Development Of Cities In China Research Articles

Data-driven insights into age-friendly smart community development in China: A case study of Beijing

The aging society has prompted a re-evaluation of community development strategies to better accommodate the needs of older populations. In this context, the concept of age-friendly smart communities has gained prominence, aiming to leverage technologies to enhance the quality of life for older residents. This article summarizes a general concept of an age-friendly community within the framework of smart city development in China. It then explores residential compounds in Beijing to investigate their potential for implementing age-friendly smart communities. Through data description and classification, the spatial distribution and local characteristics of residential compounds were examined. The results highlight housing compounds with the potential to become age-friendly smart communities, based on factors such as building age, population demographics, and typological differences reflecting community conditions and surrounding resources. Overall, by examining the intersection of the aging population, urban regeneration, and technology integration, this article contributes to understanding how data-driven insights can shape the evolution of smart communities in an aging society.

从全球百余城市低碳发展水平异同看中国城市低碳发展之道

Conducting the evaluation of low-carbon development of global cities has important guiding significance for the low-carbon city development in China. However, there are no widely accepted and applied low-carbon city indicator frameworks currently. Existing studies either focus on Chinese cities only, or apply to around 10 large world cities, failing to consider the applicability and comparability of a large number of world cities (i.e. more than 100). Therefore, this report is aimed to fill in the above knowledge gaps by developing a low carbon city indicator framework, conducting case studies and putting forward policy recommendations for different types of cities in China. The low carbon city indicator framework can: 1) reflect the low carbon development status of cities; 2) fit for both international and Chinese cities regarding data availability and comparability; 3) applicable to a large number of cities, i.e. more than 100 cities in the world.

Toward urban high-quality development: Evidence from more intelligent Chinese cities

Urban industrial intelligence (ININ) has been given great impetus to in China because it may boost urban high-quality development (HQD), which does not overlook the “quality” and “quantity” of development but focuses on the results and benefits of growth in multiple dimensions, including economic development, social equity, and the ecological environment. Three factors are suggested to explain the phenomenon: green innovation, market potential, and industrial pollution. Spatial correlations between ININ and HQD are also worthy to be detected for further strategic policy implications. On the basis of a panel of 278 Chinese cities from 2009 to 2020, this paper focuses on how ININ contributes to HQD, in hopes of advancing the process of sustainable urban development in China. Our results show that ININ is positively correlated with HQD, and significant and positive influence of ININ spillovers are found, which denotes the possibility and benefits of synergetic city development in China.

Urban climate adaptability and green total-factor productivity: Evidence from double dual machine learning and differences-in-differences techniques

Climate change has increasingly become a significant challenge to sustainable socio-economic development, and climate adaptation is a key issue that relevant research focuses on regional sustainable development models. By employing panel data between 2007 and 2020 from 284 Chinese prefecture-level cities, this study adopts quasi-experimental methods, including a difference-in-differences design and double dual machine learning model, to study the impact of climate adaptability on green regional sustainable development. Empirical results confirm that the pilot policy of building climate-resilient cities significantly improves urban green total-factor productivity. Difference-in-difference models (derived from entropy-weight and propensity score matching) and double dual learning models also support the improving effect of regional green total-factor productivity after policy intervention. The digital economy has strengthened the green development effect of pilot policies for building climate-adaptive cities. In addition, policy interventions to build climate-adaptive cities promote green urban development by optimizing industrial development structures and enhancing economic growth resilience. In addition, climate adaptability can also attract highly skilled talent and high-quality enterprises, facilitate science and technological progress in urban areas, and thus promoting the green development of cities in China. This study objectively evaluates the effects of climate policies and provides insights for global adaptation to climate change and optimization of public policies.

The Impact of Urban Renewal on Human Cognition and Behaviour: A Case Study in Tianzifang, Shanghai, China

In the background of the fast development of cities in China, urban renewal is becoming a more hotly discussed topic than ever. Lane Neighbourhood is a special presentation of old Shanghai features. But in the past decades, the Lane Neighbourhoods have experienced a decline in quantity and characteristics. Renewal of such urban districts is important for sustainable urban development and the continuation of cultural context. Most existing studies research this issue by focusing on an objective perspective. This article begins from a subjective perspective and chooses Tianzifang as a research target which goes through special renewal mode yet faces problems now. The article adopts questionnaires, interviews, cognitive mapping, space syntax, and GIS to analyse the impacts of urban renewal on peoples cognition, behaviour, and relationship and to find out important environmental factors for peoples life. Results show that community space is messy and unsustainable, with cultural characteristics fading. Relations between people are distant, and the development of industries affects a lot on cognition and life. The cognition of roads and districts is unbalanced, with the connection between factors weakened and special areas marginalized. Different aspects of features in Tianzifang are not fully recognized, utilized, and presented. This article provides suggestions for the future. The industrial pattern should be changed to address most cognitive issues. The space and life should be made more sustainable, cultural characteristics should be respected, and reasonable management should ensure all of these.

What determines the performance of low-carbon cities in China? Analysis of the grouping based on the technology-Organization-Environment framework.

Addressing climate change and reducing greenhouse gas emissions have emerged as shared global objectives. Enhancing the development performance of low-carbon cities has become an urgent and widely acknowledged concern for both government policy-making departments and academics. Drawing upon the complex grouping perspective and resource allocation theory, this study investigates how varying conditions related to technology, organization, and environment in Chinese low-carbon pilot cities can effectively allocate resources to shape the governance performance of low-carbon cities. This paper employs a comprehensive grouping analysis perspective, treating the research object as a combination of various ways between condition variables. It integrates the advantages of case studies and variable studies, and investigates the collective relationships between elemental groupings and outcomes using the fsQCA analysis method. This approach facilitates the understanding of multiple concurrent causal relationships within the technology-organization-environment (TOE) framework, accounting for different performance levels in Chinese low-carbon pilot cities, as well as addressing complex causal issues such as asymmetry and multiple scenario equivalence. Data from 30 representative low-carbon pilot cities in China were employed to validate the TOE theoretical framework. No single element alone can be considered a necessary condition for low-carbon city governance performance. However, environmental enhancement plays a more prominent role in the governance performance of low-carbon cities. Additionally, the presence of "multiple concurrent" technical, organizational, and environmental conditions leads to a diverse range of governance performance in Chinese low-carbon pilot cities. In other words, the driving paths of low-carbon city performance exhibit distinct pathways. The findings of this study can assist low-carbon pilot city managers in generating effective governance ideas, facilitating the successful implementation of low-carbon city pilot projects, and drawing valuable lessons from the experience of low-carbon city development in China.

Research on the Influencing Factors of The Green Coordinated Development of Productive Service Industry and Manufacturing Industry Under the Background of Dual Carbon

Under the dual-carbon background, along with the process of the two-wheel drive development strategy, the industrial synergistic agglomeration has quietly become the "new normal" of urban industrial spatial layout, and the green total factor productivity has become an essential measure of the quality of economic development of cities in China. This project takes the synergistic agglomeration at the factor level between the productive service industry and manufacturing industry as the perspective and analyzes the realization mechanism of green total factor productivity growth under the synergistic agglomeration of the manufacturing industry and productive service industry from the current situation of China's industrial development, which is also a deepening and expanding of the theory of agglomeration economy. This project first discusses the "greening" issue in the development process of the productive service industry and manufacturing industry, and applies the super-efficient DEA model to account for the green total factor productivity of the productive service industry and manufacturing industry according to the difference of industrial characteristics, and then expounds the inner mechanism of green total factor productivity growth under the synergistic agglomeration of industries. Then, the panel data of 24 provinces in China are used to modify the existing indexes for measuring the level of industrial synergistic agglomeration and analyze the impact factors of the synergistic evolution of the productive service industry and the manufacturing industry on the green total factor productivity. Finally, through scenario simulation analysis, different policy scenarios with different policy incentives are set up to study the impact of policy incentives further and propose corresponding policy recommendations.

How Does FDI Enhance Urban Sustainable Competitiveness in China?

Urban sustainable competitiveness (USC) is one of the important indexes to measure the high-quality development of cities in China. Meanwhile, foreign direct investment (FDI) plays the prominent role in improving urban sustainable competitiveness. Therefore, this analysis aimed to test the impact of FDI on the USC and its mechanism using the intermediary effect model with a sample of 282 cities in China during the period 2012–2018. The influencing mechanism includes the scale effect, the technological effect, and the structural effects. The results show that: first, FDI is significantly and positively related to the USC of China, and the scale, technological and structure effects all play a mediating role, with the scale effects being the most significant. Moreover, population size shows negative effect on the USC. Second, the impact of FDI on the USC is regionally heterogeneous. FDI can significantly improve the USC in the eastern region, but has no significant effects on the northeastern, central and western regions. Third, FDI in the eastern region affects USC through structural effects, while the scale and technological effects do not play a mediating role but both effects can directly affect USC. FDI in the northeast region still has the structural effect, but this structural effect does not indirectly affect USC, while FDI in the western region has both scale and structural effects. In addition, the technological and structural effects in the central region have a direct impact on USC, while the scale effect in the western region has a direct impact on USC. Therefore, the findings suggest that utilizing FDI should take into account regional characteristics in China.

Short-term traffic flow prediction: An ensemble machine learning approach

The inconvenience of travel, air pollution and consequent economic losses caused by traffic congestion have seriously restricted the healthy and sustainable development of cities in China. In this context, as the main component of current and future urban traffic management measures, intelligent transportation system is an important means to improve the traffic efficiency of road network and alleviate urban traffic congestion. Traffic flow prediction plays an important role in this connection. In this paper, an ensemble short-term traffic flow prediction method based on optimized variational mode decomposition (OVMD) and combined long short-term memory network (LSTM) is proposed. The method consists of three main components: 1. Use the improved bat algorithm to optimize the parameters of VMD to achieve better decomposition effect; 2. Use the optimized variational mode decomposition algorithm (OVMD) to decompose the unstable original traffic flow time series data into relatively stable multiple Intrinsic Mode Functions (IMFs); 3. The optimized L-BILSTM model is established by combining the basic long short-term memory network with the bidirectional long short-term memory network. It can better extract information from traffic flow data and improve the accuracy of prediction results.In the empirical study part, the traffic flow data of Changsha City is used to verify the prediction model proposed in this paper. The influence of the application of the variational mode decomposition algorithm to the training set data and the overall data on the final prediction results is also compared and analysed.

The Green Energy Transition and Peripheral City Development in China: Towards a Local Eco‐developmental State

ABSTRACTThe green energy transition is recognized for its inherent environmental contributions. This article illustrates how it can also reshape the economic landscape and create the conditions for a peripheral city to develop. Drawing on the politics of accelerating low‐carbon transition and focusing on the role that local governments play in this process, the authors illustrate how the green energy transition has commercialized wind and solar resources and constructed a new resource control system in northwest China. The Gobi Desert has extensive wind and solar energy resources; having the authority to grant access to preferential sites to exploit these resources empowers local governments to combine their interests with those of other stakeholders to build local capacity and achieve developmental goals. Governments are also able to manipulate renewable energy curtailments to promote infrastructure investment, technological progress, and the grid‐parity model. The green energy transition can therefore play a role in upgrading industrial structures, alleviating local poverty, narrowing regional development gaps, and contributing to national environmental improvement. This study provides a theoretical contribution to our understanding of how the local eco‐developmental state configures new energy spaces and restructures local governance, and argues that green industrial policies are sometimes actively nurtured by local rather than central governments.

Evaluating green city development in China using an integrated analytical toolbox

Promoting green city development has become a core measure to deliver eco-civilization in China, and China's practice in this regard could provide an insightful reference for the sustainable transformation of cities in other countries. However, multi-city empirical research on green city assessment in China has so far been limited, leaving plenty of room for improvement in the understanding of the issues regarding (1) characterization of disparities in the green development status among cities; (2) identification of key factors leading to the disparities; and (3) exploration of potential approaches to promoting green city development. This study integrates comprehensive index analysis, coordination analysis, difference analysis, and correlation analysis into an analytical toolbox, and investigates the green development of 36 major cities in China in 2015. The overall performance of these cities was not high, and showed clear regional imbalance. Relatively small cities, and the green transformation of consumption, deserve more concern in the near future. Other than a conventional comprehensive index, coordination degree brings a novel perspective to understand the green development status of cities. The key indicators contributing to the performance difference among the cities were generally related to sustainable lifestyles and decoupling consumption from resources and environmental pressures. In the end, increase of economic development quality, stimulation of social innovation, improvement of urban infrastructure, and appropriate urban density are proposed as policy suggestions to facilitate cities' green transition.

Smart Mega-City Development in Practice: A Case of Shanghai, China

As Shanghai is a megacity and pioneer in smart city development in China, this paper used Shanghai as a megacity example to investigate smart city development over the past ten years. By collecting data from multiple sources, a case study methodology was utilized to explore Shanghai’s smart megacity development in practice. Based on the key events and phases of Shanghai’s smart city development, the practical contents were systematically investigated. The main conclusions of this research included four aspects, consisting of information infrastructure, information technology and industrial development, information perception and smart applications, and a security assurance system. Moreover, a conceptual framework for Shanghai’s smart city development was constructed by integrating the phases and contents. Furthermore, the implications of Shanghai’s smart city development are critically discussed and identified from five aspects, including the development pathway, the government’s role, the financing channel, information and communication technology (ICT)-driven development, and a people-oriented concept. This study benefits academia, governments, and practitioners by providing useful insights and valuable implications for other cities to develop smart cities.

Environmental Regulation, Resource Misallocation, and Total Factor Productivity: An Empirical Analysis Based on 284 Cities at the Prefecture-Level and Above in China.

We investigated the impact of environmental regulation on total factor productivity (TFP) based on a panel dataset of 284 cities at the prefecture-level and above in mainland China from 2006 to 2020 and examined whether environmental regulation had a resource reallocation effect and thus affected TFP. The results showed that there was an "inverted U-shaped" pattern in the impact of environmental regulation on TFP in China and a moderate strengthening of environmental regulation helped to increase TFP, which still held after endogeneity treatment and robustness tests. The "inverted U-shaped" relationship between environmental regulation and TFP in eastern, central, and western cities still held, while environmental regulation did not produce significant effects on TFP in the northeast. The effect of environmental regulation on TFP in large, medium, and small cities tested in groups by city size was consistent with the full sample findings, but the effects decreased in a gradient with city size. The analysis of the impact mechanism showed that environmental regulation had a suppressive effect on resource misallocation and could generate a positive resource reallocation effect and enhance city TFP. The labor reallocation effect of environmental regulation for TFP was stronger than the capital reallocation effect. The findings of our study are of policy reference value for optimizing resource allocation through environmental regulation and thus promoting high-quality city development in China.

Transformation and development of resource-based cities in China: A review and bibliometric analysis

With increasingly serious environmental and resource problems, resource-based cities have attracted unprecedented attention at home and abroad. In recent years, resource-based cities have become a hot research topic that has produced fruitful results. However, few articles have comprehensively and systematically reviewed the research on resource-based cities, which makes it difficult to carry out further research. This study introduces the influencing factors of the urban transformation of resource-based cities, the path of urban transformation, and the evaluation index system of urban transformation in detail. At the same time, a total of 2,182 articles related to resource-based cities in the CNKI and WOS from 2002 to 2022 were taken as the research objects. CiteSpace software was used to conduct statistical analysis of publication dates, journals of publication, institutions, and highly cited literature. Using the co-occurrence network of literature keywords and the analysis of emergent words, the research status of resource-based cities at home and abroad is visually analyzed. It is found that Chinese universities attach the most importance to research on resource-based cities. Chinese-language journals focus on urban and economic transformation, while English-language journals focus on sustainable development and the circular economy, which are quite different. The overall research content of Chinese journals is scattered, the co-occurrence ability of keywords is weak, and the duration of hot research topics is short. In contrast, the overall research trend of English-language journals is more concentrated, the key words’ emergence intensity is high, and the duration is long. This study aims to systematically sort out the theories and research related to resource-based city development in China and internationally, clarify the key issues of resource-based city research and the shortcomings of existing research, and put forward feasible suggestions for future research.

Factors facilitating the development of low-carbon cities: evidence from China’s pilot cities

As the largest developing country, China has recognized the importance of low carbon cities. To date, three batches of low-carbon pilot provinces and cities were presented by the Chinese government from 2010 to 2017. Therefore, the local governments in the pilot group should take effective measures to promote the development of low-carbon cities. However, because of the lack of experience in implementing special policies for low-carbon cities, many local governments have encountered difficulties in promoting the development of low-carbon cities. This study critically analysed various policies promulgated during 2010–2021 by the Chinese local governments. The most relevant programming policies of pilot cities were selected. A multidimensional framework is developed to better understand the policies in facilitating low-carbon city development in China. The results showed that there are 16 factors at both the macro level and the micro level that affect the development of Chinese low-carbon pilot cities. The successful promotion of China’s low-carbon cities requires combined efforts from all related stakeholders. In addition, the development of pilot cities is actively promoted by the Chinese national government and linked to other strategic initiatives, such as “peak carbon” by 2030 and “carbon neutral” by 2060. The findings help to better understand the landscape of policy measures of low-carbon city development in China and provide useful references for policy making in other countries.

The impact of digital economy development on carbon emissions -- based on the Yangtze River Delta urban agglomeration

The dual carbon target has been the focus of domestic attention since it was proposed. At the same time, the digital economy based on new technologies such as the Internet and big data has become an important engine to boost China’s high-quality economic development. While the digital economy is promoting the development of the urban economy, can it also promote the low carbon development of cities in China? Based on panel data and multiple econometric models of 26 cities in the Yangtze River Delta urban agglomeration from 2006 to 2020, this paper empirically examines the impact of digital economy development on urban carbon emissions. The results show that the development of the digital economy can not only reduce the carbon emission intensity of this region but also effectively reduce the carbon emission intensity of surrounding areas. Therefore, it is necessary to further promote the construction of digital economy in the urban agglomeration, improve the inclusiveness and flexibility of the implementation of digital economy development strategy, and improve the construction of information infrastructure to give full play to the role of the digital economy in improving carbon emissions in urban agglomeration.

Inclusive green growth for sustainable development of cities in China: spatiotemporal differences and influencing factors.

Inclusive green growth (IGG) based on coordinating the society, economy, and environment is a new way to reach sustainable development. However, there is a lack of relevant research in developing countries. To bridge this gap, based on a comprehensive index that includes economy, social, and environment, this study evaluates the urban inclusive green growth index (IGGI) of 282 in China from 2003 to 2020 and analyzes the spatiotemporal dynamics and regional differences. Moreover, the spatial Durbin model is employed to explore the plausible influencing factors of urban IGGI in China. The main results show an increasing trend of IGGI in Chinese cities and imbalanced spatiotemporal dynamics. Furthermore, the econometric regress results show that upgrade of industrial structure, opening up, human capital, and urban innovation have significant positive impact on urban IGGI, while the administrative capacity of the government and urban industrialization show negative impact on urban IGGI; human capital not only affects the local IGGI but also has significant spatial spillover effects to the surrounding cities. This finding provides new evidence for China to achieve its 2030 sustainable development goals and sheds lights on how policy can be improved to boost IGGI levels and achieve carbon neutrality in 2060.

How does sponge city construction affect carbon emission from integrated urban drainage system?

The integrated urban drainage system has complicated sources of greenhouse gases (GHG) emissions, which is one of contribute to climate change. As a new model of low-carbon ecological city development in China, sponge city has great potential of carbon emission reduction. However, limited by the lack of awareness of the importance of carbon emissions from integrated urban drainage system, few studies have focused on the impact of sponge city construction on the carbon emissions from integrated urban drainage system. This study proposed an accounting framework for carbon emissions from integrated urban drainage system. The emission factor method was used to calculate carbon emissions. A case study was conducted in Xiamen, China, the carbon emission level of integrated urban drainage system and the carbon emission reduction effect of sponge city construction were discussed. The results show that the carbon emission from traditional city drainage system and sponge city drainage system accounts for about 3.4% and 1.7% of the city's carbon emission, respectively. Wastewater treatment and Sludge Treatment and Disposal are the main contributors to the carbon emissions from integrated urban drainage system. Electricity consumption is the main contributors to the indirect carbon emissions. Adjusting the sludge disposal method has the best carbon emission reduction effect, raising the standard of wastewater treatment plant tail water will lead to an increase in carbon emissions. Compared with the traditional city drainage system, the sponge city drainage system can reduce carbon emissions from integrated urban drainage system by an average of 49%, and the corresponding economic benefit was approximately 91–297 CNY/104 m3 wastewater. This study plays a positive role in understanding the carbon emission level of integrated urban drainage system and planning the low-carbon development of the city in the future.

Application and Thinking of Artificial Intelligence in Electrical Automation

With the vigorous development of China’s market economy, a new generation of artificial intelligence technology has also developed rapidly, which has strongly promoted the optimization and improvement of China’s electrical automation control system. The use of artificial intelligence technology in power automation systems mainly has the following two advantages: it can reduce the manufacturing time of power products, thereby increasing the number of workers manufacturing power products and promoting enterprises to conduct larger-scale machine manufacturing, thereby improving the comprehensive economic benefits of enterprise machine manufacturing, but also improve the quality of manufactured products of electric power products. Since the machine control of artificial intelligence is more efficient than manual manufacturing, it reduces the manufacturing problems caused by the subjective factors of manufacturing workers to a certain extent and thus improves the qualification rate of machine production. Electrical engineering plays an important role in China’s urban development, and automatic control is an important part of electrical engineering, which can have a direct impact on the quality of electrical engineering. Therefore, in order to promote the healthy development of cities in China, this paper studies the application of artificial intelligence technology in electrical engineering automation by analyzing relevant data, in order to provide a reliable basis for relevant personnel to carry out their work.

How Does City Size Affect the Cost of Household Travel? Evidence from an Urban Household Survey in China.

Travel costs are critical to the sustainable development of cities. This paper used Urban Household Survey (UHS) data from 2002 to 2014 and constructed a comprehensive city-size index from the perspectives of population and urban space to empirically test the impact of city size on the cost of household travel. The main results are as follows: (1) There is a significant positive correlation between city size and the cost of household travel. The internal mechanism is that city size affects the cost of household travel by increasing spatial distance and traffic congestion. (2) Increasing public transportation and per capita road area can restrain the positive impact of city size on the cost of household travel; moreover, the restraining effect of public transportation is stronger than that of per capita road area. (3) The impact of city size on the cost of household travel for sub-provincial cities is smaller than that for ordinary prefecture-level cities; in addition, there is an inverted U-shaped relationship between city size and the cost of household travel. This paper deepens the understanding of the impact of city size on travel costs, providing research support for the healthy development of cities in China.