【刊出新闻】《上海财经大学学报》2026年第4期目录
本期共 10 篇文章
构建中国人工智能经济学自主知识体系的思考与建议——基于国内外人工智能经济主题文献的考察与评论
摘要 · ABSTRACT
近年来，人工智能对经济社会的影响已经引发国内外学者的广泛关注，而西方学者基于其本国价值取向与实践所形成的人工智能经济理论，对促进中国经济发展的局限性日益凸显。人工智能作为引领新质生产力的核心引擎，是完全不同于传统工业技术的新型要素。文章认为，中国人工智能经济学的基本定位应保持理论自立，完成根植中国国情与回应全球发展的双重使命，研究内容上应融入中国特色的效率提升与公平挑战双重效应、场景驱动创新路径以及人机共生动态平衡三大因素，提出应建构符合国情的中国人工智能经济学“技术—制度—社会”协同的分析框架。通过梳理人工智能经济学研究范式的变化，结合我国人工智能发展和应用目标，阐明当前研究的局限以及理论上必须回应的AI 技术影响机制、AI 技术综合评估体系与目标平衡、AI 国家治理范式与全球治理架构、AI 技术对平台经济与产业转型的影响、AI 技术与创新体系的关系五个关键问题，以期推动中国人工智能经济学理论研究，提高中国人工智能学术话语权。
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Abstract
In recent years, the socioeconomic impacts of artificial intelligence (AI) have attracted extensive attention from scholars at home and abroad. The AI economic theories developed by Western scholars based on their national value orientations and practical experiences have shown growing limitations in driving China’s economic development. As a core engine leading the development of new quality productive forces, AI represents a new type of factor that is fundamentally different from traditional industrial technologies. The fundamental positioning of China’s independent AI economics lies in upholding theoretical self-reliance and fulfilling the dual mission of being rooted in China’s national conditions and responding to global development needs. In terms of research content, it is necessary to integrate three major elements: the dual effects of efficiency improvement and equity challenges with Chinese characteristics, scenario-driven innovation pathways, and the dynamic balance of man-computer symbiosis. It is proposed that an analytical framework featuring the coordination of “technology-institution-society” should be constructed for China’s independent AI economics tailored to national conditions. By sorting out the evolution of research paradigms in AI economics and aligning with China’s goals for AI development and application, this paper clarifies the limitations of current research. It also identifies five key theoretical issues that need to be addressed: the impact mechanism of AI technology, the comprehensive evaluation system and goal balance of AI technology, the national governance paradigm and global governance architecture of AI, the impact of AI technology on the platform economy and industrial transformation, and the relationship between AI technology and the innovation system. This paper aims to advance theoretical research on China’s independent AI economics and enhance China’s academic discourse power in the field of AI.
构建中国住房保障自主知识体系：概念、理论与模式
摘要 · ABSTRACT
当前，我国已建成世界上规模最大的住房保障体系，并正以保障对象分层覆盖、多主体协同供给、配租与配售并行为特征加速推进。文章对中国特色住房保障实践进行经验总结和理论提炼，从标识性概念、理论内核以及实践模式三个层面探索中国住房保障自主知识体系的构建。在概念层面，强调我国住房保障的核心特征与术语标准；在理论层面，基于以人民为中心的共同富裕导向，构建公平与效率统一的双重属性分析框架以及生存、发展和共享递进统一的三重目标体系；在实践层面，坚持问题导向，聚焦供需匹配、财政可持续与治理现代化等现实议题，以期为我国住房保障模式的进一步完善提供理论指导，也为其他发展中国家的住房治理实践贡献中国方案。
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Abstract
China has established the world’s largest housing security system, characterized by stratified coverage of beneficiary groups, coordinated provision by multiple actors, and parallel implementation of rental-based and sale-based allocation mechanisms. Grounded in the institutional evolution and practical experience of China’s housing security system, this paper systematically reflects on the limitations of applying Western housing security frameworks within the Chinese context. It further proposes a strategy for constructing an indigenous knowledge system for housing security in China from the perspectives of concepts, theories, and models. At the conceptual level, this paper advocates a structurally grounded and hierarchically organized taxonomy. “Affordable housing” is defined as the overarching institutional category, within which two principal branches—rental-based and sale-based provisions—are distinguished. They are further specified into concrete subtypes, including public rental housing, government-subsidized rental housing, shared-ownership housing, and closed-management affordable housing. This paper also emphasizes the standardization of terminology and its capacity for cross-contextual dialogue. At the theoretical level, this paper advances a core framework summarized as “one center, dual attributes, and three objectives”. “One center” refers to a people-centered orientation toward common prosperity, clarifying the fundamental question of “housing security is provided for whom”. “Dual attributes” highlight the dialectical unity of equity and efficiency, addressing the central tension between social protection and economic development. “Three objectives” encompass a progression from ensuring basic shelter (subsistence goal), to achieving adequate and livable housing (development goal), and ultimately to promoting shared prosperity (collective goal). Together, these elements form an internally coherent explanatory logic for the housing security system. At the level of practical models, this paper adopts a problem-oriented approach and focuses on three pressing issues in China’s current housing security practice. First, supply-demand alignment, which involves resolving structural mismatches in beneficiary identification, spatial distribution, and policy instrument design. Second, fiscal sustainability, which calls for an analytical framework covering cost estimation, financing mechanisms, asset management, and risk monitoring, with a particular focus on innovative approaches such as converting existing housing stock into affordable housing. Third, governance modernization, which emphasizes the development of a multi-actor governance system through improvements in organizational structures, coordination mechanisms, and performance evaluation. This paper provides theoretical guidance for further improving China’s housing security models and offers a “Chinese solution” to housing governance challenges in other developing countries.
新就业形态健康发展视域下平台劳动控制的政治经济学分析——以网约车“养号”现象为例
摘要 · ABSTRACT
党的二十届四中全会通过的“十五五”规划提出“推动灵活就业、新就业形态健康发展”，并强调“促进多劳者多得”的政策导向。网约车是数字经济时代新就业形态的典型代表，其健康发展关乎灵活就业群体的切身权益。文章以北京市、武汉市、淄博市和芜湖市的网约车与出租车司机为调研对象，通过实地调研和跨业态比较发现，平台劳动控制主要通过计件工资制度从劳动标准、劳动强度、劳动监督三个维度深化劳动对资本的实质隶属，实现对劳动过程的全面支配。在此机制下，司机为维持账号权重，普遍形成“养号”行为，导致劳动投入与收入回报持续脱节、劳动过程中积累的经验与数据被平台整合使用、自由发展空间因时间挤压而不断收窄的三重结果。当前，制度供给与平台实践之间存在落差：北京以户籍限制与合规门槛形成灰色运营与沉没成本困境，淄博、芜湖以监管弹性引发“兜底型内卷”，武汉以合规化、市场内卷、技术替代叠加形成“养号”压力。在社会主义市场经济体制下，破解平台劳动控制困境需要打破算法黑箱，从算法透明、成本分担、劳动过程保障三个层面完善治理体系，使新就业形态劳动者真正享有体面劳动的权利。
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Abstract
The 15th Five-Year Plan adopted at the Fourth Plenary Session of the 20th Central Committee of the Communist Party of China proposed to “promote the healthy development of flexible employment and new forms of employment”, and emphasized that “those who work hard should be allowed higher incomes”. Ride-hailing is a typical representative of new forms of employment in the era of the digital economy, and its healthy development is directly related to the vital interests of a large number of flexible workers. This paper takes ride-hailing and taxi drivers in Beijing, Wuhan, Zibo, and Wuhu as research subjects. Through field research and cross-industry comparison, it is found that platform labor control deepens the substantive subordination of labor to capital through the piece-rate wage system from three dimensions: labor standards, labor intensity, and labor supervision, and algorithms achieve comprehensive control over the labor process. Under this mechanism, drivers are forced to accept low-yield orders, extend their online hours, and strive for positive reviews in order to maintain account weight, forming a widespread behavior of “account maintenance”. This behavior leads to three consequences: First, there is a continuous disconnect between labor input and income return, making it difficult to achieve “the more you work, the more you earn”; second, the experience and data accumulated during the labor process are integrated and used by the platform, and drivers fail to obtain corresponding returns; third, the space for free development is continuously narrowed due to time constraints, and long-term overtime work makes it difficult for drivers to achieve skill improvement and career transformation. Further analysis shows that there is a disconnect between current institutional supply and platform practices: Beijing faces a dilemma of gray operation and sunk costs due to strict household registration restrictions and high compliance thresholds; cities such as Zibo and Wuhu are caught in a catch-all type of involution due to flexible regulation and insufficient institutional protection; in Wuhan, under the multiple overlaps of compliance, market involution, and technological substitution, drivers’ pressure from “account maintenance” is particularly prominent. These differences indicate that the interaction between local governance strategies and platform algorithm logic varies, resulting in differentiated labor control outcomes. Under the socialist market economy system, solving the dilemma of platform labor control requires breaking the algorithmic black box and improving the governance system from three levels: algorithm transparency, cost sharing, and labor process protection, so that workers in new forms of employment can truly enjoy the right to decent work.
生成式人工智能与企业劳动力需求结构分化——基于ChatGPT发布的准自然实验
摘要 · ABSTRACT
生成式人工智能正深刻改变劳动力市场结构。基于2022—2023年中国在线招聘平台数据，文章以ChatGPT发布为准自然实验，构建广义双重差分模型考察其对企业劳动力需求结构的影响。研究发现，生成式人工智能显著引发了招聘需求的结构性调整，常规职业的收缩幅度明显大于非常规职业，技术冲击主要集中于程序化程度较高的认知职业。基于任务分类的结果显示，这种影响并非均匀作用于所有认知职业，而是主要集中于常规认知职业以及信息分析与处理型非常规认知职业。机制分析表明，任务效率提升和新任务创造共同推动了劳动力需求结构分化。异质性分析表明，技术冲击在无经验要求岗位、民营企业、劳动密集型行业及传统产业中更为显著。进一步分析发现，生成式人工智能在提高岗位工资的同时加剧了职业竞争；相较于常规职业，非常规职业的工资提升更明显、职业竞争更激烈，体现出非对称技术红利和竞争加剧的特征。文章从企业招聘视角揭示了生成式人工智能重塑劳动力需求结构的微观机制，为理解技术冲击下的就业结构调整提供了经验证据。
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Abstract
Generative artificial intelligence (AI) is profoundly reshaping the occupational task structure and labor demand allocation of enterprises. Using monthly data from online recruitment platforms in China from 2022 to 2023, this paper treats the release of ChatGPT as a quasi-natural experiment and combines occupation-level large language model exposure to construct a generalized DID model, thereby systematically examining the short-run impact of generative AI on enterprise labor demand and its underlying mechanisms. The results show that generative AI significantly triggers a structural adjustment in the recruitment demand of enterprises, with the contraction in routine occupations being substantially greater than that in non-routine occupations, indicating that technological shocks are first concentrated in cognitive jobs with a higher degree of programmability. Further task-based analysis suggests that this effect is not evenly distributed across all cognitive occupations, but mainly concentrated in routine cognitive occupations and information-processing non-routine cognitive occupations, with a relatively limited impact on non-routine cognitive occupations centered on interpersonal interaction and complex decision-making. Mechanism testing shows that enterprises, on the one hand, compress demand for routine-related positions through task efficiency improvement and, on the other hand, increase the probability of new occupations in non-routine domains through new task creation. The two channels jointly reinforce the structural differentiation of labor demand. Heterogeneity analysis further indicates that the impact is more pronounced in positions without experience requirements, private enterprises, labor-intensive industries, and traditional industries, suggesting that sectors with greater market exposure and higher task replaceability are more vulnerable to generative AI shocks. Further analysis shows that although recruitment demand for routine occupations declines more rapidly, non-routine occupations experience stronger wage premiums and significantly higher competition intensity. This implies that generative AI mainly works through substitution in routine occupations, whereas in non-routine occupations it is more closely associated with skill complementarity, productivity enhancement, and intensified competition. From the perspective of enterprise recruitment, this paper uncovers the micro-level mechanisms through which generative AI reshapes labor demand structures and provides new empirical evidence for understanding employment adjustment and occupational differentiation under technological shocks.
城市算力基础设施建设、数字知识流动与数实产业技术融合
摘要 · ABSTRACT
算力基础设施是新型信息基础设施的重要组成部分，能够重构数字知识的流动路径，为数实产业技术融合提供重要支撑。文章基于2010—2023年工信部电信业务经营许可证数据与中国专利申请数据，围绕数字知识这一关键中介载体，实证检验城市算力基础设施建设对数实产业技术融合的影响效应及内在机制。研究发现，城市算力基础设施建设能够显著促进数实产业技术融合。机制分析表明，算力基础设施建设能够促进数字知识要素的高效流通与共享，使得数字知识快速渗透产业链各环节，推动数实产业技术融合。异质性分析表明，东部城市、三线及以上城市、非资源型城市以及隶属于国家级城市群的城市进行算力基础设施建设对数实产业技术融合的促进作用更强。研究结论为不同城市与区域之间优化算力基础设施布局、提升数字知识共享效率以及推动数实产业深度融合提供理论支持与决策参考。
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Abstract
Computing infrastructure is a vital component of new information infrastructure. It can reshape the flow paths of digital knowledge and provide important support for the technological convergence of digital and real economy industries. Based on data of telecom business operating licenses from the Ministry of Industry and Information Technology and Chinese patent application data from 2010 to 2023, this paper empirically examines the impact and internal mechanisms of urban computing infrastructure construction on the technological convergence of digital and real economy industries, using digital knowledge as the key intermediary carrier. The results show that urban computing infrastructure construction can significantly promote the technological convergence of digital and real economy industries. Mechanism testing indicates that computing infrastructure construction facilitates the efficient circulation and sharing of digital knowledge factors, enables the rapid penetration of digital knowledge into all links of the industrial chain, and thus drives the technological convergence of digital and real economy industries. Heterogeneity analysis reveals that this promoting effect is stronger in eastern cities, cities above the third-tier, non-resource-based cities, and cities belonging to national-level urban agglomerations. Based on the above conclusions, this paper draws the following policy implications: First, accelerate the construction of urban computing infrastructure and strengthen the supporting role of computing power supply in the technological convergence of digital and real economy industries. Through policy instruments such as fiscal subsidies and tax reductions, cities should be guided to increase investment in core fields of computing infrastructure in accordance with their own industrial foundations. Second, take the construction of urban computing power networks as the starting point to improve the mechanisms for digital knowledge flow and sharing. On the one hand, efforts should be made to promote the coordinated application of computing power, algorithms, and data within cities, and to build city-level computing power sharing platforms. On the other hand, the linkage of urban computing power networks within large urban agglomerations should be enhanced to establish cross-city alliances for computing power and digital knowledge sharing. Third, promote the construction of urban computing infrastructure in a hierarchical and classified manner based on heterogeneous urban characteristics. Central cities should focus on building real-time computing power hubs to meet low-latency and high-computing-power demands, while peripheral cities should develop green computing power bases and ultra-large-scale data center clusters, mainly undertaking non-real-time computing power needs.
数据安全监管与企业全要素生产率——来自《数据安全法》实施的经验证据
摘要 · ABSTRACT
《数据安全法》作为政府实施数据安全监管的重要法律保障，其核心目标是化解数据安全风险、护航经济高质量发展，但该法的实际监管成效，尤其是对企业全要素生产率的驱动效应尚未明晰。文章以《数据安全法》的实施作为准自然实验，利用沪深A股非金融上市公司数据，构建双重差分模型，实证检验《数据安全法》的实施对企业全要素生产率的驱动效应及其作用机制。研究结果表明，《数据安全法》的实施显著提高了企业全要素生产率。机制分析发现，《数据安全法》能够发挥数据安全治理效应，通过推动企业技术创新和优化人力资本结构提升了企业全要素生产率。进一步研究发现，对于国有企业、高科技企业、政策感知能力较强以及外部环境不确定性较低的企业，《数据安全法》的实施对其全要素生产率的驱动效应更为明显。文章不仅揭示了数据安全监管赋能企业全要素生产率的内在逻辑，而且为中国政府完善数据安全政策法规体系和实现高质量发展提供有益参考。
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Abstract
In the era of the digital economy, data elements have become an important engine to promote economic growth, but they also hide data security risks while releasing dividends. Data security governance is related to high-quality economic development, and it is difficult to effectively solve digital security problems only by relying on enterprises themselves. It is urgent for the government to strengthen data security regulation. The implementation of the Data Security Law marks that the data security regulation in China has entered the stage of the rule of law. Its core goal is to resolve data security risks and safeguard high-quality economic development. However, the actual regulatory effectiveness of this law, especially its driving effect on enterprise total factor productivity (TFP), has not been clearly studied. This paper takes Shanghai and Shenzhen A-share listed enterprises as the research object, and uses the DID method to test the impact of the Data Security Law on enterprises TFP. The results show that the Data Security Law significantly improves enterprise TFP, and after a series of robustness tests, this conclusion remains valid. Mechanism testing reveals that the Data Security Law can give full play to the effect of data security governance, and improve enterprise TFP by promoting technological innovation and optimizing human capital structure. Heterogeneity analysis finds that the driving effect of the Data Security Law on enterprise TFP is heterogeneous due to enterprise characteristics and external environment constraints, as is manifested in state-owned enterprises, high-tech enterprises, enterprises with stronger policy perception capabilities, and enterprises facing lower external environment uncertainty. This paper not only helps to deepen the understanding of the impact of data security regulation on micro-enterprise behavior, but also provides a useful reference for the Chinese government to improve the data security policy and regulation system and achieve high-quality development.
国内大循环与产业链外部风险敞口
摘要 · ABSTRACT
构建新发展格局是应对国内外形势发展变化的战略选择，立足和依托国内大循环，能够有效防范化解外部风险，推动我国经济安全稳定发展。文章基于2000—2018年45个国家17个制造业行业数据，探讨了国内大循环对产业链外部风险敞口的影响及作用机制。研究发现，国内大循环能够显著缩小产业链外部风险敞口；国内大循环对产业链外部风险敞口的抑制作用在“内资主导型”“内资—外资型”国内大循环以及劳动和技术密集型行业中更为明显，但在直接与间接贸易联系中无明显差异。机制检验表明，国内大循环有利于强化国内供给、提升国内需求和优化供需匹配，进而缩小产业链外部风险敞口。拓展性分析指出，贸易网络深化与数字技术创新分别发挥“压舱石”效应和“加速器”效应，进一步强化了国内大循环对缩小产业链外部风险敞口的积极作用。研究结论为加快构建新发展格局和安全稳定、自主可控的产业链供应链体系提供重要启示。
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Abstract
Against the backdrop of multiple uncertainties including international economic and trade frictions, geopolitical conflicts, and external technological sanctions, building a new “dual circulation” development pattern with the domestic circulation as the mainstay is an important strategic choice to effectively prevent and defuse external risks and promote the secure and stable development of China’s economy. Existing literature mainly examines the influencing factors of the external risk exposure of industrial chains from the perspectives of digital economy development and changes in foreign capital structure, while relevant studies from the dimension of domestic economic circulation remain insufficient. To fill this research gap, this paper systematically explores the impact and mechanism of domestic circulation on the external risk exposure of industrial chains using panel data covering 17 manufacturing industries in 45 countries from 2000 to 2018. The results show that domestic circulation significantly reduces the external risk exposure of industrial chains. Heterogeneity analysis indicates that this inhibitory effect is more pronounced in the “domestic-funded dominated” and “domestic-foreign funded” types of domestic circulation, as well as in labor-intensive and technology-intensive industries, while no significant heterogeneity is observed in direct and indirect trade links. Mechanism testing reveals that domestic circulation helps strengthen domestic supply, boost domestic demand, and optimize supply-demand matching, thereby narrowing the external risk exposure of industrial chains. Further analysis points out that trade network deepening and digital technology innovation exert “ballast stone” and “accelerator” effects respectively, further enhancing the positive role of domestic circulation in reducing the external risk exposure of industrial chains. From the perspective of “ex-ante risk control”, this paper systematically reveals the internal mechanism through which domestic circulation affects global industrial chain security, as well as the heterogeneous characteristics across different industries, enterprises, and trade types. The conclusions not only expand the research scope in the fields of the new development pattern and industrial and supply chain security, but also provide more targeted empirical evidence for industrial chain risk warning and security construction.
工业互联网应用对企业供应链韧性的影响——基于工业互联网试点示范项目的准自然实验
摘要 · ABSTRACT
促进工业互联网与供应链深度融合是提升供应链韧性的新途径，对保障产业安全、维护经济稳定运行意义重大。文章以工业和信息化部推出的工业互联网试点示范项目为准自然实验，构建多期双重差分模型，实证检验工业互联网应用对企业供应链韧性的影响及其机制。研究发现，工业互联网应用能够提升企业供应链韧性，其作用机制在于工业互联网应用能够助力企业增强质量优势、提升营销能力、降低交易成本。异质性分析表明，工业互联网应用提升企业供应链韧性的作用在数字化应用水平高、供应商配置多元化程度高、声誉较好的企业中更显著；同时，该作用在低集中度行业、产业链下游、受公共卫生事件冲击较重地区的企业中也更显著，具有明显的纾困效应。进一步分析发现，工业互联网应用对企业供应链韧性的提升作用依赖企业库存的冗余设计，这将增加库存水平和存货管理压力；然而，库存冗余并不会降低企业全要素生产率，随着供应链韧性增强，全要素生产率也相应提高，即工业互联网应用具有提升企业供应链韧性与全要素生产率的双重效果。
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Abstract
Promoting the deep integration of the industrial Internet with supply chains is a new approach to enhancing supply chain resilience, which is of great significance for ensuring industrial security and maintaining stable economic operations. Taking the Industrial Internet Pilot Demonstration Projects launched by the Ministry of Industry and Information Technology as a quasi-natural experiment, this paper constructs a time-varying DID model to empirically examine the impact of industrial Internet application on corporate supply chain resilience and its underlying mechanisms. The results show that industrial Internet application significantly enhances corporate supply chain resilience. Mechanism testing reveals that industrial Internet empowers supply chain resilience primarily by strengthening corporate quality advantages, boosting marketing capabilities, and reducing transaction costs. Heterogeneity analysis indicates that this promoting effect is more pronounced among firms with deeper digital adoption, more diversified supplier configurations, and better reputation, suggesting that the full realization of such empowerment requires supporting conditions. Additionally, the effect is more salient for firms operating in less concentrated industries, positioned closer to the downstream end of the industrial chain, and facing severe disruptions from uncontrollable supply chain shocks, reflecting a distinct crisis-mitigation feature. Further analysis demonstrates that the effect is contingent on firms’ redundant inventory design, which elevates inventory levels and imposes pressure on inventory management. Nevertheless, the increased capital investment and inventory costs stemming from redundant design do not reduce TFP. Instead, enhanced supply chain resilience contributes to higher TFP, indicating that industrial Internet application delivers dual benefits of improved supply chain resilience and operational efficiency. This paper enriches the research on the economic consequences of industrial Internet application and the determinants of supply chain resilience, providing empirical evidence for further promoting industrial Internet application and optimizing corporate supply chain management.
数据交易所的双重属性及规则建构
摘要 · ABSTRACT
我国数据交易所采取公司制的市场主体定位，在数据流通市场中应符合竞争性的要求。在推进全国统一大市场建设的过程中，数据交易所面临制度定位与功能定位的矛盾，引发对其场内交易管理职权向场外不当扩张的担忧。为实现监管范式的转换，应当重新审视证券交易所监管制度的镜鉴意义，将看门人理论引入我国数据交易所的中介交易市场，通过更明确的内部积极义务引导场内的数据中介交易。数据交易所的内部积极义务应着力促进公平竞争并提升市场效益，安全有序地推动数据市场的培育、扩大及统一。同时，数据交易所的消极义务应作为其外部规制的约束机制，并由监管部门对义务落实情况与制度最终目标的实现程度进行评估。通过构建看门人双重属性下的双层义务结构，数据交易所可有效培育数据流通服务机构，加快推进数据要素的市场化与价值化进程，实现制度设计的预期目标。
关键词 · KEYWORDS
Abstract
Data exchanges in China are positioned as corporate market entities and should therefore meet the requirements of competition in the data circulation market. In the process of building a unified national market, however, data exchanges face a tension between their institutional design and functional positioning. China’s institutional construction of data exchanges has largely drawn on the model of stock exchanges. Yet data trading differs significantly from securities trading in terms of basic business operations, trading objects, and authority structures, giving rise to concerns that on-exchange regulatory powers may improperly expand into off-exchange transactions. In response, the regulatory paradigm for data exchanges should shift from a single model of self-regulation toward a more institutionalized paradigm of market regulation. To this end, it is necessary to re-examine the theoretical origins of the stock exchange system as a reference model and introduce the gatekeeper theory into China’s data exchange market. The rule-making framework of data exchanges should establish an internally and externally coordinated dual structure of “positive-negative” obligations, with positive obligations as the core. This structure should guide trading conduct, enhance market efficiency under fair competition, and promote the safe and orderly cultivation, expansion, and integration of the data market. The key distinction between internal positive obligations and external negative obligations lies in their respective regulatory functions. Internal positive obligations constitute the substantive core of regulation, emphasizing the self-restraint and structural optimization of data exchanges as gatekeepers of the on-exchange data factor market ecosystem. External regulation, by contrast, serves as a procedural guarantee and baseline constraint for internal obligations, reflected in the public authority’s recognition of gatekeeper qualifications, continuous supervision, and residual remedies when rules fail. External regulation should aim to ensure the implementation of internal obligations, thereby avoiding excessive public intervention in the dynamic operation of the data trading market. Accordingly, negative obligations should function as a constraint mechanism for external regulation, used to evaluate the implementation of obligations and the realization of the system’s ultimate objectives. Through the construction of this dual-layer obligation structure, data exchanges can effectively foster data circulation service institutions, accelerate the marketization and value realization of data factors, and achieve the expected goals of institutional design.
企业数据权独立成权的逻辑证成与制度设计
摘要 · ABSTRACT
数据是与传统权利客体存在根本不同属性的新型生产要素，企业数据凝聚了劳动投入与信息价值。为了调整企业数据蕴含的独特利益关系，企业数据权具有独立成权的可行性与正当性。以商业秘密保护企业数据与数字经济运行逻辑不契合，而《反不正当竞争法》则着重于规制不正当侵害企业数据权益的竞争行为。企业数据权蕴含一般民事财产利益与竞争优势利益，应得到民法与《反不正当竞争法》的协同保护。企业数据权成为一项独立民事权利后，才能得到侵权责任法的普遍性救济、基础性保护，并通过侵权过错归责原则实现权利人控制权益与外部主体行为自由之间的平衡。在个人数据、企业数据、公共数据分类确权的背景下，未来立法应当对企业数据权单独规定，并明确企业数据权的主体、客体、内容、公示、限制等问题。企业数据权属于支配权，为了避免数据垄断，衍生出新的数据形态、创造出新的数据价值的各种数据加工、整理行为，其行为主体都应当享有相应数据权。作品与数据都具有可复制性，可借鉴著作权合理使用制度来建立企业数据权合理使用制度，促进企业数据权保护与数据流通之间的平衡。
关键词 · KEYWORDS
Abstract
Data is a new type of production factor with fundamentally different attributes from traditional objects of rights. Enterprise data embodies labor input and extracts information value, making the right to enterprise data both feasible and justified as an independent right to regulate the unique interest relationships above it. Protecting enterprise data under trade secrets does not align with the operational logic of the digital economy, whereas the Anti-Unfair Competition Law focuses on regulating unfair competition behaviors that infringe upon enterprise data rights. The general civil property interests and competitive advantage interests inherent in the right to enterprise data should receive coordinated protection from civil law and the Anti-Unfair Competition Law. Only when the right to enterprise data becomes an independent civil right can it receive universal remedies and foundational protection under tort law, which regulates behaviors infringing upon enterprise data rights, thereby clarifying the scope of legally protected enterprise data rights. Moreover, the principle of fault-based liability helps balance the interests of rights holders in controlling their rights and the freedom of external entities. Blanket recognition of data rights may lead to overgeneralization of rights, while subject-based recognition of enterprise data rights helps establish a legal foundation for scenarios such as data inclusion in financial statements and data transactions. Against the backdrop of classified recognition of personal data, enterprise data, and public data, future legislation should separately stipulate the right to enterprise data, defining its subject, object, content, publicity, and limitations. Since the right to enterprise data is a type of dominion right, an enterprise’s control over the data object can be categorized into static and dynamic control, direct and indirect control, and individual and collaborative control. Given that the subject of data rights can exclusively enjoy the content of the rights, a specialized registration and publicity system for enterprise data rights should be established. To prevent data monopolies, various data processing and organization activities that create new data forms and generate new data value should all be entitled to derive corresponding data rights. Both works and data can be infinitely replicated, so the principle of fair use in copyright law can be adapted to establish a fair use system for enterprise data rights, promoting a balance between the protection of enterprise data rights and data circulation.