Documentation, Informaiton & Knowledge ›› 2025, Vol. 42 ›› Issue (5): 31-43.doi: 10.13366/j.dik.2025.05.031

• Special Topic(1): Trusted Data Space • Previous Articles     Next Articles

The Subject Composition and Constructive Characteristics of Industry Data Space Value Networks: An International Multi-Case Analysis

XIA Yikun, WANG Xue, JIANG Siqi   

  1. Research Institute for Data Management Innovation, Nanjing University, Suzhou, 215163
  • Online:2025-09-10 Published:2025-11-13
  • Contact: Correspondence should be addressed to WANG Xue, Email: wx@smail.nju.edu.cn, ORCID: 0000-0002-5560-515X
  • Supported by:
    This is an outcome of the Special Project for Interpretation of the Spirit of the Third Plenary Session of the 20th Central Committee of the Communist Party of China "Research on the Institutional Mechanisms for Building a Nationally Integrated Technology and Data Market"(2025300088)supported by a grant from Nanjing University for the Research of Party's Innovation Theory.

Abstract: [Purpose/Significance] Focusing on the industry data space value networks, this study aims to systematically analyze the subject composition, functional boundaries, and collaborative relationships within data spaces, clarify the characteristics of value network construction, and promote trusted industry data circulation through ecological thinking. [Design/Methodology] Based on ecological synergy theory, this study adopts case analysis and comparative analysis methods, selecting four typical industry cases as research objects. Through multi-case analysis and feature extraction, it summarizes the rights and responsibilities boundaries of different subjects and the construction characteristics of value networks, then identifies the practical challenges, and proposes targeted optimization strategies tailored to China's context. [Findings/Conclusion] The value networks of industrial data spaces primarily consist of six types of subjects: conveners and fund providers, operators, regulators, service providers, rule-makers, data providers and users. These networks exhibit five key characteristics: multi-stakeholder participation, collaborative interactivity, rule consensus, hierarchical progression, and value co-creation. However, there exist issues such as imbalanced stakeholder participation structures, weak cross-sector collaboration, insufficient dynamic adaptability, and unclear business models. Therefore, it is necessary for our country to enhance its approach from multiple dimensions, including strengthening comprehensive strategic planning, building linkage governance mechanisms, enhancing network resilience, and innovating business model. [Originality/Value] This research reveals the subject composition and constructive features of industry data space value networks, offering insights for fostering trusted data ecosystems grounded in value co-creation and multi-subject symbiosis.

Keywords: Industry data spaces, Value networks, Subject linkage, Ecological construction, Data circulation