The innovative development of the ice-snow industry economy requires reform-driven impetus, with its underlying logic rooted in industrial empowerment that stimulates new development vitality of traditional industries. Digitalization serves as a new power source for promoting industrial innovation. This study constructs a digital innovation model for the development of the ice-snow industry economy. Regression results show that subject factors, talent factors and ecological factors all exert a positive impact on the development of Jilin Province’s ice snow industry economy. Finally, the paper puts forward suggestions including stimulating the development vitality of multiple subjects in the ice-snow economy, strengthening the cultivation of digital talents for the ice-snow economy, promoting the construction of a multi-format model through digital applications, and enhancing the development dynamics of Jilin Province’s ice-snow industry economy.

As the core element of the digital economy, differences in data governance rules have become a key variable reshaping the global trade landscape. By conducting an in-depth analysis of the internal logic behind the data governance policies of the three major economies—the United States, the European Union and China—this paper draws the following findings: the United States drives global expansion with efficiency as a priority, the European Union builds a defensive system through rule export, and China explores classified and hierarchical governance amid the dynamic balance between security and development. Policy heterogeneity not only gives rise to new type digital trade barriers, but also drives the fragmentation of global rules and restructures the value chain layout of multinational enterprises. Based on this, China should establish a proactive, leading mindset for rule-making, improve the classified and hierarchical cross-border data flow management system, empower the real economy with data, and build a digital trade ecosystem that connects domestic and international markets, so as to achieve a strategic leap from a follower to a shaper in the international rule game.

Artificial intelligence (AI) technology has played a pivotal role in upgrading of supply chains. This paper investigates the application value of AI: the enhancement of efficiency, network, and resilience effects. Underdeveloped technical foundations, suboptimal data quality and the lack of security accountability entities have constrained the driving efficacy of AI. The study reveals that multi-stakeholder collaboration, refining the fiscal support, deepening data security, and promoting innovations in interdisciplinary talent cultivation could be the driving potential of AI in the digital and intelligent transformation of supply chains. 

Using the coupling coordination degree model to evaluate the level of integration between science and technology and the economy, combined with social network analysis to present the collaborative relationships among innovation entities, this study systematically analyzes the current status and core pain points of the integration of science and technology and the economy in China. It constructs a “policy-market-society” triple-driven mechanism and proposes differentiated implementation paths for the eastern innovation highlands, the central and western catching-up regions, and the northeast old industrial base. The research shows that the foundation of the integration of science and technology and the economy in China is gradually solidifying, but issues such as regional imbalance, hindered factor flow, and inefficient achievement transformation are prominent. The differentiated paths can precisely address development bottlenecks in various regions and provide practical guidance for high-quality economic and social development.

The development of the digital economy has played a significant role in improving income levels, but its impact on the structure of income has not yet been fully understood. This paper uses a simultaneous equation model to conduct an empirical analysis based on data from 30 provinces in mainland China (excluding Tibet) from 2013 to 2021. The results show that the digital economy has not had a significant impact on wage income and net transfer income, but it has a negative impact on net operating income and a positive impact on net property income. Based on the research results, the government should support the development of small and medium-sized enterprises in the digital economy and effectively improve the income structure of residents.

With the deep integration of digital technologies into industrial activities, high-tech industries have become increasingly dependent on data resources, while the efficiency of high-tech achievement commercialization remains limited.Based on theories of the digital economy and innovation economics, this study analyzes the industrialization process from the perspective of data factor allocation, drawing on high-tech industry operations and science and technology management practices, and constructs an analytical framework of “data factor allocation–technological innovation–industrialization performance.”The results show that rational data factor allocation can reduce innovation uncertainty, alleviate information asymmetry, and improve high-tech industrialization performance by optimizing collaborative structures. Accordingly, policy recommendations are proposed to improve data governance, strengthen cross-actor data collaboration, and enhance industrialization support mechanisms.

Amidst pressures from climate change, frequent disasters, and urban-rural disparity, rural system vulnerability is escalating. Enhancing rural resilience is thus a critical path to sustainable development. This study investigates the mechanism through which digital village construction, via “digital empowerment,” strengthens rural resilience in less-developed regions. It proposes a theoretical framework encompassing digital infrastructure, application, literacy, and governance to analyze the multi-dimensional (economic, social, ecological, governance) enhancement of rural resilience by digital technologies. Findings reveal that digital empowerment significantly fortifies rural adaptability, recoverability, and transformability by optimizing resource allocation, enhancing social connectivity, and improving governance efficacy. However, structural challenges persist, including a deepening digital divide, technology-supply mismatch, and high project dependency. Accordingly, this paper proposes optimization pathways: inclusive policies centered on enhancing “capabilities,” participatory technology adaptation mechanisms, and resilient governance innovation. These aim to elevate digital empowerment from “incremental” to “transformative” resilience, offering theoretical and practical insights for comprehensive rural revitalization.

Against the backdrop of digital economy development, researching the “triple-chain co-construction” mechanism of industrial chain, supply chain, and value chain in Northeast China constitutes an important path for realizing industrial transformation and upgrading. Based on the industrial development status and latest policy orientations of Northeast China, this paper proposes specific strategies for the region’s “triple-chain co-construction” from dimensions including building digital industrial platforms, upgrading intelligent logistics systems, expanding value-added links of the value chain, strengthening cross-regional collaboration, improving the policy guarantee system, and cultivating interdisciplinary talents. The research aims to provide practical guidance for Northeast China to leverage digital economy empowerment, promote in-depth integration and efficient linkage of the “three chains”, and offer practical reference for the revitalization of China’s old industrial bases and industrial collaborative development in the digital economy era.

This article explores the driving role of the digital economy in the development of new types of productive forces, emphasizing its key position in building a modern industrial system, promoting technological innovation, and improving production efficiency. Taking Shanxi Province as an example, the article analyzes how the digital economy supports economic transformation, breaks free from resource dependence, and drives the industry towards intelligent and green transformation. It also proposes a series of suggestions, aiming to enhance the supporting role of the digital economy in promoting high-quality regional development.

Under the guidance of China's national strategies of “Digital China” and “Manufacturing Power,” the digital economy has become a core engine driving high-quality regional economic development. As the country’s first comprehensive big data pilot zone, Guizhou represents a historic convergence between its advantages in digital economic development and the needs of its manufacturing industry’s transformation and upgrading [1]. This paper takes Guizhou Tyre Co., Ltd.—an exemplary case of digital transformation in traditional manufacturing— as an example to conduct an in-depth analysis of its innovative practices in achieving deep integration through the digital economy. The case demonstrates that an innovation path centered on intelligent transformation, platform based collaboration, and data value realization can effectively help traditional manufacturing reduce costs, improve efficiency, and enhance core competitiveness. It provides a valuable practical model for promoting high-quality development in manufacturing industries in Guizhou and other similar regions in Western China [2].

Under the background of the global industrial digital and intelligent transformation and the in-depth advancement of China’s “Manufacturing Powerhouse” strategy, the integration of the manufacturing industry and the digital economy has become a core path for regional industries to break through bottlenecks and achieve high quality development. As China’s first national big data comprehensive pilot zone, Guizhou, leveraging its advantages in digital infrastructure and the transformation needs of its manufacturing sector, has carried out numerous practices to integrate the real and digital economy. This paper systematically sorts out the current status of the integration of Guizhou’s manufacturing industry and the digital economy, and finds that it still faces problems such as gaps in the application of digital technologies, an underdeveloped integration ecosystem, a shortage of professional talents. Corresponding suggestions are put forward to provide reference and guidance for Guizhou’s manufacturing industry, so as to break through the obstacles and build a benchmark for manufacturing in western China.

This article takes the development of the regional digital economy industry as the research object. Based on defining the connotation of the digital economy industry, it systematically organizes the technological iteration and market expansion trends of its key sub-sectors, as well as the differentiated development patterns of key regions in our country. The research aims to clarify the key logic of regional digital economy industry development, providing theoretical references and practical guidance for optimizing factor allocation and promoting high-quality industrial development.

The digital economy profoundly reshapes the traditional pattern of factor allocation and has become a key driving force in the formation of new-quality productivity. Centering on factor allocation efficiency, this paper analyzes the impact pathways of data factors, platform mechanisms, and digital technologies on the allocation of labor, capital, and technological resources, and constructs an analytical framework covering basic impact mechanisms, changes in key areas, real-world obstacles, and optimization pathways. Empirical methods are used to verify that the digital economy has a direct effect, mediating effect, and threshold effect, which significantly promote new-quality productivity. Optimizing digital infrastructure and data market mechanisms will effectively enhance factor mobility and collaborative efficiency, thereby driving high-quality development.

China, among the world’s fastest-growing digital economies, has accumulated a massive stock of data, which has been formally designated as a “factor of production.” Capitalizing these data assets is now pivotal for unlocking their value and sustaining digital-economic growth. This study examines the practices of listed Chinese firms in data-factor capitalization. Drawing on firm-level evidence, we show that although early progress has been achieved in recognizing data on balance sheets, persistent challenges remain in rights confirmation, valuation, market circulation, and cross industry penetration. To foster the sound capitalization of data factors, future efforts must simultaneously refine policy and regulatory frameworks, harmonize technical standards, advance technological innovation, and cultivate specialized talent.

In recent years, private enterprises in Jiangsu counties have achieved remarkable results in policy support, digital infrastructure, and industrial chain upgrading through intelligent transformation, digital transformation, and industrial chain collaboration. They have gradually established a relatively complete and mature digital economic development ecosystem. However, these enterprises still face challenges such as high costs of digital transformation, shortage of digital technology talents, and difficulties in data security and privacy protection. This study explores the high-quality development paths of private enterprises in county areas from multiple aspects such as digital transformation, innovative development, and talent cultivation, with the aim of providing useful references for the high-quality development of private enterprises in county areas of Jiangsu Province and other regions.