government has carried out exploratory regulation of collection, processing and analysis of data and other aspects, and the increased emphasis on governance at the source involving data-related monopoly behavior can be seen in the intensive introduction of laws such as the Cybersecurity Law, the Data Security Law, and the Personal Information Protection Law.

In 2023, The establishment of the National Data Administration (NDA) in 2023 marked a significant institutional reform in China’s data governance framework by providing a centralized authority responsible for coordinating national data policies and infrastructure. In response to data-related monopolization, both source governance and multi-governance have been implemented, and the relationship between data and enterprises has been adjusted at the source to break the data-related monopoly. On January 4, 2024, the NDA and 17 other departments jointly issued the “Three-Year Action Plan for ‘Data Elements X’ (2024-2026),” which outlines the goal of forming a relatively complete data industry ecosystem by the end of 2026. It also aims to significantly improve the quality and efficiency of data products and services, with the data industry expected to grow at an annual rate of over 20%. This plan reiterates the importance of improving the foundational data system and sets specific phase targets.

Improving the theory of data can mainly focus on three aspects as follow. First, the data property rights system should be clarified to form the interaction between multiple subjects of data, thereby reducing the institutional cost of data transactions and promoting data circulation. Second, the protection system for data property rights should be improved to enhance the risk control capability of the data factor market. Third, precautionary supervisory measures should be taken to build a multi-law cooperative system with the antitrust law at its core and fully utilizing the role of market-based governance systems and avoiding excessive supervision.

4.4. Strengthening the Construction of Data Infrastructure

The development of data infrastructure should begin with a well-defined data classification and categorization system. Guided by China’s “Twenty Data Measures”, differentiated governance rules should be established for public data, enterprise data and personal data, together with clear ownership and authorization mechanisms. This will provide a clearer regulatory framework for data governance. Public data, as a key resource for national governance, should prioritize the protection of national security and public interests, with strict controls over its commercialization. Enterprise data, on the other hand, should ensure the legitimate rights and interests of market entities while promoting the reasonable allocation and sharing of data property rights. Personal data must be safeguarded to ensure that privacy and security rights are not violated. Establishing this classification and grading system will help form differentiated protection and refined management within data governance, laying the institutional foundation for the development of data infrastructure.

A sound data infrastructure also requires secure and legally compliant data transactions. At present, China’s data transaction market is still in the exploratory phase, with issues such as unclear data ownership, incomplete transaction rules, and insufficient legal protection remaining prominent. To address these issues, a security and compliance mechanism covering the entire process of data collection, processing, storage, circulation, and use should be built, clarifying the legal boundaries and standards for data transactions. Additionally, there should be enhanced regulation of data transaction platforms to ensure that transactions comply with legal and regulatory requirements, preventing data misuse.

Developing a competitive and efficient data market should become another important objective of data infrastructure construction. Currently, the development of the data transaction market faces many challenges, such as information asymmetry between data supply and demand, incomplete transaction rules, and a single operating model for platforms. In the process of market development, it is important to optimize the mechanism for connecting data supply and demand, promoting the efficient circulation and sharing of data resources between different entities. At the same time, various market participants should be encouraged to actively engage in data transactions, improving data pricing mechanisms and benefit-sharing systems to ensure the reasonable protection of all parties’ interests.

4.5. Maintaining Fair Competition in the Data Market

In response to the frequent occurrence of platform behaviors that hinder the free flow of data elements, such as refusing data interoperability, it is essential to precisely identify and swiftly govern data monopoly and unfair competition practices. First, it is necessary to enrich the factors considered in defining relevant markets and determining market dominance. For example, the market can be defined by testing whether consumers would switch to other platforms if privacy protection measures were significantly reduced but not temporarily, or by assessing whether the platform has the ability to control and process data to determine if it holds market dominance. Secondly, the illegality of platform refusal of data interoperability should be carefully evaluated. Such behavior should only be considered an abuse of market dominance when it has the effect of excluding or restricting competition.

Furthermore, it is important to refine the criteria for identifying unfair competition in the data sector by introducing new judgment methods. In AI training, the use of web scraping technology by robots to collect data has become the primary means for data companies to obtain raw materials. The legitimacy and legality of such data acquisition behaviors should not be judged solely based on static data ownership but should be considered in the context of the value brought about by dynamic data innovation. By establishing standards for reasonable use of data, dynamic data rights allocation should be incorporated into judicial decisions, focusing on balancing data security, flow, and value realization. It is crucial to ensure that data companies’ necessary costs and reasonable returns during data collection, usage, storage, and trading processes are fully protected, thereby clearly defining, regulating, and encouraging the proper use of data-by-data companies.

5. Conclusion

The rapid development of the digital economy has transformed data into a strategic competitive asset. Data-driven digital platforms have consequently become an increasingly important focus of antitrust enforcement across multiple jurisdictions (Crémer et al. 2019). At the same time, the concept, scope and legal implications of data-related monopoly remain contested in both academic literature and regulatory practice. Because the competitive value of data depends on its quality, scale, substitutability and integration with platforms, algorithms and computing resources, the regulation of data-related monopolistic conduct must reflect the distinctive economic and technological characteristics of digital markets. At present, China’s main regulatory model is to regulate the competitive behavior that may be brought about by the development of the digital economy on the premise of promoting the development of the digital economy and incentivizing development of the data industry under the premise of safety. Regulatory means in countries around the world are more focused on the impact on the overall market than on the structure of specific behaviors, although there are differences in the regulation of monopoly standards (Wang 2015).

Compared with the European Union and the United States, China has pursued a more integrated regulatory approach by incorporating data-related competition concerns into antitrust law while simultaneously developing broader legislation on data security, personal information and platform governance. Although there are still controversies over whether and how data can directly form a monopoly, and there is no unanimous opinion on the concept of “data monopoly” either in theory or practice, China’s anti-monopoly authorities have formulated a series of laws and regulations on data-related monopoly behavior to regulate potential anti-competitive behavior. However, existing regulatory tools remain insufficient to identify and address data-driven market power in digital ecosystems characterized by zero-price services, multi-sided markets, network effects, algorithmic opacity and rapid market tipping (Furman 2019). However, China’s anti-monopoly authorities have introduced a series of means that are closely aligned with their practices in response to the characteristics of the data elements and competitive behaviors, and have enriched and perfected the anti-monopoly regularization regulatory means by continuously enriching anti-monopoly regulatory tools and implementation methods, strengthening and refining anti-monopoly prior review in the platform economy, helping data enterprises to do a good job of complying with the regulations, and creating a full-cycle, full-chain regulatory mechanism for data competition, so as to achieve the ultimate goal of prospering the data industry market and protecting fair competition in the market.