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Carbon emission issues are becoming increasingly severe, and the carbon emissions in shrinking cities, primarily characterized by population loss, are often overlooked and insufficiently studied. This paper focuses on the carbon emissions from county-level administrative units in China's three northeastern provinces from 2001 to 2017. The study scientifically identified shrinking cities and measured the differences in carbon emission characteristics between growing and shrinking cities using the Theil index. Ultimately, the paper constructs a panel spatial econometric model to analyze the factors influencing them and explore their spatial effects. (1) The total carbon emissions in the Three Northeastern Provinces exhibited an inverted U-shaped trend, increasing from 734.21 million tons in 2001 to 1731.73 million tons in 2017, with the Mann–Kendall trend test showing a significant increase; spatially, this manifests as a significant positive spatial autocorrelation. (2) The region has 138 shrinking cities, accounting for over 50%; regarding carbon emission characteristics, the Theil index has consistently remained above 0.18, indicating significant differences between the carbon emissions of growing and shrinking cities. (3) The panel spatial econometric model results show that the influencing factors of carbon emissions in shrinking cities have unique directions, intensities, and spatial effects. In shrinking cities, aside from localized GDP effects and per-capita GDP acting as a suppressant, the population size has a pronounced inhibitory effect on local and surrounding carbon emissions. The analysis reveals significant differences in the carbon emission patterns and mechanisms between growing and shrinking cities; based on these results, the paper proposes differentiated carbon control strategies. [ABSTRACT FROM AUTHOR]

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities. [ABSTRACT FROM AUTHOR]

The regional networking strategy is widely implemented in China as a normative policy aimed at fostering cohesion and enhancing competitiveness. However, the empirical basis for this strategy remains relatively weak due to limitations in measurement methods and data availability. This paper establishes the urban networks by the enterprise investment data, and then accurately measures the network's external effects of each city by the method of MGWR model. The results show that: (1) Regional networking plays a significant role in urban development, although it is not the dominant factor. (2) The benefits of network connections may vary depending on the location and level of cities. (3) The major cities assume a pivotal role in the urban network. Based upon the aforementioned research conclusions, this paper presents strategic measures to enhance the network's external impacts, aiming to offer insights for other regions in formulating regional development strategies and establishing regional urban networks. [ABSTRACT FROM AUTHOR]

With the increasing uncertainty of urban security, urban resilience construction with risk awareness and bottom-line thinking has become essential for promoting sustainable urban development. This paper measures China's urban resilience development index (CRDI) based on 284 cities in China (except Tibet) using the entropy method from four dimensions: economic, social, environmental, and infrastructure, and analyzes it by combining coupling coordination degree and barrier factor analysis. We find that: (1) At the national level, CRDI and its sub-dimensions show an increasing trend in time, a decreasing spatial layout from coastal to inland, and a "high-high-low-low" clustering feature in space. (2) At the regional level, the CRDI is from high to low in the east, middle, and west order. The sub-dimensions are from high to low in the order of east, middle, and west for economic, social, and infrastructure resilience and from high to low in the order of east, west, and middle for environmental resilience. (3) To coupling coordination degree, the CRDI index coupling coordination is increasing in time trend but is still on the verge of dissonance. (4) Social resilience is the main obstacle factor. In the indicator layer, human resources, innovation, education, security, living, and environmental protection are the areas where CRDI coordinated development is the key to improvement. Based on the above empirical evidence, this paper proposes countermeasures to optimize urban resilience construction from four perspectives: economic, social, environmental, and infrastructure. [ABSTRACT FROM AUTHOR]

During the past 40 years of reform and opening-up, the implementation of an unbalanced enhancement strategy has led to severe resource misallocation, making the mitigation and rectification of this misallocation an urgent issue. This paper utilizes urban data from China between 2006 and 2020 to examine the impact of two-way foreign direct investment (FDI) on resource misallocation, as well as the pathways through which coordinated advancement of two-way FDI affects resource misallocation. After undergoing a series of robustness and endogeneity tests, the conclusion remains stable. Mechanism testing reveals that coordinated advancement of two-way FDI improves capital resource misallocation by enhancing the enhancement level of the financial industry, while exacerbating labor misallocation by increasing labor costs. This paper integrates the coordinated advancement of two-way FDI and resource misallocation into the same analytical framework, proposing policy recommendations to alleviate China's resource misallocation issue. [ABSTRACT FROM AUTHOR]

The virtual water flow behind product trade provides researchers with ideas to alleviate water problems in China's coastal areas, with accompanying resource and economic implications. This paper adopts a multi-region input–output model to calculate virtual water flows in coastal areas and analyses resource benefits and economic benefits, by combining the water stress index and shadow price, to measure gains and losses of virtual water flow. This study shows that (1) China's coastal areas depends on external water supplies; (2) virtual water flows between coastal and inland areas generated 38.26 billion m3 of net scarce water savings and CNY 31,751 billion of net economic benefits, indicating that coastal areas benefited from virtual water flows from both resource and economic perspectives; (3) virtual water flows among coastal provinces and cities caused 11.10 billion m3 of net scarce water losses, but generated CNY 9784 billion of net economic gains, indicating that a further intensification of water stress in coastal areas, but such a virtual water flow pattern was beneficial from an economic perspective. This paper reveals the resource and economic impacts of virtual water flow at the national scale and among coastal provinces and cities and further proposes suggestions for promoting the beneficial flow of virtual water in coastal areas. [ABSTRACT FROM AUTHOR]

China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions. [ABSTRACT FROM AUTHOR]

In the critical period of strengthening the construction of ecological civilization, the construction of forest cities has become an important measure to promote urban ecosystem restoration and achieve sustainable development. Based on the mechanism of forest city promoting green development, the construction of a national forest city is regarded as a "quasi-natural experiment". Using China's urban panel data from 2005 to 2019, the impact of national forest city construction on urban green total factor productivity was evaluated using Multistage asymptotic double difference. The results show that National Forest Cities with environmental regulation can significantly promote regional green total factor productivity, which is still valid after a series of Robustness tests. Mechanism analysis shows that forest city construction not only affects territorial spatial planning but also forms a linkage with green technology innovation, mutual promotion and mutual promotion to jointly promote the sustainable development goals. This paper argues that building a national forest city is an important measure to achieve China's sustainable development goals in the new era, but in the process of policy implementation, it is necessary to implement the national forest city selection system according to local conditions. [ABSTRACT FROM AUTHOR]

Since entering the 21st century, many developing countries around the world have begun to enter a stage of rapid urbanization; large-scale "rural-urban" population migration has become a typical social phenomenon in these countries. Against this backdrop, this paper aims to elucidate the spatial migration characteristics of rural populations and to discuss future rural–urban development strategies. For this purpose, this paper takes China as a case and employs methods such as spatial autocorrelation analysis, hotspot analysis, and network analysis to construct an intercity migration network of rural migrants and analyze its spatial characteristics and internal structure. The results indicate that the migration pattern of the rural population exhibits notable spatial clustering features. Cities in the eastern and central regions are, respectively, hotspots for the inflow and outflow of rural populations, with internal migration dominating in western cities and relatively inactive rural population movements in northeastern cities. Municipalities directly under the central government, sub-provincial cities, and provincial capitals show a significant tendency to attract rural populations, while prefecture-level and county-level cities mainly radiate rural populations outward. Cities nationwide form seven major clusters in the migration network, and these clusters exhibit distinct structural characteristics. Rural population migration is influenced by various factors. In the future, considerations should focus on the county as the primary unit, attracting rural populations for local employment, and promoting rural revitalization and agriculture development. The findings of this paper are of reference significance not only to China but also to many developing countries with similar national conditions in the world. [ABSTRACT FROM AUTHOR]

In the process of global urban development, there are urgent ecological security and environmental pollution problems, green development is the fundamental way for urban sustainable development, economic transformation and mitigation of ecological and environmental problems. Based on the panel data of 283 cities at prefecture level and above in China from 2003 to 2017, this paper analyzes spatial–temporal evolution characteristics of urban green development efficiency (UGDE) and the peer effects of UGDE between cities of different grades. It is found that during the study period, in terms of temporal evolution, the average UGDE in China increased from 0.47 in 2003 to 0.61 in 2017, with a cumulative growth rate of 29.79%, showing a rising trend in general. In terms of spatial evolution, the number of low-efficiency cities and medium-efficiency cities continued to decrease. The eastern region has always been the main distribution area of higher-efficiency cities and high-efficiency cities; in the central region, UGDE in most cities improved significantly; in the western region, UGDE has always lagged behind that in the eastern and central regions. In addition, the center of gravity of UGDE presented a trend of northwest migration in general, with a total displacement of 100.07 km, and UGDE showed a spatial dispersion trend. The empirical results indicate that the improvement of UGDE in large cities has a driving effect on that in neighboring medium cities and small cities through the positive peer effect, and the growth of UGDE in medium cities has a promoting effect on that in neighboring small cities through the positive peer effect; the increase of UGDE in medium cities has a positive peer effect on that in neighboring large cities, and the growth of UGDE in small cities has a positive peer effect on that in neighboring medium cities; UGDE promotes each other between large cities through the positive peer effect. [ABSTRACT FROM AUTHOR]

Introduction: With the rapid development of digital technology and its deep integration with environmental and ecological fields, the digital economy has become an effective way to guide the transition of cities to an eco-friendly model. However, empirical studies on the nonlinear spatial effects between digital economy and ecological welfare performance are still insufficient. Methods: Based on the panel data of 270 prefecture-level cities in China from 2011 to 2020, this paper empirically examines the impact of the digital economy on the ecological welfare performance of cities and its mechanism of action using spatial econometric modeling. Results: The promotion effect of digital economy development on the ecological welfare performance of cities is characterized by the "J" shape of increasing marginal effect, and the spatial spillover effect on the ecological welfare performance of neighboring cities is the inverted "U" shape of inhibiting first and then promoting later. The mechanism test shows that the development of digital economy can enhance the ecological welfare performance of cities through the marginal incremental promotion of green technological innovation in local and neighboring cities and has a positive spatial spillover effect. The development of digital economy can have a direct U shape effect on local ecological welfare performance by influencing factor allocation efficiency and energy utilization efficiency. It also has an inverted U-shaped spatial spillover effect. Environmental regulation has an inverted U-shaped moderating effect on the local eco-welfare performance affected by the digital economy. As the level of rural revitalization increases, it produces a U-shaped moderating effect of inhibiting. Heterogeneity analysis reveals that digital economy development has a more significant facilitating effect and a positive spatial spillover effect on the ecological welfare performance of cities in central China. Discussion: This paper will provide a reference for the synergistic optimization of digital economy development and ecological welfare performance among regions. The findings of the study will promote the development of digital economy and accelerate the realization of the goal of "Beautiful China". [ABSTRACT FROM AUTHOR]

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006–2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations. [ABSTRACT FROM AUTHOR]

Judicial improvement and trade structure optimization are important elements in achieving a high level of openness. This paper develops a theoretical framework on the impact of local protectionism on market integration and export technical complexity, and then empirically analyses the effect of judicial improvement on the technical complexity of urban product exports and its mechanism of action based on a quasi-natural experiment with the establishment of circuit courts. The study finds that the establishment of circuit courts significantly increases the technical complexity of product exports, and the findings remain valid after a series of robustness tests. Further analysis shows that the technology enhancement effect of the establishment of circuit courts is more pronounced in the group of cities with higher administrative levels, better location advantages, and less advanced rule of law. Mechanism Analysis shows that a superior institutional environment can have a two-sided effect on different types of firms. Overall, however, the productivity-enhancing effect of low-productivity firms exiting the market is lower than the productivity-reducing effect of higher-productivity firms' increased compliance costs, which in turn weakens the positive promotional effect of circuit courts. The above theoretical and empirical findings provide policy implications for maximizing the technology enhancement effect of the establishment of circuit courts on product exports, thereby promoting a high level of openness in China. [ABSTRACT FROM AUTHOR]

With the intensification of global economic competition, innovation has become one of the core elements of vigorous development in various regions. Improving the innovation ability of cross-regional central cities is the main factor influencing whether a region can achieve economic and social development. In this paper, an innovation primacy index system is designed according to the links of the innovation value chain, and the innovation advantages and empirical effects are comprehensively analyzed by using the point-to-point method, entropy weight method, gravity model and two-way fixed effect model. Based on the data of 8 cities in the core area of the Huaihai Economic Zone from 2010 to 2020 in China, Xuzhou's innovation primacy ranks first in the core area of the Huaihai Economic Zone, which accords with its status as the central city of the region. Its index has been rising, and its development trend is also good. However, the overall innovation ability of the core area of the Huaihai Economic Zone is unbalanced; the overall economic foundation is not solid enough. In terms of knowledge innovation, R&D innovation and industrial innovation, the industrialization level, around the activation of Xuzhou city vitality, enhances the Xuzhou innovation radiation drive, leading to a decrease in the Huaihai Economic Zone. Finally, some corresponding suggestions on innovation primacy have been proposed for the city of the Huaihai Economic Zone. [ABSTRACT FROM AUTHOR]

In the knowledge economy era, innovation has become a key emphasis for urban competitions. This paper constructs a theoretical research framework that integrates the basic understandings, influencing factors and ensuing results of intercity innovative competition relations. On the basis of data from the general programs of the National Natural Science Foundation of China from 2005 to 2019, this paper constructs intercity innovative competition relations in China, analyses their spatial distribution and quantitative characteristics, and quantitatively investigates the impact of urban innovation capacity and multidimensional proximity (e.g., geographical proximity, institutional proximity and cognitive proximity) on intercity innovative competition relations through a negative binomial model. The study obtained the following findings: (1) In terms of the overall intercity innovative competition relations, the intensity of China's intercity innovative competition relations gradually increased from 2005 to 2019, with a spatial clustering towards cities with high administrative ranks (e.g., municipalities directly under the central government, sub-provincial cities and provincial capitals); Beijing is always at the centre of innovative competition relations, but its standing has slightly slipped in recent years. (2) From the perspective of disciplines, cities can become benchmarks in particular fields of innovative competitions by competing according to their disciplinary strengths; intercity innovative competition relations in China vary across various academic disciplines. (3) In terms of influencing factors, urban innovation capacity has significant positive effects on intercity innovative competition relations; geographical proximity, institutional proximity and cognitive proximity all have significant positive effects on innovative competition relations; and interactions occur between multidimensional proximities, including a complementary effect between geographical proximity and institutional proximity, a substitutive effect between cognitive proximity and geographical proximity, and a substitutive effect between cognitive proximity and institutional proximity. [ABSTRACT FROM AUTHOR]

As the digital revolution deepens, the digital economy (DE) is reshaping the global industrial structure (IS). This paper utilizes data from 280 Chinese cities between 2007 and 2020 to conduct an in-depth analysis of how DE propels the upgrading of IS and explores the role of human capital (HC) in this process. The research indicates that DE significantly fosters the optimization of IS. Additionally, it was discovered that the growth of HC plays a pivotal mediating role in this evolution, complementing existing research on the relationship between higher education and industrial upgrading. By adopting spatial econometric methods, this study unveils the spillover effects of DE in geographical space, identifying a positive influence on the industrial upgrading of surrounding regions. The paper also confirms the nonlinear characteristics of DE's impact on IS upgrading, which manifests as a pronounced inverted U-shaped trend, marking a novel discovery. Further findings suggest that in regions with more advanced artificial intelligence technologies, the impact of DE on industrial optimization is more significant, highlighting the role of regional disparities in the digital transformation. In conclusion, the paper proposes policy recommendations based on the research findings to facilitate the development of DE and the elevation of IS levels, thereby promoting high-quality economic growth. [ABSTRACT FROM AUTHOR]

Food consumption has resulted in great carbon emissions in recent years. China has been facing the new mitigation challenge of carbon emissions with its emerging middle-income groups, especially in urban areas. This paper analyzes and predicts carbon emissions from food consumption (CEFC) of middle-income groups in the Yangtze River Economic Belt (YREB), which has a higher emerging middle-income group and the highest economic corridor in China. Few studies address CEFC analysis from middle-income groups perspective; thus, this paper calculates urban–rural CEFC of middle-income groups spanning 2010–2018 and predicts them in 2025, 2030 and 2035 using the extended IPAT model. Results are as follows: (1) YREB's urban–rural CEFC of middle-income groups show an upward trend and present a spatial pattern of "low–high–low–high" from the western region to the eastern region. Urban CEFC of middle-income groups are significantly higher than that of rural areas; (2) rural CEFC of middle-income groups in the YREB will first increase in 2025 and then decrease in 2030 and 2035. The growing trend of urban CEFC of middle-income groups will show a significant downward from 2025 to 2035. The growing proportion of urban CEFC of middle-income groups will exhibit an objective growth in 2035. Understanding the changing trend of CEFC of middle-income groups provides governments with differentiated and forward-looking suggestions toward coordinating middle-income groups' expansion and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

Two-wheeled non-motorized vehicles (TNVs) have become the primary mode of transportation for short-distance travel among residents in many underdeveloped cities in China due to their convenience and low cost. However, this trend also brings corresponding risks of traffic accidents. Therefore, it is necessary to analyze the driving behavior characteristics of TNVs through their trajectory data in order to provide guidance for traffic safety. Nevertheless, the compact size, agile steering, and high maneuverability of these TNVs pose substantial challenges in acquiring high-precision trajectories. These characteristics complicate the tracking and analysis processes essential for understanding their movement patterns. To tackle this challenge, we propose an enhanced You Only Look Once Version X (YOLOx) model, which incorporates a median pooling-Convolutional Block Attention Mechanism (M-CBAM). This model is specifically designed for the detection of TNVs, and aims to improve accuracy and efficiency in trajectory tracking. Furthermore, based on this enhanced YOLOx model, we have developed a micro-trajectory data mining framework specifically for TNVs. Initially, the paper establishes an aerial dataset dedicated to the detection of TNVs, which then serves as a foundational resource for training the detection model. Subsequently, an augmentation of the Convolutional Block Attention Mechanism (CBAM) is introduced, integrating median pooling to amplify the model's feature extraction capabilities. Subsequently, additional detection heads are integrated into the YOLOx model to elevate the detection rate of small-scale targets, particularly focusing on TNVs. Concurrently, the Deep Sort algorithm is utilized for the precise tracking of vehicle targets. The process culminates with the reconstruction of trajectories, which is achieved through a combination of video stabilization, coordinate mapping, and filtering denoising techniques. The experimental results derived from our self-constructed dataset reveal that the enhanced YOLOx model demonstrates superior detection performance in comparison to other analogous methods. The comprehensive framework accomplishes an average trajectory recall rate of 85% across three test videos. This significant achievement provides a reliable method for data acquisition, which is essential for investigating the micro-level operational mechanisms of TNVs. The results of this study can further contribute to the understanding and improvement of traffic safety on mixed-use roads. [ABSTRACT FROM AUTHOR]

The organizational forms of infrastructure in China are divided into two categories, the traditional Public Procurement Model (PUB) model and Public–Private Partnership(PPP) model. The main difference is the separation or binding of the construction and operation phases. A systematic understanding is needed of how Chinese local governments choose between these two models. In this paper, we take public capital congestion and local government objectives as the entry point to study the effects of both on PPP choice. Firstly, by constructing an endogenous economic growth model under the PPP model, and comparing it with the model under the PUB model, this paper initially explains how the rise in public capital congestion affects the choice of the PPP by growth-oriented local governments. Then the data from prefecture-level cities from 2009–2018 are utilized to conduct empirical tests. We find that urban economic growth pressures have a positive effect on the choice of PPP when the congestion of public capital increases. Furthermore, the implementation of PPP is indeed conducive to economic performance, and its core mechanism is to provide more infrastructure (like roads) rather than tax competition. The PPP model is more sustainable. We are the first to employ both modeling approach and the empirical research to address the implementation of Public–Private Partnership in China. And we have systematically analyzed the conditions and results of PPP selection by local governments. It formulates the Chinese PPP theory. [ABSTRACT FROM AUTHOR]

This paper presents new evidence on knowledge flows in the Beijing-Tianjin-Hebei region of China, involving 43 cities (districts) in the Beijing-Tianjin-Hebei region, based on the invention patent transfer data from the State Intellectual Property Office of China. First, the characteristics of technology flows in the Beijing-Tianjin-Hebei region are analyzed in terms of changes in the number of flows, types of flowing subjects and spatial distribution characteristics. Then, a multi-level patent technology flow network in the Beijing-Tianjin-Hebei region was constructed, and the structural characteristics and node characteristics of each level network were explored separately. The key findings of the study are as follows. (1) The number of patented technology flows has been growing over time, showing obvious phase characteristics during the study period. As a whole, the intra-city (district) technology flow in the Beijing-Tianjin-Hebei region is higher than the inter-city (district). (2) The multi-level patent technology flow network in the Beijing-Tianjin-Hebei region shows dynamic characteristics, with more and more mobile subjects participating in the patent technology flow network, some network nodes becoming closer to each other, and the trend of small group technology flow increasing significantly. (3) Enterprises are the core hub of the patent technology flow network in Beijing-Tianjin-Hebei region. Individual invention patent technology transfer also occupies a high proportion and the participation of universities and colleges in the patent technology flow network in the Beijing-Tianjin-Hebei region is gradually increasing. (4) Over time, the flow of patent technology in the 43 cities (districts) in the Beijing-Tianjin-Hebei region has gradually become active and no longer relies excessively on a particular city (district) for patent technology transfer. [ABSTRACT FROM AUTHOR]

The accountability audit of natural resources (AANR) is a major institutional arrangement for advancing the construction of an ecological civilization in China. Based on the panel data of 271 cities in China from 2005 to 2017, this paper investigates the relationship between the AANR and carbon dioxide (CO2) emissions using a multi-period difference-in-differences (DID) model. The results show that AANR significantly increases the CO2 emission reduction rate by 0.009 units at the 5% significance level. The results still hold after a series of robustness tests. Given all else being equal, this significant effect is 0.001. Further analyses show that AANR improves pilot cities' CO2 emission reduction rates mainly by enhancing their green innovation capability. The mediating effect of cities' green technology innovation capability accounts for 96.00%, while the AANR's direct effect only accounts for 4.00%. The AANR has significantly positive effects of 0.017% and 0.029% for western cities and cities with high fiscal pressure at the 5% and 1% significance levels, respectively. Therefore, strengthening AANR implementation by enhancing the mediating efficiency of cities' green technology innovations and implementing dynamically differentiated AANR policies in Chinese meso-cities will contribute to the achievement of China's carbon peaking and carbon neutrality targets. [ABSTRACT FROM AUTHOR]

While economic development brings serious environmental problems, technological advances can effectively reduce pollution, which helps to achieve the Sustainable Development Goals. Although the impact of green technology innovation on atmospheric pollutants and carbon emissions has been extensively studied, the effect of such innovation on pollutant reduction varies due to the diverse regional distribution characteristics of different pollutants. Thus, this paper contributes to the literature by examining the influence of green technology innovation on water pollution from a regional perspective, with a particular emphasis on the pronounced clustering of wastewater pollution in China's coastal areas. Both Fixed-Effect model and spatial analysis are adopted. Our findings reveal a significant U-shaped relationship between technology innovation and water pollution, as measured by both industrial wastewater and the ratio of unprocessed sewage. Interestingly, this pollution reduction effect also exhibits a U-shaped spatial spillover. Given the rapid development of the digital economy, it can further amplify the spatial spillover effect of green innovation, especially in eastern regions. This study also provides recent empirical evidence from China to the Environmental Kuznets Curve. [ABSTRACT FROM AUTHOR]

Scientific and technological innovation and ecological progress are important forces for China's high-quality development. Nevertheless, the current body of research seldom explores the mutual dependence and evolutionary patterns of the two regional systems when considering both historical and future perspectives. This paper aims to enhance the current theoretical research framework by focusing on the coastal region of China. It analyzes and predicts the co-evolution and space–time distribution process of two systems by constructing a coupled model and a gray prediction model. The results show the following: (1) the coupling and coordinated development level of the two coastal systems has basically reached the stage of good coupling and coordinated development, and the level has increased, but the gap has gradually increased, and Jiangsu and Guangdong have reached the leading level; (2) the spatial distribution in coastal areas is uneven, showing a convex spatial pattern of "high in the middle and low at both ends"; (3) during the forecast period, the overall coupling and coordination level of the two systems will continue to improve, but individual cities still cannot jump out of the development state of slow development processes. With the aim of fostering the harmonious growth of both systems at both regional and national levels, this paper proposes practical recommendations concerning the establishment of a sustainable interaction mechanism, the evolution of the industrial structure towards ecological sustainability, and the economic contribution to scientific and technological innovation. Furthermore, this article serves as a valuable reference for advancing the sustainable development of other nations. [ABSTRACT FROM AUTHOR]

In response to the intensification of urbanization, characterized by increasingly dense land use, the proliferation of high-rise residences has emerged as a predominant housing solution, particularly evident in developed cities like those in China. With a primary aim of enhancing the residential living environment within high-rise structures, this study advocates for a comprehensive whole life cycle perspective. By employing digital technology and conducting experiments centered on a representative case study, this paper focuses on optimizing the functional layout of public activity spaces within high-rise residential projects. Specifically, this article aims to address challenges such as the inadequate configuration and articulation of various public spaces, along with the underutilization of peripheral activity areas. Central to the optimization efforts is the utilization of the Kruskal algorithm, which enables the analysis of flow lines and functions, ultimately leading to the derivation of optimal solutions. Through a detailed analysis of our case study, this paper provides actionable insights into enhancing the feasibility and effectiveness of public spaces within high-rise residential projects. Recognizing the pivotal role of public space layout in shaping residents' living experiences, the importance of addressing this issue early in the design phase was emphasized. By integrating scientifically driven digital technology solutions, smart, inclusive, and convenient communities that cater to the diverse needs of their inhabitants are aspired to be created. [ABSTRACT FROM AUTHOR]

Green finance (GF) is recognized as a key driver of sustainable development. While existing studies have extensively discussed the relationship between GF and the Sustainable Development Goals (SDGs), few have explored the coupling coordination relationship between GF and SDGs. In this paper, we use data from thirty Chinese provinces (municipalities and autonomous regions) from 2008–2021 to examine the degree of coupling coordination development (CCD) between GF and the SDGs systems using the CCD model. We find that most SDGs and their sub-goals exhibit a significant upward trend, except for SDG8, 14–16. GF presents a fluctuating upward trend, with a significant decline in 2010 and 2019. The CCDs between GF and SDGs and their sub-goals generally show an M-shaped upward trend in most regions, with most of them experiencing a synchronous decline in 2011–2012 and 2019. In the analysis of regional heterogeneity, the eastern region performs better in SDG8–9, the central region performs better in SDG3, 14–15, while the western region performs better in SDG7. This paper provides empirical evidence for a further in-depth understanding of the relationship between GF and SDGs, which can contribute to advancing GF development and the SDG process. [ABSTRACT FROM AUTHOR]

The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China's urban industrial green TFPs as derived from the STE-SRM, employing Dagum's Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China's urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China's urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China's urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods. [ABSTRACT FROM AUTHOR]

Environmental pollution has become a pressing global issue, severely threatening human health and ecosystems. As an emerging driver of economic development in countries worldwide, the digital economy (DE) has the potential to enhance resource utilization efficiency and promote the development of clean technologies, thereby reducing environmental pollution. Based on the panel data of 267 cities in China from 2012 to 2021, the spatial econometric model is used to test the impact of DE on environmental pollution. The mediating effect model is used to explore the transmission mechanism of DE affecting environmental pollution. The panel threshold model is used to examine the threshold effect of marketization. The results are as follows: (1) DE can significantly reduce environmental pollution. The conclusion is still valid after conducting robustness tests such as selecting historical data as instrumental variables and the "Broadband China" pilot as a quasi-natural experiment. (2) From the perspective of transmission mechanism, DE can reduce environmental pollution through green technology innovation and industrial structure upgrading. (3) From the perspective of spatial spillover effect, DE can reduce the environmental pollution level of surrounding cities. (4) From the perspective of threshold effect, DE has obvious market-oriented single threshold effect on environmental pollution. When the marketization level crosses the threshold of 11.6611, the emission reduction effect of DE is significant. (5) From the perspective of heterogeneity, DE has a heterogeneous impact on environmental pollution in cities with different geographic locations, resource endowments and administrative level. Regarding geographical heterogeneity, DE can effectively reduce environmental pollution in eastern and central regions, but has no significant impact on environmental pollution in western regions. Regarding the heterogeneity of resource endowment, compared to non-resource-based cities, resource-based cities suffer more from the negative effects of DE on their environment. Regarding the heterogeneity of administrative levels, compared with non-central cities, the DE of central cities has a greater emission reduction effect. Based on empirical results, this paper proposes strategic recommendations in areas such as enhancing the application of DE in emission reduction, upgrading industrial structures, promoting green technology innovation, and improving the level of marketization. This study not only enriches the research of DE and environmental pollution, but also provides a reference for the formulation of environmental pollution control policies. [ABSTRACT FROM AUTHOR]

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development. [ABSTRACT FROM AUTHOR]

Different choices of living space for urban residents are concrete reflections of a social class divide. Emerging residential space differentiation is a critical issue in Chinese cities. This paper aims to explore the current situations and mechanisms of residential spatial differentiation, and reveal its social responses in Chinese cities. Taking Wuhan, the largest city in central China, as an example, this research divides the residential space based on social resource structures. It analyzes and compares spatial differentiation and influencing factors of different residential areas and houses with different prices in Wuhan by spatial differentiation indicators and geographic detector. The results show that residential areas are divergent due to differences in urban resource spatial structure, with few and concentrated high-quality residential areas. The spatial differentiation level of different residential areas also varies, with central location, landscape, educational resources, and other dominant scarce resources being the key to residential spatial differentiation in most of China's big cities. In addition, residential spatial differentiation can lead to issues including housing wealth inequality, resource deprivation, and class identity solidification. In the end, this paper puts forward policy implications on alleviating residential spatial differentiation and optimizing allocation of residential resources. [ABSTRACT FROM AUTHOR]

Park green space is a big part of public infrastructure in cities, and how to evaluate and optimize the mismatch of urban park green space (UPGS) has become the focus of current research in academia and industry. Taking China's 286 cities as an example, this paper used the spatial cluster and Boston Consulting Group Matrix to analyze the aggregation laws and changing modes of UPGS from 2010 to 2020, introduced the spatial mismatch model to analyze the matching of its supply and demand with GDP and population, and adopted the Geodetector to analyze the influencing factors. The findings: (1) The evolution of UPGS in China had long been characterized by a "pyramidal" pattern, i.e., limited green cities > developing green cities > steady green cities > booming green cities, exhibiting the spatial characteristics of gradient differences between the coasts and inland areas, and the aggregation of blocks in some areas. (2) The supply and demand mismatches of the UPGS were relatively stable, with negative matching being the main supply mismatch type, and positive matching being the main demand mismatch type. The contribution of supply and demand mismatches similarly showed a spatial pattern of a gradual decrease from the coast to inland and the aggregation of blocks in some areas. (3) Five types of factors played different driving roles on UPGS, with social development remaining a weak factor, and the strong factor switching from urban infrastructure to construction land scale. The interaction detection was dominated by a bilinear enhancement, with super-interaction factors changing from an output value of the tertiary industry and population urbanization rate to education expenditure in local general public budgets. (4) Based on the mismatch between the supply and demand for UPGS in China, 286 cities were classified into four types, namely a smart shrinking zone, smart growing zone, status quo zone, and overlay policy zone, and differentiated development proposals for the corresponding zoning were put forward. This paper constructed an application framework of "evolution pattern + supply demand match + driving factors + policy zoning" for UPGS at a large scale, which will effectively enhance the effective allocation of its resources across the country. [ABSTRACT FROM AUTHOR]

The attainment of regional high-quality development necessitates the critical role of the digital economy in facilitating the transformation of industrial structures. This study intends to investigate the effect of the digital economy on industrial structure transformation from the perspective of innovation factor allocation using a panel dataset of 41 cities in the Yangtze River Delta region for the period from 2011 to 2020. This paper considers four dimensions to measure the level of industrial structure transformation i.e. industrial structure servitization, industrial structure upgradation, service industry structure upgradation and industrial interaction level. The results of the study suggest that the digital economy can significantly improve industrial structure transformation. The results remain consistent even after several robustness checks. Further, the analysis of the mechanism of action shows that the digital economy can promote industrial structure transformation by optimizing the innovation factor allocation. The study provides several policy implications for the digital economy and its role in the promotion of industrial structure transformation. [ABSTRACT FROM AUTHOR]

While the cancellation of highway tolls can reduce costs and increase efficiency in the transportation industry, it also triggers environmental problems. Using panel data on 276 cities in China from 2005 to 2019, we explore the urban haze pollution and its mechanism caused by cancellation of high-grade highway tolls with a combination of propensity score matching and time-varying difference in differences, and also apply a spatial Durbin model to test the haze pollution spatial spillover effect. The study shows that the cancellation of high-grade highway tolls significantly aggravates haze pollution in cities. Regional heterogeneity analysis indicates that the policy has a greater impact on eastern cities and raises haze pollutions in resource-based cities more than in non-resource-based cities. Further mechanism tests show that the policy exacerbates urban haze pollution through the detour effect and pollution spatial spillover effect. The findings of this paper enrich the literature on the environmental impacts of highway toll behavior and provide experiences for the formulation and implementation of highway toll policies in China's transportation sector. [ABSTRACT FROM AUTHOR]

Shrinking cities suffer from a decreased level of resident activities. As a result, areas with low levels of resident activities may become breeding grounds for social issues. To ease and prevent social issues, it is important to deploy physical space optimisation strategies to effectively guide the distribution of resident activities in shrinking cities. To support the development of such spatial strategies, this paper introduces machine learning-based methods for analysing the nuanced non-linear relationship between resident activities and physical space in shrinking cities. Utilising dual-scale grids, this study calculates multi-source spatial elements, which are subsequently integrated with resident activity data to construct a gradient boosting decision tree model. It then analyses the weight of different spatial elements' impacts on resident activities and their nonlinear relationships. The model proposed in this study demonstrates good precision in construing the relationship between resident activities and physical space. Based on the research findings, strategies for different types of spatial development in shrinking cities are drawn out. This paper advocates for the application of this analytical approach before conducting spatial planning in shrinking cities to maximise the effectiveness of spatial development in guiding resident activities. [ABSTRACT FROM AUTHOR]

Due to the increasingly complex global climatic environment and the rapid development of China's urban construction, China's historical and cultural cities are experiencing an external impact as well as internal fragility. Representing the capacity of the urban system to address impact and pressure, resilience can effectively guarantee the sustainable development of historical and cultural cities. A scientific and reasonable resilience assessment system can guide the resilience construction of historical and cultural cities in an effort to effectively counter the impact and pressure they face. Therefore, it is necessary to research the resilience of historical and cultural cities. On the basis of the complex adaptive system (CAS), and by applying multiple assessment indicators, this paper established a resilience assessment system for China's historical and cultural cities, comprising 38 indicators in six dimensions, to analyze the characteristics and the influencing mechanisms of the resilience of the historical and cultural cities and to reveal the inherent logic underlying their complex presentation. Using six historical and cultural cities in east China as an example, the study applied the assessment system to assess and analyze the different resilience levels of the cities. The comprehensive resilience of Changzhou City obtained the highest score at 0.64, indicating a higher degree of resilience; the scores of Yantai City, Huzhou City, and Nantong City were 0.59, 0.54, and 0.50, respectively, representing moderate degrees of resilience; the scores of Zhongshan City and Quzhou City were 0.44 and 0.40, respectively, exhibiting a lower degree of resilience. Moreover, the factors that result in an unbalanced development of urban resilience were explored from the perspectives of economy, system, and culture. The paper contains some significance in guiding the development of the resilience of historical and cultural cities. [ABSTRACT FROM AUTHOR]

Sunken green space is one of the urban rainwater collection facilities, which belongs to Low Impact Development (LID) techniques. It plays a key role in the construction of sponge city, and the amount of runoff collection is usually affected by the area of the sunken green space, the infiltration rate of the soil, and the annual runoff collection rate. To determine the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio of sponge cities, this paper selects a residential district in Hefei city, China, as the case study. Based on 45 years of precipitation data, the designed rainfall corresponding to annual runoff collection ratios of 75%, 80% and 85% is 21.3 mm, 23.4 mm and 27.5 mm, respectively. The characteristics of rainfall infiltration in sunken green space are analyzed by using the water balance model and runoff yield and conflux model. The results reveal that the soil infiltration rate is 1.16×10−4 cm/s~3.88×10−3 cm/s when the sunken depth is 0.1 m~0.3 m and that the ratio of green space area is 5%~25%. The runoff collection of the reconstructed sunken green space is 2.87 times and 1.98 times that of the nonsunken green space and the nonreconstructed sunken green space, respectively. That is to say, under the comprehensive performance of the sunken depth, sunken green space area, the steady soil infiltration rater of the reconstructed sunken green space cannot be less than the value obtained in this paper. Otherwise, the requirements of annual total runoff reduction ratio of the sponge city cannot be met. Therefore, this study provides references for realizing the ratio of annual runoff collection and sponge city construction in similar urban areas. It can also be applied to optimal selection of sunken green space in some sponge city projects. [ABSTRACT FROM AUTHOR]

In order to explore the causal relationship between the level of urban digital construction and urban economic growth, this paper takes 280 cities in China as the research object and constructs a comprehensive indicator evaluation system covering digital infrastructure, overall economic level, innovation development level, digital industry development status, and ecological environment conditions. Using the entropy method to weigh various indicators, this paper has obtained the evaluation results of the digital construction level of each city from 2011 to 2021. Furthermore, a panel data regression model is used to empirically analyze the impact of urban digital construction level on urban economic growth. The results show that for every 1% increase in the level of urban digital construction, the GDP will increase by 0.974. Through the above research, we hope to further enrich the theoretical and empirical research in the field of the digital economy, provide a scientific and reasonable method for quantitatively evaluating the level of urban digital construction, and provide decision-making references for improving the level of urban digital construction and promoting sustainable urban development. [ABSTRACT FROM AUTHOR]

Elucidating the impacts of service industry's agglomeration on the optimization of industrial structures holds paramount significance in advancing urban economic growth and fostering the coordinated and sustainable development of city economies. This study leverages panel data encompassing 251 prefecture-level cities spanning from 2003 to 2019, employing a spatial Dubin model to scrutinize the influence of distinct types of service industry agglomeration on industrial structure optimization. The results show that specialized agglomeration within the service sector significantly inhibits the rationalization of industrial structures and their underlying fundamentals. Conversely, heightened levels of agglomeration in diversified service industries facilitate the rationalization of industrial structure, predominantly driven by regional spatial spillover effects. Further analysis reveals heterogeneity in service industry agglomeration across cities of varying sizes concerning industrial structure optimization, notably accentuating underutilized spatial spillover effects in smaller cities. In light of these insights, this paper advocates for cities to capitalize on the agglomeration and spillover effects between the service industry and other sectors, strategically selecting optimal service industry agglomeration modes to propel industrial structure optimization. [ABSTRACT FROM AUTHOR]

Using the peak ground acceleration (PGA) under four exceedance probabilities calculated via a probabilistic seismic hazard analysis method for China, the probability density function of PGA was obtained by fitting with the Cornell seismic hazard exceedance probability PGA function model. Combined with the seismic fragility function of the water supply system calculated on the basis of the empirical matrix of actual earthquake damage and the exposure of fixed assets, the expected seismic loss and expected loss rate models of the water supply system were established, and the classification standard with the expected seismic loss rate of the water supply system as the index was proposed. The seismic fragility of the water supply system was classified, and the exposure of the water supply system was analyzed. The total fixed assets in the Statistical Yearbook of Urban Water Supply, henceforth called Water Supply Yearbook, were taken as the exposure to earthquake in the region. The accuracy of the fragility model in this paper was verified through the actual earthquake damage losses in Deyang. Taking the water supply system of 720 cities in mainland China as an example, the distribution maps of expected seismic loss and expected loss rate were calculated and drawn. The expected loss rate model was verified by the key earthquake prevention areas in mainland China. The assessment model based on the expected loss and expected loss rate was taken as the seismic risk assessment model of water supply systems in mainland China. [ABSTRACT FROM AUTHOR]

The digital economy provides a new path to promote industrial structure upgrading. Using panel data from 2011 to 2020 for 85 resource-based cities in China, this paper empirically investigates the impact of the digital economy on industrial structure upgrading and the primary mechanism. The results show that the digital economy is conducive to promoting industrial structure upgrading in resource-based cities, and innovation is the primary mechanism of action. According to the different stages of resource development, we classify resource-based cities into growth, maturity, decline, and regeneration cities, and we further analyze the heterogeneous influence. In terms of influence degree, the digital economy has a more prominent role in promoting industrial structure upgrading in resource-exhausted cities. In addition, we also found that the closer to the provincial capital city, the more pronounced the promotion of the digital economy to the industrial structure upgrading. [ABSTRACT FROM AUTHOR]

This paper methodically investigates the influence of inclusive income growth on city size, examining it through the dual lenses of "income" and "distribution." The analysis leverages meticulously collected panel data encompassing 276 Chinese cities at the prefecture level and above, spanning the period from 2005 to 2019. Theoretical analysis indicates that the effect of city size expansion on per capita income adheres to a 'U'-shaped trajectory, while its influence on the urban-rural income gap manifests an 'inverted U' pattern. Moreover, the inclusive income growth stemming from city size demonstrates notable heterogeneity across various geographic locations and city hierarchies. The findings reveal that human capital serves as the primary mechanism through which city size influences inclusive income growth. After decomposing the income inclusiveness index, it becomes evident that the expansion of city size exerts a more potent direct driving effect on the income of urban residents. On the one hand, city size expansion directly increases rural residents' income levels by improving labor productivity. On the other hand, it facilitates leapfrog income development by inducing the rural labor force to move to cities. [ABSTRACT FROM AUTHOR]

Hub economy is a kind of emerging economic form. Developing a hub economy is essential to strengthen domestic and foreign connectivity and build a powerful country in transportation. This paper designs a two-stage analysis framework for the evaluation and impact study of the input-output efficiency of the hub economy based on the super SBM model, Malmquist model, and Tobit model. In the first stage, the Super SBM and Malmquist models are used to measure the static and dynamic efficiency of the hub economy. In the second stage, the Tobit model is used to analyze the factors influencing the efficiency of the hub economy. Among them, the explained variable in the second stage is the measurement result of technical efficiency in the first stage. The empirical results of 30 provinces and cities in China from 2012 to 2021 show that (1) the technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) of China's hub economy are 0.585, 0.740, and 0.820, respectively, which do not reach the effective state; (2) the technical efficiency change index (Effch), technical progress change index (Techch), and total factor productivity change index (Tfpch) of China's hub economy are 0.994, 0.945, and 0.939, respectively, indicating that the corresponding efficiencies show a downward trend; and (3) industrial structure, innovation, and technology are significantly and positively correlated with the efficiency of the hub economy; policy and enterprises are significantly negatively correlated with the efficiency of the hub economy; and education does not correlate with the efficiency of the hub economy. [ABSTRACT FROM AUTHOR]

Scientifically measuring the level of environmental governance (EGL) and understanding its spatial convergence has important reference value for ecological governance. In this paper, the global entropy method is applied to measure the EGL of 284 prefecture-level cities in China from 2007 to 2019, which are divided into three major river basins, including the Yellow River, Yangtze River, and Pearl River, to observe the spatial–temporal evolutionary characterization through a standard deviation ellipse model. The coefficient of variation and the spatial econometric model are the tools used to conduct the spatial convergence test. The results are as follows: (1) China's EGL is low overall, though it is fluctuating upward at low magnitude, and the three major river basins follow the ranking: The Pearl River Basin > The Yangtze River Basin > The Yellow River Basin. (2) Spatially, the distribution pattern of China's EGL changes from "scattered and sporadic" to "multipolar core". (3) The center of China's environmental governance was concentrated in the east from 2007 to 2019, and the EGL in the midstream and downstream regions of the three major river basins increased rapidly. (4) Environmental governance in China has significant absolute and conditional β-convergence characteristics, as do the three major basins, while the ranking of convergence speed remains "Yangtze River Basin > Yellow River Basin > Pearl River Basin". Of these, economic development accelerated the convergence rate of environmental governance in China and its three major river basins; financial pressure significantly inhibited the convergence of the EGL of the Yellow River Basin. The improvement of the EGL in the Pearl River Basin was also negatively influenced by the industrial structure. [ABSTRACT FROM AUTHOR]

The question of whether China can become a creative nation has been a topic of much debate in academic circles. The Chinese government has expressed its belief that China can develop a unique form of creativity to move the country from the periphery to the center of the global creative ecosystem. This perspective has led to a series of state-led trials and experiments, including the adoption of cultural and creative industries, creative clusters and cities, and the recent maker movement. This paper utilizes the center-periphery theory to analyze the emergence, development, and evolution of China's maker movement, aiming to revisit the creativity issues in contemporary China. Based on three years of ethnographic research, the paper unpacks the maker movement at three interrelated levels: individual, organizational, and urban. Empirical data indicates that the transformation of China's maker movement is characterized by commodification, formalization, and infrastructuralization processes. The tension between growth and development, and stability and control has turned the once grassroots maker movement into a contested creative hybrid. This paper challenges the conventional view that China is resistant to change and incapable of creativity due to institutional and ideological influences. It demonstrates how an alternative mode of creativity can emerge outside global creative centers and proposes a new perspective on China's potential to become a creative nation. [ABSTRACT FROM AUTHOR]

Colleges and universities play a crucial role in fostering innovation, making it essential to explore effective strategies for promoting innovation at the institutional policy level. This paper focuses on the establishment of intellectual property model cities as a starting point and conducts an empirical analysis using innovation data from 234 cities and 942 colleges and universities between 2007 and 2017. By constructing a multi-temporal double-difference model, this study reveals that the establishment of intellectual property model cities effectively fosters innovation in colleges and universities. Further analysis demonstrates that this promotional effect is particularly significant in the western region, key cities, and key colleges and universities, as well as in the fields of invention and utility model patents. These conclusions withstand a series of robustness tests, confirming their validity. This study reveals that the national intellectual property pilot city policy has a significant influence on university innovation. It achieves this by encouraging investment in research and development and enhancing collaboration in innovation. The findings of this study provide important policy suggestions for maximizing the innovation potential of the intellectual property model city policy. This, in turn, can contribute to economic transformation, upgrading, and the promotion of innovation development in China. [ABSTRACT FROM AUTHOR]

China is in the transition period of urbanization, and the imbalance of land use generated during the original rapid development of megacities still exists, resulting in the preservation of a large number of urban villages in the peripheral areas of cities. Unlike formal housing, these villages are heavily influenced by the confrontation and interweaving between top-down policies of local governments and bottom-up spontaneous construction by local villagers, resulting in a diverse and complex status quo. At the same time, self-built housing in urban villages has become a gathering place for a large number of low-income migrants due to its relatively low rental prices. In terms of the research of urban villages on the current situation of housing, the real needs of users and housing performance are mostly subjective judgments and conclusions. Therefore, the entry point of this paper is the leased space and the leasers, taking Laojuntang Village in Chaoyang District of Beijing as the research object and analyzing its current problems and the real needs of users. This paper adopts an integrated approach of fuzzy Kano model evaluation and building performance simulation. After analyzing the data and discussing the influencing factors, this paper identifies the specific problems and user needs that exist in leased spaces in Laojuntang Village: (1) The architectural performance of leased space is a Must-be Quality, which is the bottom-line requirement and must be improved. (2) The quality of the basic facilities and equipment of the leased space is mostly a One-dimensional Quality, Attractive Quality, and the degree of importance is lower than that of the building performance. (3) The external activity facilities of the leased space are mostly undifferentiated needs, for which the local users are not particularly prominent. (4) The scale and plot ratio of local housing is relatively high, and users are dissatisfied and complaining, which falls under the category of Reverse Quality. [ABSTRACT FROM AUTHOR]

Low-carbon pilot city (LCPC) plays a pivotal role in stimulating green innovation among enterprises. However, relying solely on policy often proves less effective, necessitating support from financial development. Yet, current research frequently overlooks the impact of financial development on LCPC policy. Drawing on economic, management, and organizational psychology theories, we investigate the influence of the financial development level on enterprise green innovation in LCPC, utilizing data from listed companies between 2010 and 2018. The main finding is that LCPC facilitates institutional-level green innovation. Concurrently, financial development augments the effectiveness of LCPC policy, further expediting green innovation activities among enterprises in these pilot cities. Heterogeneity analyses reveal that financial development significantly promotes green innovation, particularly among state-owned enterprises, those with myopic management, non-high technology industries, and businesses in the southern region within LCPC. Mechanism tests identify enterprises' financing constraints and R&D investment levels as key pathways through which financial development fosters green economic development in LCPC. This study provides micro-level evidence from China elucidating the effects of environmental policies and offers practical implications for the low-carbon transformation of the manufacturing sector amid peak emissions and carbon-neutral targets. Additionally, it provides valuable guidance for other emerging economies seeking enhanced resource and environmental protection through the implementation of energy-saving and emission-reduction fiscal policy. [ABSTRACT FROM AUTHOR]

China's green financial pilot policies (GFPPs) are an important start to build a green financial system in China. It is also an important part of achieving the "dual-carbon" goal. This paper calculates China's total factor energy efficiency (TFEE), analyzes the impact of GFPPs on TFEE, and explores the conduction mechanism. The results show that the relationship between GFPPs and TFEE in the pilot areas is statistically significant. The GFPP mainly improves the TFEE through the green innovation effect and the optimization of the energy structure. The GFPP has a significant effect on TFEE enhancement in eastern coastal cities, non-old traditional industrial cities, and non-resource-based cities with high initial energy. China should continue to deepen the pilot work of green finance, formulate differentiated green finance policies, and ensure green technology innovation. This study provides empirical evidence for further optimization of green finance and energy efficiency. [ABSTRACT FROM AUTHOR]

As major carriers of modern economy and population, cities and towns are vortex centers of pollution migration, and the environmental effects brought about by China's unprecedented urbanization can be imagined, although the specific scale is still a mystery. This paper focuses on the nonlinear response mechanism of urban PM2.5 concentration to the urbanization population scale, considering that China's urbanization development path is dominated by large- and medium-sized cities. The panel data of PM2.5 concentration of Chinese cities observed by satellite during 1998–2016 are used to capture the nonlinear characteristics of panel threshold model (PTM). The estimation results of the double-threshold PTM including the quadratic term of urbanization population show that the U-shaped relationship between urbanization population and PM2.5 concentration is nonlinear adjusted by urban GDP per capita with the two thresholds of 6777 Yuan and 10,296 Yuan at 2010 constant price. When the urban GDP per capita exceeds 10,296 Yuan, the urbanized population at the turning point of the U-shaped curve is 12.967 million people, which only appears in a few super-large cities such as Beijing, Tianjin, Shanghai and Chongqing. The size matching of urban economy and population is an important follow-up of environmental policies. [ABSTRACT FROM AUTHOR]

As global warming intensifies, reducing carbon emissions has become a global common mission. Tourism transportation is one of the important sources of carbon emissions, and reducing its carbon emissions is a key part of achieving China's carbon reduction goals. Based on the panel data of various provinces and cities in North China from 2000 to 2022, this paper calculates the carbon emissions of tourism transportation by using the carbon emission coefficients of different transportation modes in different segments. Moreover, the temporal and spatial evolution of the tourism economy is systematically analyzed. The Tapio decoupling model and LMDI addition decomposition model are used to analyze the relationship between carbon emissions and tourism economic growth and the effects of 11 influencing factors on carbon emissions. The results show that: (1) The carbon emission of tourism transportation in North China has experienced four stages: a steady growth period, a transitional adaptation period, a stable equilibrium period, and a drastic decline period. The overall carbon emission level of tourism transportation is as follows: Hebei Province > Shanxi Province > Inner Mongolia Autonomous Region > Beijing City > Tianjin City. (2) The decoupling coefficient between tourism traffic carbon emissions and economic development fluctuates but mainly shows a weak decoupling state. (3) In terms of influencing factors, passenger size and passenger density have the greatest impact on the carbon emissions of tourism transportation. [ABSTRACT FROM AUTHOR]

New urbanization in counties and the logistics industry are closely related and are essential in promoting regional economic and social development. There are specific challenges and obstacles to revealing the interaction mechanism and system state measurement between the two. This paper explains the two coupling mechanisms and constructs the evaluation index system. It proposes a new analysis method based on the coupling coordination degree model, the spatio-temporal evolution analysis, and the grey prediction model. The goal is to learn more about and fully realize the coordinated development mechanisms of the two. It then uses the Hebei province of China as an example to empirically analyze its systematic cross-sectional data from 2013 to 2022. Research findings: (1) In Hebei province, the new urbanization in counties and the logistics industry have a systematic coupling relationship. However, the logistics industry's comprehensive development level is relatively lagging. The two systems have been at a high-level coupling stage for the last decade and maintain a high coupling status. The coupling coordination has shown significant improvement. (2) Although the geographical distribution of the coupling and coordination degree of the new urbanization in counties and logistics industry system has short-term volatility, it is still stable in the long term and presents economic-related spatial characteristics. (3) Over the next five years, the coupling coordination of 11 cities in Hebei province will steadily grow. There will be greater harmonization between the two systems. (4) From the analysis results, the evaluation index system of the coupled system constructed is scientific and reasonable. The analysis method can not only measure the system's coupling degree, but it can also predict the development trend and analyze the spatial evolution. The technique has novelty and validity, which can be used as a reference for analyzing and making decisions about similar systems. [ABSTRACT FROM AUTHOR]