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The agglomeration and dispersion of tourist attractions in space greatly affect the development of regional tourism resources and the consumption choice of tourism market. At present, the research on the spatial distribution characteristics of tourist attractions and their influencing factors mainly adopts induction and investigation, and there is a lack of effective statistical models for the research on the spatial distribution of tourist attractions and their influencing factors in some historical and cultural ancient cities. This paper uses Internet technology to obtain the spatial distribution data of tourist attractions in Shaoxing city, and uses mean nearest neighbor analysis, nuclear density analysis, imbalance index analysis, standard deviation ellipse and other spatial statistical analysis techniques and geographical detector methods to study the spatial distribution characteristics and influencing factors of tourist attractions in Shaoxing City. This paper studied the distribution characteristics of tourist attractions in Shaoxing city, such as spatial aggregation, distribution equilibrium and spatial orientation, and applied geographical detector to study the influencing factors of the spatial distribution of scenic spots. It was concluded that the spatial distribution pattern of scenic spots was affected by various factors such as natural environment, social environment and economic environment. The explanatory power of two-factor interaction is obviously stronger than that of single factor. The research results provide scientific basis for the planning, layout and development of tourist attractions in Shaoxing and its similar cities, and then promote the high-quality development of tourism in Shaoxing and its similar historical and cultural ancient cities. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the digital economy on urban environmental pollution by analyzing panel data from 283 prefecture-level cities in China from 2011 to 2019 and using the digital technology comprehensive pilot zone of China as a natural experiment. The results demonstrate that digital technology has a significant effect in reducing pollutant emissions and empowering urban environmental governance. The findings are proven to be robust based on various tests, including parallel trend, PSM-DID, and placebo tests. Our analysis further shows that digital technology is particularly effective in controlling pollution in old industrial areas, high digital areas, and low energy efficiency areas. We also find that the national digital technology integrated pilot zone can mitigate environmental pollution in prefecture-level cities by increasing public environmental awareness and encouraging green technology innovation. Moreover, our research indicates that digital technology-enabled urban pollution control can contribute to the formation of a new urbanization pattern in China. These findings provide valuable insights for promoting the digital economy and achieving the goal of carbon reduction in China. [ABSTRACT FROM AUTHOR]

Logistics resilience is a significant representation of sustainable development ability and a necessary support for high-quality economic development. In order to explore the influencing factors and realization mechanism of the improvement of logistics resilience of the Yangtze River Economic Belt and the high-quality and sustainable development of the economy, this paper comprehensively considers factors of the supply and demand relationship of the logistics market, industrial structure and ecological environment, and evaluates the urban logistics resilience of the Yangtze River Economic Belt by using POI data and statistical data. Combined with the spatial Durbin model, the influencing factors and spatial spillover effects of inter-city logistics resilience were revealed. This study found that the urban logistics resilience in the lower reaches of the Yangtze River has been high. Except Chongqing and Shanghai, the COVID-19 epidemic happened in 2020 led to a significant decrease in logistics resilience. In the meanwhile, every 1% increase in the logistics resilience of the city will promote the logistics resilience of the adjacent cities by 0.145%. Economic condition and urban development potential have positive effects on logistics resilience of the city and its adjacent cities. The economic condition has a direct effect coefficient of 0.166 and an indirect effect coefficient of 0.181, The direct and indirect effects of urban development potential are significantly positive, and the coefficients are 0.001 and 0.006, respectively. The level of information, government support and ability of technological innovation are helpful for the improvement of urban logistics resilience while hindering the enhancement of logistics resilience in adjacent cities. The research area can be extended in the future and more influencing factors can be considered in the future. [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 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]

This study is a comprehensive assessment of the waste management system in Besisahar municipality. Information and some data have been collected from the municipality of Besisahar, followed by interviews with municipal officials responsible for waste management, stakeholders, waste workers, and residents. A total of 230 households, 20 schools, 10 government and private offices, 10 financial institutions, 60 commercial hotels, restaurants, and shops, and 20 medical shops and healthcare institutions, were selected in this study by random sampling. An extensive field study was conducted within all municipal wards and at dump sites. The results indicated that 42.14% of solid waste was collected through door-to-door collection services, 5.87% was mismanaged in open public places, 11.21% was used as compost manure, and the rest was discarded on riverbanks, dug up, and burned. A large component of the characterization of household waste consisted of organic waste (68.03%), followed by paper/paper products (8.13%), agricultural waste (5.5%), plastic (5.21%), construction (3.81%), textile (2.72%), metals (0.54%), glass (1.01%), rubber (0.10%), electronic (0.05%), pharmaceutical (0.1%) and others (4.78%) in the Besishahar municipality. Solid waste generation was found to be at 197.604 g/capita/day, as revealed by cluster sampling in 230 households. Around 4.285 tons-solid waste/day were generated in urban areas, while 16.13 tons-solid waste/day was estimated for the whole municipality. An important correlation between the parameters of solid waste was found by statistical analysis. Currently, solid waste is dumped on riverbanks, open fields, and springs, creating environmental and health hazards. The findings of this study will be useful to Besisahar municipality and its stakeholders in forming policies that facilitate waste management practices in this region and promote sustainable waste management systems. [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]

The rapid economic development and accelerating urbanization have led to a significant mismatch between the urban bus network allocation and the population flow. Therefore, this paper investigates this challenge by exploring the intricate relationship between the population flow dynamics, traffic congestion conditions, and the efficient allocation of bus resources. In response, two key indexes were introduced based on spatial matching patterns to assess the urban bus network: the Population-Bus Match Index evaluates the matching degree between supply and demand, and the Population-Congestion Match Index evaluates the matching degree between utilization and saturation. Additionally, two distinct optimization strategies have been proposed to enhance the urban bus network. The first optimization strategy considers the bus network's current status, while the second aspires to an idealized scenario. Subsequently, the potential contributions of each bus station in reducing CO2 emission reduction after implementing the two optimization strategies are quantified. Utilizing a case study focused on Harbin, the proposed methods are validated. The findings unveil a substantial misalignment between supply and demand within the bus network during peak periods, with nearly half of the bus stations experiencing a disparity between utilization and saturation. Comparative experiments across different optimization strategies reveal that the second optimization strategy significantly outperforms the first, but the first optimization strategy has a higher degree of CO2 emission reduction contribution. The results of this study provide decision-makers with an environmentally oriented vantage point for the discerning selection of optimization strategies and leave valuable insights for urban areas confronting transportation challenges. [ABSTRACT FROM AUTHOR]

The railway network connects different cities and regions and plays an important role in the transportation system. This paper theoretically analyzes the causal effect and mechanisms of the railway network on urban economic growth, and explores the direct effects, threshold effects, and spatial spillover effects of improved centrality in the railway network on urban economic growth in Northeast China. The results show that: (1) There is a similarity between the economic growth level and the trend of the railway network in Northeast China. From a spatial perspective, there are regional differences in the development of the railway network. (2) From the perspective of the direct effects, each unit improvement in railway network centrality leads to a 0.160 unit increase in urban economic growth in Northeast China. The degree of influence of other variables on urban economic growth, in descending order, is labor employment level, material capital investment, information development level, technological development level, human capital, and degree of openness. (3) From the perspective of the threshold effects of the railway network, the threshold values and the number of threshold levels are different for different regions. (4) There are significant spatial spillover effects in the railway network of Northeast China, and an increase in the centrality of a city's network can have negative spatial spillover effects on the economies of surrounding areas. Based on these results, we recommend that Northeast China should focus on the construction and improvement of the railway network, strengthen the connections between regions, and promote the overall economic growth of the region while improving its international competitiveness. [ABSTRACT FROM AUTHOR]

Using publicly available data, this paper investigates the diffusion of COVID-19 across neighborhoods in two major cities, London and New York. We link neighborhood demographics to incidence, and we investigate patterns of change over time in conjunction with changing policy responses to the pandemic. By comparing and contrasting these two cities, we are able to exploit surveillance and policy differences, demonstrating how each contributes information to the other. We conclude that better coordination can be translated into improved health policy. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) is an important engine of national economic development and a leading region in international competition. As economic exchanges and resource flows in the YRD region become closer, the inter-regional industrial linkages continue to grow, resulting in the formation of an industrial network structure characterized by a "complex network". The strength of the links between industrial sectors and the value and significance of the existence of industries in the network change over time, thus causing the overall evolution of the industrial network in the YRD region. Based on the input-output tables of the YRD region in 2012 and 2017, this paper uses the prediction index of network structure similarity to construct the prediction model of industrial network link between the YRD regions, and calculates the possibility of future links between industries in the Yangtze River Delta region through comparative analysis and selection of the RWR index of random walk similarity with the best effect, and concludes that: (1) the homogeneity of industries among provinces and cities in the Yangtze River Delta region is relatively high, resulting in homogeneous competition; (2) the overall nature of the industrial layout of the YRD is not prominent, and the depth and intensity of cross-regional industrial cooperation are lacking. On the basis of analysis and research, the countermeasures and suggestions for effectively realizing industrial integration are put forward from the macro level of the government and the meso level of the industry, so as to achieve a more complete industrial network in the YRD region and a more extensive length and width of the cross-regional industrial chain. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic introduced imminent and lasting impacts on the opioid crisis in the U.S., including a significant increase in opioid overdose and deaths and in use of telehealth in treatment. What lessons can we learn from the treatment transition during the pandemic that could help tackle the opioid crisis when future pandemics strike? In this paper, we conducted a phone survey with opioid treatment facilities in Pennsylvania to examine the COVID-19's impacts on treatment facilities and individuals with opioid use disorder during the first year of the pandemic. We separated the lockdown period (Mid-March through Mid-May, 2020) from the reopening period that followed, and urban areas from rural areas, to explore temporal evolution and rural-urban variations in the COVID-19's impacts. We found rural-urban heterogeneity in facilities' adoption of telehealth in treatment and in challenges and risk factors faced by their clients during the lockdown period. During the reopening, telehealth was adopted by most facilities, and telehealth-related challenges became less salient; however, both rural and urban facilities reported higher relapse risks faced by their clients, citing factors more likely to be at clients' end and related to socioeconomic stressors and mental health. Our results highlight the vitality of addressing socioeconomic and mental health challenges faced by individuals with OUD, via government policies and community interventions, when future pandemics strike. The findings also indicate the importance of maintaining facilities' financial well-being to provide treatment services. [ABSTRACT FROM AUTHOR]

The continuous decline in the birth rate can lead to a series of social and economic problems. Accurately predicting the birth rate of a region will help national and local governments to formulate more scientifically sound development policies. This paper proposes a discrete-aware model BRP-Net based on attention mechanism and LSTM, for effectively predicting the birth rate of prefecture-level cities. BRP-Net is trained using multiple variables related to comprehensive development of prefecture-level cities, covering factors such as economy, education and population structure that can influence the birth rate. Additionally, the comprehensive data of China's prefecture-level cities exhibits strong spatiotemporal specificity. Our model leverages the advantages of attention mechanism to identify the feature correlation and temporal relationships of these multi-variable time series input data. Extensive experimental results demonstrate that the proposed BRP-Net has higher accuracy and better generalization performance compared to other mainstream methods, while being able to adapt to the spatiotemporal specificity of variables between prefecture-level cities. Using BRP-Net to achieve precise and robust prediction estimates of the birth rate in prefecture-level cities can provide more effective decision-making references for local governments to formulate more accurate and reasonable fertility encouragement policies. [ABSTRACT FROM AUTHOR]

With rising environmental concerns, accurate air quality predictions have become paramount as they help in planning preventive measures and policies for potential health hazards and environmental problems caused by poor air quality. Most of the time, air quality data are time series data. However, due to various reasons, we often encounter missing values in datasets collected during data preparation and aggregation steps. The inability to analyze and handle missing data will significantly hinder the data analysis process. To address this issue, this paper offers an extensive review of air quality prediction and missing data imputation techniques for time series, particularly in relation to environmental challenges. In addition, we empirically assess eight imputation methods, including mean, median, kNNI, MICE, SAITS, BRITS, MRNN, and Transformer, to scrutinize their impact on air quality data. The evaluation is conducted using diverse air quality datasets gathered from numerous cities globally. Based on these evaluations, we offer practical recommendations for practitioners dealing with missing data in time series scenarios for environmental data. [ABSTRACT FROM AUTHOR]

The study of the perceived affective qualities (PAQs) in soundscape assessments have increased in recent years, with methods varying from in-situ to laboratory. Through technological advances, virtual reality (VR) has facilitated evaluations of multiple locations in the same experiment. In this paper, VR reproductions of different urban sites were presented in an online and laboratory environment testing three locations in Greater Manchester ('Park', 'Plaza', and pedestrian 'Street') in two population densities (empty and busy) using ISO/TS 12913–2 (2018) soundscape PAQs. The studied areas had audio and video recordings prepared for 360 video and binaural audio VR reproductions. The aims were to observe population density effects within locations (Wilcoxon test) and variations between locations (Mann-Whitney U test) within methods. Population density and comparisons among locations demonstrated a significant effect on most PAQs. Results also suggested that big cities can present homogenous sounds, composing a 'blended' urban soundscape, independently of functionality. These findings can support urban design in a low-cost approach, where urban planners can test different scenarios and interventions. [ABSTRACT FROM AUTHOR]

The coupled and coordinated development of the digital economy and tourism economy has become an inevitable choice for achieving high-quality development in both sectors. This paper proposes a conceptual index system using entropy weight method and coupling coordination degree model for analysis of the coupling coordination relationship between digital economy and tourism economy. After that, the paper introduces the Moran's Index to examines the spatial heterogeneous effects of coupling coordination degree. This framework is applied to 41 cities in the Yangtze River Delta region during 2011–2021. The results show that the temporal changes of the coupling coordination relationship between digital economy and tourism economy in 41 cities are quite satisfactory, while the regional differences are large. Furthermore, the coupling degree between digital economy and tourism economy shows the strong spatial agglomeration effect, and the spatial proximity of regions with similar integration indicates that the "Matthew Effect" gradually highlights the clustering of high and low levels. Based on the results of analysis, this paper finally puts forward several policy recommendations to provide a referential path for the integration of digital economy and tourism. [ABSTRACT FROM AUTHOR]

Network Signalling Data (NSD) have the potential to provide continuous spatio-temporal information about the presence, mobility, and usage patterns of cell phone services by individuals. Such information is invaluable for monitoring large urban areas and supporting the implementation of decision-making services. When analyzed in real time, NSD can enable the early detection of critical urban events, including fires, large accidents, stampedes, terrorist attacks, and sports and leisure gatherings, especially if these events significantly impact mobile phone network activity in the affected areas. This paper presents empirical evidence that advanced NSD can detect anomalies in mobile traffic service consumption, attributable to critical urban events, with fine spatial (a spatial resolution of a few decameters) and temporal (minutes) resolutions. We introduce two methodologies for real-time anomaly detection from multivariate time series extracted from large-scale NSD, utilizing a range of algorithms adapted from the state-of-the-art in unsupervised machine learning techniques for anomaly detection. Our research includes a comprehensive quantitative evaluation of these algorithms on a large-scale dataset of NSD service consumption for the Paris region. The evaluation uses an original dataset of documented critical or unusual urban events. This dataset has been built as a ground truth basis for assessing the algorithms' performance. The obtained results demonstrate that our framework can detect unusual events almost instantaneously and locate the affected areas with high precision, largely outperforming random classifiers. This efficiency and effectiveness underline the potential of NSD-based anomaly detection in significantly enhancing emergency response strategies and urban planning. By offering a proactive approach to managing urban safety and resilience, our findings highlight the transformative potential of leveraging NSD for anomaly detection in urban environments. [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]

Efficient city logistics is essential to build smart sustainable cities where inhabitants' well-being is a priority. Meanwhile, despite the great importance of city logistics processes, their improvement is problematic for many cities. Although solutions from the field of emerging technologies are more and more often used, the question is whether implementing technological tools and filling cities with sensors is a sufficient solution that can solve the problems of intensely growing urban freight transport. The aim of the paper is to examine the role of knowledge management in city logistics and identify barriers to the implementation of knowledge-based city logistics. A key element of the research procedure was an expert survey, to which 31 international experts specialising in city logistics issues were invited, characterised by extensive experience working on research projects in the area of interest. Four knowledge management processes have been transferred to the city logistics area. The results of the study show that the difficulties are observed mainly in the processes of data gathering and knowledge acquisition. The main reason for difficulties in that area is the reluctance of city users, retailers, transport and logistics operators to share information. Identifying these processes as the most problematic is a valuable hint for logistics managers, municipalities and academics. To improve knowledge-based city logistics, it is therefore necessary to focus on these processes and look for the best solutions and new forms of organisational and business support. The solution to the problems identified in the study is the proposal to create a city logistics collaborative knowledge base which is a combination of an IT tool ‐ the CL knowledge management platform, and the Freight Quality Partnership. [ABSTRACT FROM AUTHOR]

Noise pollution is one of the consequences of urbanization that can cause environmental disturbances in urban areas. Urban ecosystems provide noise reduction services through Urban Green infrastructures (UGIs). Many studies have been conducted to evaluate and model traffic noise, but none have addressed the flow, supply, and demand of noise reduction ecosystem services. The main purpose of this paper is to present a new methodology for estimating flow, supply, and demand for noise reduction in Hamadan city that has not been mentioned in any paper so far. UGIs were classified into six main categories: agricultural lands, gardens, parks, abandoned lands, single trees, and street trees. A total of 57 sampling stations for sound measurement were made in August 2018. The current map of noise pollution (flow) was created using the Kriging method. The amount of supply was measured up to a distance of 50 meters from the main roads based on two approaches (the distance effect and the sound barrier effect). To quantify the demand, the current sound intensity level in the noise-sensitive land uses was compared with standards. Zonal statistics was used for spatial analysis of supply-demand in the urban neighborhood as a working unit. Results showed that at distances of 5m, 10m, 15m, and 20m, the average noise reduction was found to be 1.61, 2.83, 3.92, and 5.33 dB, respectively. Sound barriers at distances of 5m and 10m resulted in an average sound reduction of 1.61 and 2.83 dB, respectively. Individual trees, strip trees, abandoned lands, parks, and gardens led to a decrease in traffic noise by 0.3, 1, 0.1, 3.5, and 4.5 dB, respectively. The clustering analysis revealed a significant spatial clustering of noise pollution in Hamedan. The results and new methodology of this research can be used in similar areas to estimate the supply and demand of noise reduction and also for decision-makers to take management actions to increase supply and meet the demand for noise reduction service. [ABSTRACT FROM AUTHOR]

Charging infrastructure deployment has taken off in many cities with the rise of the number of electric vehicles on the road. Expansion of infrastructure is a matter of prioritisation of resources to optimise the infrastructure. This paper explores how to measure charging station performance, to address the challenges that policy makers face. These performance indicators are used in a regression model, based upon current utilisation of the network, to predict which charging stations perform best. The results show that a model based on available geographical data and performance metrics of the current network are best combined to predict infrastructure performance. The variability between public charging stations is however big, as frequent user characteristics do determine the performance to a large extent. [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]

With the rapid development of the world city network, the traditional location theory has gradually been disproven, and the advantages of the flow space over the traditional vertical organizational structure are gradually being revealed. Therefore, from corporate branch networks and corporate investment networks, 21 cities in urban agglomerations of Guangdong are taken as case studies for this paper. Furthermore, in this paper, 5 representative types of corporate contact data (catering service, financial service, life service, sports and leisure and accommodation service) are selected, the social network analysis (SNA) method is used to quantitatively analyze the network structure characteristics of urban agglomerations, and a spatial interaction model is constructed to explore the factors influencing. The results indicate that secondary networks have developed in Guangdong. The financial service network is the most complex, followed by the life services, sports and leisure and catering networks. The accommodation service network structure is the simplest. Among all kinds of networks, Guangzhou and Shenzhen have the highest status. The catering and accommodation corporations in Yangjiang in the west have a relatively major external development. Shantou in the east has many branches of various types, while most of the capital exchange in the region is concentrated in Heyuan and Qingyuan in the north. The coefficients of geographical proximity and the urban development level play a significant role in promoting the development of networks. However, administrative capacity limits the attractiveness of origin cities to a certain extent. [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]

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]

Drug checking services (DCS) enable individuals to voluntarily submit a small amount of a substance for analysis, providing information about the content of the substance along with tailored harm reduction support and advice. There is some evidence suggesting that DCS may lead to behaviour and system change, with impacts for people who use drugs, staff and services, and public health structures. The evidence base is still relatively nascent, however, and several evidence gaps persist. This paper reports on qualitative interviews with forty-three participants across three Scottish cities where the implementation of community-based DCS is being planned. Participants were drawn from three groups: professional participants; people with experience of drug use; and affected family members. Findings focus on perceived harm reduction impacts of DCS delivery in Scotland, with participants highlighting the potential for drug checking to impact a number of key groups including: individual service users; harm reduction services and staff; drug market monitoring structures and networks; and wider groups of people who use and sell drugs, in shaping their interactions with the drug market. Whilst continued evaluation of individual health behaviour outcomes is crucial to building the evidence base for DCS, the findings highlight the importance of extending evaluation beyond these outcomes. This would include evaluation of processes such as: information sharing across a range of parties; engagement with harm reduction and treatment services; knowledge building; and increased drug literacy. These broader dynamics may be particularly important for evaluations of community-based DCS serving individuals at higher-risk, given the complex relationship between information provision and health behaviour change which may be mediated by mental and physical health, stigma, criminalisation and the risk environment. This paper is of international relevance and adds to existing literature on the potential impact of DCS on individuals, organisations, and public health structures. [ABSTRACT FROM AUTHOR]

The destination image perceived by tourists is crucial to coastal tourism market positioning and marketing. This paper utilizes tourists' Internet-generated content from 2017–2021, adopts the jieba text analysis method to identify the cognitive, emotional, and overall image of coastal tourism, divides the constituent elements of the destination image into four main classes and 20 subclasses through the text clustering method, and explores the tourists' perception of the image of coastal tourism with the help of the IPA model. The study found that: 1) The commonality of the cognitive image of "ocean" in 12 coastal cities is outstanding, but the internal characteristics are obvious, tourists pay more attention to coastal tourism in Bohai Rim and southern coastal areas, and Shanghai, Ningbo and Hangzhou show strong correlation; 2) Tourists' emotional image of coastal tourism destinations is dominated by positive attitudes, with a high overlap of adjectives representing positive emotions, but with heat differences in different cities; 3) The overall image of coastal tourism can be divided into three circles, including "traditional core-characteristic structure-peripheral perception", and there are obvious differences in the characteristics of the social semantic network of each city; 4) Tourists are more satisfied with the components of coastal tourism image, but pay more attention to the construction of optimized coastal tourism environment. Based on this, in the process of coastal tourism development, it is necessary to focus on creating distinctive and diversified tourism values, focusing on tourists' experience needs, improving the construction of quality tourism facilities and services, and promoting the high-quality development of coastal tourism. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) ports are pivotal in shaping the Yangtze River Economic Belt and advancing urban economies across China. This article utilizes panel data from 20 cities with ports in the YRD area, spanning from 2011 to 2020, using the spatial Durbin model to explore how these ports influence urban economic growth. The findings indicate that: (1) The YRD ports significantly contribute to economic growth in both the port cities and their surrounding areas, with the indirect impact on neighboring cities being more substantial than the direct effect on the cities themselves; (2) The beneficial spillover effects of the YRD ports on the economic growth of nearby cities vary in intensity over different spatial ranges, marked by distinct boundary effects and geographical attenuation. The influence extends up to approximately 110km; (3) Within the various elements impacting the economic growth of cities in the YRD, financial development prominently exhibits a threshold effect on urban economic growth; (4) Upon analyzing heterogeneity, inland and coastal port cities manifest divergent spillover effects, with inland port cities predominantly exerting a positive spillover on adjacent regions. Accordingly, in order to eventually achieve the shared prosperity of the region's economy, it is recommended that a strong top-level design be established and that efforts be made to transform the YRD region into a core region a diffusion and driving effect. [ABSTRACT FROM AUTHOR]

Pilot Free Trade Zones (PFTZs) are a crucial new platform for China to build a more open economic system. Existing literature primarily focuses on the 'Bring In' effect of PFTZs, often overlooking the importance of 'Going Out' aspects. To bridge this gap, this paper uses data from China's Shanghai and Shenzhen A-share listed enterprises from 2007 to 2021 and constructs a time-varying difference-in-differences (DID) model to test the impact of establishment of PFTZs on international expansion of enterprises. The study finds that establishment of PFTZs can significantly promote international expansion of enterprises, with a more pronounced effect on the scope of international expansion than on its depth. Mechanism analysis reveals that PFTZs can facilitate international expansion of enterprises by driving digital transformation, enhancing total factor productivity and management efficiency, and alleviating financing constraints. Notably, senior managers with overseas work experience play a crucial role in enhancing this relationship. Further, PFTZs not only have a linkage effect with the Belt and Road Initiative but also a radiation effect on neighboring cities. This study provides an analytical perspective and empirical evidence for evaluating policy effects of PFTZs and offers valuable insights that will enable PFTZ policies to be refined and facilitate successful implementation of the 'Going Out' strategy. [ABSTRACT FROM AUTHOR]

Due to the impact of natural disasters and public security incidents, the industrial chain is broken, and the economy has declined, especially in western resource-based cities of China where enterprises have closed down, the unemployed have increased sharply, and social contradictions have become prominent. Therefore, the resilience of the industrial structure is an urgent problem to solve in the academic circle and sustainable development. This paper identifies the spatio-temporal evolution characteristics of the resilience of the resource-based cities' industrial structure in western China from 2006 to 2021 to provide a reference for the improvement of their industrial structure resilience. [ABSTRACT FROM AUTHOR]

This paper aims to examine the impact of the digital economy on urban entrepreneurship and its spatial spillover effects. To achieve this purpose, this research relies on data from 252 prefecture-level cities in China from 2012 to 2019. The findings demonstrate that the development of the digital economy has a positive influence on entrepreneurial activity in cities, with particularly effects observed robust at higher quantile levels. Additionally, the results suggest that urban entrepreneurial activity may be a siphoning effect, impeding entrepreneurship in neighboring cities. Furthermore, further investigation shows regional and policy heterogeneity. [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]

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]

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]

This study examines the potential negative effects of city-county mergers on firm-level total factor productivity (TFP). A theoretical framework is established to explain how city-county mergers could lead to higher institutional and non-institutional costs, thus influencing government decision-making and resource allocation. As a result, firms operating in the economy will absorb these costs and adjust their behavior accordingly. By employing Chinese firm-level data in a difference-in-differences approach, this study finds a statistically significant negative effect of transitioning county-level cities into municipal districts (TCD) on firm-level productivity. Additionally, this study identifies the financial situation of reformed governments and the internal environment of firms as two mechanisms through which the TCD reform influences firm-level productivity. [ABSTRACT FROM AUTHOR]

The growth of the online short-term rental market, facilitated by platforms such as Airbnb, has added to pressure on cities' housing supply. Without detailed data on activity levels, it is difficult to design and evaluate appropriate policy interventions. Up until now, the data sources and methods used to derive activity measures have not provided the detail and rigour needed to robustly carry out these tasks. This paper demonstrates an approach based on daily scrapes of the calendars of Airbnb listings. We provide a systematic interpretation of types of calendar activity derived from these scrapes and define a set of indicators of listing activity levels. We exploit a unique period in short-term rental markets during the UK's first COVID-19 lockdown to demonstrate the value of this approach. [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]

Under the goal of " carbon peaking and carbon neutrality," how to create a low-carbon and green development path for cities is an urgent problem in China. One of the effective ways to solve this problem is through industrial collaborative agglomeration. In this paper, panel data of 276 prefecture-level cities in China from 2010 to 2020 was selected to investigate the relationship between the collaborative agglomeration of manufacturing and producer service and carbon emission intensity by using a fixed-effects model, intermediary model, and SDM in multiple dimensions. The study found that the collaborative agglomeration of manufacturing and producer service industries significantly influences carbon emission intensity with an inverted U-shaped curve, and the agglomeration of manufacturing and producer service industries can influence carbon emission intensity through technological progress. In addition, the inverted U-shaped impact of collaborative agglomeration of manufacturing and producer services on carbon emission intensity has a spatial spillover effect, and the spatial spillover effect generated is stronger than the impact on the local area. Moreover, from the perspective of industry heterogeneity, compared with low-end producer services, the agglomeration of manufacturing and high-end producer services can play a better role in carbon emission reduction. Regarding regional heterogeneity, compared with the central and western regions, the impact of manufacturing and production services agglomeration on carbon intensity is far more obvious in the more economically developed eastern regions. [ABSTRACT FROM AUTHOR]

This paper analyzes the green production efficiency (GPE) and spatial divergence of the hog breeding industry, with the aim of providing a foundation for the rational layout of hog breeding and promoting the industry's high-quality development. The paper uses the SBM model to estimate GPE in 29 provinces, cities, and districts of China from 2006 to 2019. Furthermore, it analyzes the spatial divergence of GPE and its driving factors using divergence indexes and the Geodetector. The results show that China's GPE of the hog breeding industry increased from 0.409 to 0.496 between 2006 and 2019. The highest efficiency occurred during the I-period, while the lowest efficiency was observed during the II-period. The highest efficiency was in the key development region, and the lowest efficiency was in the potential growth region. The spatial divergence of GPE in the hog breeding industry expanded, with labor input, non-point source pollution, resource endowment, and environmental load bearing being the main driving factors for the expansion in each period. The potential growth region had the largest spatial divergence, mainly affected by resource endowment. In contrast, the constrained development region had the smallest spatial divergence, mainly affected by resource endowment and pollutant emissions. The spatial divergence of moderate and key development regions was considerable, mainly affected by environmental investment, environmental load bearing, and pollutant emissions. Therefore, the key to improving the GPE of the hog breeding industry is to promote the adoption of advanced technology, such as labor-saving, material-saving, and emission reduction technologies. Moreover, several actions should be taken to reduce the spatial divergence among different regions, such as integrated breeding, clean standards, large-scale breeding, and high-end boutique. [ABSTRACT FROM AUTHOR]

Background: Spatial complexity is always associated with spatial autocorrelation. Spatial autocorrelation coefficients including Moran's index proved to be an eigenvalue of the spatial correlation matrixes. An eigenvalue represents a kind of characteristic length for quantitative analysis. However, if a spatial correlation process is based on self-organized evolution, complex structure, and the distributions without characteristic scale, the eigenvalue will be ineffective. In this case, a scaling exponent such as fractal dimension can be used to compensate for the shortcoming of characteristic length parameters such as Moran's index. Method: This paper is devoted to finding an intrinsic relationship between Moran's index and fractal dimension by means of spatial correlation modeling. Using relative step function as spatial contiguity function, we can convert spatial autocorrelation coefficients into spatial autocorrelation functions. Result: By decomposition of spatial autocorrelation functions, we can derive the relation between spatial correlation dimension and spatial autocorrelation functions. As results, a series of useful mathematical models are constructed, including the functional relation between Moran's index and fractal parameters. Correlation dimension proved to be a scaling exponent in the spatial correlation equation based on Moran's index. As for empirical analysis, the scaling exponent of spatial autocorrelation of Chinese cities is Dc = 1.3623±0.0358, which is equal to the spatial correlation dimension of the same urban system, D2. The goodness of fit is about R2 = 0.9965. This fractal parameter value suggests weak spatial autocorrelation of Chinese cities. Conclusion: A conclusion can be drawn that we can utilize spatial correlation dimension to make deep spatial autocorrelation analysis, and employ spatial autocorrelation functions to make complex spatial autocorrelation analysis. This study reveals the inherent association of fractal patterns with spatial autocorrelation processes. The work may inspire new ideas for spatial modeling and exploration of complex systems such as cities. [ABSTRACT FROM AUTHOR]

As a new business model, E-commerce brings new changes to the global economy and society. So, can E-commerce development policies promote high-quality agricultural development? This article regards the pilot construction of national e-commerce demonstration cities as a quasi-natural experiment for the development of e-commerce. Based on the E-commerce pilot and economic and social development data of national prefecture-level cities from 2004 to 2018, the agricultural total factor productivity calculated by the Fare-Primont index method is used as the characterization of the quality of urban agricultural development, and an empirical model is constructed under the progressive Differences-in-Differences framework. This paper empirically tests the overall impact of E-commerce development on the high-quality development of agriculture and its sources, analyzes the heterogeneity and dynamics of the impact, and investigates the possible impact mechanism. The result shows that from the overall impact and its sources, the development of E-commerce in cities has a positive impact on the high-quality development of agriculture, and the impact is mainly due to its role in promoting technological innovation and economies of scale. From the perspective of heterogeneity, the larger the population size of a city, the more significant the level of e-conomic development or Internet development. From the perspective of the dynamic impact, the positive impact of e-commerce development becomes more significant over time. With the passage of time, the impact of E-commerce on high-quality agricultural development policies shows a trend of first increasing and then decreasing. Overall, this study provides empirical evidence for the rationality and effectiveness of policies and measures related to E-commerce to promote the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

Environmental public interest litigation (EPIL) is a significant part of the judicial system; it is aimed at strengthening judicial protections and safeguarding public interests. Based on the quasi-natural experimental setting of China's EPIL pilot project, this study examines the impact of EPIL on the country's urban land green use efficiency (ULGUE). The findings show that effectively implementing EPIL enhances ULGUE. Specifically, this policy has led to a 6.6% increase in ULGUE in pilot cities, and its impact has grown stronger over time. Mechanism analysis results show that EPIL mainly enhances ULGUE by strengthening environmental supervision and law enforcement, by increasing public participation in environmental governance, and by promoting green innovation and industrial structure upgrades. Furthermore, heterogeneity analysis revealed that the positive effects of this policy implementation are more pronounced in resource-based cities, cities with open environmental information, and cities with high marketization. This paper provides empirical evidence for the effectiveness of environmental governance via EPIL. [ABSTRACT FROM AUTHOR]

Leading with the principle of 'people-oriented urbanization,' the adaptation of rural migrants in urban China has attracted increasing concerns from policy-makers and scholars. Today, China has proceeded to a new stage of urbanization. Many rural migrants prefer moving to cities near their home villages rather than to large cities, reflecting the changes in migration patterns and expectations of rural migrants. Although migrant adaptation has been repeatedly investigated in academia, researchers tend to address the topic in one host setting, while migrant adaptation in diverse urban settings has rarely been compared. This paper seeks to fill this research gap via a survey conducted in two cities with different urban settings in Jiangsu. The rural migrant adaptation experiences in the two cities are systematically compared. Our statistical results show that economic structure and living costs, on the one hand, and local regulations and socio-cultural environments, on the other hand, determine rural migrant adaptation experiences in different urban settings. Despite abundant employment opportunities in more-developed cities, the high living costs, working pressure, and strict institutional schemes significantly hamper rural migrant adaptation. In less-developed cities, limited employment opportunities and conservative socio-cultural environments hinder rural migrants from adapting in host societies. Our findings suggest that the governments of different cities need to tailor strategies to assist rural migrants in adapting in urban communities. [ABSTRACT FROM AUTHOR]

Under the influence of development strategies with regard to national fitness and health in China, the interactive development between national fitness and national health is becoming increasingly strong. To explore the coupling and coordination relationship between national fitness and national health, this paper conducts an empirical analysis of the coupling and coordination relationship between national fitness and national health in 11 provinces and cities in Eastern China using the entropy weight method, a coupling coordination model, spatial visualization of the coupling coordination degree and spatial autocorrelation analysis. The research confirms that the comprehensive development level of national fitness and national health in Eastern China shows a steady upward trend, with a lag in national fitness as a whole, and that the growth rate of national fitness development is faster than that of national health development. The coupling coordination degree of the two systems of national fitness and national health in Eastern China shows a slow upward trend, and the coupling coordination degree rises from barely coordinated to primary coordination. There are significant differences in the spatial pattern of coupling coordination: the spatial pattern from north to south generally shows 'low-high-high-low-high-low' characteristics, and the spatial spillover effect of coupling coordination in various regions has not yet appeared. The revised GM(1.1) prediction results indicate that the level and improvement rate of coupling coordination will accelerate significantly in the next 10 years, but the spatial differences will still exist. Finally, suggestions are proposed to optimize the coupling and coordinated development of national fitness and national health based on policy guarantees as well as strengthening and cross-regional cooperation. [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]