Mapping China’s digital transformation: a multilayer network analysis of technology diffusion in manufacturing

Why digital technology spread matters

Across the world, factories are being quietly rewired by software, sensors, and data. China, as a major manufacturing power, is investing heavily in these digital tools, yet many plants still struggle to use them fully. This article asks a simple but vital question: how exactly do digital technologies spread through China’s manufacturing system, and who or what shapes their journeys from lab to shop floor?

Following the trails of new ideas

To answer this, the authors track more than 4.5 million patents related to digital technologies used in Chinese manufacturing between 2000 and 2024. They build three connected maps: one shows how patents cite one another, another shows how organizations such as firms and universities pass ideas between them, and a third shows how knowledge flows between cities. Using these multilayer maps, they identify the strongest “main paths” of diffusion and then apply statistical models to uncover why certain routes become highways for innovation while others remain side roads.

Key routes of digital change

The patent map reveals 14 major paths where digital technologies have developed and spread. Many of the busiest paths center on image recognition, deep learning, and computer vision applied to tasks like vehicle detection, quality inspection, and multimedia services. Others follow display circuits, exoskeleton robots, blockchain security, and new materials for batteries and steel. The authors measure the speed, breadth, and depth of diffusion along each path. Image recognition and object detection stand out: they spread quickly, connect to many other patents, and are deeply woven into industrial use. By contrast, some material and energy technologies move more slowly and touch fewer fields, suggesting that integrating digital tools with heavy industry is harder than wiring up information-based services.

Who connects science and industry

When the focus shifts from patents to organizations, a clear pattern emerges. Universities sit at the heart of the network, acting as major bridges between different firms and regions. Although they hold fewer nodes than companies, their positions in the network give them far greater influence on how knowledge travels. Companies frequently build on university patents, and universities in turn learn from industrial inventions. The analysis shows that organizations with rich, diverse knowledge portfolios and strong collaboration ties are most likely to lie on the main diffusion paths. Diversity gives them more raw material for creative combinations, while intense collaboration positions them as hubs that others repeatedly connect to.

Where innovation clusters and where it lags

The city-level map shows that digital manufacturing in China has a strong “core and periphery” pattern. Beijing, Shanghai, Shenzhen, Guangzhou, and Hangzhou act as powerful hubs, with dense two-way flows of technology among them. Many other cities sit on the edges of this structure, linked weakly or not at all. Interestingly, the study finds that cities with very broad and similar technology portfolios are less likely to form the main diffusion routes. Instead, successful diffusion between places depends on focused strengths and complementary know-how. In developed eastern regions, the key driver is the ability to recombine different types of knowledge, while in less developed western regions diffusion depends heavily on tapping into a few central technological hubs.

Different rules for universities, firms, and regions

By comparing universities and firms directly, the authors show that they follow different “logics” when spreading digital technologies. Universities thrive on variety: they connect distant fields, fill structural gaps in the network, and experiment across boundaries. Firms, guided by market pressure and risk, prefer to build around proven, high-value technologies and partners they already resemble. A similar split appears across regions. Eastern coastal areas push forward by mixing diverse knowledge combinations, whereas western regions rely on links to strong core players, and central regions have yet to form a stable pattern. These findings suggest that digital transformation depends not just on how much knowledge exists, but on how it is structured and who does the connecting.

What this means for the future

For a lay reader, the main message is that digital innovation does not spread automatically once a technology is invented. Instead, it moves along a layered web of patents, organizations, and cities shaped by collaboration, diversity, and geography. The study concludes that policy should support universities as bridge builders, encourage firms to combine different kinds of knowledge without losing focus, and design regional strategies that play to local strengths while linking peripheral areas to core hubs. In short, successful digital transformation in manufacturing depends on nurturing the right connections so that valuable ideas can travel, combine, and take root where they are needed most.

Citation: Ren, J., Zhou, Y., Yang, Y. et al. Mapping China’s digital transformation: a multilayer network analysis of technology diffusion in manufacturing. Humanit Soc Sci Commun 13, 626 (2026). https://doi.org/10.1057/s41599-026-07070-w

Keywords: digital technology diffusion, China manufacturing, innovation networks, technology policy, universities and industry