In the realm of digital development, the proliferation and permeation of digital technologies into rural regions have exerted a profound influence on the political, economic, cultural, and organizational frameworks of these areas, which has catalyzed a transformative reconstruction of the rural spatial configuration in turn. Taking Lianzhang Village, a quintessential poverty alleviation site in Guangdong Province as an example, the underlying mechanisms of digitalization and its impact on the reshaping of public spaces was meticulously dissected. Findings indicate that the digital edifice can significantly facilitate the metamorphosis of rural spatial structures through the agency of digital forces, including the digital economy, digital technology, and digital infrastructure. This is realized through the application of digital operational paradigms within the realms of economic, cultural, and social spaces.The trajectory of reconstructing rural public spaces primarily involves leveraging the productive potential of these spaces to drive the digital transformation of the rural economic sector. This is achieved by enhancing the cultural gravitas and governance efficacy of these spaces, endowing rural culture with enhanced spiritual resonance and improving the convenience and openness of the inhabitants' daily lives, thereby synergistically advancing the transformation of the rural spatial structure.

The study of “production, living and ecological space” plays a significant role in optimizing national land layout, advancing ecological construction, and achieving sustainable development. Taking the central city of Lanzhou as the research object, based on POI(point of interest) data, grid division, sample square statistics, AHP(analytic hierarchy process) hierarchical analysis and GIS(geographic information system) spatial analysis techniques were used to identify and characterize the production, living and ecological spaces. The results show that the production space is concentrated in the periphery, the living space is clustered in the core area, and the ecological space is distributed in a decentralized manner.The quantity is dominated by the production and living space, the ecological space accounts for the smallest proportion, and there are very few mixed-function zones,and the four types of space all show obvious clustering characteristics. The study shows that POI data are scientific and practical in spatial identification and can provide reference for urban territorial spatial planning.

In order to realize of the Poyang Lake Eco-economic Region's “dual-carbon” goal, carbon emissions was analyzed on energy consumption, and carbon emissions from 2024 to 2035 was predicted using the logistic model. The results showed the the maximum inaccuracies between the carbon emissions predicted by the Logistic model and the actual value from 2011 to 2022 was 9.0%, and the average inaccuracies was 2.43%, which is able to fit the trend of carbon emissions in Poyang Lake Eco-economic Region. The logistic model predicts that carbon emissions in 2035 will reach 23 345.38×10⁴ t. The growth rate of carbon emissions is in a decreasing trend, from 0.85% in 2024 to 0.04% in 2035, and the carbon peak would be basically realized in 2035. The research results are of great significance in promoting the scientific development of carbon emission reduction pathway in Poyang Lake Ecological and Economic Zone.

Digital-enabled green transformation is an important path and inevitable choice to achieve high-quality development. Based on the data of Shanghai and Shenzhen A-share specialized and new “small giants” enterprises from 2013 to 2023, the impact of the digital transformation of specialized and sophisticated small and medium-sized enterprises on green technological innovation and the intrinsic mechanism of its effect were empirically examined. It is found that the digital transformation of specialized and sophisticated SMEs significantly promotes green technological innovation. This effect is more pronounced among firms in the eastern and central regions, high-level digital infrastructure firms, and high-tech firms. The mechanism analysis shows that digital transformation can promote green technology innovation by optimizing human capital structure and increasing analysts' attention. Finally, specific policy recommendations are put forward from the level of government and enterprises themselves to provide insights into the digital transformation of enterprises and the high-quality development of the economy.

The deep integration of the digital economy and real economy(DRI) serves as a pivotal strategy for driving China's high-quality economic development. Leveraging social network analysis (SNA), a DRI network was constructed using patent data from listed construction enterprises, their DRI levels were measured, and its impact mechanisms on corporate performance were investigated. Key findings include DRI significantly enhances corporate performance through dual pathways of knowledge breadth expansion and product competitiveness enhancement, with results remaining robust after addressing endogeneity concerns and rigorous robustness checks. Heterogeneity analysis reveals stronger performance improvements in high-tech enterprises, private-owned enterprises, and firms in growth/maturity stages, while stronger intellectual property protection and advanced digital infrastructure amplify these effects. Building on these insights, targeted policy recommendations are proposed to deepen DRI adoption in the construction sector.

Based on the resource-based view and dynamic capability theory, using large sample survey data from high-tech manufacturing enterprises, the mechanism and boundary conditions of the impact of digital orientation on new product development(NPD) performance was empirically analyzed. The results show that digital orientation has a positive impact on NPD performance.Organizational agility partially mediates the relationship between digital orientation and NPD performance.Top management team heterogeneity not only enhances the positive impact of digital orientation on organizational agility, but also strengthens the mediating path of organizational agility between digital orientation and NPD performance, that is, top management team heterogeneity plays a moderated mediating role. The research conclusion can provide theoretical and practical guidance for enterprises to effectively improve NPD performance under the drive of digitalization.

In recent years, high-tech enterprises have shown good performance in innovation output. Using a total of 5 418 sample data from 2021 to 2023, a regression model for empirical analysis was established to explore the impact of R&D expenses and R&D personnel on the innovation performance of enterprises. The research results show that both R&D expenses and R&D personnel have a positive impact on the innovation performance of enterprises. Heterogeneity analysis reveals that R&D expenses positively promote the innovation performance of large, medium, and small enterprises, but have no significant impact on the innovation performance of micro enterprises.

At present, the environmental costs of a large number of enterprises in China remain high. Exploring can the introduction of artificial intelligence effectively control the environmental costs of enterprises has significant importance. The financial data of Shanghai and Shenzhen A-share listed companies from 2013 to 2023 was collected to empirically test the relationship between the artificial intelligence level of enterprises and environmental costs. The research findings are as follows there is a significantly negative correlation between the introduction of artificial intelligence technology and the environmental costs of enterprises. The mechanism of action shows that the development of artificial intelligence by enterprises reduces their environmental costs through the mediating effects of alleviating financing constraints, improving the quality of internal control, and enhancing the quality of innovation. The heterogeneity analysis indicates that the impact of artificial intelligence on environmental costs varies under different enterprise scales and industry attributes.

Quantitatively assessing the incentive effect of tax incentives is of practical significance for playing the regulatory role of tax policy and promoting the development of enterprises. Taking the implementation of accelerated depreciation policy of fixed assets as a quasi-natural experiment, selecting the data of A-share listed companies in Shanghai and Shenzhen from 2010 to 2022 as samples, a multi-period double difference model was constructed to empirically test the incentive effect of tax preferential policies on enterprise growth. It is found that the policy of accelerated depreciation of fixed assets can significantly promote the growth of enterprises, and the incentive effect of this policy is heterogeneous, subject to the nature of the enterprise's equity, the nature of the industry and the size of the constraints, the growth incentive effect on non-state-owned enterprises, high-tech industry enterprises and large-scale enterprises is better. On the basis of empirical research, suggestions are proposed to further improve the tax preference policy and promote the growth of enterprises.

Under the context of China's energy powerhouse strategy and the development of characteristic new-type think tanks, focusing on the talent mechanisms of central SOE think tanks in the energy sector, a systematic analysis of their current status was conducted. The research reveals that these institutes have established a five-dimensional influence system encompassing policy, enterprises, academia, international cooperation, and society, demonstrating notable achievements in strategic support, professional capacity, and institutional innovation. However, challenges persist, including delayed pilot implementations, talent structure imbalances, and rigid incentive mechanisms. Based on comparative case studies, a three-dimensional optimization framework was proposed: structuring strategic-level collaborations through “government-industry-academia-research-application”integration to establish four-dimensional talent development objectives, designing operational mechanisms including differentiated training, market-oriented incentives, and digital governance platforms, and instituting institutional reforms such as dual-track evaluation systems and intellectual property sharing arrangements. The conclusions provide theoretical foundations and practical pathways for advancing the modernization of talent teams in energy SOE think tanks and supporting national energy security strategies.