科学学与科学技术管理

科学学与科学技术管理 ›› 2024, Vol. 45 ›› Issue (04): 157-172.

• 创新战略与管理 • 上一篇    下一篇

数据要素市场发展影响因素组态分析 ——基于多中心治理的视角

  

  1. 1. 中国科学院大学 经济与管理学院，北京 100190；2. 天津大学 管理与经济学部，天津 300072
  • 收稿日期:2023-08-25 出版日期:2024-04-10 发布日期:2024-04-28
  • 通讯作者: 石焱文，syw_huohuo@tju.edu.cn
  • 作者简介:于清（1976— ），男，汉族，天津人，中国科学院大学经济与管理学院博士研究生，天津市旅游（控股）集团有限公司党 委书记、董事长，研究方向：金融学、数据要素；石焱文（1997— ），男，汉族，重庆人，天津大学管理与经济学部博士研究生，研 究方向：数据要素；孙可欣（2000— ），女，汉族，山东潍坊人，天津大学管理与经济学部硕士研究生，研究方向：数据要素；张兮 （1982— ），男，汉族，安徽淮北人，天津大学管理与经济学部教授、博士生导师，研究方向：数据要素、知识管理、人工智能、机 器行为学。
  • 基金资助:
    国家自然科学基金项目（72241432）

Configuration Analysis of Influencing Factors on the Development of Data Factor Markets: A Perspective Based on Multi-Center Governance

  1. 1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;2. School of Management and Economics, Tianjin University, Tianjin 300072, China
  • Received:2023-08-25 Online:2024-04-10 Published:2024-04-28

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摘要： 随着数字创新和传统产业的数字化转型，数据要素市场的发展变得至关重要，其可以重塑产业体系、推动关键技 术突破，从而助力中国式现代化的实现。然而，数据要素市场的发展面临着特殊和复杂的治理挑战，需要建立独特的治 理体系以促进数据要素的安全和高效流通。目前，对于影响数据要素市场发展的关键治理因素及其作用机制的研究仍 然不足，缺乏综合的理论分析框架来揭示不同治理因素之间的协同作用。以中国大陆31个省市自治区数据要素市场发 展情况为例，基于多中心治理理论框架梳理政府机制、市场机制、公众参与机制三个维度的 6 个前因变量条件，应用模 糊集定性比较分析（fsQCA）方法探究影响区域数据要素市场发展水平的条件之间的联动效应及其路径选择，以期因地 制宜地提升各区域数据要素市场发展水平。结果表明，政府机制、市场机制和参与者机制的协同作用可以形成4种类型 的高数据要素市场发展水平的条件组合。

关键词: 多中心治理理论, 数据要素市场治理, 数据要素市场, 定性比较分析, 组态分析

Abstract: The rise of the data factor market plays a crucial role in China's path to modernization, with its development poised to reshape industrial ecosystems and facilitate the achievement of modernization goals. The unique characteristics of data factor, such as non-competitiveness, externality, replicability, and measurability, dictate the special complexity of governing the data factor market, needing the establishment of unique governance mechanisms to ensure the secure and efficient circulation of data factor. Due to the involvement of diverse data types, domains, and scenarios, a singular management approach falls short of covering its diversity, thus requiring industry-driven integration. Additionally, the multitude of stakeholders in the data factor market makes it challenging for a single governing body to address public issues adequately. Moreover, widespread support for governance principles may be challenged, leading to potential power imbalances that could harm the interests of other participants. However, governing the data factor market is a complex endeavor involving multiple stakeholders, stages, and levels, and analyzing it solely from a single governance dimension is insufficient. Currently, there is a lack of a comprehensive theoretical framework to reveal how different governance factors interact synergistically and influence the development of the data factor market. Through exploring the development trajectory of the data factor market from a configuration perspective, focusing on the theoretical framework of multi-stakeholder integrated governance and the combined effect of governance factors in driving market development. It aims to uncover the synergistic mechanisms of multi-dimensional governance and promote high-quality development tailored to local conditions, fostering a fair, competitive, and well-regulated market environment.It is not only an important practical issue but also a scientific problem in urgent need of resolution. Drawing on existing research and integrating polycentric governance theory, the study employs fuzzy set qualitative comparative analysis (fsQCA) to reveal the path choices of data factor market governance in different regions of China, answering two key questions: what are the governance mechanisms of the data factor market, and what governance paths drive its development? By addressing these questions, the study provides theoretical support for the complex governance mechanisms and logical relationships underlying the data factor market. The findings show that government, market, and public participation factors alone cannot constitute necessary conditions for an important level of data factor market development, emphasizing the need to balance multiple factors simultaneously. Furthermore, there are six paths to enhance data factor market development, reflecting the importance of multi-stakeholder collaborative governance. Finally, market mechanisms appear as core influencing factors across all paths toward high development levels, highlighting their critical role in polycentric governance. The conclusions offer practical insights into the design and formulation of governance and regulatory schemes for the data factor market. Firstly, governance of the data factor market should focus on the comprehensive balance and synergistic effects among government, market, and public participation factors. Secondly, market mechanisms play a crucial role in data factor market governance, causing a focus on their construction. Lastly, the choice of governance path for the data factor market should be tailored to local conditions, considering regional economic development, business environments, and platform construction.

Key words: polycentric governance theory, data factor market governance, data factor market, qualitative comparative analysis, configuration analysis

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