Digital News

　　The National Data Resource Survey Report (2024) reveals that China continues to strengthen its advantage in the scale of data resources, while steadily advancing the development and utilization of these resources. Various entities are accelerating their investment in artificial intelligence (AI), further speeding up the marketization and value realization of data elements. In the context of the rapid growth of the digital economy and the rising value of data elements, every link of data elements, from production and storage to computation, circulation, and application, is further unleashing its multiplier effect on economic and social development. The in-depth integration of massive data resources with next-generation information technologies such as AI, applied to a wide range of real-world scenarios, can significantly boost the allocation efficiency of traditional elements. It also drives market vitality, fosters social innovation, and strengthens the resilience and sustainability of economic growth, providing fresh momentum for economic growth and creating new competitive advantages for the country on the global stage.

　　I. Synergy Across Multiple Stages of Data Elements Boosts Economic Efficiency

　　According to the National Data Resource Survey Report (2024), China generated 41.06 zettabytes (ZB) of data in 2024, marking an increase of 25% year on year. The total data storage reached 2.09 ZB, growing by 20.81% year on year, with a storage utilization rate of 61%. This substantial growth in data production, along with the steady increase in storage capacity, clearly highlights the thriving development of these two key pillars of data elements. As a key production factor in the digital economy, the value of data elements depends on the dynamic interaction of three key stages: production, storage, and circulation. Each stage not only independently drives regional economies but also, through synergies, reshapes the drivers and pathways of economic growth.

　　A team led by Academician Li Jun from the Shanghai Center for Mathematical Sciences at Fudan University developed a statistical model based on provincial panel data to quantify the contribution of inter-provincial data flow to economic growth. Focusing on regional GDP trends from 2023 to 2024, the study achieved significant breakthroughs in empirical analysis using methods such as multiple regression and structural equation modeling. On the one hand, the regression model quantified the contribution of inter-provincial data flow to economic growth, highlighting its role in driving regional economic growth. On the other hand, the structural equation model provided an in-depth analysis of the direct and indirect effects, as well as the transmission pathways between the different stages of data elements—such as production, storage, and circulation—and regional GDP, offering a comprehensive interpretation of the synergy mechanism and complex interactions among these stages.

　　The study shows that data production, storage, and interaction all significantly boost regional GDP growth, with data interaction (circulation) playing the most prominent role. The structural equation model highlights data interaction as the central hub of the digital economy, connecting the outcomes of data production and storage while fueling regional economic development.

　　(I) Data Production

　　Data production forms the starting point of the value chain, with its primary role being the conversion of raw information into valuable data assets. In the digital economy era, data resources are often dubbed the “new oil.” The significant growth in national data production in 2024 has fueled emerging economic activities, including data collection, generation, and processing, all of which contribute to GDP growth. Data indirectly empowers the economy in two main ways. First, the large-scale, diverse data accumulated during the production phase can be reused by upstream and downstream industries, driving algorithm optimization and model iteration. Furthermore, by collaborating with other elements, the data production stage creates multiplier effects that enhance efficiency and foster innovation. This accelerates the emergence of new technologies, models, and business formats, with spillover effects into industries such as manufacturing, agriculture, and services, continually injecting fresh momentum into regional economies. Second, businesses streamline their operations by analyzing production data in real time, shifting from traditional experience-based decision-making to data-driven decision-making. This approach not only minimizes trial-and-error costs and resource misallocation but also improves decision-making and drives value creation.

　　(II) Data Storage

　　According to the National Data Resource Survey Report (2024), China’s total data storage is on the rise, highlighting the increasing economic influence of data storage. Data storage, a critical cornerstone of the digital economy, has its infrastructure and operations deeply integrated into traditional economic indicators. From land leasing and equipment procurement to energy consumption, the development and operation of large-scale data centers and cloud platforms not only stimulate investments in upstream and downstream industries such as equipment manufacturing, energy, and construction, generating a significant fixed asset investment effect, but also convert fragmented data resources into manageable data assets, fostering value-added services like data storage and cloud computing. Meanwhile, centralized storage and cloud hosting help reduce data redundancy and management costs, allowing small and medium-sized businesses to access storage services more affordably. This, in turn, frees up more funds for research, development, and market expansion. Additionally, by establishing unified storage standards and security frameworks, the trust and usability of data assets across society can be enhanced, which encourages greater willingness to share data across industries and regions, facilitating the broader flow of data elements.

　　(III) Data Circulation

　　In the circulation stage, data, as a tradable commodity, is priced and exchanged through data trading platforms or markets. This directly generates trading volumes and service fees, which are classified under the tertiary industry, thereby driving value-added growth in the service industry. Data circulation also extends the reach of data products to a broader range of application scenarios, creating market-scale effects. This, in turn, generates new service demands in areas such as data analysis, consulting, and application development, further boosting the output of the regional service sector. As the circulation scale grows and more participants get involved, data circulation efficiency increases. This sparks innovative combinations of different datasets, creating a positive feedback loop that further enhances the role of data in driving industrial structural upgrades.

　　(IV) Synergy and Interaction among Various Stages

　　The production, storage, and circulation of data each play a significant positive role in driving regional economic growth, with the synergy and interaction among these stages creating a multiplier effect. Data interaction and circulation serve as the core pillars of the digital economy, connecting the results of data production and storage while fueling regional economic development. Increased data interaction can improve the allocation of elements and enhance production efficiency, thus driving higher demand for storage and fostering innovation in storage technologies. Meanwhile, a positive feedback loop forms across the stages, that is, “circulation drives production—production fuels storage—storage boosts circulation.” The feedback from market pricing in data circulation helps steer production strategies, while real-time data collection during production drives upgrades in storage technology. As storage technology advances and costs decrease, the size of trading further expands. The synergy among the three stages of data elements can generate exponential returns and bolster the economy’s resilience to shocks, driving greater economic efficiency by continuously unleashing the vitality of data elements. As the scale of national data resources continues to grow, the synergy among the three stages will become more prominent, positioning them as a crucial engine for promoting high-quality economic development.

　　II. Highlighting the Value of Data Elements, Driving Regional Economic Growth

　　In the digital age, inter-provincial data flow has emerged as a key driver of regional economic growth. As a new production factor, data is shaping a new paradigm for regional economic development. By breaking down geographic barriers and redefining resource allocation rules, it overcomes the physical constraints and structural limitations of traditional growth models. This facilitates more efficient flows of resources while promoting industrial collaboration and the diffusion of innovations, ultimately promoting steady economic growth and optimizing the economic structure.

　　(I) Breaking Down Geographical Barriers and Reshaping Economic Spatial Patterns. The cross-domain flow of data elements has challenged the traditional logic of “location determinism.” In conventional economic activities, geographical distance is a natural barrier to the movement of elements. However, inter-provincial data flow enables economic entities across different provinces to engage within a unified “digital marketplace,” lowering transaction and information search costs across provinces. This significantly facilitates the free flow of data elements on a larger scale, thereby strengthening the depth and reach of the national integrated market. Meanwhile, information asymmetry often exacerbates regional development imbalances. However, inter-provincial data flow, with its zero marginal cost transmission in virtual space, enables remote areas to access the technological networks and market systems of more developed regions without the need for physical migration. This not only enables the timely transfer of industrial experience and technical standards from developed to underdeveloped regions, fostering the reverse diffusion of industrial factors and supporting the national digital transformation, but also mitigates geographic disadvantages by data connection. This allows each region to cultivate a unique competitive advantage based on its data resources, driving the shift of regional economies from imbalanced concentration to collaborative distribution. By leveraging the flow of data elements to build value exchange channels across geographical spaces, we can overcome the geographic constraints of regional labor divisions, facilitating the transformation of economic space from “gradient differences” to “network nodes.”

　　(II) Blurring Industry Boundaries and Accelerating the Diffusion of Innovations across Regions. The universal nature of data elements makes them a “super connector” connecting different industries. Supported by the flow of data, traditional industries such as finance, logistics, energy, and manufacturing can seamlessly integrate with digital sectors, establishing a new model of “data + physical” integration. This fosters an industry community linked by data, boosting the marginal productivity of all elements and driving the overall value growth of the industry chain. The industry chain is transitioning from vertical integration to a networked, interconnected model, generating compound value where “ one plus one is greater than two.” This amplifies the exponential value-added effect of industry data in cross-domain circulation, making regional economic competitiveness increasingly reliant on the ability to integrate industry data, rather than on the size of individual industries. Additionally, the aggregation and sharing of data across provinces can generate powerful network effects. The larger the data volume and the more diverse the data types, the more robust the support for algorithm optimization and model training. This, in turn, attracts more participants to engage in data exchange, creating a virtuous cycle that ultimately leads to a multiplication of industry innovation capabilities. When provincial regions develop data-driven innovation clusters, their technologies and experience can rapidly spill over to neighboring and surrounding areas through inter-provincial data channels. This accelerates industrial upgrades and the spread of emerging business models, thereby boosting the regional technological spillover effect and growth potential.

　　(III) Enhancing Economic Resilience and Building a Risk Resistance System. The cross-domain allocation of data elements provides regions with diverse needs and sources of supply, strengthening the system resilience of regional economies. In supply shock scenarios, inter-provincial data flow offers real-time visibility into key nodes of the industrial chain, allowing businesses to swiftly switch to backup suppliers or adjust production plans. In the face of demand fluctuations, cross-regional consumer data analysis enables precise market trend forecasting, helping avoid overcapacity and resource misallocation. Additionally, when a region faces external shocks, its economic functions can be shifted to other nodes through data migration, establishing a “decentralized” risk-buffering mechanism. This fundamental boost in risk resistance enhances the overall resilience and sustainability of regional economic development.

　　III. Future Outlook of Data Elements Driving Economic Growth

　　The core role of data elements in driving economic growth is becoming increasingly evident. However, the realization of their full value still faces challenges, such as technical bottlenecks that hinder the marketization process, as well as regional fragmentation and conflicting rules within the market ecosystem. To address these issues, a comprehensive approach involving institutional, technological, and market measures is required. From a systemic perspective, these barriers can be overcome, unlocking the full potential of data elements to foster higher-quality and more sustainable growth.

　　Looking ahead, data elements, propelled by both institutional innovation and technological breakthroughs, will gradually transition from being a “resource” to an “asset” and ultimately to “capital.” They will evolve into a new type of production factor that is measurable and tradable, promoting the shift of the growth logic from “factor accumulation” to “intelligent collaboration.” The spatial pattern will transform from “geographical constraints” to “digital-physical integration,” driving a qualitative leap in total factor productivity driven by algorithms and computing power, and fostering a cross-domain, interconnected “digital economy.” Driven by data elements, economic development will continue to grow in scale while increasing complexity, strengthening resilience, and achieving balanced growth in well-being for all, opening new pathways for sustainable development in human society. (Text | Li Jun and Wang Tiandong, Shanghai Center for Mathematical Sciences, Fudan University)