科技创新和产业创新深度融合的时空演化特征及影响因素研究

The development of sci-tech parks (STPs), as the spatial carrier of urbanization and the growth pole of the innovation economy, cannot be separated from the integration of the three key elements of “industry”, “city”, and “innovation”. This study selects the Hangzhou West Hi-Tech Corridor, which represents the forefront of development practice of China’s STPs and which is a high-quality model with highly integrated “industry–city–innovation” functions, as a case. By using multi-source data, such as geographic information and the point of interest (POI), and research methods, such as the Shannon entropy index and quadratic curve regression, this study examines the influence of “industry–city–innovation” functional mixing on the innovative development of STPs, and explores the optimal mixing degree interval. The results show that the mixing of “industry–city–innovation” functions can promote the STPs’ innovative development, to a certain extent, in the spatial design of urban planning. However, higher mixing is not always better, and excessively high mixing may inhibit innovative development. The optimal functional mixing degree conducive to the STPs’ innovative development is in the range of 0.14 to 0.16. This study is an effective application of the “industry¬–city–innovation” integration theory, provides a constant source of power for urban innovative development, and acts as a reference for future new cities and STPs.

Accurate understanding of the spatial and temporal development of the agglomeration of green high-tech industries holds significant importance for the scientific formulation of policies promoting industrial innovation and development. This has attracted increasing attention from scholars. Utilizing nearly a decade's worth of statistical data on China's green high-tech industries, this paper employs methods from spatial geography and other disciplines to analyze the temporal and spatial variations, as well as the agglomeration characteristics of these industries in China. A comprehensive analysis of the development levels of China's high-tech industries and their sub-sectors is conducted through calculations of spatial Gini coefficients, industrial concentration ratios, location quotients, and coefficients of variation.Results indicate that the four key indicators of the development of China's major high-tech industries, namely the number of enterprises, employment figures, operating income, and profits, exhibit linear growth trends. Overall, the agglomeration level of the industry shows a fluctuating downward trend. The regional agglomeration level follows a gradient distribution trend of "eastern region - central region - western region - northeastern region," with a decreasing concentration trend. Regional disparities in the agglomeration level of industries evolve over time, with an increasing concentration in the western and central regions, and a decreasing concentration in the eastern and northeastern regions. From a provincial perspective, Guangdong and Jiangsu provinces stand out with significantly higher levels of development in high-tech industries.Furthermore, distinct differences are observed in the development processes of four typical industries. The agglomeration levels, ranked from high to low, are as follows: computer and office equipment manufacturing, electronic information and communication equipment manufacturing, medical device manufacturing, and pharmaceutical manufacturing，the development of the four types of industries has undergone certain transfers and optimizations.

New-quality productivity and industrial structure upgrading has become a primary area of concern with respect to regional economic transformation and sustainable development. Based on static panel data of 108 prefecture-level-and-above cities in the Yangtze River Economic Belt from 2013 to 2022, the projection pursuit model, coupling coordination degree model, and obstacle degree model were used to study the spatiotemporal patterns and key obstacle factors in the coupling of new-quality productivity and levels of industrial upgrading. Results show the following: (1) The average coupling coordination degree increased from 0.42 in 2013 to 0.53 in 2022, exhibiting a three-stage trend of “initial advancement, rapid growth, and high-level fluctuation”. (2) Regionally, a gradient pattern of “downstream leading, midstream following, and upstream catching up” persists, but regional gaps have narrowed significantly. (3) Spatially, the coupling coordination level shows a pattern of “high in the east, low in the west, led by the core, and breakthrough in the local area”, with significant positive aggregation characteristics. (4) The main obstacle factors across the entire area include digital patents (7.03%), green patents (7.03%), and the number of high-tech enterprises (6.96%), but the weights of the obstacle factors vary greatly across different areas. These findings provide scientific support for green transformation, regional integration, and sustainability-oriented industrial policy design in the Yangtze River Economic Belt.

Disparities in the development of regions of the PRC have not lost their relevance since the formation of the state and to this day. Central China became the object of regional policy last of all, giving way to the eastern, western and northeastern provinces. The development strategy of the Center of the country began to take shape and be implemented during the Eleventh Five-Year Plan. Hubei Province, which has significant potential and an advantageous strategic position, should become the center of the rise. Consistent state regional policy in Hubei Province is implemented in the field of transport, energy, development of new high-tech industries, qualitative transformation of basic industries, integration of scientific and technical and industrial innovations, strengthening investment attractiveness, as well as taking into account the ideas of green transformation. In Hubei Province, such well-known national programs as “Rise of the Central Part” and “Development of the Yangtze River Economic Belt” have been implemented. The presented analysis of the dynamics of socio-economic indicators of Hubei Province confirms the success of the chosen strategy and allows us to state that Hubei is the “locomotive” of development of the whole of Central China. The source base of the study consists of documents and reports in Russian, English and Chinese, allowing us to analyze the goals, objectives and implementation of regional policy in the regions of China.

The scientific measurement of high-quality industries development (Abbreviated as HQID) level is crucial for promoting their advancement in China. This measurement holds significant importance in reducing regional differences in HQID among cities and fostering coordinated urban industry development. This study utilizes panel data encompassing 286 cities in China from 2003 to 2022. It comprehensively examines the essence of HQID, focusing on factor output efficiency and the industrialization process. To achieve this, an evaluation index system encompassing seven key aspects is constructed: technological innovation intensity, factor productivity, resource utilization intensity, pollution emission intensity, open competition intensity, industrialization level, and industrialization quality. Subsequently, the HQID level of China is measured, and the spatial–temporal evolution characteristics are revealed through various methods, including spatial correlation analysis, hot spot analysis, and Dagum Gini coefficient decomposition. The findings indicate the following: (1) China’s urban industry is experiencing slow but steady improvement in its overall high-quality development level. The number of regions with medium and high levels has notably increased. Furthermore, the spatial distribution is predominantly concentrated in the Eastern coastal areas. (2) The spatial distribution of HQID index in Chinese cities reveals positive correlation between the H–H type spatial agglomeration pattern and the L–L type spatial agglomeration pattern. (3) The highest level of HQID and the most pronounced growth trend are observed in Eastern coast and Northern coastal. Since 2018, the trend of HQID in the northeast and northwest areas has shown a decline. From 2003 to 2022 inter-regional differences were primary source of overall regional disparities, with significant variation in the contribution rates among the three factors.

In recent years, China’s transport logistics industry has experienced rapid development, driven by the technological advancements. But the coupling mechanism between transport logistics and technology is currently unclear, and there are likely regional differences. This study uses the entropy weight method, coupling coordination models and 20-year provincial panel data to measure the coupling coordinated development level of transport logistics and technology across 31 Chinese provinces (districts, cities). The spatial–temporal distribution, dynamic evolution, and regional differences in the coupling coordination development were analysed using kernel density estimation and the Moran index. Through the application of the Spatial Durbin Model (SDM), the mechanisms and spatial effects of selected influencing factors on the development levels are revealed. The results of this study revealed the following findings. (1) The levels of development in transport logistics and technology have consistently shown a positive upward trend with regional disparities. (2) Most provinces demonstrated a positive upward trend in the coupling coordinated development with a multi-polarised state. The overall level of coupling coordination is decreasing from east to west. In 2022, the difference between the highest and lowest coupling coordination degree between provinces is 0.78. (3) The national economy, industrial structure, urbanisation level, and consumption intensity have positive impacts on the coupling coordinated development of local regions. The findings of this study, which reveal positive trends and significant regional disparities, underscore the importance of formulating strategic plans tailored to local conditions to promote the coupled development of transport logistics and technology.

Based on patent data spanning 2000 to 2020 from 168 counties in Hebei Province, this study investigates the spatio-temporal evolution of county-level innovation and its determinants using methodologies such as standard deviation ellipses, spatial Markov chains, spatial autocorrelation, and geographical detectors. The findings indicate: (1) A rising trend in overall innovation levels across Hebei's counties, with a shift in innovation structure from low concentration to multi-type equilibrium. Core areas of county-level innovation, centered around Shijiazhuang, Langfang, and Tangshan, are gradually forming spatially, transitioning from a dispersed “point-like” pattern to a “concentrated and contiguous” distribution. (2) The “Northeast-Southwest” innovation pattern at the county level remains stable, but exhibits unstable focal points shifting predominantly southwestward, indicative of a trend towards following innovative resources and emerging industries. (3) The spatial distribution of innovation levels in counties is shaped by multiple factors, including temporal dynamics and economic development models, reflecting noticeable shifts over time.

With the increase in global economic integration, high-quality economic development (HQED) has become a common goal of all countries. Based on these five development concepts, this paper uses the Gini coefficient, trend surface analysis, geographically weighted regression (GWR), the entropy weighting method, and standard deviation ellipse analysis to study the spatio-temporal pattern and driving mechanism of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). This paper examines the spatial and temporal patterns and driving mechanisms of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) based on five development concepts. The study revealed that (1) HQED is on the rise overall, but at the same time, it highlights the uneven development of multiple dimensions, especially in terms of significant differences in innovation, openness, and sharing. (2) HQED shows a clear center-periphery structure, with Guangzhou, Shenzhen, and Hong Kong as the core high-value areas; the growth rate of HQED capacity in the internal areas is significantly greater than that in the external areas, and HQED is prominent in the cities around Guangzhou, Shenzhen, and Hong Kong. (3) Factors such as agglomeration level, human capital, foreign investment, infrastructure development, financial and environmental protection expenditures, and financial inputs, and scientific, and technological inputs have a significant positive effect on HQED, and their interactions are further strengthened. This study reveals the importance of the realization of HQED in the GBA and the promotion of the overall development of the region.

Promoting technological innovation in the natural gas industry is a feasible means of achieving energy transition. Guided by the geographic innovation theory, this article carries out research on the scale, technical fields, capabilities, and influencing factors of technological innovation in the natural gas industry of 312 Chinese prefecture-level cities, making use of the cusp catastrophe model, the center of gravity and standard deviational ellipse, exploratory spatial data analysis, and geographically and temporally weighted regression (GTWR). The research shows the following: (1) Technological innovation in China’s natural gas industry has continuously expanded in terms of scale, with the number of participating cities increasing, showing a spatially uneven pattern of local agglomeration and national diffusion. (2) There have been significant innovation achievements in natural gas equipment and engineering, but natural gas utilization is lagging in comparison, with drilling, new materials, environmental protection, pipe network engineering, and digital services becoming frontier fields, and collaborative innovation with the thermoelectric, metalworking, automotive, and other related industries having been initially established. (3) The unevenness of technological innovation capabilities is obvious, with the core advantages of Beijing–Tianjin being continuously strengthened and Sichuan–Chongqing, the Yangtze River Delta, the Pearl River Delta, Shandong Peninsula, and Liaodong Peninsula forming high-level technological innovation capability agglomerations. (4) The spatiotemporal pattern of technological innovation capability is the result of multiple factors, with northeastern cities mainly being affected by natural gas demands, northwestern cities being highly sensitive to capital strength, eastern cities mostly relying on urban development, and cities in North China mainly being bolstered by the strength of talent. (5) It is necessary to carry out further multi-agent and multi-scale future research on technological innovation in the natural gas industry and its relationship with the energy transition and to explore the interactivity of the influencing factors. This study may provide strategies for technological innovation in the natural gas industry from the perspective of the energy transition.

No abstract available

The digital economy offers a strategy for grasping new opportunities in the latest technological revolution and industrial change. The study of location about digital industry is essential for the digital progress of the Yellow River Basin (YRB). Selecting 687,117 digital industry enterprises in YRB of China from 1994 to 2021 as a sample, this study uses a standard deviation ellipse, nuclear density estimation, average nearest neighbor index, and geographic detector to explore the digital industry’s spatial evolution scale in the YRB and its driving factors. The results indicate that (1) digital industry enterprises in the YRB have experienced the development process of “dispersal followed by agglomeration,” generally showing a trend of “east (slightly north) - west (slightly south)” agglomeration. It has apparent socioeconomic preferences, offering a core circular structure that gradually spreads to the peripheral regions based on provincial capital cities; (2) there is an obvious imbalance in the advancement of the service-oriented and digital manufacturing industries in the YRB. The trend of change in the aggregation degree of the manufacturing digital industry during 1994 to 2021 is slight, while the direction of change in the aggregation degree of the service-oriented digital industry is significant; (3) market potential factors such as the innovation development level, innovation, and entrepreneurship vitality, and digital agglomeration factors such as the informatization development level have a stronger impact on the spatial advancement of the digital industry in the YRB, while economic development level factors such as the economic fundamentals and industrial structure have a weaker impact.

In the context of high-quality development, the development paradigm of integrating scientific and technological innovation, talent agglomeration, and new-type urbanization has become a key issue in regional development. Taking the Yangtze River Economic Belt as an example, this paper analyzes the interaction mechanism of the three systems and constructs an evaluation index system from the perspective of regional high-quality development. This paper combined entropy weight TOPSIS, coupling coordination degree model, and Gini coefficient to explore the spatial and temporal characteristics and regional differences of system coupling coordination. The evolution trend of the coupling coordination type is predicted by the Markov chain model. The research shows that: (1) The development index of the three major systems in the Yangtze River Economic Belt is on the rise, and the coupling coordination degree is in the running-in stage as a whole. The resistance restricting the coupling coordination degree is mainly the lag of scientific and technological innovation in the upstream, and the lag of talent gathering in the middle and downstream. ( 2) The coupling coordination degree of the three systems has obvious spatial agglomeration characteristics, showing a high level in the lower reaches of the Yangtze River, and a low level in the middle and upper reaches of the Yangtze River. (3) The gap of the coupling coordination degree of the three systems in the whole Yangtze River Economic Belt is gradually narrowing, and the large development gap among different regions is still the main cause of the Gini coefficient of the Yangtze River Economic Belt. (4) There is a location difference in the probability of coupling coordination level transfer, and the upper and middle reaches of the Yangtze River will still be in the antagonistic or running-in stage in the next stage, while the lower reaches of the Yangtze River will be in the coordination stage. The research conclusions provide scientific references for the high-quality development of the Yangtze River Economic Belt.

Against the backdrop of global economic digital transformation and the rapid flow of creative factors, innovation spaces, as the key carriers of inventive activities, drive high-quality development in urban agglomerations. This study develops a three-dimensional framework of “Spatial Structure–Factor Synergy–Institutional Drivers” to uncover the evolution of innovation spaces and industrial shifts in the Beijing–Tianjin–Hebei urban agglomeration, China. Methodologically, spatial econometric techniques were applied to capture both the overall concentration and spatial disparities of innovation. Spatial Gini and variation coefficients measured innovation clustering, while standard deviation ellipses and location entropy identified spatial linkages among high-tech innovation clusters. Geographically weighted regression models explored spatial heterogeneity in influencing factors, and a policy intensity index was constructed to assess the effectiveness of differentiated policy interventions in optimizing innovation resources. Key findings include the following: (1) Innovation spaces are spatially polarized in a “core–periphery” pattern, yet require cross-regional collaboration. Concurrently, high-tech industries demonstrate a gradient structure: central cities leading in R&D, sub-central cities driving industrial applications, and node cities achieving specialized development through industrial transfer. (2) The driving mechanisms exhibit significant spatial heterogeneity: economic density shows diminishing returns in core areas, whereas R&D investment and ecological quality demonstrate increasingly positive effects, with foreign investment’s role evolving positively post-institutional reforms. (3) Regional innovation synergy has formed a preliminary framework, but strengthening sustainable policy mechanisms remains pivotal to advancing market-driven coordination and dismantling administrative barriers. These findings underscore the importance of integrated policy reforms for achieving balanced and high-quality innovation development in administratively coordinated urban agglomerations like BTH.

Carbon emission and sustainable development have attracted global attention. Promoting urban green innovation (UGI) in the Yellow River Basin (YRB) will help in lowering the intensity of carbon emissions and improve the safety and sustainability. A SBM-DEA model was constructed to measure carbon emission efficiency (CEE) and the degree of coupling and coordination with UGI was calculated in 73 prefecture-level cities in the YRB. The spatial association network of CEE coupled with UGI is constructed by using a modified gravity model, social network analysis and the quadratic assignment procedure (QAP), to analyze spatial potential energy, network characteristics and clustering characteristics. The study found that: (1) The coupling coordination degree of CEE and UGI in the YRB shows fluctuating growth, mutual promotion and continuous coordinated development. (2) The spatial linkage between CEE and UGI is gradually close, and the potential energy of the spatial linkage increases year by year, with obvious spatial spillover effect, indicating that the radiation and influence between cities are gradually increasing. In contrast to the middle stream, the upstream and downstream regions show a higher percentage of spatial potential energy in the entire network, and their network structure is more intricate and robust. (3) The clustering patterns of the three major urban clusters are examined using the block model, exploring the positioning and functions of various cities in these urban conglomerations, which includes the net spillover, net benefit, two-way spillover and broker plate, so as to strengthen the connection and coordinated development between cities. (4) Factors such as spatial adjacency, industrial structure, population density, digital economy and urbanization level, and energy intensity significantly impact the spatial association network, along with temporal and regional heterogeneity. Therefore, tailored policies are needed in the YRB to strengthen collaboration between CEE and UGI, fostering the development of a circular economy and promoting sustainable development.

In recent times, a new wave of scientific and technological advancements has significantly reshaped the global economic structure. This shift has redefined the role of regional innovation, particularly in its contribution to developing the Guangdong–Hong Kong–Macao Greater Bay area (GBA) into a renowned center for science, technology, and innovation. This study constructs a comprehensive evaluation system for the Regional Innovation Ecosystem (RIE). By applying the coupling coordination degree model and social network analysis, we have extensively analyzed the spatial structure and network attributes of the coupled and coordinated innovation ecosystem in the GBA from 2010 to 2019. Our findings reveal several key developments: (1) There has been a noticeable rightward shift in the kernel density curve, indicating an ongoing optimization of the overall coupling coordination level. Notably, the center of gravity for coupling coordination has progressively moved southeast. This shift has led to a reduction in the elliptical area each year, while the trend surface consistently shows a convex orientation toward the center. The most significant development is observed along the ‘Guangdong–Shenzhen–Hong Kong–Macao Science and Technology Innovation Corridor’, where the level of coupling coordination has become increasingly pronounced. (2) The spatial linkages within the GBA have been strengthening. There are significant spatial transaction costs in the regional innovation ecological network. In the context of the 2019 US-China trade war, the cities of Jiangmen and Zhaoqing experienced a notable decrease in connectivity with other cities, raising concerns about their potential marginalization. (3) Guangzhou, Shenzhen, and Hong Kong have emerged as core nodes within the network. The network exhibits a distinctive “core–edge” spatial structure, characterized by both robustness and vulnerability in various aspects.

No abstract available

The synergistic evolution of digital technological innovation (DTI) and urban economic resilience (UER) has become an inherent requirement for the high-quality development of urban agglomerations. Based on panel data at the prefecture-level city scale from 2011 to 2022, this paper explores the spatiotemporal patterns and driving factors of the coupling coordination between DTI and UER across the three major urban agglomerations in the Yangtze River Economic Belt (YREB). The study yields the following key findings: First, during the study period, the coupling coordination degree between digital innovation and UER experienced a fundamental shift from disorder to coordination, but high-quality coupling coordination has not yet been fully achieved. Second, the spatial distribution of coupling coordination exhibits a clear upstream-downstream gradient, with higher coordination in the upper reaches and lower coordination in the middle and lower reaches, forming a distinct core-periphery structure within each agglomeration. Third, the overall inequality in coupling coordination shows a declining trend, but inter-agglomeration differences remain the primary source of inequality. Finally, economic development, fiscal pressure, innovation capacity, and scientific research support are identified as the key driving factors influencing coupling coordination. Based on these findings, the study recommends: promoting regional collaboration, enhancing fiscal support, and optimizing the spillover effects of core cities to foster more balanced and resilient development across the YREB.

To scientifically evaluate the dynamic operational efficiency, spatial differences, as well as the formation mechanisms of the urban Innovation Ecosystem within the Yellow River Basin is highly important for the high-quality development of China. In the present research, both the economic circulation theory with the Innovation Ecosystem and the Data Envelopment Analysis – Malmquist Productivity Index (DEA-Malmquist) model were adopted to analysis the database from 59 cities along the Yellow River Basin. In parallel, the kernel density estimation, the Gini coefficient, and Panel Vector Autoregression (PVAR) model were applied for further comparison. The results revealed that the dynamic operational efficiency of the Innovation Ecosystem within the Yellow River Basin exhibited an obvious fluctuating downwards trend. The efficiency of spatial distribution in the upstream and midstream basins shows a left-skewed and polarized pattern, whereas the downstream basins exhibited a right-skewed distribution with less pronounced polarization. The results also revealed that the overall Gini coefficients for dynamic operational efficiency (TFP) and technical efficiency (EFF) in the Yellow River Basin tended to convergence, whereas those for technological change (TECH) are of an increasing trend. Moreover, the hypervariable density emerged as the primary factor driving disparities in TFP, TECH, and EFF within the basin. Furthermore, the relationships among TFP, TECH, and EFF were featured with the regional heterogeneity. In the midstream areas, there existed a self-improvement mechanism for the TFP, TECH, as well as the EFF. However, there was a stronger self-improvement mechanism for TECH but a self-weakening mechanism for TFP and EFF in the downstream regions.

Based on the theories of industrial value chain and network embeddedness, this paper takes Guangxi as an example and uses the entropy-weighted TOPSIS model to measure the two-way embedding level of the industrial chain and innovation chain in 14 prefecture-level cities from 2017 to 2023.Combined with the geographical detector, the spatial-temporal differentiation mechanisms are analyzed. The results show that the dual-chain embedding presents a three-tier gradient pattern led by Nanning and Liuzhou, with regional synergy constrained by the imbalance of innovation resource allocation and barriers to factor flow. The time-series dimension exhibits a fluctuating curve of "rise-sharp decline-recovery," where demand-embedded elements have the strongest explanatory power for spatial heterogeneity and exhibit a nonlinear enhancement effect. The study reveals the unique patterns of dual-chain synergy in Guangxi and proposes pathways for upgrading strategic awareness, optimizing market mechanisms, and cultivating technological potential, providing theoretical support for breaking the inefficient lock-in of regional innovation and fostering new quality productivity.

It has become a consensus in academic circles that enterprise spatial agglomeration promotes technological innovation through comparative advantage of factor cost and knowledge spillover effect. With the increase of agglomeration degree, the advantage of low cost is gradually lost, and even under the constraint of financing, it will inhibit the innovation and development of enterprises. By constructing a new micro-level spatial agglomeration index, this paper investigates the dynamic impact of corporate spatial agglomeration on corporate innovation from the perspective of agglomeration cost. On the basis of using the longitude and latitude of industrial enterprises to construct a new index of agglomeration, this paper further carries out a comprehensive matching on the land market transaction data, patent application data and industrial enterprise data, obtains the micro-data at the enterprise level from 2007 to 2014, and constructs a non-linear intermediary effect model with industrial land price as the breakthrough point. The empirical results show that corporate spatial agglomeration has an “inverted U” effect on corporate innovation. The reason is that agglomeration costs such as increased competition caused by excessive spatial agglomeration and the rise in industrial land prices tighten corporate capital constraints, affect corporate resource allocation, and cause enterprises to reduce research and development investment. Research on heterogeneity shows that industrial enterprises have obvious preference characteristics for the direction of innovation investment in different stages of spatial agglomeration. According to this, the local government should scientifically control the agglomeration layout, on the one hand, give full play to the knowledge spillover effect of agglomeration, and on the other hand, mitigate the adverse impact of the rapid increase in land prices on innovation.

Relevance. The paper explores interregional cooperation, examining the challenges of aligning spatial and innovation development in macro-regions, with a focus on two federal districts of Russia. The study assesses the potential of interregional cooperation among neighboring regions within a single federal district, as well as among more distant regions across different federal districts. Research Objective. The study aims to test two hypotheses: the first deals with the viability of imitation innovation strategies in peripheral regions of both intra and inter-federal districts. The second hypothesis concerns the presence of innovation interdependence (autocorrelation) among regions from different federal districts, influenced by the level and industrial compatibility of innovation outputs. Data and methods. The study employs the DEA method to identify central and peripheral regions (imitator regions) by calculating technical efficiency indicators. It also uses coupling interregional complementarity indexes to assess the potential for interregional cooperation in innovation and technological import substitution, considering the industrial profiles of the regions. Spatial autocorrelation is evaluated by using Moran's Index to estimate the level of regional interdependence, factoring in the level and industry conformity of innovation output. The novelty of the proposed methodological approach lies in the application of interregional indexes of innovation complementarity as weighting coefficients in Moran's Index calculation. Results. The study reveals a rise in spatial inequality, competition among regions, and constrained interregional innovation cooperation across federal districts. Geographical proximity currently plays a pivotal role in cooperation, with initial indications of a macro-regional space evolving through knowledge exchange. However, both hypotheses concerning imitation strategies and autocorrelation are only confirmed for regions within a single federal district. Conclusions. The findings of this study regarding spatial autocorrelation offer valuable insights for policymakers in the sphere of regional innovation.

In the context of “space of flows”, city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a large number of innovation resources. Here our report is to provide new ideas for improving the innovation capability of high-tech zones and accelerating the construction of Chinese high-quality innovation system. Here we take 142 cities with high-tech zones as research samples, and explore the characteristics and influencing factors of spatial network of city-based innovation correlation in China, through modified gravity modelsocial, network analysis and QAP analysis. The results show that city-based innovation network is not closely connected, the number of redundant connection channels is low efficiency, showing a four-level spatial pattern of “Z” shaped spindle. Among them, degree centrality of cities in eastern China is higher than that in the western region, the core cities in central China play a bridging role, and western remote cities are easily affected by related cities. Moreover, there are four innovation cohesion subgroups, including the northern hinterland subgroup, the eastern coastal subgroup, the southern subgroup and the western cooperation subgroup. Furthermore, the results of the influencing factors analysis show the differences in administrative level, economic development level, openness to the outside world, and investment in technology are conducive to the innovation association between cities, while the similarities in spatial adjacency and industrial structure will promote the strong innovation association between cities.

This study examines the new characteristics and multidimensional impacts of digital technology innovation on the regional industrial gradient shift in China. Through empirical analysis of a dataset at the prefectural level from 2008 to 2020, the research reveals that digital technology innovation has driven the outward relocation of midstream industries and the concentration of downstream industries in digital technology innovation hubs, with this effect strengthening over the sample period. Heterogeneity analysis further indicates that digital technology innovation not only facilitates the traditional coastal‐to‐inland gradient transfer but also introduces new pathways, such as hierarchical diffusion centred around urban clusters and network diffusion at transport hubs. Mechanism testing shows that digital technology innovation enhances innovation spillover effects and labour‐saving production process improvements, thereby providing impetus for industrial migration. This study expands the applicability of the traditional ‘flying geese’ theory and offers policy insights for developing countries in managing industrial layout under large‐scale economies.

Strategic emerging industries (SEIs) have the potential to be a nation’s leading industries in the post-industrialization era. Exploring the spatial distribution of SEIs and the impetuses of their location choice plays a key role in formulating policies conducive to regional industrial and economic development. However, most studies on relevant topics neglected the impact of institutional environment and local innovation on the formation of spatial patterns of SEIs. By investigating 12,979 industrial enterprises in China, this research applied spatial autocorrelation and spatial regression analysis to explore the spatial characteristics of SEIs and identify the variables affecting the location selection of SEIs that result in these spatial patterns. The findings indicated significant spatial differences in the spatial distributions and agglomeration patterns of SEIs. Institutional environment, local innovation, and regional economy have significant impacts on the location choice of SEIs. The interactive effects of local innovation and institutional environment on the spatial agglomeration of SEIs revealed that a higher degree of decentralization and stronger local innovation capability would promote a stronger agglomeration of SEIs. Regions with strong (weak) marketization and weak (strong) institutions of higher education would promote SEIs agglomeration. Based on the findings, policy options were suggested to facilitate SEIs planning and differentiated pathways of industrial transformation.

This article explores the relationship between knowledge sources at different levels and corporate innovation from the perspective of urban cluster, with a focus on enterprises. This paper conducted an empirical analysis of 375 listed companies in 27 cities within the Yangtze River Delta urban cluster in China from 2009 to 2019. The findings showed that: (1) Local scientific knowledge spillovers, mediated by industry relevance, positively influence firms’ innovation performance. This study verifies how spatial knowledge is dimensionally reduced from scientific spillovers to industrial technological innovation. (2) Emerging industries acquire relevant scientific knowledge for transformation from a broader regional scope. Regional knowledge creation in the Yangtze River Delta urban cluster has stimulated industrial innovation across various sectors, thereby enhancing the overall innovation capacity and level of the urban cluster. (3) Regional diversity significantly affects the process of transforming knowledge into innovation. This paper supports the existence of a unified spatial innovation network among heterogeneous spatial economic entities and emphasizes the innovation synergy from lower to higher levels within heterogeneous hierarchical innovation networks. Developing urban agglomeration strategies that leverage the resource advantages of industrial clusters and adjust industrial layouts is an important approach to promote innovation and economic growth.

The coordinated development of industrial agglomeration and economic resilience can drive regional economic advantages; this type of development has become a catalyst for sustainable growth and high-quality development of the economy in China. This study applied models, including the coupling coordination degree, spatial autocorrelation, and Tobit, to explore the heterogeneous characteristics of the coupling of China’s industrial agglomeration and regional economic resilience from 2005 to 2019. Additionally, by applying the perspectives of economic and geographic location, indicators were selected to analyze the associated influencing factors, including industrial externalities, new economic geographies, economic policy factors, and other aspects. We found that the overall coupling between industrial agglomeration and economic resilience increased over the study period, but with only a moderate level of coordination. Provinces with high, moderate, and low levels of coordination eventually emerged along a strip-like alternating pattern in space. The dependence increased with an increase in space, but was not significant, and there was a lack of benign interaction between the regions. With respect to interactivity between locations, the interaction of the east and the coast was the most active. There were lower levels of interaction between the west and inland regions. This further confirmed the significant temporal and spatial heterogeneity of the coupling. Environmental pollution, market consumption, the quality of space, and technological support significantly promoted the coupling; opening to the outside world did not. Specifically, with respect to economic location, market consumption and spatial quality had a significant positive effect on the eastern coupling. The center and west regions were significantly affected by economic density and market consumption, and the northeast region was affected by spatial quality and capital intensity. Concerning geographical location, market and technological forces strongly promoted interactions in both the coast and inland regions. The study found that both the government and the market need better guidance to effectively engage with and shape industrial agglomeration and economic resilience in a scientific, reasonable, localized, and distinctive manner.

China’s rapid technological growth and aggressive globalization policies have led to an increasing interest in Chinese patents abroad. This study uses strategic emerging industries (SEIs) that are important for the future development of the world as examples and constructs a novel dataset of Chinese SEI patents abroad (1993–2017) to explore the spatiotemporal evolution and determinants of the geography of these patents. Our results show that the number of Chinese SEI patents abroad is growing rapidly, and the new-generation information technology industry is increasingly dominating, accounting for approximately 50% of all SEI patents abroad. Chinese SEI patents abroad are highly concentrated in the United States, Western Europe, and East Asia, and their influence is gradually spreading from African countries to developed countries. The host country’s intellectual property rights (IPR) protection level, technology market size and imitation risk have significant positive effects on Chinese SEI patents abroad, while the host country’s high-tech product market size and competition risk have negative effects on Chinese patents abroad. The conclusions provide new information for understanding Chinese patents abroad activities and the motivation of China’s technology globalization and provide evidence from an emerging country for research of the international diffusion of technology innovation.

The coordinated development and agglomeration of the digital and manufacturing sectors have reached widespread consensus. However, its potential environmental impacts remain underexplored. To bridge this gap, utilizing the panel data of China's prefecture-level cities from 2006 to 2021, this paper analyzes the spatiotemporal evolution of digital and manufacturing industry co-agglomeration (DMCA), and then investigates the environmental impact and mechanisms of DMCA, using urban air pollution as a case study. It delves into the mechanism and heterogeneity from dual perspectives of geographical and virtual agglomeration. Key findings include: First, DMCA level in China has steadily increased, with higher concentrations in the Eastern and Central regions, especially in core urban clusters and economic belts. Second, DMCA significantly mitigates urban air pollution by leveraging its positive environmental externality, a result validated through robustness and endogeneity tests. Meanwhile, the impacts exhibit asymmetry, spatial heterogeneity, and nonlinear effects. Third, industrial upgrading, technological innovation, energy transition and factor allocation are verified as primary mediating channels through which DMCA mitigates urban air pollution, and environmental regulation is also verified as a positive moderating effect. Last but not the least, the differentiated of digital and manufacturing virtual agglomeration on urban air pollution are further investigated, particularly in the mechanisms and differentiated pathways of production intensification and lifestyle digitalization. This study enriches the theoretical framework concerning on industrial co-agglomeration, providing policymakers with critical insights to enhance the synergistic effect and positive environmental externalities of DMCA.

With the rapid advancement of global technology, high-tech industries have become key drivers for the economic growth of many nations and regions. This study delves into the spatiotemporal dynamics and determinants influencing China’s high-tech sector from 2007 to 2021. The key findings include the following: (1) Nationally, the high-tech sector has been a cornerstone for China’s GDP growth over the preceding 15 years. The expansion rate of the high-tech domain consistently outpaces the broader economy. In particular, since 2015, the percentage of high-tech industries’ GDP has surged to approximately 42%. (2) At the provincial level, the spatial representation of the high-tech sector’s GDP predominantly leans towards the east and the south, revealing pronounced spatial autocorrelation. Nevertheless, the demarcations between east and west and between north and south are progressively diminishing. (3) Regarding influential determinants, R&D internal expenditure, operating revenue, and industry agglomeration have been instrumental in spearheading innovation and bolstering growth within the high-tech realm. These insights are invaluable for comprehending the evolutional nuances of China’s high-tech industry and devising pertinent policy measures.

This article provides an in-depth understanding of the concept of industry space. It introduces a novel industrial correlation index, known as the industrial co-agglomeration index, which is based on the Wasserstein distance algorithm and optimization solution method. Our analytical framework for industrial space is built on complex network theory, and it highlights three key aspects: network space parameters, core nodes, and industrial space density indicators. To demonstrate the applicability of our framework, we use the Yangtze River Delta urban agglomeration as a case study. The study period covers the years from 1998 to 2013, and the findings indicate that the spatial structure of the industrial space underwent an “inverted U-shaped” transformation, becoming more centralized before 2008 and then becoming increasingly dispersed. The results of the study also show that the Yangtze River Delta region has experienced a transformation towards a more diverse, high-quality and high-tech industrial structure. The status of labor-intensive industries has declined while the status of technology-intensive and scale economy industries has increased. In conclusion, this article provides valuable insights into the structural form and evolution trend of industrial space, and the proposed analytical framework can serve as a useful tool for future research in this field.

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Purpose The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments. Design/methodology/approach Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle. Findings The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development. Originality/value Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

Interactions between universities and industry are essential for innovation systems, whereby the process is catalyzed by the proximity between these actors in different dimensions (cognitive, organizational, social, institutional and geographical). The present paper seeks to investigate the specific importance of geographical proximity for university-industry interactions during a specific moment in Brazil’s peripheral socioeconomic formation, with the construction of an institutional framework that proved favorable to peripheral innovation and the advancement of information and communication technologies that would dispense with co-location and face-to-face contact in collective learning processes. By applying multiple linear regression analysis and smallest space analysis (SSA) to a database obtained from an extensive survey, it was observed that, associated with the cognitive dimension, geographical proximity still prevails in interactions for innovation in peripheral contexts.

Abstract This study extends evolutionary economic geography to science by mapping how regional scientific capabilities emerge and evolve across Europe. Using Web of Science publications (2000–2017) geo-coded to 1,216 regions in 35 countries and classified into 228 subjects, we construct a pan-European “Science Space” based on subject co-occurrence and relatedness, and test whether relatedness density, i.e., the embeddedness of a subject in a region’s existing portfolio, predicts subsequent entry (Revealed Scientific Advantage ≥ 1). Network evidence shows Europe’s science system becoming more interdisciplinary, with technology-adjacent subjects (e.g., nanoscience, robotics, computer science) gaining centrality, while Life Sciences & Biomedicine remain dominant by volume. Econometric results (pooled OLS and GLM for binary entry, with region/subject/period fixed effects and controls for the regional economy and knowledge base) indicate that higher relatedness density significantly raises the likelihood of scientific entry. The effect is stronger in non-metropolitan regions and when a subject’s initial RSA is very low, consistent with relatedness seeding new capabilities rather than merely consolidating near-threshold strengths. These findings generalise the principle of relatedness from technology to science and advise regional innovation policy to prioritise adjacent scientific opportunities, invest in bridging infrastructures, and design interdisciplinary platforms where relatedness density is high but specialisation has not yet emerged.

The purpose of this article is to contextualize the geographical changes of automobile industry, analyzing the relationship between the main producing countries and the evolution of science, technology and innovation in this sector. In this sense, an empirical research was carried out, with the construction and analysis of a database of Dewert Innovation plataform, showing the evolution of patent registration. We also investigate the recent transformation of this industry towards electromobility, which has been made possible by advances in production of batteries. Thus, the lithium-ion battery (LIB) sector was studied, which highlights the change in innovative leadership from the West to the East, with the increasing relevance of Japan, South Korea and China. Keywords: development; Science, technology and innovation; automobile industry.

The article examines the characteristics of the formation and development of the innovation infrastructure of the Lviv agglomeration in the context of military challenges and intensified regional competition. It demonstrates that despite the destructive impact of the ongoing war, the Lviv region retains its position as one of the leading hubs of Ukraine’s innovation ecosystem, with the Lviv agglomeration being the core of the regional innovation system. The aim of the article is to analyze the structural and spatial features of the innovation infrastructure of the Lviv agglomeration, identify the key drivers of its development, and evaluate the role of the agglomeration in strengthening regional innovation potential. The methodological foundation of the research is based on a combination of systemic and spatial-structural approaches, a case study of agglomeration formation, analysis of official statistics and analytical materials, innovation development indicators, data from industry dashboards, as well as elements of institutional analysis. The study reveals the contribution of industrial infrastructure (networks of industrial parks), the IT sector, cluster associations, science parks, higher education institutions, and research institutes to the formation of the agglomeration’s innovation ecosystem. It is shown that the Lviv agglomeration concentrates a significant share of business entities in the field of information technology and scientific research, providing a high level of concentration of intellectual property objects and university inventive activity. The role of the Lviv IT Cluster, the LvivTech.City and Innovation District IT Park innovation parks, university startup schools, and science parks as institutional integrators of the «science – business – government» interaction is outlined. It has been demonstrated that the innovation infrastructure of the agglomeration is comprehensive and covers the entire value creation chain – from fundamental research and workforce training to technology commercialization, development of co-working networks, and youth innovation spaces. It is concluded that the Lviv agglomeration forms a structurally balanced innovation ecosystem at the supra-regional level, enhancing the competitiveness of the Carpathian region and creating the conditions for a transition to a model of knowledge and technology generation capable of supporting sustainable development in the context of post-war recovery and European integration.

Development zones are crucial spatial carriers driving economic growth and industrial upgrading, playing a key role in China’s development. After years of expansion, these zones face significant challenges in industrial land development and performance enhancement. This paper takes Suzhou Industrial Park (SIP) as a case, which is a model of Sino–Singaporean government cooperation. Using Landsat 4–5 TM data, socioeconomic data, and industrial land use data, spatial analysis and statistical modeling were employed to examine the evolution and phased patterns of industrial land use in SIP from 1994 to 2022. A performance evaluation system encompassing economic benefits, innovation-driven growth, development intensity, green development, and social security was developed to assess land use performance and its responses to spatial transformations. The results reveal that industrial land in SIP experienced a significant change in the intensity of land expansion from 1.031 to 0.352 during 1994–2022, and the peak circle density expanded from 3 km to 15 km. The mean value of the comprehensive performance score during 2017–2022 was 42.18, with the highest economic efficiency (40.54) and a lower innovation capacity (16.98). The development of industrial land in SIP presents the stage characteristics of monocentric polarization, polycentricity, and spatial diffusion toward a generalized development zone, showing significant path dependence, and the difference in the land use performance of different industrial types is obvious. In the future, the optimization and redevelopment of the stock of land should be strengthened to promote the optimization of the spatial layout of technology-intensive industries and the technological upgrading of labor-intensive industries, as well as achieving sustainable economic growth through innovation-driven, green development and enclave economy collaboration. This study provides a reference for the industrial layout and high-quality sustainable development of development zones.

In the context of uncertain economic environments urban agglomerations play a crucial role in economic development, reshaping industrial chains and fostering inter-city cooperation. This study employs the Global Production Network (GPN) theory to enhance our understanding of how cities integrate into regions, emphasizing the often-overlooked governmental influence in strategic coupling processes. In examining the evolution of China’s smartphone industry within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) this research categorizes 19,599 smartphone companies into five distinct groups. Through analyzing their spatial distribution and geographical linkage the study identifies four strategic coupling modes based on the localization of assets, considering spatial influence and technological complexity along horizontal and vertical dimensions. Structural and institutional elements within these modes are also explored. The research uncovers unique integration patterns among nine cities in the GBA’s mobile industry, revealing distinct spatial clusters rooted in technological, resource and innovation factors. Crucially, local policies play a pivotal role. Cities such as Shenzhen and Dongguan emerge as technology hubs, contrasting with Foshan and Zhongshan, which leverage resource advantages. The spatial impact, contingent on specific assets, underscores the necessity for nuanced top-down coupling methods in regional development. Moreover, the study emphasizes the significance of nurturing innovation links, not only between leading companies but also among midstream and downstream enterprises, enhancing cities’ strategic coupling capabilities.

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In recent years, manufacturing development has received renewed attention from developing and developed countries alike. As mega-city regions (MCRs) are where manufacturing industries converge, the research on urban networks of MCRs under the dominance of manufacturing transaction linkages is currently insufficient. Based on the buyer–supplier linkages of listed manufacturing firms, this paper investigated the characteristics of the urban network in the Yangtze River Delta region (YRDR) in China using the social network analysis method; explored the determinants of nodal centrality and city dyads of the urban network by the stepwise regression and quadratic assignment procedures, respectively; and proposes a “characteristics-determinants-strategies” technical framework for the analysis and optimization of interurban collaboration in manufacturing transactions within MCRs. The findings were as follows: (1) The characteristics of the urban manufacturing transaction networks differed from those of transaction linkages of advanced producer services (APS) firms, intra-firm organization hierarchies, and innovation cooperation networks; (2) the network and geographical “core-periphery” structure of urban power and the circulation corridor of the urban manufacturing transaction network was formed within the YRDR; (3) cooperation parks, innovation collaboration, high-speed rail (HSR) linkage, and geographical proximity between cities were found to facilitate the formation of urban manufacturing transaction networks, and the similarity of industry structures and driving distance between cities inhibits the network; (4) the number of urban industrial firms, GDP per capita, and city government spending on science and technology contributed to the centrality of a city in urban manufacturing transaction networks, while the urban population in a city had a negative impact. The research provides a complementary perspective to the urban network research of MCRs under the perspective of production factors and product circulation and provides policy and urban planning insights for the synergistic development of interurban manufacturing in MCRs.

Agglomeration and spillovers are key phenomena of technological innovation, driving regional economic growth. Here, we investigate these phenomena through technological outputs of over 4,000 regions spanning 42 countries, by analyzing more than 30 years of patent data (approximately 2.7 million patents) from the European Patent Office. We construct a bipartite network—based on revealed comparative advantage—linking geographic regions with areas of technology and compare its properties to those of artificial networks using a series of randomization strategies, to uncover the patterns of regional diversity and technological ubiquity. Our results show that the technological outputs of regions create nested patterns similar to those of ecological networks. These patterns suggest that regions need to dominate various technologies first (those allegedly less sophisticated), creating a diverse knowledge base, before subsequently developing less ubiquitous (and perhaps more sophisticated) technologies as a consequence of complementary knowledge that facilitates innovation. Finally, we create a map—the Patent Space Network—showing the interactions between technologies according to their regional presence. This network reveals how technology across industries co-appear to form several explicit clusters, which may aid future works on predicting technological innovation due to agglomeration and spillovers.

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This paper constructs a theoretical framework for new quality productive forces. It explores the connotation of new quality productive forces from the perspectives of labor, production factors, and technological innovation. Using statistical methods such as the entropy method and the Dagum Gini coefficient method, it quantitatively evaluates the new quality productive forces levels of 30 provinces in China from 2012 to 2022. The study reveals that, overall, the new quality productive forces levels of these provinces have witnessed a significant increase. However, there are notable disparities among regions, with the eastern region having the highest level and the western region the lowest. There is no sign of convergence within the four major regions, and the inter -- regional differences continue to widen. In light of these findings, this paper proposes that policy - making should precisely target regional differences, strengthen coordinated regional development, promote the sustainable development of all regions, and establish a dynamic monitoring mechanism. The aim is to provide a theoretical basis and policy reference for the high - quality development of the Chinese economy.

The development of new-type urbanization (NTU) represents a crucial strategic approach to fostering new drivers of economic growth. Despite its importance, limited research has explored the effects and underlying mechanisms through which NTU influences new quality productive forces (NQPFs), key indicators of emerging economic dynamism. Addressing this research gap, the present study analyzes panel data from 283 Chinese cities spanning from 2009 to 2022, applying a difference-in-differences (DID) model to empirically evaluate the impact of the New-Type Urbanization Pilot Policy (NTUPP) on NQPFs. The findings reveal that the NTUPP has a significant positive effect on NQPFs, a conclusion that is supported by a series of robustness and endogeneity checks. Specifically, the NTUPP’s implementation corresponds to an average increase of 1.1% in NQPFs. The policy facilitates NQPF growth primarily through mechanisms such as talent agglomeration and optimal resource allocation. Notably, the NTUPP is particularly effective in boosting NQPFs at lower initial levels. Since NQPFs inherently reflect green productivity, NTU’s emphasis on green, low-carbon, and civilizational features markedly amplifies the policy’s positive impact on NQPFs, while NTU’s focus on smart urbanization aspects appears to mitigate this effect. These findings contribute valuable empirical insights from the Chinese context, highlighting the potential of NTU to accelerate new economic growth drivers.

New quality productive forces serve as a catalyst for high-quality development and act as a critical driver of Chinese-style modernization. This study evaluated the degree of new quality productive force in China’s five major urban agglomerations between 2013 and 2022 using the entropy approach. Additionally, it utilized kernel density estimation, the Dagum Gini coefficient, and Markov chain analysis to explore the spatial and temporal dynamics of these forces and their evolutionary trends. The findings revealed the following: (1) Overall, the new quality productive forces in China’s five major urban agglomerations have exhibited a steady upward trend, although the overall level remains relatively low. Among these regions, the Pearl River Delta ranks the highest, followed by the Yangtze River Delta, Beijing–Tianjin–Hebei, Chengdu–Chongqing, and the Urban Cluster in the Middle Reaches of the Yangtze River. Nevertheless, significant potential for improvement persists. (2) The traditional Markov probability transfer matrix suggests that the new quality productive forces in these urban agglomerations are relatively stable, with evidence of “club convergence”. Meanwhile, the spatial Markov transfer probability matrix indicates that transfer probabilities are influenced by neighborhood contexts. (3) Over time, the new quality productive forces in Chinese urban agglomerations show a tendency to concentrate at higher levels, reflecting gradual improvement. The developmental state and evolutionary patterns of new quality productive forces in Chinese urban agglomerations are thoroughly evaluated in this paper, along with advice for accelerating their growth to promote Chinese-style modernization.

As a pivotal engine driving China’s economic development, new quality productive forces are profoundly shaping the pathways for realizing common prosperity and Chinese modernization. The study constructs multidimensional evaluation frameworks for new quality productive forces and common prosperity, respectively, measures the development levels of new quality productive forces and common prosperity across 277 prefectural-level and above cities in China from 2013 to 2022, and analyzes the spatial and temporal evolution characteristics of China’s new quality productive forces over the past decade using ArcGIS 10.8.1. Meanwhile, the two-way fixed model and the spatial Durbin model are used to analyze the impact of new quality productive forces on common prosperity and its spatial spillover effect. The study finds the following: (1) China’s new quality productive forces development levels generally show a spatial pattern of “high in the east and low in the west”, in which cities located in the Yangtze River Economic Belt and the eastern coastal strip have a higher level of new quality productive forces than other cities, with significant inter-regional differences. (2) New quality productive forces exhibit a robust and significant promoting effect on common prosperity. Mechanism analysis reveals that this effect operates through three channels: enhancing economic agglomeration, advancing industrial structure upgrading, and improving labor misallocation. (3) Regional heterogeneity shows that the promotion effect of new quality productive forces on common prosperity is particularly prominent in Northeast China and Eastern China. Structural heterogeneity reveals that labor materials and objects of labor exhibit more pronounced effects in enhancing common prosperity compared with laborers. (4) Spatial econometric analysis confirms that the new quality productive forces have a significant spatial spillover effect on common prosperity. The findings provide theoretical support for advancing common prosperity while contributing to China’s approach to addressing developmental imbalances among developing countries within the global community with a shared future.

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Water-scarce river basins face the dual challenge of sustaining development progress while maintaining water resources carrying capacity (WRCC), yet city-scale evidence remains limited on how New Quality Productive Force (NQPF)-driven high-quality development reshapes WRCC through coupled coordination and development–pressure decoupling processes. Using a balanced panel of 15 cities in the Weihe River Basin (WRB) during 2014–2023, an integrated analytical framework was implemented by combining composite index evaluation (WRCC and the high-quality development index (HQDI)), the Coupling Coordination Degree (CCD) model, Tapio decoupling diagnosis between HQDI and total water use (TWU), and logarithmic mean Divisia index (LMDI) decomposition. The results indicate that: (1) both the HQD index and WRCC exhibited sustained growth, with their CCD improving significantly from mild imbalance to primary coordination, while a distinct spatial pattern of “Guanzhong leading, northern Shaanxi improving, and eastern Gansu stabilizing” emerged; (2) the HQDI–WRCC linkage was further supported by pooled statistical tests and a two-way fixed effects specification with city-clustered robust standard errors, confirming a significant positive association (Pearson = 0.517, p < 0.01; Spearman = 0.183, p < 0.05) and a stable positive effect of HQDI on WRCC (β = 0.194, p = 0.0088); (3) Tapio results reveal an overall transition from earlier volatility toward a later-period regime dominated by Weak Decoupling (WD) and Strong Decoupling (SD), implying that development progress became less dependent on rising TWU, although pronounced inter-city heterogeneity persisted; (4) LMDI decomposition further identified water use intensity and industrial structure as primary inhibitors of water consumption, whereas the R&D scale effect increased nearly 60-fold, emerging as a major driver of water demand. This study provides a mechanistic basis for coordinating ecological protection and high-quality development under rigid water constraints in water-scarce basins.

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New productive forces are the new impetus for the high-quality development of the marine economy. To accurately measure the development level of marine new productive forces, this study constructs an evaluation index system from four aspects: development impetus, development structure, development mode, and development achievements. This study determines the combination weights of indicators based on relative entropy. Kernel density estimation, spatial Markov chain and Dagum Gini coefficient are used to analyze the spatiotemporal evolution, regional disparities and sources of marine new productive forces in coastal provinces of China. Finally, the decision-making trial and evaluation laboratory together with interpretative structural modeling (DEMATEL-ISM) is used to analyze the key influencing factors of marine new productive forces. Results show that the marine new productive forces have been increasing year by year, but the overall level is relatively low. There is a phenomenon of “club convergence” in the development level of marine new productive forces, and the state transfer occurs between adjacent types. The overall variation in marine new productive forces is showing a downward trend, with disparities arising mainly from inter-regional variation and hypervariable densities. The key influencing factors include investment in marine R&D, the openness of foreign investment, the openness of foreign trade, and investment in pollution control. The study conclusion provides support for designing a development path for marine new productive forces that conforms to regional characteristics.

Amidst global economic stagnation, China is undergoing a significant economic transformation by fostering new high-quality productive forces (NHPFs). In this transformative context, specialized and sophisticated small and medium-sized enterprises (SpecSof SMEs) play a critical role. This paper develops a framework from an evolutionary economic geography (EEG) perspective to analyze how these SMEs influence NHPFs. The study assesses the impact of specialized and sophisticated SMEs on NHPFs using OLS and addresses potential endogeneity issues through the application of instrumental variables. The results show that the Specialized and Sophistication Index (SSI) positively impacts NHPFs, with its effect strengthening from the company to the municipal level (by about 25%) but weakening at the provincial and national levels (to half of the municipal level), highlighting a clear marginal effect on regional NHPFs. Additionally, the geographically weighted regression (GWR) model was employed to investigate the complex and spatially varied relationships between key characteristics of specialized and sophisticated SMEs and NHPFs. Our findings suggest that while the relationship between SSI and NHPFs is generally positive, it is spatially heterogeneous, arising from variations in regional economic structures, market maturity, and industrial characteristics. This study provides a theoretical framework for understanding regional disparities in NHPF development through SpecSof SMEs and offers empirical evidence to inform region-specific policies and spatial planning strategies.

： The development level of urban new quality productivity is of great significance for improving regional new quality productivity and leading high-quality economic development. However, the monitoring indicator system for the development level of new quality productivity in mega cities has not yet been systematically defined. On the basis of reviewing relevant policy documents and research literature, this article combined the characteristics of mega cities to determine the connotation of the monitoring and monitoring indicator system for the development level of new productive forces. It further constructed a monitoring system for the development level of new productive forces in mega cities. Then total index and sub-indexes of the monitoring system for the development level of new quality productivity in mega cities were measured based on the monitoring system. Relevant suggestions are proposed based on the calculation results, in order to provide reference for the government and relevant departments.

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Building upon the theoretical foundation of New Quality Productivity Forces (NQPF) and its integration with industrial applications, this study takes wellness tourism as the research carrier and constructs the theoretical framework of “three-dimensional empowerment and four-dimensional evaluation”. Methodologically, We employ an integrated approach combining ArcGIS 10.8 spatial analysis technology with a two-way fixed effects model to empirically examine the spatiotemporal evolution characteristics and driving mechanisms of wellness tourism industries across 30 Chinese provinces from 2014 to 2022. Key findings reveal that: (1) NQPF significantly enhance the resilience of wellness tourism by promoting industrial structure upgrading. (2) Human capital agglomeration, as a critical threshold variable, exhibits a dual-threshold effect on the enabling impact of NQPF, demonstrating a distinct nonlinear leapfrog pattern. This research not only expands the application boundary of NQPF theory in the health field but also provides a reference for the government to formulate health tourism industry policy with both theoretical depth and practical value.

New quality productivity is a kind of advanced productivity form driven by innovation, breaking through the traditional path of dependence, with scientific and technological innovation as its core,

This study examines the impact of the spatial flow of new quality productive forces (NQPFS) and the optimal combination of new quality productive forces (NQPFC) on the high-quality economic development (HQMED) of China’s coastal regions. Based on panel data from 53 coastal cities (2004–2023), the research constructs comprehensive evaluation systems and employs a two-way fixed effects model for empirical analysis. The main findings are as follows: First, Spatial Evolution: The HQMED level of coastal areas shows a continuous upward trend with marked regional disparities, forming a spatial pattern of “one core, two wings” characterized by “Eastern leadership with Northern and Southern regions following.” The inter-city development gap has widened, with the overall spatial structure evolving from a “core-periphery” model toward a clustered stage of “one core, multiple poles, and networked linkage.” Correspondingly, New Quality Productive Forces have transitioned from initial single-point agglomeration to a multi-polar and ultimately networked distribution. Second, both the spatial flow and optimal combination of New Quality Productive Forces exert stable positive effects on coastal HQMED. The marginal contribution of the factor optimal combination is significantly greater than that of spatial flow. Third, two complete mediation pathways are identified: NQPFS promotes HQMED primarily by enhancing the resilience of the marine industrial chain, while NQPFC drives HQMED mainly through cultivating new-quality marine business forms. Fourth, resource misallocation exerts a significant negative moderating effect on the relationship between NQPFS and HQMED. Conversely, a sound innovation ecosystem positively moderates the impact of NQPFC on HQMED. Fifth, the effects exhibit significant regional and institutional variation. Geographically, the impact follows a pattern of “strong in the East, suppressed in the North, and insignificant in the South.” Administratively, core cities demonstrate stronger factor capture and configuration efficiency compared to ordinary cities. The study confirms that facilitating the cross-regional flow and efficient internal recombination of the New Quality Productive Force is crucial for driving coastal HQMED. Policy should focus on reducing resource misallocation to remove barriers to factor mobility, optimizing regional innovation ecosystems to enhance factor synergy, and implementing differentiated strategies that balance the radiating role of core cities with the distinctive development of ordinary cities, thereby fostering a new, coordinated pattern of high-quality development across coastal regions.

The high-quality economic development (HQED) of the Yellow River Basin (YRB) faces dual constraints of growth momentum transformation and regional imbalance. New Quality Productive Forces (NQP) are regarded as a key breakthrough, yet the complex causal mechanisms through which they drive HQED remain unclear. Traditional research methods fall short in uncovering the multifactorial, concurrent causal relationships and the spatio-temporal dynamics involved. Therefore, drawing on panel data from 49 prefecture-level cities in the YRB from 2012 to 2022, this study employs the CRITIC–TOPSIS method and dynamic QCA to measure the HQED index and to explore in depth the configurational pathways and dynamic processes through which NQP evolution fosters the emergence of HQED. The findings are as follows: (1) During the study period, the HQED index of the YRB exhibited a “W-shaped” evolutionary trend, with a spatial gradient of “higher in the east and lower in the west.” (2) No single NQP factor emerged as a necessary condition for HQED. (3) The pathways to HQED in the YRB can be categorized into three models: the single-core innovation–driven model, the region-wide innovation resource synergy–driven model, and the comprehensive digital transformation–driven model. Technological innovation plays a universal role, but its effectiveness requires synergy with other factors to be fully realized. (4) While no obvious temporal effects were observed in the configurational pathways, significant spatial heterogeneity exists, with different urban agglomerations displaying distinct pathway preferences. This study reveals the complex interactive mechanisms through which NQP drives HQED in the YRB and provides refined policy implications for place-based and coordinated regional development.

This paper constructs a comprehensive evaluation index system for new quality productive forces based on three core dimensions: laborers, objects of labor, and means of production. The study emphasizes that improving new quality productive forces is a critical driver for promoting regional development and fostering balanced growth in China's national economy. Using the entropy method, it quantitatively measures the development levels of new quality productive forces across 30 provinces in China from 2012 to 2022. The selection of these 30 provinces excludes Special Administrative Regions, Autonomous Regions, and Municipalities to ensure consistency in administrative structure and data comparability. Data were sourced from official statistical yearbooks and related reports, with normalization conducted to ensure the comparability of indicators across regions and time periods. Furthermore, the Kernel density estimation method is applied to analyze spatial-temporal distribution differences and the dynamic evolution characteristics of new quality productive forces nationwide and in the three major regions: Eastern, Central, and Western China. The results indicate that the overall development level of new quality productive forces shows a continuous upward trend, albeit with significant regional disparities. The Eastern region leads significantly, driven by its strong economic foundation, policy support, and innovation-driven growth. The Central region exhibits fluctuations in certain years and provinces, but the overall development trend remains positive. The Western region has relatively low overall development levels, though provinces such as Sichuan and Chongqing show promising potential. These findings highlight the need for targeted policies to address regional imbalances and unlock new drivers of economic growth.

With the rapid development of international economic integration, industrial competition has gradually evolved from a competition of enterprise capabilities and resources to a game of comprehensive system collaboration capabilities among all participating parties. That is, the competition in the current international economy has evolved into an interactive and collaborative competition among the “three chains” of industry chain, capital chain, and innovation chain. Based on analyzing the current situation of the integration of the industrial chain, innovation chain, and supply chain, this article deeply analyzes the geographical advantages of the three chains in the Beijing-Tianjin-Hebei region. From the perspective of scientific and technological innovation and talent cooperation synergy, it proposes the integration strategy of the three chains in the Beijing-Tianjin-Hebei region.

. The relationship between enterprises is the key to industrial relationships. Strengthening the analysis of industrial spatial networks based on the relationship between enterprises in the construction industry is of great significance to enrich the theoretical research of industrial networks in the construction industry.Based on the transaction relationship data of listed companies in the construction industry and their top five suppliers and customers from 2014 to 2022, this paper constructs the urban network in China, and analyzes the spatiotemporal evolution characteristics of the urban network in the construction industry based on the perspective of inter-enterprise transaction connection. The results show that during the study period, the overall spatial structure of the network spreads from the center of the urban agglomeration to the outside, provincial strong associations were distributed in Beijing, Shandong province, Shanghai, Guangdong province, and the surrounding provinces, and the urban agglomerations on the north slope of Tianshan mountain in northwest China gradually developed and spread within the construction industry urban agglomerations, with the release of urban agglomerations policies, the development and evolution of the network structure gradually transformed into a more balanced and complex stable state.

ABSTRACT This study deconstructs the triple helix structure of urban industry-university-research collaborative innovation into a two-stage chain structure of knowledge innovation and technological innovation. Based on data of 285 China prefecture-level cities from 2004 to 2018, this study measures the urban industry-university-research collaborative innovation performance using the network data envelopment analysis model. Additionally, it clarifies its spatial convergence mechanism and spatial spillover effects using the spatial convergence test and spatial Durbin model. The results suggest that: (1) the performance of China's urban industry-university-research collaborative innovation at different stages shows a spatial pattern with obvious regional differences and diversified development modes. (2) The overall performance shows a trend of gradual σ convergence with a slightly fluctuating rate, and the gap is constantly decreasing. Additionally, it shows an absolute β convergence trend at different stages, with an obvious geospatial club convergence trend in the eastern, central, and western regions. (3) The spatial spillover effects of ‘research-to-production’ performance and overall performance are stronger than that of ‘university-to-research’ performance. Finally, the collaborative innovation performance of various cities is dominated by the polarisation effect, and the its role as the driving force of regional innovation needs to be strengthened.

No abstract available

This study examines the spatiotemporal evolution of China’s grain supply chain resilience and regional disparities from 2012 to 2022, employing provincial data and a multidimensional framework encompassing resistance capacity, adaptive adjustment capacity, and innovation-driven transition capacity, and utilizing entropy weight method, kernel density estimation, convergence models and barrier factor analysis with GIS (v10.8,2) visualization. The results reveal a fluctuating upward trajectory in the composite resilience index. However, spatial heterogeneity persists as Major Grain-Producing Areas demonstrate high resistance capacity but lag in transformation due to path dependency, Major Grain-Consuming Areas excel in innovation yet face vulnerability from import dependence, and Grain Self-Sufficient Areas display rapid adaptive capacity growth but spatial polarization intensifies. Theil index decomposition confirmed that inter-regional disparities dominated, reflecting uneven technological diffusion and institutional priorities. Key drivers include natural endowments, infrastructure investments, and digitalization, though threshold effects in policy regulation and path dependency paradoxes constrain convergence. This study advances a dynamic governance framework to balance resilience trade-offs and align supply chain modernization with sustainable food security goals.

The electronic information manufacturing industry is characterized by a very significant intra-product specialization and can display the characteristics of a regional division of labor. Looking at the existing literature, most studies have mainly examined the position of different countries in the spatial division of labor from the perspective of global value chains, with fewer empirical analyses at the city level or regional scale. Furthermore, deepening the regional division of labor in value chains is an effective way to promote regional industrial synergy and high-quality economic development. Based on the number of listed enterprises and the total number of parent–subsidiary investment connections in the electronic information manufacturing industry, this study reveals the characteristics of the deeper regional division of labor among cities by analyzing the Value Chain Division Index (VCDI). Subsequently, we used the fractional response regression model to analyze influencing factors. We found that, firstly, the core cities are dominated by the production of high-value parts, while the peripheral cities are mainly dominated by the production of middle- and low-value parts. Specifically, northern Anhui, northern Jiangsu, and southwestern Zhejiang are obviously in a disadvantaged position regarding the regional division of labor in the value chain. In the production of middle- and high-value parts, there are close investment connections between the core cities, and only a few peripheral cities maintain a certain degree of connection with the core cities. Therefore, there is a need to further strengthen industrial investment connections between the core and peripheral cities. Secondly, the regional division of labor in the value chain in the Yangtze River Delta region shows the following characteristic: a “one super, many strong” pattern. That is to say, the VCDI value of Shanghai is the highest, and the VCDI value of Suzhou, Ningbo, and Wuxi is also relatively high, while the VCDI value of peripheral cities is relatively low. Furthermore, we found that there is a relatively obvious regional division of labor among cities, but the core cities have strong homogeneity in the high-value areas. Therefore, it is necessary to further strengthen the dislocation of competition between core cities. Thirdly, the model results show that rising land prices and construction in the development zones at the provincial and national levels both have significant contributing effects on the enhancement of the regional division of labor in the value chain, while the innovation inputs, innovation outputs, and their interaction terms show a negative effect. There is a need to further enhance the efficiency of innovation transformation and improve the quality of innovation transformation in order to promote upgrading in the value chain.

The intelligent connected vehicle (ICV) industry is the core arena for the integration of the automotive industry + digital technologies, and the integration of industry and innovation is key to enhancing the sectors competitiveness. Taking Tesla (Shanghai) as the study sample, this paper investigates the pathways of industryinnovation integration in the ICV sector within an urban agglomeration and the spatial support mechanisms that enable it. The study finds that Tesla (Shanghai) achieves industryinnovation integration through the following pathways: (1) staged transformation of R&D focus; (2) upstream firms building R&D bases to strengthen their autonomous core-technology capabilities; (3) construction of localized, vertically integrated supply-chain networks; and (4) realizing industryinnovation coordination through diversified collaboration and standards alignment, thereby expanding brand influence and generating network effects. The paper concludes that Tesla (Shanghai), by establishing the Shanghai Gigafactory as a spatial carrier, has formed a hierarchical distribution of supply chains and a pattern of regional division of labor across Shanghaithe urban agglomerationthe nation, and has made full use of the multidimensional support mechanisms such as preferential policies in the Lingang New Area to drive industryinnovation integration. Finally, the paper offers policy, corporate, and spatial-level lessons for urban agglomerations aiming to develop ICV industry clusters.

With the global increase in disaster risks, enhancing urban resilience has become a critical strategy for risk mitigation and sustainable development. This study develops a two-dimensional indicator framework based on urban systems and resilience capacity from the perspective of the disaster management cycle and applies an improved CRITIC-TOPSIS method to evaluate the resilience levels of the Chengdu–Chongqing urban agglomeration, China. The spatiotemporal evolution of urban resilience from 2010 to 2022 is systematically examined. Furthermore, the dynamics of urban resilience transitions are investigated using a spatial Markov chain model, and the driving factors behind the spatial distribution of resilience are explored through the Geo-detector method. The results indicate the following: (1) Comprehensive resilience demonstrated a steady upward trend during the study period, with Chengdu and Chongqing, as core cities, driving regional resilience improvement and reducing disparities within the urban agglomeration. (2) Significant spatial heterogeneity was observed in the distribution of the comprehensive resilience index and the indices of individual resilience dimensions. (3) The Markov chain analysis revealed a distinct “club convergence” pattern in the dynamic transitions of resilience levels, with development trends closely tied to spatial factors. (4) The Geo-detector model analysis highlighted that infrastructure development and technological innovation exert long-term and substantial impacts on resilience improvement. These findings provide valuable insights for enhancing resilience and promoting sustainable development in the Chengdu–Chongqing region and other similar urban systems.

The Yellow River Basin (YRB) is a significant economic development region in China; however, it faces the challenge of underdeveloped economic levels, which impacts the sustainable development of the national economy. This study constructs an index system for high-quality economic development (HQED) based on five development concepts. The CRITIC method was utilized to comprehensively evaluate 78 prefecture-level cities in the YRB from 2000 to 2022. Techniques such as the Dagum Gini coefficient, exploratory spatial data analysis, Markov chain analysis, and the obstacle degree model were employed to investigate the temporal and spatial evolution of HQED levels and their associated obstacles in the YRB. The findings indicate a positive temporal trend in the HQED index, with increasing intra-group differences and overlapping issues among regions, while inter-group differences are decreasing. Nevertheless, the primary contradiction in the YRB continues to arise from inter-group disparities. Spatially, the development regions are predominantly centered around provincial capitals, exhibiting a pronounced “fault line” phenomenon and characteristic “spatial proximity.” In terms of evolutionary trends, the likelihood of each region maintaining its current state is relatively high; however, regions with higher-quality neighborhoods demonstrate a lower probability of stability and a greater likelihood of upward mobility. The positive impacts of high-quality neighborhoods outweigh the negative effects associated with low-quality areas. In terms of obstacles, factors such as sharing and coordination hinder progress in HQED in the YRB, with challenges related to coordination, innovation, and openness intensifying in recent years.

With the ongoing progress of urbanization, the urban ecosystem is becoming increasingly fragile, exacerbated further by the emergence of urban agglomerations. Based on the ‘Pressure-State-Response’ model and panel data covering the period from 2010 to 2021, the step-by-step vertical and horizontal tiered evaluation method is employed to calculate the scores of ecological resilience in China’s urban agglomerations. The Dagum’s Gini coefficient, global and local Moran’s index, unite strength and unite threshold, Markov chain, and geographic detector are utilized to reveal regional disparities, dynamic evolution, and driving factors of ecological resilience in China’s urban agglomerations. The results reveal several significant findings: (1) The ecological resilience in Chinese urban agglomerations exhibited a fluctuating yet upward trend. (2) Although disparities in the ecological resilience of China’s urban agglomerations are decreasing, differences between them remain significant. (3) Spatial correlation is evident in the ecological resilience of China’s urban agglomerations. High-high clusters are primarily found in the eastern and upgrading urban agglomerations, while low-low clusters are concentrated in the western and fostering urban agglomerations. (4) The number of cities exceeding the ecological resilience threshold is gradually increasing, with core cities playing a pivotal role. (5) The probability of transition in a city is affected by the ecological resilience states of adjacent cities. (6) Driving factors such as Internet penetration rate, informatization level, and innovation capacity have significant but heterogeneous effects on ecological resilience. This paper enlightens that spatial co-governance and zoning management of ecological resilience are crucial for achieving regional ecological security.

Rapid advances in digital technologies are reshaping value creation and the trade landscape of global financial services, yet the channels through which they influence the spatial evolution of financial services global value chains (GVCs) remain insufficiently identified. Using a global panel of 52 countries over 2013–2021, we estimate a dynamic Spatial Durbin Model (SDM) to identify overall effects and quantify spatial spillovers and temporal dynamics. We then combine Geographically and Temporally Weighted Regression (GTWR) with spatial mediation models to examine heterogeneity and underlying mechanisms. Our findings show that digital technology significantly drives the spatial evolution of financial services GVCs. Its influence is dominated by spatial diffusion, exhibiting a dynamic pattern of a strong short-run boost followed by long-run reallocation. This dynamic effect is not homogeneous; rather, it reflects a pronounced dual-driver structure: the momentum is more robust when human capital and R&D output reinforce each other, whereas increases in innovation level alone are unlikely to translate into sustained impetus for spatial restructuring. Crucially, digital technologies reshape GVC geography through three core channels: attenuating distance decay, strengthening spatial proximity, and amplifying spatial heterogeneity. These forces deepen the domestic diffusion of knowledge, capital, and technology and extend their spillovers to neighboring and connected economies. The results provide robust empirical evidence on financial geography in the digital era and have clear implications for policies that facilitate cross-border financial services and strengthen regional coordination in support of the 2030 Agenda for Sustainable Development, particularly SDG 8 (financial inclusion) and SDG 10 (global financial governance).

PurposeAutonomous and connected mobility technologies have led to a reconfiguration of the automotive industry value chain. This may involve an impact on the geography of the European automotive industry, especially for peripheral countries. The aim of the paper is to analyse the repositioning of a peripheral country (Portugal) in the core-periphery model of the automotive industry derived from this new technological context.Design/methodology/approachAn eclectic theoretical framework, based on the global value chain (GVC) approach, the spatial division of labour and location theory, supports this research. Moreover, an original empirical study was developed. This study comprised a comparative analysis of two samples of firms based on the key variables related to country position. One sample comprised Portuguese traditional automotive firms and the other Portuguese firms linked to autonomous and connected mobility technologies.FindingsThe results highlight the upgrading of Portugal in the European core-periphery model of the automotive industry. This is due to the presence of domestic firms, especially multinationals, linked to autonomous and connected mobility technologies in the country. The decision power derived from their position on the first levels of supply and the added value of activities and technological innovation of these new actors change the role of the country in the European automotive industry. The main implication is that managers of domestic firms and policy makers in peripheral countries can upgrade a country’s position in the European core-periphery model by shifting its competitiveness toward knowledge-based activities linked to the new mobility technologies.Originality/valueThis research is supported by a novel eclectic theoretical framework based on the global value chain (GVC) approach, the spatial division of labour and location theory. Moreover, country position is analysed through empirical evidence. An original comparative empirical study based on the key variables defined under this theoretical framework was developed.

As urbanization accelerates globally, higher education agglomeration (HEA) emerges as a critical mechanism for integrating regional economic theories with practical strategies, driving innovation and sustainable development. This paper examines how HEA promotes innovation, human capital accumulation, industrial restructuring, and equitable income distribution across 193 cities in the “Two Transverse and Three Lengthways” urban clusters from 2006 to 2020. Using dynamic panel regression and spatial econometric models, the results show that HEA yields significant local and spatial spillover benefits, particularly in core cities that facilitate knowledge diffusion and resource sharing. Heterogeneity analysis reveals that these positive spillovers are strongest in first-tier, highly developed clusters and third-tier, early-stage clusters but weaker or even negative in second-tier, rapidly expanding regions. These spatial effects grow over time, reflecting the evolving patterns of regional integration. Theoretically, the paper advances the understanding of spatial synergy and spillover mechanisms in HEA in urban clusters. Practically, the findings highlight the need to tailor higher education strategies to the developmental stage of each urban cluster to optimize resource allocation and foster inclusive growth. This paper provides policy insights for using HEA as a catalyst for coordinated urban development.

This study employs a Dynamic Spatial Durbin Model (DSDM) based on panel data from China's 31 provinces spanning 2000–2020 to systematically examine the direct effects and spatial spillover effects of regional innovation investment on high-quality economic development (HQED). Findings reveal that both HQED and innovation investment exhibit significant positive spatial correlations, with spatial dependence intensifying over time. Innovation investment not only substantially promotes local HQED (direct effect: 0.089%) but also generates positive spillovers to neighboring regions through mechanisms such as knowledge spillovers and technology diffusion (indirect effect: 0.061%). These conclusions remain robust when varying spatial weight matrices and dependent variable measurement approaches. The study recommends strengthening the cross-regional coordination of innovation resources, establishing basic research platforms in innovation hubs, and mitigating the “siphon effect” through fiscal transfers to promote coordinated regional development and high-quality growth.

Relevance. University science is the basis for the progressive development of the regions of the Russian Federation, providing new knowledge and ideas, turning knowledge into technology and accelerated development of the cultural environment. The introduction of scientific research into the educational process is necessary and important conditions for maintaining the high professional level of teachers, the formation of professional competencies, and advanced training of future specialists. In the last few years, the main economic processes have demonstrated positive dynamics, which indicates the effectiveness of the implemented strategy of socio-economic development of the region, as well as an effective policy of spatial development of the territory are key factors in achieving a positive trend in the development of the region. Minister of Science and Higher Education V.N. Falkov in April 2024 He stated the need to transform the higher education system, focusing on specialized higher education based on an interdisciplinary approach that will more effectively integrate university science into regional spatial development and the national innovation system.The purpose of the study is to determine the mechanisms of integration of university science in the spatial development of the Voronezh region through the innovation system.Objectives: to analyze the impact of the mechanisms of integration of university science on the trends of spatial development; to analyze scientific and technological development; to formulate the main conclusions about university science as part of the socio-economic system of the territory.Methodology. The general scientific methods of logical analysis, method of desk research, method of systematization, descriptive method were used in the study. Results. The study revealed the key factors that contributed to the positive dynamics of the economy of the Voronezh region and considered the mechanisms of integration of university science into the regional innovation system.Conclusions. In the realities of scientific and technological development there is a need to improve the methods of integration of university science into the regional innovation system, and recommendations related to the optimization of spatial development of the Voronezh region in order to improve the quality and attractiveness of university science on the basis of innovative aspects functioning in the region have been proposed.

This study explains disparities in regional innovation through specific features of regional knowledge bases, including recently discussed concepts such as, technological relatedness, knowledge complexity, and technological complementarity among neighboring regions and regions connected in R&D networks. We employ a spatial autoregressive panel model for 405 European regions to estimate the effects of these characteristics. While being connected to complementary regions and having a high region‐internal technological relatedness are conducive to regional innovation, knowledge complexity has no positive effect interestingly. In illustrative convergence scenarios, we demonstrate the potential of increasing relatedness and complementarity to reduce inequalities in Europe, pointing to important policy implications.

The paper deals with a spatial econometric analysis of 220 European regions. The analysis follows the Mixed Geographically Weighted Regression – Spatial Autoregressive approach. Patent applications were a proxy for innovation output. Instead of traditionally applied geographical proximity, the technological similarity was considered. The results supported the assumption of spatial differentiation of model parameters and indicated that regional innovation activities do not have only a local character in almost half of the regions. The region's technological similarity appears to be a significant factor stimulating innovation for regions that are not among the top innovators.

The existing literature has not discussed spatial interconnectedness in the case of agglomeration and productivity for the Indian manufacturing sector. The study aims to bridge the gap in understanding the impact of regional interdependence mediated by skill, infrastructure and labor diffusion on total factor productivity (TFP). This study uses factory-level panel data for the Indian manufacturing sector and uses spatial autoregressive (SAR) and spatial Durbin model (SDM) based on distance and contiguity spatial weight matrix. The findings suggest that there exists positive spatial correlation for TFP, indicating that states share close interdependent productivity patterns. There exists a non-linear relationship between productivity and agglomeration. Further, manufacturing performance is enhanced when skill intensity is integrated with investment in information and communication technology, resulting in synergistic effects. It is evident from spatially lagged explanatory variables, carbon emission and energy intensities that highlight the role of productivity spillover across the regions, highlighting the role of heterogeneous industrial and resource concentration. Policymakers in India should focus on spatial interconnectedness between the regions. There should be a push for balancing the industrial concentration, strengthening digital infrastructure and enhancing skills for the synergistic productivity gains. Given India’s diverse industrial structure and heterogeneous industrial concentration, the findings highlight the need for a balanced and integrated regional policy for India, as the productivity of one region is affected by the other neighboring region. It advocates for a spatially coordinated regional planning and development of industrial corridors that can harness the spillovers. Further, investment should be made in infrastructure development and skill enhancement, which can further increase the benefits of the agglomeration. The findings highlight the need for a balanced and integrated regional policy for India, as the productivity of one region is affected by the other neighboring region. It advocates for a spatially coordinated regional planning and development of industrial corridors that can harness the spillovers. Further, investment should be made in infrastructure development and skill enhancement, which can further increase the benefits of the agglomeration. This study is novel as it is the first study to integrate spatial econometric methodology to understand the impact of agglomeration on the productivity of the Indian manufacturing sector. It offers a comprehensive understanding of the development of spatially formed policies and highlights spillover effects across states.

Regional development has a significant impact on Rural Industrial Integration (RII), which substantially boosts economic growth in rural regions and decreases the economic disparity between rural regions and urban areas. Addressing the Spatio-Temporal Patterns (STP) of RII and the factors that impact these developments is essential for today's economies to attempt balanced regional development successfully. The objective of the present study is to investigate the STP of RII during time considering Zhejiang Province, China, as a case study. The present research examines the primary social, economic, and environmental variables that result in RII applying spatial economic frameworks like Adaptive Geographically Weighted Regression (AGWR) and Multiscale Geographically Weighted Regression (MGWR). The research study evaluated how they relate and impact these factors to integration across multiple spatial scales. With AGWR and MGWR values achieving 0.0083 and 0.0085, respectively, the study indicated that the most significant variable determining RII is the development of urban infrastructure. Significant grouping impacts have been shown by the spatial autocorrelation (Moran's I) for this metric, which attained values that were as high as 0.4205. Significant variables comprised the cost of investment and the urban-rural per capita disposable income (PCDI) proportion, with PCDI ratio ratios of 0.0053 (AGWR) and 0.0056 (MGWR), respectively.

No abstract available

The integrated development of rural industry is an important path to accelerate rural revitalization, promote modernization of agriculture and rural areas, and build a strong agricultural country. Based on the evaluation index system of rural industrial integration, the level of rural industrial integration of 31 provinces (municipalities and autonomous regions) in China is measured from 2012 to 2022; ArcGIS, exploratory spatial data analysis method, and Tobit model are used to classify the level of rural industrial integration, explore the spatial distribution characteristics, and analyse the influencing factors, respectively. The results show that: (1) Rural industrial integration indicator scores show an increasing trend. (2) The level of rural industrial integration varies greatly from region to region, generally showing the development trend of eastern region > central region > western region. (3) The comprehensive level of rural industrial integration and other subsystems in general show significant polarised agglomeration. (4) There is regional heterogeneity in the impact of different factors on rural industrial integration. In view of this, it is recommended to improve the benefit linkage mechanism, give full play to the regional characteristics and advantageous resources of each region, and strengthen inter-regional exchanges and cooperation.

The innovation atmosphere of industrial parks, a crucial indicator of urban spatial vitality and regional economic dynamism, is difficult to assess using traditional, experience-driven methods. To overcome these limitations, this study proposes a novel, data-driven framework for urban spatial perception using Multimodal Large Language Models (MLLMs). Focusing on typical industrial parks in Wuhan, China, we harnessed MLLMs to interpret multi-source urban data, validating their diagnostic accuracy against expert evaluations. Subsequently, we simulated the diverse cognitive perspectives of four key stakeholder groups to diagnose the innovation atmosphere, diagnose the innovation atmosphere, quantifying the subjective spatial perceptions of different user groups and reflecting a nuanced understanding of human-environment interactions. The principal findings are: (1) The diagnostic assessments from the Gemini-2.5-pro model demonstrated a significant correlation (r = 0.890, p < 0.001) with the expert judgment baseline, affirming the high feasibility of this data-driven approach. (2) The MLLM framework effectively quantified perceptual heterogeneity among simulated stakeholders, offering deep insights into the varied dimensions of the parks’ city image and perceived quality. (3) Spatial analysis revealed a consistent overall assessment of the innovation atmosphere across different perspectives, with parks in the southeastern and northwestern regions exhibiting higher spatial vitality. This research contributes an objective and automated tool for diagnosing the innovation atmosphere, a key facet of urban spatial perception. Crucially, the proposed framework provides robust empirical support for big data-driven strategies in urban planning, enabling the refined management of innovation spaces to be more productive, collaborative, and sustainable.

Since a few years, the international economic system has been experiencing the risk of growing fragmentation and uncertainty. However, research on Regional Innovation Systems (RIS) has yet to comprehensively engage with this phenomenon, despite its (spatial) significance. The paper contributes to addressing this gap, in particular by exploring the potential implications for RIS arising from the decline, disruption or reconfiguration of international knowledge flows associated with economic de‐globalisation. The study seeks to define a theoretical approach grounded in economic geography to assess this trend. It applies such perspective to three types of RIS (metropolitan, old industrial and peripheral) across five analytical dimensions that capture the structural and relational factors shaping RIS exposure and resilience to de‐globalisation. The discussion highlights that, in the face of knowledge and technological disruptions or shifts arising from international instability, metropolitan RIS may leverage their diversified knowledge bases, dense institutional frameworks and strong global connectivity to successfully reconfigure external linkages; old industrial RIS may follow mixed trajectories, with the risk of deepening economic and policy lock‐ins; while peripheral RIS, due to their reliance on external knowledge sources and limited endogenous innovation capacity, emerge as the most vulnerable.

In the context of globalization and accelerating digitalization, companies’ patent activity has become a key factor in regional economic growth. This paper examines the impact of spatial concentration and interaction effects, as well as government support, on the number of patents filed by technological companies in European regions. The key differences among Marshall, Jacobs, and MAR (Marshall–Arrow–Romer) effects are analyzed in terms of specialization or concentration, types of interactions, and assessment tools. An econometric analysis was conducted using statistical data from 124 regions for the period 2017–2022. The results demonstrate that a significant share of industrial companies exhibit a high level of technological intensity. The COVID‑19 pandemic negatively affected the resilience of European industries, leading to disruptions in supply chains and shortages of goods and components. Nonetheless, industries with high innovation intensity experienced faster growth rates. For most European countries, moderate growth in the number of patent applications was observed, reflecting a general interest in innovation. However, large economies such as Germany, Switzerland, and France continue to dominate, while smaller countries display either rapid growth or unstable trends. Agglomeration processes in regions have a positive impact on companies’ patent activity. The relationship between these two indicators strengthened during the 2017–2022 period, driven by the creation of favorable environments for innovation and knowledge exchange. In regions where enterprises, research institutions, and skilled labor are concentrated, interactions among companies, universities, and research centers intensify, accelerating the diffusion of ideas and technologies. An increase in the Herfindahl-Hirschman Index, which measures market concentration, leads to a decrease in the number of patent applications in European regions. This can be technically explained by the predominance of large and medium-sized companies in the sample, which are the primary filers of patent applications. However, such growth in market concentration may also reduce competition and resource availability for new entrants, as well as diminish incentives to develop new technologies. Addressing this issue requires fostering competition, creating equal opportunities for startups and small businesses, and incentivizing investment in research activities. Government support has a positive effect on patent activity. The scientific novelty of this study lies in identifying spatial and institutional factors that contribute to enhancing the innovation potential of European regions. The practical significance of the research lies in its potential application for developing policy recommendations aimed at stimulating regional innovation activities.