ARTICLE INFO
Keywords:
Chengdu-chongqing Economic Circle
Urban resilience
Spatial-temporal evolution
Driving factor
ABSTRACT
To clarify the connotations and extensions of urban resilience, this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects. A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020. The spatial-temporal evolution characteristics were analyzed using Kernel density estimation, standard deviation ellipse, and spatial Markov chain analysis, and the spatial Tobit model was introduced to discover the influencing factors. The results indicate the following: (1) Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend, with the center of gravity moving to the southwest, and the polarization phenomenon intensifying. (2) The urban resilience level in a region has certain spatial and geographical dependence, while the probability of urban resilience transfer differs in adjacent cities with different resilience levels. (3) Urban centrality, economic scale, openness level, and financial development promote urban resilience, whereas government scale significantly inhibits it. Finally, this paper proposes countermeasures and suggestions to improve the urban resilience of the ChengduChongqing Economic Circle.
(ProQuest: ... denotes formulae omitted.)
1. Introduction
Today, more than half of the global population lives in cities. Moreover, with the rapid development of modern economies, more people worldwide will enter cities in search of opportunities (Tao, 2022). Cities are complex systems in which factors such as the natural environment, infrastructure, business, and society interact. However, with the acceleration of urbanization among other factors, cities are more vulnerable to the impact of adverse events, such as earthquakes, climate change, extreme weather, energy shortages, infectious diseases, and social conflicts (Sheng, 2023). In response, international initiatives, such as the Global 100 Resilient Cities, United Nations 2030 Sustainable Development Goals, and New Urban Agenda, have been proposed to enhance the sustainable development capacity of cities. In this context, a new approach to urban risk management, urban resilience, has grown as a research topic in the field of urban sustainability science, the core of which is the conviction that urban systems can effectively resist internal and external shocks and adapt to various uncertainties (Shao and Xu, 2015).
The word "resilience" comes from the Latin "resilio", meaning to return to the original state. The concept of resilience first appeared in the engineering field, termed "engineering resilience", and described the ability of objects to return to their original state after deformation under the action of external forces (Zhao et al., 2020). Subsequently, the Canadian ecologist Holling (1973) was the first to apply the concept of resilience to systems ecology to describe the stable state of ecosystems. Resilience in systems ecology refers to the speed and ability of ecosystems to adapt, self-reorganize, and restore equilibrium when disturbed from their original equilibrium state. Gradually, this concept was extended to human social systems (Carl, 2006). For instance, since the 1990s, the concept of resilience has been applied to anthropology, disaster science, economics, sociology, urban planning, and other social disciplines (Adger, 2000). In 2002, Local Governments for Sustainability (ICLEI) first proposed the concept of "urban resilience" and introduced it into the study of urban and disaster prevention, aiming to strengthen urban planning, architectural design, infrastructure construction, emergency preparedness, among other aspects. By strengthening these disciplines, it would improve the comprehensive coping ability of urban systems to adapt to the challenges such as climate change and disaster risk (Liu, 2021).
In recent years, the study of urban resilience has developed from a simple response to natural disasters to a frontier focus of urban construction, planning, management, and governance research. At present, it covers a number of crosscutting fields involving planning, the economy, society, the environment and systems, while constantly deepening its conceptual connotations. Practically, it represents a strategic pathway and policy tool for preventing risks in major cities around the world. Urban resilience can be defined as the ability of cities to mitigate the impact of acute shocks and chronic pressures such as natural disasters, climate change, environmental pollution, energy shortages, economic pressure and resilience aftershocks (Cere et al., 2019; Lee and Lee, 2016).
Domestic and foreign scholars have studied urban resilience primarily from the perspectives of urban planning, climate disaster, social economy, and community governance (Egidi and Salvati, 2020; Guo et al., 2020). From the perspective of planning and design, Pickett et al. (2010) consider adaptability as a key component of resilience as a concept. Tan and Lu (2021) proposed response planning strategies for prominent public health events based on the framework of early warning, response, and recovery. Cities worldwide have explored different aspects of macro-framework, urban design, and underground space (Papa et al., 2015). Cutter et al. (2008) proposed disaster resilience from the perspective of climatic disasters. Li and Zhai (2017) believed that geographical location has an important impact on the spatial differential distribution of urban disaster resilience. Li et al. (2022) described the resilience of urban responses to waterlogging disasters from three perspectives: disaster-causing, disasterresistant, and disaster-bearing. Wang et al. (2022) considered the Beijing-Tianjin-Hebei Urban Agglomeration as the research object and conducted a study on the resilience of urban built environments in response to rainstorm waterlogging by establishing a spectrum of resilience units. From a socioeconomic perspective, Vallance and Carlton (2015) pointed out that community groups and non-governmental organizations play a role in post-disaster reconstruction and flexible responses to risk reduction. Ma and Shen (2021) believed that urban resilience has a strong interactive relationship with the level of economic development. From the perspective of community governance, scholars such as Joerin et al. (2012) set up an urban community resilience evaluation index system with five dimensions (including infrastructure, society, economy, institutions and nature) aimed at community actions oriented toward resilience. Yang et al. (2019) used the BRIC measurement model to evaluate differences in community resilience in response to public health risks in Guangzhou from five dimensions: natural environment, built environment, society, economy and system.
In summary, existing literature has conducted beneficial discussions on the issue of urban resilience, providing a rich theoretical basis for this study. However, existing studies have not yet proposed a comprehensive urban resilience evaluation index system, and mostly focus on the Beijing-Tianjin-Hebei Urban Agglomeration (Zhang et al. 2021), the Yangtze River Delta (Zhang et al. 2022) and other regions with rapid development and good economic prospects. Alternatively, they focus on disaster-prone areas such as the Yellow River basin (Shi, 2022) and Shandong Peninsula (Wang and Niu 2022), while there are few studies that consider the "chronic impact" and factors affecting urban resilience in the western region. To address this, this paper took 16 cities in the Chengdu-Chongqing Economic Circle as research subjects and constructed a comprehensive evaluation index system for urban resilience consisting of dimensions-society, economy, ecology and infrastructure. The TOPSIS model was employed to evaluate the resilience level of each city in this urban agglomeration from 2003 to 2020, and a GIS visual analysis of urban resilience level was conducted. The spatial and temporal evolution trend was analyzed by the methods of Kernel density estimation and standard deviation ellipse. The spatial Markov chain model was used to describe in detail the direction and probability of the transition between different levels of urban resilience in the Chengdu-Chongqing Economic Circle, and the evolutionary trend of the Chengdu-Chongqing Economic Circle was predicted. Finally, a spatial Dubin model was constructed to explore the factors influencing urban resilience.
The contributions of this paper are as follows. Firstly, it builds a scientific, reasonable and adaptable urban resilience evaluation index system. Secondly, it provides a reference for urban sustainable development urban which can assist to strengthen the adaptability of urban ecosystems. Thirdly, it provides a scientific basis and technical support for urban planning and construction of the ChengduChongqing Economic Circle, promoting the coordination and interaction of the east, central and west regions.
The structure of this paper is as follows. Section 2 describes the research subject and index system developed for evaluating urban resilience. Section 3 analyzes the spatiotemporal evolution of urban resilience in the Chengdu-Chongqing Economic Circle. Section 4 introduces the factors influencing urban resilience. Section 5 presents the policy implications based on the research conclusions.
2. Comprehensive evaluation of urban resilience in ChengduChongqing Economic Circle
2.1. Chengdu-Chongqing Economic Circle
The Chengdu-Chongqing Economic Circle comprises 16 cities, including Chongqing and Chengdu. The urban cluster was estimated to reach a total area of 185 000 km2 by 2022. The permanent resident population in the region is about 97 million, and the regional GDP reaches 7.35 trillion yuan, up by 8.5% year on year. It is the most densely populated region in western China, with the strongest industrial base, the strongest innovation capacity, the broadest market space and the highest degree of openness. Moreover, it is situated on the important node of the Belt and Road Initiative and the Yangtze River Economic Belt and the main axis of the national "two horizontal and three vertical" development pattern. With the unique advantage of connecting the east and west, it is the center of Southwest China and occupies an important strategic position in the overall national development. It compensates for the lack of a "leading" in the development of western China and will work with the Beijing-TianjinHebei Urban Agglomeration, the Yangtze River Delta and the Guangdong-Hong Kong-Macao Greater Bay Area three economic circles to promote the coordinated development of the east, central and west.
2.2. Comprehensive evaluation index system and data description of urban resilience
To scientifically evaluate the level of urban resilience in the Chengdu-Chongqing Economic Circle, this study incorporates the evaluation theories of Zhang and Feng (2018), Shi et al. (2022), and Han et al. (2022) to systematically construct an evaluation index system of urban resilience in combination with the actual development of the Chengdu-Chongqing Economic Circle. The indicator system was divided into 30 indicator layers under four criteria: economic resilience, social resilience, ecological resilience and infrastructure resilience, as shown in Table 1.
(1) Economic resilience. Urban economic development is the foundation and driving force of urban resilience, which directly affects the ecology, environment, and social level of a city. This study selected seven indexes for evaluation: GDP per capita, proportion of tertiary industry in GDP, average salary of employees, general budget income, total retail sales of social consumer goods, proportion of science and education investment in GDP, and total investment of fixed assets.
(2) Social resilience. A healthy urban social environment guaran- tees residents a stable life and sustainable urban development. This study selected nine indicators for evaluation: the natural growth rate of the population, population density, grain output, number of tals and centers, number of doctors per 10 000 people, number of students in ordinary colleges and universities, number of employees in public management and social organizations, and number of urban workers participating in basic old-age insurance.
(3) Ecological resilience. Protecting the ecological environment is conducive to improving the living environment and maintaining the biodiversity of cities and enhancing their anti-interference ability in the face of natural disasters. In this study, six indicators were selected for evaluation: green space area of parks, green coverage rate of built-up areas, total water supply, industrial wastewater discharge, harmless treatment rate of household garbage and sewage treatment rate.
(4) Infrastructure resilience. Infrastructure is the "lifeline" of a city and an important guarantee for the evacuation and rescue of a city in the face of disasters. In this paper, eight indicators were selected for evaluation: the total number of telecommunications services, the length of water supply pipelines, the density of drainage pipelines in the built-up area, the penetration rate of gas, the per capita urban road area, the number of public toilets per 10 000 people, urban road lighting and the expenditure of maintenance and construction funds.
The data in the above index system came mainly from the China City Statistical Yearbook and China Urban Construction Statistical Yearbook from 2004 to 2021, while some of the data came from the Sichuan Statistical Yearbook and Chongqing Statistical Yearbook. The missing values of individual indicators were supplemented using the interpolation method.
2.3. Comprehensive evaluation results of urban resilience
The TOPSIS model was used to comprehensively evaluate the urban resilience of the Chengdu-Chongqing Economic Circle from 2003 to 2020. The scores indicating the level of urban resilience of each of the 16 cities are shown in Table 2. In the period from 2003 to 2020, the urban resilience of the Chengdu-Chongqing Economic Circle showed only a brief downward trend between 2009 and 2010, maintaining a steady upward trend overall. Of all the cities, the average values of Chengdu and Chongqing during the investigation period were 0.375 and 0.525, respectively, far exceeding the overall average value of urban resilience in the Chengdu-Chongqing Economic Circle of 0.118. The resilience of the other 14 cities was significantly different from that of Chongqing and Chengdu, mainly because Chongqing, as a municipality directly under the Central Government, is the only super-large city in the upper reaches of the Yangtze River in China. Moreover, it has a concentration of water, land, and air transportation resources and is a comprehensive transportation hub in Southwest China. Consequently, it is relatively rich in national resources and has certain advantages in the development of its economy, society, ecology, and infrastructure. Chengdu, as the capital city of Sichuan Province, is an important central city in western China, an important national high-tech industrial base, a business and logistics center and a comprehensive transportation hub. Chengdu can not only absorb a large number of talented workers in the process of urban development, but also a continuous influx of resources from surrounding cities. Therefore, due to their many advantages, Chengdu and Chongqing have a level of comprehensive urban resilience that the other 14 cities cannot match. Moreover, this level increased significantly from 2010 to 2020. The growth of their level of urban resilience came mainly from the growth of economic resilience and infrastructure resilience, accounting for 45.78% and 30.77%, respectively, of the total growth. The reason is that in 2011, The State Council officially approved the Chengdu-Chongqing Economic Regional Plan, pointing out that by 2015, the economic strength of the Chengdu-Chongqing Economic Zone should be significantly enhanced, an important economic center in the western region and an important modern industrial base in China should be built, the level of basic public services as well as the living standards of the people should be significantly improved. It is evident from the scores just presented that the program has achieved remarkable success.
3. Analysis of spatial and temporal dynamic evolution characteristics of urban resilience
3.1. GIS visual analysis of urban resilience in Chengdu-Chongqing Economic Circle
Based on the urban resilience value of the Chengdu-Chongqing Economic Circle, the natural breakpoint method was used to divide the 16 cities in the Chengdu-Chongqing Economic Circle into three categories, from which the distribution range of the different cities as measured by urban resilience was obtained. The categories were as follows: I-low urban resilience area, II-medium urban resilience area, Ш-high urban resilience area.
The calculation results of the urban resilience level of each city in 2003, 2010 and 2020 were selected, and the spatial pattern evolution of the urban resilience level of each research unit was drawn using ArcGIS software, as shown in Figure 1. The spatial distribution pattern of the resilience level reveals spatial heterogeneity in the resilience levels of the cities in the study area. The two core areas of Chengdu and Chongqing always occupied areas with high levels of urban resilience, whereas areas with low levels of urban resilience were mainly distributed in the middle, west, south, and northeast of the study area. In general, the urban resilience levels of the ChengduChongqing Economic Circle present a spatial distribution pattern of "dual-core prominence and central collapse".
From the perspective of the spatial evolution of the urban resilience level, the overall resilience level of the Chengdu-Chongqing Economic Circle declined significantly in 2003, 2010 and 2020. In 2003, the urban resilience value ranged from 0.036 to 0.309, and urban resilience was mainly in the medium urban resilience area (Category II), accounting for 50% of the total area. By 2010, urban resilience was still dominated by low urban resilience areas (Category I), accounting for 62.5% of the total area, among which Dazhou, Zigong, Yibin, and Luzhou declined from medium to low urban resilience areas. By 2020, the urban resilience value of the Chengdu-Chongqing Economic Circle ranged from 0.083 to 0.766, with the low urban resilience area accounting for 68.75% of the total area, and the number of cities in the medium urban resilience area having decreased to three. Only Mianyang and Nanchong remained in the medium urban resilience area.
3.2. Standard deviation ellipse analysis of urban resilience
To explore the spatial distribution of urban resilience in the Chengdu-Chongqing Economic Circle further, the center of gravitystandard deviation ellipse was used to draw the standard deviation ellipse and the trajectory of the urban resilience center of gravity in 2003, 2010 and 2020, as shown in Figure 2. Through this method, changes in the center of gravity, the direction of movement, and the discrete trend of urban resilience in the Chengdu-Chongqing Economic Circle could be plotted as shown in Figure 2. During the study period, the ellipse of the standard deviation of urban resilience in the Chengdu-Chongqing Economic Circle showed an east-west pattern and moved to the southwest as a whole, while the total coverage area shrunk by 0.24 million square kilometers. The azimuth angle first increased and then decreased from 89.14° in 2003 to 90.34° in 2010 and then to 90.03° in 2020. This clearly indicates that the urban resil- ience of the Chengdu-Chongqing Economic Circle displays a trend of continuous anticlockwise movement. From the perspective of the long half axis and the short half axis, the main axis and the secondary axis of the standard deviation ellipse showed a fluctuating change of first increasing and then decreasing during the study period. This shows that the spatial evolution of urban resilience in the ChengduChongqing Economic Circle was temporarily unstable in the east-west and north-south directions.
3.3. Kernel density estimation analysis
To reveal the dynamic evolutionary characteristics of urban resilience in the Chengdu-Chongqing Economic Circle, a Kernel density estimation of urban resilience in the period from 2003 to 2020 was carried out. The results are presented in Figure 3. From the perspective of distribution position, the urban resilience of the ChengduChongqing Economic Circle shows a trend of moving to the right, in- dicating that the urban resilience of this region is constantly improving. From the perspective of the distribution pattern, the height of the main peak decreases and the width expands, indicating that the absolute difference in urban resilience within the cities of the ChengduChongqing Economic Circle has increased. From the perspective of distribution ductility, there is a right-trailing phenomenon of urban resilience in the Chengdu-Chongqing Economic Circle, and distribution ductility is expanding, indicating that the improvement in the urban resilience of cities in urban clusters is evidently unbalanced. From the perspective of polarization characteristics, the urban resilience of the Chengdu-Chongqing Economic Circle showed a "single peak-double peak" trend and the polarization phenomenon within urban clusters gradually intensified.
3.4. Spatial Markov chain analysis
The Kernel density estimation described the evolutionary trend of urban resilience in the Chengdu-Chongqing Economic Circle. To describe in detail the direction and probability of the transfer between different levels of urban resilience, this study utilized a spatial Markov transition probability matrix, forecasting the evolution of the Chengdu-Chongqing Economic Circle. Firstly, the Chengdu-Chongqing Economic Circle was divided into four levels using a quartile method. Below 0.054 is the level of low urban resilience (I); between 0.054 and 0.070, the medium-low level of urban resilience (II); between 0.070 and 0.095, the medium-high level of urban resilience (III); and above 0.095, the high level of urban resilience (IV). Next, the spatial Markov transfer probability matrix of urban resilience of the Chengdu-Chongqing Economic Circle was calculated with a one- year lag. The results are shown in Table 3.
Table 3 reflects the spatial Markov transition probability of the urban resilience level in the Chengdu-Chongqing Economic Circle. The level of urban resilience in the Chengdu-Chongqing Economic Circle has a certain spatial and geographical dependence, and the probability of urban resilience level transfer is different under different urban resilience levels. Cities with high levels of urban resilience exhibit strong stability and are less affected by spatial and geographical environments. In the spatial Markov transfer probability matrix, a city with a high urban resilience level, regardless of whether it is adjacent to a city with a low or high urban resilience level, retains its original state with a 100% probability. Cities with high urban resilience levels can promote the improvement of cities with medium-high urban resilience levels but have no significant effect on cities with low and medium-low urban resilience levels. When the adjacent city has a low urban resilience level, the probability of a city with a medium and high urban resilience level transferring to a city with a high urban resilience level is 0, and the probability of a downward transfer is 33.3%. When the adjacent city has a high level of urban resilience, the probability of an upward transition increases to 15% and the probability of a downward transition drops to 5%. However, the probability changes were not evident when the level of urban resilience was low or medium-low.
4. Analysis of the influencing factors of urban resilience
4.1. Construction of spatial econometric model
The above analysis demonstrates that urban resilience in the Chengdu-Chongqing Economic Circle has a certain spatial and geographical dependence. Regrettably, the traditional econometric model ignores the spatial spillover effect between regions and cannot be used to explore the factors that influence urban resilience. Therefore, this study follows the approach of Liu et al. (2022) and Wang et al. (2022) in constructing the spatial Dubin model. Based on the traditional econometric model, a spatial adjacency matrix is used to introduce spatial elements, making the estimation results more accurate. The model is as follows.
...
Where, i represents the city and t represents the year. yit is the dependent variable; xij is the independent variable; wijyit is the interaction term between the dependent variable and the weight matrix; p is the spatial autoregressive coefficient; ß is the coefficient of the independent variable; θ is the regression coefficient of the spatial lag term; μi is the individual fixed effect; λt is the time fixed effect; and is the random error term.
Wij is the spatially adjacent weight matrix; that is, when the urban units are not adjacent, the elements of the matrix are set to 0; when they are adjacent, the elements of the matrix are set to 1 and the diagonal elements set to 0. The specific settings were as follows.
...
4.2. Variables and data description
This study considered the urban resilience level of the ChengduChongqing Economic Circle as a dependent variable. This variable can be divided into four dimensions: economic, social, ecological, and infrastructural. The explanatory variables included urban centrality, economic size, population size, level of openness, financial development, and government scale. Economic scale was expressed by GDP. Population size was represented by the total registered population at the end of the year. The level of openness was measured by the ratio of total imports and exports to GDP. Financial development was measured as the ratio of outstanding deposits and loans to GDP. Government scale was measured by fiscal spending as a share of GDP. Given that the size of the economy and the size of the population are aggregate indicators, the natural logarithm of these two variables was taken in the regression. Additionally, the gravity model was introduced to determine the spatial relationship of the urban resilience of each city, and the UCINET software was used to calculate the urban centrality.
4.3. Model selection
This study first used the global Moran index to test whether the urban resilience of the 16 cities in the Chengdu-Chongqing Economic Circle is spatially correlated. Table 4 shows that the global Moran index of the urban resilience of these cities from 2003 to 2020 was negative and significant at the 5% level. This indicates that the level of urban resilience has a significant negative spatial effect, and a spatial econometric model should be adopted.
To further verify the accuracy of the selected spatial econometric model, the Hausman, LM, LR and Wald tests were performed (Table 5). The H-statistic of the Hausman test rejects the null hypothesis of using random effects in fixed effects and random effects at a significance level of 1%; therefore, the fixed effect is selected as the initial model. The LM test results show that the LM_Error, R_LM_Error, LM_Lagt, and R_LM_Lag statistics pass the significance test, indicating that the level of urban resilience in the Chengdu-Chongqing Economic Circle is spatially dependent. The LR and Wald test results show that the LR-SAR, LR-SEM, Wald-SAR, and Wald-SEM statistics reject the null hypothesis that they degenerate into spatial lag and spatial error models at a significance level of 1%, indicating that there are spatial lag terms and spatial error effects in the model. Therefore, this study chose the spatial Dubin model, which combines spatial lag and spatial error models.
4.4. Analysis of results
Columns (1) to (4) of Table 6 report the regression results for the two-way fixed effects, SAR, SEM, and SDM, respectively. In view of the above model selection, this study mainly analyzed the estimation results of the two-way fixed SDM. It is apparent from the estimation results that five factors, including urban centrality, economic scale, openness, financial development, and government scale, have a sig- nificant impact on urban resilience. Urban centrality, economic scale, openness, and financial development play positive roles in promoting urban resilience. Their influence coefficients were 0.018, 0.103, 0.039 and 0.026, respectively. Urban centrality plays a significant role in promoting resilience because cities with high urban centrality, such as Chengdu and Chongqing, have closer connections with other cities, and therefore, when they encounter disasters, they can easily gather the strength of the surrounding cities to jointly resist. Economic scale plays a significant role in promoting urban resilience because the development of various social undertakings is inseparable from the economy. A city with a higher level of economic development has a greater material foundation and economic security to resist disaster in the face of sudden danger. The level of openness plays a significant role in promoting urban resilience because by having access to international resources. The cities in the Chengdu-Chongqing Economic Circle can constantly make rapid adjustments to adapt to risks and crises, effectively enhancing the prevention capacity of their urban systems. The expansion of financial development is conducive to absorbing the idle funds within society, promoting the upgrading of regional industrial structure, and thus contributing to the improvement of urban resilience. In contrast to the aforementioned factors, Government scale has a significant hindering effect on urban resilience. This is due to excessive governmental intervention interfering with market adjustments, resulting in the misallocation of the resources within a region or city and reducing the ability of the region or city to resist shocks.
Next, this study adopts the SDM model with two-way fixed effects to discuss the influence of the above six factors on the four dimensions of urban resilience in the Chengdu-Chongqing Economic Circle: economic resilience, social resilience, ecological resilience, and infrastructural resilience. The results are presented in Table 7.
It is apparent from the estimation results that the impact of urban centrality on the four dimensions is significantly positive. This translates into an overall positive effect on urban resilience. Economic scale plays a positive role in economic, ecological, and infrastructure resilience, but a negative role in social resilience. Compared with social resilience, it has a stronger impact on economic and infrastructure resilience, which may be the reason for its positive impact of on urban resilience. Population size has a positive impact on a city's social and infrastructure resilience but a negative impact on its ecological resilience. Its impact on economic resilience is not significant. Overall, population size has no significant impact on urban resilience. It may be that its positive impact on social and infrastructural resilience and negative impact on ecological resilience are of the same magnitude and cancel each other out.
Openness has a positive impact on economic resilience, social resilience, and infrastructural resilience but no significant impact on social resilience. Therefore, the degree of openness positively impacts urban resilience. Financial development plays a positive role in promoting a city's economic and infrastructure resilience. It also has an inhibitory effect on social resilience but no significant effect on ecological resilience, resulting in an overall positive promotion effect on urban resilience. Government scale restricts economic, ecological, and infrastructure resilience, which, in turn, has a significant inhibitory effect on urban resilience.
5. Conclusions and policy implications
5.1. Conclusions
This study constructs a set of index systems to comprehensively evaluate the urban resilience of 16 cities in the Chengdu-Chongqing Economic Circle from 2003 to 2020. It also reveals the space-time evolution trend and driving factors of urban resilience and draws the following conclusions. First, the overall resilience level of the Chengdu-Chongqing Economic Circle shows an upward trend. However, it was dominated by cities with low levels of urban resilience. Chengdu and Chongqing were the only two cities with high levels of urban resilience, levels which were significantly higher than those of other cities in the region. Furthermore, these levels showed a spatial distribution pattern of "dual-core prominence and central collapse". Second, from a spatial evolution perspective, the overall urban resilience of the Chengdu-Chongqing Economic Circle shows a trend of moving southwest: the proportion of cities with low urban resilience in the total region gradually increases; the absolute difference within the region gradually expands; and polarization intensifies. Thirdly, the Matthew effect can be observed in the urban resilience of the Chengdu-Chongqing Economic Circle. Cities with high levels of urban resilience tend to maintain their original state in the future, likewise for cities with low levels. It is not easy to leapfrog across levels. Cities with medium and high levels of urban resilience are promoted to higher levels when they are adjacent to cities with high levels of urban resilience. Fourth, urban centrality, economic scale, level of openness, and financial development had a significant positive impact on urban resilience, while government scale had a significant inhibitory effect.
5.2. Policy implications
Based on the preceding conclusions, the following countermeasures and suggestions are put forward. First, full scope should be given to the radiation and driving role of cities with high level of urban resilience in the Chengdu-Chongqing Economic Circle. This study reveals that the urban resilience level of the Chengdu-Chongqing Economic Circle has a spatial distribution pattern of "dual-core prominent and central collapse" , and increasing polarization. Therefore, to break through the administrative boundary restrictions of the Chengdu-Chongqing Economic Circle and drive the overall development of urban resilience, full scope should be given to the role of "dual-core" cities as important fulcrum and power sources of highquality development. Second, to strengthen the ecological environment protection of the Chengdu-Chongqing Economic Circle, it is necessary to vigorously develop a green economy, comprehensively promote energy conservation and consumption reduction, establish an assessment system for urban ecological resilience, and develop a sound big data platform for ecological and environmental supervision. These measures will enable the Chengdu-Chongqing Economic Circle to continuously improve its level of ecological environment governance, reduce the occurrence of natural disasters and enhance its resilience level. Third, the safety-guaranteeing role of social resilience should be emphasized by formulating a sound social security system, improving the coverage rate of social security that covers medical treatment, introducing high-level medical personnel, and improving the city's overall quality of medical care. Fourth, the government functions of the Chengdu-Chongqing Economic Circle should be optimized by standardizing government budgets and expenditure systems and improving the efficiency of fiscal expenditures on ecology and infrastructure projects. Moreover, in the process of economic development, full scope should be given to the positive role of market resource allocation. Fifth, because economic scale and level of openness play a significant role in promoting urban resilience, a high-level open economy should be developed in the Chengdu-Chongqing Economic Circle. This would involve making full use of The New International Land-Sea Trade Corridor, the Belt and Road Initiative and the Yangtze River Economic Belt, resources from open platforms such as the Chengdu-Chongqing free trade area and comprehensive bonded zones, and China ' s important inland modern open industrial base.
5.3. Limitations and research outlook
This study measured the urban resilience of 16 cities in the Chengdu-Chongqing Economic Circle in terms of the four dimensions of urban resilience: society, economy, ecology and infrastructure. It analyzed the factors that influence urban resilience from a spatial perspective, and proposed strategies for improvement. However, owing to the availability of data, this study has some shortcomings. This study can be improved in the following two aspects: First, the precision of the research unit can be expanded. Currently, literature on the measurement of urban resilience at the county level is limited. However, because counties are the smallest urban units, evaluating urban resilience at that scale can indicate more accurately the level of resilience of urban clusters. This would be of great value for improving urban resilience. Second, the indicator system used to assess urban resilience can be improved. A city is a complex socio-ecological system; therefore, any aspect has the potential to affect the development of urban resilience. This study draws on the results of previous studies and selects 30 indicators based on the principles of scientific simplicity and systematicity. Future research can improve the indicator system of urban resilience from multiple perspectives and aspects, based on existing research and practical needs.
Disclosure statement
No potential conflict of interest was reported by the authors.
Author contributions
Xin Li: software, validation, writing-original draft preparation, visualization, writing, reviewing and Editing. Shuyi Zhang: data curation. Rongxi Ren: investigation. Yafei Wang: conceptualization, methodology, supervision
Funding
This study was supported by the Graduate Research and Innovation Project of Chongqing Normal University [Grant No. YKC23035], comprehensive evaluation, and driving factors of urban resilience in the Chengdu-Chongqing Economic Circle.
Received 12 August 2023; Accepted 02 January 2024
* Corresponding author.
E-mail address: [email protected] (Y. Wang)
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Abstract
To clarify the connotations and extensions of urban resilience, this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects. A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020. The spatial-temporal evolution characteristics were analyzed using Kernel density estimation, standard deviation ellipse, and spatial Markov chain analysis, and the spatial Tobit model was introduced to discover the influencing factors. The results indicate the following: (1) Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend, with the center of gravity moving to the southwest, and the polarization phenomenon intensifying. (2) The urban resilience level in a region has certain spatial and geographical dependence, while the probability of urban resilience transfer differs in adjacent cities with different resilience levels. (3) Urban centrality, economic scale, openness level, and financial development promote urban resilience, whereas government scale significantly inhibits it. Finally, this paper proposes countermeasures and suggestions to improve the urban resilience of the ChengduChongqing Economic Circle.
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Details
1 School of Economics and Management, Chongqing Normal University, Chongqing 401331, China
2 College of Marxism, Taiyuan Normal University, Taiyuan 030619, China
3 Family Institute, Northwestern University, Chicago 60208, USA