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论文编号：	16066
作者编号：	1120221308
上传时间：	2026/6/4 21:29:10
中文题目：	数据生态系统行动者互动机制有效性研究
英文题目：	Research on the Effectiveness of Actor Interaction Mechanisms in Data Ecosystem
指导老师：	王芳
中文关键字：	数据生态系统；行动者互动机制；召集者；数据市场
英文关键字：	Data Ecosystem; Actor Interaction Mechanism; Convener; Data Market
中文摘要：	当前我国正处于新一轮科技革命和产业变革的交汇点，数据已经成为驱动经济高质量发展的重要引擎。我国将数据列为生产要素，是对传统生产要素理论的重大突破，引发了各界广泛讨论。然而，从实践来看，当前我国数据要素市场培育面临数据流通技术不成熟，市场运行机制尚未准备就绪，政府与市场之间的关系尚未厘清等诸多挑战。尽管现有研究对数据要素和生态系统进行了广泛讨论，但主要聚焦于数据要素本身，对数据生态系统的整体性探讨相对匮乏，且相关研究忽视了行动者在生态系统中所处“位置”，对启动和协调数据要素市场的“召集者”以及其采取的互动机制关注不足。 本文以数据要素市场为分析对象，对数据生态系统中的行动者互动机制有效性展开研究。研究始于对数据生态系统相关理论梳理及数据要素市场实践调研，以此明确研究对象和研究问题。首先，通过文献调研梳理数据生态系统涉及的行动主体，采用相对客观的米切尔评分法，识别出生态系统中的关键行动者（含召集者）、重要行动者和边缘行动者。其次，遵循理论抽样思路选取杭州市数据要素市场化改革实践为研究对象，质性分析生态系统中的召集者在数据要素市场培育中采取的互动机制。最后，将上述召集者互动机制转化为影响企业数据市场行为的关键外部变量（额外性政策），引入数据企业拥有的数据资源和数字人力资源（内部可供性）两个变量，构建理论模型并提出研究假设。通过问卷调查实证检验上述互动机制的有效性。 研究发现：（1）数据要素市场是“政产学研用金”多元主体构成的数据生态系统。研究基于文献梳理了数据要素市场12类行动主体，并依据米切尔评分法将其划分为关键行动者（管理部门、公共部门数源单位、金融机构、数据供给企业、数据交易机构）、重要行动者（数据消费者、技术供应商、高校和科研院所、数据经纪人）和边缘行动者（律所、会计师事务所、个人）三类。（2）数据生态系统行动主体面临的困境以不可分解问题为主。研究遵循“知识隐藏性-交互程度”框架将行动主体面临的18种现实困境划分为可分解问题（占比16.7%）、部分可分解问题（占比27.8%）、不可分解问题（占比55.6%）三种。并根据问题类型匹配了用户社群创新模式、市场化合约模式、基于共识的层级制模式、技术制度创新模式、联盟伙伴模式和基于权威的层级制模式等治理模式。（3）政府与准公共机构在数据生态系统建设中发挥了召集者作用。基于杭州数据要素市场培育案例分析表明，由政府和准公共机构在当前阶段扮演着启动和协调数据要素市场的“召集者”角色。（4）召集者通过多样化互动机制启动和激活数据生态系统。针对平台、算法等技术工具，召集者采取平台界面搭建、基础设施共建、模型行业自建等三种互动机制，为数据生态系统的整体运作提供初始资源，也为数据主体交互和数据流通提供必要载体。针对数商等数据主体，召集者采取制度设计、动员连接、学习催化、创新刺激和冲突调解等五种互动机制，激发产品创新和供需匹配等交互行为，实现数据生态系统有效运转和开放透明。（5）召集者额外性政策工具的有效性存在不确定性。回归分析结果表明，政府作为召集者采取的政策性互动工具中，仅数据流通政策（PC）、连接动员政策（PM）稳健显著正向影响数据市场进入意愿（EI）。（6）一般行动者内部可供性是数据要素市场参与行为的核心驱动力。企业作为一般行动者，具备的企业数据资源（DS）和企业数字人力资源（HS）等可供性变量均稳健显著正向影响数据市场进入意愿（EI）和数据市场进入行为（EB）。 本文揭示了数据生态系统行动者互动机制并检验了其有效性。在理论贡献方面：（1）扩展理论适用性。拓展生态系统理论、问题解决视角、可供性等理论在数据要素市场研究中的适用性；（2）行动机制细化。细化数据生态中行动者所处“位置”，并提炼召集者与人类行动者和技术行动者互动的具体机制；（3）作用机制检验。深化数据生态系统领域的政策知识，揭示一般行动者（数据企业）数据市场进入意愿和进入行为影响因素的作用机制。在实践启示方面，（1）为当前阶段治理重点明晰思路。针对当前不同行动者面临的实践问题，划分问题类型并匹配了六种问题治理模式；（2）提供了可复制、可借鉴实践经验。通过探索性案例展示了在数据生态系统启动阶段，召集者如何启动、激活数据生态系统。（3）提供政策激励机制设计思路。当前额外性政策工具有效性存在不确定性，企业内部可供性是影响数据市场行为的核心驱动力，召集者需要根据数据生态系统变化情况不断动态调整政策工具，以形成政府和市场合力。图30幅，表31个，参考文献358篇。
英文摘要：	China is currently at the confluence of a new round of technological revolution and industrial transformation, where data has become a critical engine driving high-quality economic development. The designation of data as a element of production represents a significant breakthrough in the traditional theory of production factors, sparking extensive discussion across various sectors. However, from a practical perspective, the cultivation of China's data market currently confronts numerous challenges, including the immaturity of data circulation technologies, the insufficient preparation of market operation mechanisms, and the unresolved delineation of roles between the government and the market. Although existing research has extensively discussed data factors and ecosystems, it has predominantly focused on data factors themselves, resulting in a relative lack of holistic exploration of the data ecosystem. Moreover, related studies have overlooked the position of actors within the ecosystem, paying insufficient attention to the conveners who initiate and coordinate the data factor market and the interactive mechanisms they employ. This study takes the data market as the object of analysis and investigates the effectiveness of actor interaction mechanisms within the data ecosystem. This study begins with a theoretical review of data ecosystems and an empirical investigation of data factor markets, thereby clarifying the research object and research questions. First, through a literature review, the actors involved in the data ecosystem are identified. The relatively objective Mitchell scoring method is adopted to identify key actors (including conveners), significant actors, and peripheral actors within the ecosystem. Second, following the logic of theoretical sampling, the data market-oriented reform practice in Hangzhou is selected as the research object. A qualitative analysis is conducted to examine the interactive mechanisms adopted by conveners in the cultivation of the data market. Finally, these interactive mechanisms of conveners are transformed into key external variables (i.e. additionality policies) that influence enterprises' data market behaviors. Two internal variables—data resources and digital human resources (i.e. internal affordances) possessed by data enterprises—are introduced. Accordingly, a theoretical model is constructed and research hypotheses are proposed. The effectiveness of the aforementioned interactive mechanisms is empirically tested through a questionnaire survey. The study findings are as follows: (1) The data market is a data ecosystem composed of diverse entities. Based on a literature review, this study identifies 12 types of actors in the data market and, employing the Mitchell scoring method, classifies them into three categories: key actors (namely regulatory authorities, public sector data-providing units, financial institutions, data supply enterprises, and data trading institutions), significant actors (namely data consumers, technology suppliers, universities and research institutes, and data brokers), and peripheral actors (namely law firms, accounting firms, and individuals). (2)The challenges faced by actors in data governance are predominantly non-decomposable problems. Following the knowledge concealment and interaction analytical framework, this study decomposes the 18 practical challenges confronting these actors into three categories: decomposable problems (16.7%), partially decomposable problems (27.8%), and non-decomposable problems (55.6%). Accordingly, governance models, including the user community innovation mode, market-oriented contract mode, consensus-based hierarchical mode, technology-institution innovation mode, alliance partnership mode, and authority-based hierarchical mode, are matched to the respective problem types. (3)Government and quasi-public institutions play a convening role in initiating and coordinating the data ecosystem. Based on a case study of the cultivation of the data market in Hangzhou, it is demonstrated that, government and quasi-public institutions currently assume the role of conveners in initiating and coordinating the data market. (4)The convener initiates and activates the data ecosystem through diversified interaction mechanisms. Regarding technical tools such as platforms and algorithms, the convener adopts three methods, namely platform interface construction, shared infrastructure development, and self-building of industry-specific models. These mechanisms provide initial resources for the overall operation of the data ecosystem and serve as necessary carriers for interactions among data subjects and for data circulation. With respect to data subjects such as data traders, the convener employs five interaction mechanisms, namely institutional design, mobilization and connection, learning and catalysis, innovation stimulation, and conflict mediation. These mechanisms, which stimulate interactive behaviors such as product innovation and supply-demand matching, are aimed at enabling the effective, open, and transparent operation of the data ecosystem. (5)There is uncertainty regarding the effectiveness of convener additionality policy instruments. The regression analysis results indicate that among the policy interactive instruments adopted by the government as a convener, only the data circulation policy (PC) and the connection mobilization policy (PM) have a robust and significant positive impact on the intention to enter the data market (EI). (6)The internal affordances of general actors serve as the fundamental impetus for engaging in the data factor market. For data enterprises operating as general actors, firm-level affordance variables—including data resource (DS) and digital human resource (HS)—exert a robust and statistically significant positive effect on both the intention to enter the data market (EI) and the data market entry behavior (EB). This study reveals the interaction mechanisms among actors in the data ecosystem and examines their validity. In terms of theoretical contributions: (1) Theories applicability extension. It broadens the applicability of ecosystem theory, the problem-solving perspective, and the affordance theory in the research of data markets. (2) Refinement of action mechanisms. It details the positions of actors within the data ecology and extracts specific mechanisms for how convenors interact with both human and technological actors. (3) Examination of mechanisms. It deepens the policy knowledge in the field of data ecosystems, revealing the mechanisms through which influencing factors affect the data market enter willingness and behavior of general actors (data enterprises). Regarding practical implications: (1) Clarify the governance focus. In response to practical problems faced by different actors, it categorizes problem types and matches them with six governance models. (2) Provide replicable and referable practical experience. Through exploratory cases, it demonstrates how convenors can initiate and activate data ecosystems during their construction. (3) Offer design ideas for policy tools. Given the uncertainty surrounding the effectiveness of current policy tools and the fact that the internal affordance is a core driver influencing data market behavior, convenors need to dynamically adjust policy tools accordingly. The paper includes 30 figures, 31 tables, and 358 references.
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