With China's economic development entering a new normal, improving the quality of economic development has become the core task of transformation and development in various regions. As an important economic sector in central China, Jiangxi Province plays a leading role in optimizing and upgrading its industrial structure through the use of new quality productive forces, which is of great significance for promoting high-quality economic development in Jiangxi Province. The promotion of new quality productive forces in optimizing and upgrading the industrial structure of Jiangxi Province was studied from both theoretical logic and path perspectives, providing theoretical guidance and practical references for the development of Jiangxi Province's industries in the new era.

Taking the research hotspot of “science and technology boosting rural revitalization” as the research object, the research hotspots and development trends in this field were explored through bibliometric analysis and CiteSpace software. The results show that in recent years, the research enthusiasm for “science and technology boosting rural revitalization” has continued to rise, mainly focusing on four aspects: industrial prosperity, talent revitalization, rural governance, and common prosperity. The research content mainly includes digital countryside, smart agriculture, green agriculture, modern agriculture, rural governance, vocational education, and so on. Meanwhile, emerging fields such as science and technology courtyard, digital economy, and green finance will become the key directions for future research.

Artificial intelligence is a new driving force for promoting the high-quality development of the economy. The mechanism of artificial intelligence promoting economic development through the optimization and upgrading of the industrial structure, technological innovation, and human capital was analyzed. Based on the panel data of 12 major cities in Hubei Province from 2013 to 2022, a fixed-effects model was constructed for empirical testing. The research found that artificial intelligence can significantly promote economic development. Artificial intelligence can drive economic development through three paths: the optimization and upgrading of the industrial structure, technological innovation, and human capital. The impact of artificial intelligence on economic development has regional heterogeneity. Finally, countermeasures and suggestions are provided to better promote economic development with the help of artificial intelligence.

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.

Based on panel data from nine cities in Fujian Province, how trade between Fujian Province and ASEAN promotes industrial structure upgrading was analyzed. The empirical results indicate that increasing imports and exports to ASEAN can promote the upgrading and rationalization of Fujian Province's industrial structure. In regions with higher levels of economic development in Fujian Province, expanding trade has a greater positive impact on industrial structure upgrading. Financial support plays a positive regulatory role in the chain of expanding imports and exports to promote industrial structure upgrading. In the process of increasing exports and expanding imports in Fujian Province and ASEAN, innovation or boosting consumption are both beneficial for promoting industrial structure upgrading.

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.

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.

Using the logistics index from 2010 to 2022 and the DEA-BCC (data envelopment analysis and Banker-Charnes-Cooper) model, it is found that the static comprehensive logistics efficiency in China is 0.668, which is at a low level. Using DEA-Malmquist index method to analyze dynamic logistics efficiency, the total factor productivity is 0.981, and the overall productivity is slightly reduced. Tobit regression model was used to explore the factors affecting logistics industry efficiency, among which economic development level had a significant and weak negative impact on logistics efficiency. The degree of industrial agglomeration and the level of innovation have significant positive effects on logistics efficiency. The degree of government intervention, informatization level and opening to the outside world have no significant influence on logistics efficiency. According to the research results, some countermeasures and suggestions are puts forward to improve the efficiency of logistics industry in China, that is, to improve the level of logistics service, optimize the level of resource allocation and improve the capability of technology research and development.

Guangxi, as an important province in southwest China, has had an increasing demand for young scientific and technological talents in recent years driven by policy support and industrial transformation and upgrading. From the perspective of matching policy support and industrial needs, the optimization strategies for cultivating young scientific and technological talents in Guangxi were explored. The current situation of Guangxi's science and technology policies, industrial structure characteristics, and the current situation and dilemma of cultivating young scientific and technological talents were analyzed. Some ways are proposed to achieve talent training, including improving the policy system, optimizing the allocation of educational resources, deepening the integration of industry and education, improving practical ability training, and strengthening incentive mechanisms, in order to realize the effective docking with industrial needs. It is verified the correlation between policy support and talent training effectiveness, and can provided theoretical basis and practical reference for the training of young scientific and technological talents in Guangxi.

Taking the national advanced manufacturing clusters in the Yangtze River Delta region as a sample, the mechanism of knowledge collaboration networks on collaborative innovation performance was explored. Findings reveal that knowledge network characteristics (knowledge diversity, knowledge network density, knowledge recombination opportunities) have a positive impact on collaborative innovation performance, with knowledge absorption capacity playing a mediating role and cooperative network structural features exerting moderating effects. Specifically, network centralization and average shortest path inhibit the positive influence of knowledge network structure on collaborative innovation performance, while connectivity strengthens this positive effect. The research can provide theoretical references for enhancing collaborative innovation performance in advanced manufacturing clusters from the perspective of knowledge collaboration networks.