General purpose technologies (GPTs) exhibit strong externalities and innovational complementarities. Their diffusion within supply chains and impact on the technology ecosystem are of significant interest to both industry and academia. Based on the resource dependence theory and absorptive capacity theory, the nonlinear effects of leader firms' GPT innovation on the technological complementarity between leader firm and its supply chain partners was examined. It also explores the boundary conditions of these effects. Analyzing panel data from 1,405 firm-year observations of 145 biopharmaceutical firms from 2010 to 2019, the findings reveal that an inverted U-shaped effect of GPT innovation performance on the technological complementarity between leader firm and its supply chain partners.Within the supply chain, partners' capability in GPT innovation positively moderates this inverted U-shaped relationship.

Data factor allocation is an important driving force of enterprise digital technology innovation, and is gradually regarded as the core production factor of new quality productivity because of its significant multiplier effect and innovation engine. Taking enterprise data factor allocation as the starting point, listed manufacturing enterprises from 2011 to 2022 were selected as samples to empirically study the relationship between data factor allocation and enterprise new quality productivity, and the intermediary mechanism effect was studied from the two dimensions of digital technology innovation quantity and quality. It is found that data factor allocation of manufacturing enterprises can effectively promote the improvement of new quality productivity of enterprises, especially for state-owned enterprises, high-tech enterprises and the eastern region. The mechanism effect test shows that data element allocation can improve the new quality productivity of enterprises through the “incremental quality improvement” effect of digital technology innovation. In order to promote the formation of new quality productivity, it is suggested that manufacturing enterprises actively integrate the “data factor x” action, improve the level of data factor allocation, promote the synergy between data and technology factors, and promote the double improvement of the quantity and quality of digital technology output.

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.

Methods such as literature review, logical analysis, and SWOT (strengths, weaknesses, opportunities, threats) analysis were used to conduct a systematic examination of the development of sports tourism in Guiping City, aiming to explore its strengths and weaknesses while proposing feasible countermeasures. Through SWOT analysis, it is found that Guiping's advantages including strategic transportation positioning, abundant tourism resources, and rich historical heritage. However, challenges persist in inadequate understanding of sports tourism and insufficient market development expertise. Opportunities arise from contemporary demands for integrated development, supportive policies, and digital-intelligent empowerment, while threats include ecological-environmental conflicts and homogeneous competition from neighboring cities. Development strategies for Guiping's sports tourism are proposed, including the rational integration and development of sports tourism resources, adopting a “sports + tourism” oriented approach citywide, cultivating interdisciplinary management professionals, creating an eco-sports tourism brand with local characteristics, and enhancing governmental support and policy reinforcement.

The high-quality development of the sports goods manufacturing industry serves as a significant driver for building a sports powerhouse. Based on the summarization and interpretation of the connotation of high-quality development in sports goods manufacturing, an evaluation system was constructed using the entropy method. The evaluation system encompasses five dimensions, industry scale, industrial quality, innovation level, structural optimization, and green development along with 12 measurement indicators. Utilizing these indicators, the high-quality development level of the sports goods manufacturing industry in Henan Province was measured, and it is compared with that of 14 other provinces, including Fujian, Jiangsu, Zhejiang, and Guangdong. Building on this analysis, recommendations are proposed to enhance the high-quality development of the sports goods manufacturing industry in Henan Province.

In recent years, the rapid development of digital new quality productivity has given rise to the smart transportation industry chain. Taking the resilience of the smart transportation industry chain as the research object, its resilience connotation and influencing factors were defined. The OSM(objective-strategy-measurement) model was employed to construct a diagnostic index system for industry chain resilience from three dimensions: resistance, transformation, and recovery capabilities. “G1+CRITIC”(order relation+CRITeria importance through intercriteria correlation) information entropy diagnostic model was proposed for diagnosing industry chain resilience. Data from 2015 to 2024 of Jiangsu Province was selected for empirical analysis. The results indicate that the level of resilience in the smart transportation industry chain mainly depends on the recovery capability of the industry chain. The diagnostic model can effectively evaluate the resilience level of the industry chain and identify weaknesses. Based on the diagnostic results, precise measures to solidify and strengthen the industry chain can be proposed.

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.

Exploring the coupled coordination between regional economic high-quality development and ecological environmental protection is the basis for integrating the promotion of high-quality development and high-level ecological protection. Based on the data of Heilongjiang Province from 2010 to 2022, the coupling coordination model and decoupling model were used to measure the coupling coordination degree and decoupling index between the two systems. The results show that the index of high-quality economic development in Heilongjiang province shows a fluctuating upward trend, and the index of ecological environmental protection steadily recovers after experiencing a significant decline. The degree of coupling and coordination between the two systems generally shows a rising trend, but there is still a gap with the state of high-quality coupling and coordination. Heilongjiang Province has experienced the decoupling state transition of “strong negative decoupling-expansive negative decoupling-weak decoupling” at various stages, and the decoupling state is great, while only a few years of each prefectural-level city have reached the ideal decoupling state. Based on the conclusions, countermeasures are proposed to promote the synergistic development of regional economic quality and ecological environment.

Based on data from 13 cities in the Beijing-Tianjin-Hebei Region from 2015 to 2022, an integrated evaluation system was constructed to assess urban development comprehensively across subsystems such as environmental quality, economic scale, social progress, and scientific and technological innovation. The coupling coordination degree model was then employed to measure the coordination of urban development, while the LMDI(logarithmic mean Didier index)model is used to quantitatively assess the contributions of these subsystems to overall coordination. The research results indicate that from 2015 to 2022, the overall development level of the Beijing-Tianjin-Hebei Urban Agglomeration has shown a steady upward trend, reflecting continued progress in economic, social, and technological aspects across cities in the region. However, significant spatial gradients persist in the development levels among these cities. Core cities like Beijing and Tianjin maintain a leading position in overall development, while cities farther from the core area lag behind, leading to a relatively differentiated development landscape within the region. In addition, the degree of coordination of urban development has improved, but the differences in the coordination of development among various cities are still significant. Among them, scientific and technological innovation is the main driving force for the coordinated development and changes of the Beijing-Tianjin-Hebei Urban Agglomeration, while environmental quality is still a key bottleneck restricting coordinated development and has the lowest contribution to coordinated development and changes. Finally, recommendations for optimizing the coordinated development of cities are proposed, including enhancing the radiative influence of core cities, promoting cross-regional interconnectivity, prioritizing innovation resource allocation, and strengthening cooperation in environmental protection and governance.

Based on the data of Shanghai and Shenzhen A-share listed companies from 2011 to 2022, a two-way fixed effect model was used to study the impact of digital transformation of enterprises in the Guangdong-Hong Kong-Macao Greater Bay Area on new quality productivity. The results show that the digital transformation of enterprises has significantly improved the level of new quality productivity. Mechanism-wise, the digital transformation of enterprises further promotes the development of new quality productivity by optimizing human capital, enhancing innovation quality, overcoming financing constraints, and broadening international perspectives. Heterogeneity analysis indicates that non-state-owned enterprises and high-tech enterprises perform more outstandingly in terms of improving new quality productivity in Guangzhou and Shenzhen.