山东数据市场发展观察：国企先行探路，生态构建待深化

Core Insights - The article discusses the significant impact of digitalization and data as a production factor in various sectors, highlighting the emergence of data as a crucial asset in economic development, particularly in Shandong Province [1][2] - It emphasizes the challenges faced in the implementation of data asset accounting, including insufficient infrastructure, lack of active participation from private enterprises, and the need for a robust data market [3][4] Group 1: Data Asset Accounting - By 2024, data is expected to be recognized as a key asset, with 92 listed companies and 228 non-listed companies in China reporting data asset accounting [1] - Shandong Province has seen state-owned enterprises leading the way in data asset accounting, with the Shandong High-Speed Group reporting a data asset value of 3.51 million yuan and an assessed value exceeding 72 million yuan [2][3] - The reluctance of private enterprises to engage in data asset accounting is attributed to high costs, low returns, and operational complexities [2][3] Group 2: Challenges in Data Market Development - The article identifies several challenges, including a lack of active participation from enterprises, an immature data market, and insufficient infrastructure for data operations [3][4] - Shandong has established regional data trading institutions, but its trading volume of 220 million yuan is significantly lower than that of leading cities like Shenzhen and Shanghai [5][6] - The absence of a provincial-level public data operation platform hinders the development of a robust data market ecosystem in Shandong [6][7] Group 3: Data Security and Trust - Concerns regarding data security and the establishment of a trusted data space are highlighted as critical issues for the industry [7][8] - The need for a trusted data space is emphasized to ensure data can be shared and utilized securely, with various types of trusted spaces being proposed [8][9] Group 4: Revenue Distribution and Coordination - The article discusses the importance of coordinating interests across departments and levels for effective data utilization and revenue distribution [10][11] - A proposed revenue-sharing model in Qingdao suggests that 50% of the revenue generated from public data operations would be reinvested into supporting data resource management [10][11]