Resilience Assessment and Influencing Factors of Chinese Megacities

Abstract

Urban resilience is one of the crucial components of sustainable urban development, yet challenges to sustainable urban development are created by the dangers of uncertainty in the context of global urbanization. Based on the perspective of the economic, social, ecological, infrastructural, and institutional components, this research constructs an indicator system to assess urban resilience. Using seven megacities in China as the research area, the evolution of the resilience level of China’s megacities is investigated, and its influencing factors are examined. The findings demonstrate an upward trend from 2010 to 2021 in the resilience of China’s seven megacities. Furthermore, the rising trend in the contribution of urban institutional resilience to overall resilience is most evident during the 2010–2021 period. Urban ecological resilience’s contribution to overall resilience declines most noticeably between 2010 and 2021. The contribution of each megacity subsystem resilience to overall resilience varies in different cities. Industry structure, market capacity, and urban maintenance positively affect the overall resilience of cities. Additionally, this work offers a strong, practical theoretical foundation for sustainable urban development. The research contents and findings of this study can support the decision-making procedures in the development of megacities.

1. Introduction

Human activities continue to encroach on ecological resources as global urbanization develops, imposing a significant pressure on the entire world. On the other hand, when cities become more densely inhabited, a variety of urban issues arise, including traffic jams, pollution of the environment, and water shortages. China is still going through a period of rough growth in urbanization, and cities’ capacity to handle crises still needs to be strengthened. The increase in population and urban expansion of already dense urban areas is leading to a new phenomenon of megacity formation. In China, cities with a permanent population of 10 million or more in urban areas are considered megacities. Megacities now face an unprecedented level of uncertainty, which has a significant impact on urban planning and administration and poses numerous challenges for more conventional approaches to risk analysis and risk management. China’s megacities face diverse and complex challenges, such as the need for economic transformation and upgrading, unbalanced social development, and high pressure on resources and the environment. Megacities need to be resilient during social emergencies, major accidents, natural disasters, and large-scale epidemics. They should be able to withstand adverse influences and shocks and even prevent disasters and accidents directly or indirectly.

Resilience offers novel strategies for cities to deal with risks of uncertainty, lessen the negative effects of disruptions, and achieve long-term adaptive development thanks to its emphasis on a society-wide systemic approach. Resilience has been referred to as the emergency room of sustainability and is a key component or expression of sustainability [1]. City resilience entails absorbing, preparing, and recovering from shocks and preparing for future shocks to our cities. Compared to cities of normal size, megacities face a more complex economic environment, major social conflicts, greater population mobility, and more intense disturbances to the ecosystem. A comprehensive assessment of the resilience of megacities can provide urban decision makers with an upfront prognosis and subsequent decision-making information. This process can contribute to improving economic development, public safety, and government management of an entire city.

Resilience was first conceptualized with a bias toward engineering. The emphasis of the resilience idea increasingly shifted throughout time. The concept of resilience has gone through engineering resilience, ecological resilience, and social-ecological system resilience. There is no agreement on the precise definition of urban resilience since different disciplines see the concept of resilience from different perspectives. However, an increasing number of studies have documented urban resilience concepts and characteristics [2,3]. Studies have defined urban resilience from the perspectives of different disciplines or viewpoints [4,5]. For instance, Wang and Blackmore’s [6] definition of resilience is that it is the system’s capacity to quickly recover to normal operational levels in the case of a failure situation with a low probability of failure. Ecological resilience, according to Liao [7], highlights a system’s capacity to endure regardless of whether its status changes. According to Folke et al. [8], social-ecological systems’ persistence, adaptation, and transformability are the three primary pillars of resilience. The widely accepted ones are those according to the Resilience Alliance (RA); resilient cities and urban systems are those that can withstand outside disturbances while preserving their essential features, vital structures, and critical functions [4].

Recent studies have evaluated urban resilience. However, rather than from multidimensional disciplinary perspectives, the majority of these analyses have been done from different individual disciplinary viewpoints. Based on a three-dimensional scale-density-morphology resilience analysis framework, Wang et al. investigated the geographic aspects of the spatial and temporal characteristics of urban resilience in Lanzhou [9]. From the climate change and disaster risk perspective, Chen et al. analyzed how the resilience concept was integrated into the planning system in Singapore in the context of climate change [10]. Furthermore, the urban resilience of certain provinces, prefecture level cities, or specific urban agglomerations has been assessed in these researches. Zhang et al. investigated urban resilience’s spatial and temporal patterns and the factors influencing them in 17 cities in Shandong Province [11]. Zhang and Feng conducted a comprehensive measure of urban resilience above the prefecture level in 30 provinces and municipalities in China [12]. Chen et al. used 11 prefecture-level cities in the Ha-Chang urban agglomeration as research objects to construct a city resilience evaluation system [13]. Very little literature exists in terms of which megacity resilience and assessment are the subject of study. In addition, clarifying the elements influencing the resilience of megacities is of practical significance since megacities are crucial to the national economic and social growth of China. Analyzing and assessing the resilience of urban systems in the context of rapid urbanization is vital to achieving urban sustainability.

This paper aims to contribute to the following inquiries. First and foremost, current indicators for the quantitative analysis of urban resilience are primarily based on a particular research perspective or dimension. A rare quantitative investigation, this paper considers the combined economic, social, ecological, infrastructural, institutional, resilience indicators or perspectives. In particular, institutional resilience has been added to economic, social, ecological, and infrastructure resilience. Second, recent studies primarily concentrate on single provinces [11], prefecture-level cities [12,14], and single city clusters [15,16] as their research objectives. Megacities have a greater influence on the national economy since they are the growth pole and leader of China’s economic development. However, China’s megacities are facing many risks and challenges, necessitating the urgent need to fortify resilient cities. Comparative studies of urban resilience among China’s megacities are lacking. In this study, the urban resilience levels of seven megacities are measured and compared. Third, identifying the megacity resilience evolution patterns and the factors influencing them might offer suggestions for advancing and incorporating their sustainable development. Our study adds empirical evidence to evaluating resilience and influencing factors of China’s megacities.

To fill some voids in the abovementioned lines of research, this paper measures and compares the resilience of seven megacities in China from a multidimensional perspective and quantifies their impact factors. The analysis and findings of this study have important significance for megacities’ efforts to build resilience. The remainder of the paper is structured as follows. Section 2 reviews the relevant literature. In Section 3, the data and research method are introduced. Then, in Section 4, the available research results are provided. Finally, the conclusions and discussion are addressed in Section 5.

2. Literature Review

2.1. Research on the Concept of Urban Resilience

Originally meaning “to return to its original state”, resilience is a concept with an engineering focus. The term “resilience” was first used in the field of ecology by Canadian ecologist Holling in 1973 to refer to “an ecosystem’s ability to return to a stable state after a disturbance” [17]. Subsequently, resilience has gradually expanded from nature to humanities and social studies [18]. The International Council originally recommended resilient cities in 2002, and they were incorporated into research on urban disasters, which sparked a study surge in the area of urban resilience [2]. Researchers are beginning to pay more attention to urban resilience and the factors that affect it. Resilient cities, as described by Wilbanks and Sathaye, are those with the capacity to prepare for certain dangers, respond to them, and recover from them with the least possible disruption to the economy, public health, or public safety [3]. Urban resilience, according to the RA, is the capacity of urban systems to withstand external perturbations while retaining their essential traits and essential functions [4]. The strength of urban resilience is that it encompasses aspects of responsiveness to unexpected conditions, and it has the capacity to adapt to risk over time [4].

Urban resilience encompasses the ability of urban functions to maintain smooth operations and the capacity of the urban fabric to restore function and order quickly. With the advancement of urban resilience research, Shao and Xu [4] analyzed the concept of urban resilience. They asserted that strengthening urban resilience is a novel strategy to expand on established theories that serve as a foundation for sustainable urban development. Currently, no universally accepted definition of urban resilience exists in academia. Combining the meanings of relevant resilience concepts, we discover that urban resilience encompasses all aspects of cities, including the urban environment dimension represented by facilities and ecology. It also incorporates the human dimension of the city, including elements of the economic and social dimensions. Urban systems are characterized by complex processes and self-organization [5]. This paper considers urban resilience as the ability of cities to respond to frequent shocks and disruptions by continuously adjusting their structure and state of development and ultimately achieving sustainable development.

2.2. Research on Urban Resilience Evaluation

The connections between resilience and vulnerability, their distinctions, and notably their boundaries remained largely undefined during the early phase of resilience research. Urban vulnerability and urban resilience are intertwined and inclusive. To achieve sustainable urban development, it is important to both increase urban resilience and decrease urban exposure. As research continues, resilience concepts are becoming enriched. Research on resilience assessment from the connotation of resilience has become mainstream, and the research output is becoming richer. The Rockefeller Foundation evaluates urban resilience across four dimensions: leadership and strategy, infrastructure and ecology, health and well-being, and economy and society. The San Francisco Resilient City Assessment System creates resilience evaluations for the environment, social culture, education, disaster, health, infrastructure, and lifeline based on the aforementioned framework. In 2016, ISO/TC268, with the assistance of United Nations International Strategy for Disaster Reduction (UNISDR), launched the preparation of ISO 37,123 Resilient Cities Indicators, which focuses on the 17 United Nations Sustainable Development Goals and the selection of indicators from the economy, education, energy, environment, and climate change. The study area’s context and the availability of the data must be taken into consideration while conducting research based on these resilience evaluation frameworks.

According to study perspectives, scholars have recently preferred employing different assessment indicator systems for resilience evaluations. The Organization for Economic Cooperation and Development (OECD) resilience framework primarily aims to measure resilience and implement strategies for cities with better resilience [19]. The OECD resilience framework identifies four dimensions for a resilient city: economy, society, governance, and environment, and each dimension can be assessed by using indicators [20]. From the urban system perspective, scholars view the city as a massive, complex system and evaluate the city based on a systems theory perspective. Masik and Grabkowska [21] presented a multidimensional hierarchical resilience strategy based on four components: institutional, economic, social, and environmental resilience. Sun et al. [15] adopted the perspective of urban social-ecological systems. Using GIS spatial analysis and the overlay function approach, they experimentally examined the resilience of 16 prefecture-level cities in the Yangtze River Delta region in 2014. Using the Thiel index and its decomposition, spatial measurements, and other techniques, Zhang et al. [11] examined the spatial and temporal patterns of urban resilience in 17 cities in Shandong Province and the affecting factors. From the climate change and disaster risk perspective, researchers have concentrated on the possible risks of climate change to cities. Chen et al. [10] researched the literature to analyze, in the context of climate change, how the concept of resilience is integrated into the planning system to support the development of a healthy water environment and urban space. Dai et al. [17] examined the future coping strategies of several world delta cities that have suffered from disasters and deduced a reference for resilient development for delta cities. From a geographic perspective, Feng et al. [22] presented a “scale-density-morphology” resilience framework and an index model to examine the evolution of urban resilience according to the ideas of landscape ecology and evolutionary resilience. Based on the “scale-density-morphology” three-dimensional resilience analysis framework, Wang et al. [9] employed remote sensing technologies and geographic information system platforms to assess the spatial and temporal aspects of urban resilience in Lanzhou. From the viewpoint of the evaluation index system, an existing multidimensional assessment index system of the economy, society, ecology, infrastructure, and institution is lacking. Indeed, increased urban resilience and sustainable urban development require the synergistic effort of all aspects of the city.

On the other hand, China is going through the stage of high-quality urban development, and as it opens up to the outside world, megacities are progressively becoming a crucial source of support for China’s economic growth. In recent years, China has emphasized the importance of building resilient cities in a series of policy documents. In 2014, China’s National New Urbanization Plan (2014–2020) proposed improving the capacity of sustainable urban development. In 2016, China’s State Council proposed promoting sponge city construction in “Several Opinions on Deepening the Construction of New Type of Urbanization”. The 14th Five-Year Plan for National Economic and Social Development of the People’s Republic of China and the Outline of Vision 2035 in 2021 proposed the goal of building “resilient cities”. In order to increase the resilience of China’s megacities and ultimately achieve sustainable urban development, it can be valuable to evaluate the resilience of China’s megacities from a multidimensional perspective.

2.3. Urban Resilience Influencing Factors

Although a great deal of research has been conducted by scholars on the influencing factors of urban resilience, a unified consensus on the selection of influencing factors is needed. Cities within a particular region are the primary focus of the empirical examination. Gao and Ding [23] examined the factors influencing urban resilience in 30 prefecture-level cities in Northwest China through panel regressions. They discovered that factors such as administrative power and technology significantly affected social and infrastructure resilience. Zhu and Sun [24] empirically analyzed the factors influencing urban resilience using a spatial Durbin model from five dimensions: government, market, technology, openness, and finance. Ma et al. [25] used grey correlation analysis to investigate the factors influencing the resilience of urban agglomerations in the Guanzhong Plain. The results showed that economic conditions had become one of the main factors influencing changes in urban resilience. Zhang et al. [26] used empirical analysis to argue that urban dynamism, the proportion of foreign investment utilized, GDP, and the proportion of urban pension insurance positively impact urban resilience.

The market, economic, and openness factors are the most significant ones taken into account in the literature when choosing influencing factors. In addition, Zhu and Sun argue that market capacity can contribute to resilience by accelerating population clustering and enhancing regional competitiveness [24]. Huang and Zhang argue that industrial structure can significantly affect the level of resilience of resource-based cities in China [27]. Wang and Zhao found a significant effect between urban exports and urban resilience [28]. Dong et al. found that public infrastructure was strongly correlated with urban resilience. In addition, megacities are densely populated, and the concentration of people can impact all aspects of urban development [29]. This study draws on previous research findings and considers the actual situation of seven megacities in China. A panel model regression was conducted for each dimension of resilience and the city’s overall resilience’s influencing factors. The influencing factors included industry structure (Ind), using upgrading coefficient of industrial structure; population (Pop), using total population; openness (Ope), using actual utilization of foreign capital; market capacity (Mar), using total retail sales of consumer goods; urban maintenance (Mai), using investment in urban maintenance.

3. Materials and Methods

3.1. Study Area

Megacities are distinctive outcomes and symbolic accomplishments of human society’s growth at the nexus of industrial and information civilization [30]. According to the Notice on Adjusting the Criteria for Classifying the Size of Cities issued by the State Council of the People’s Republic of China in 2014, cities with a permanent population of 10 million or more in urban areas are considered megacities. China has seven megacities: Shanghai, Beijing, Shenzhen, Chongqing, Guangzhou, Chengdu, and Tianjin [31]. Figure 1 shows the geographical location of China’s seven megacities. Shanghai is the central economic city of China, and it is a cosmopolitan city with global influence. Beijing is the capital of China and is considered the country’s economic, cultural, and political center city. Shenzhen, a renowned global metropolis, is the result of China’s reform and opening up. Chongqing is the largest city in the central and western regions and bears the strategic burden of China’s western development. Guangzhou is an important trade city in China and historically was once the only port city open to foreign trade in China. The top provincial capital in China’s central and western areas, Chengdu is significant for cross-cultural exchanges with other countries. Tianjin is the first port city in northern China and the national major city in the north, as determined by the state.

As a crucial growth pole for China’s economic development, the vulnerability of megacities has become increasingly evident under China’s distinctive economic and social development trend and urbanization development pattern. Megacities face a number of challenges and risks, starting with the dangers to China’s megacities’ economic security. Megacities in China are essential to driving industrial transformation and sustaining economic growth. They must also deal with a challenging economic environment and relatively significant economic shocks. The second challenge is Chinese megacities’ social security issues. China is going through a time of both apparent social tensions and fast economic growth. The population has become increasingly mobile and a significant portion of it is absorbed by the megacities. Finally, the megacities in China face ecological security problems. Megacities’ rapid urbanization in China is disrupting the ecology in increasingly severe ways. Increasingly dense urban populations have brought about various urban diseases, such as traffic jams, pollution, and a lack of water. In already crowded urban regions, rising population and urban sprawl heighten the risks of megacities. In this regard, it is crucial to conduct resilience studies of the seven megacities in China with the aim of enhancing their resistance to risks and promoting the sustainable development of megacities under practical guidance.

3.2. Variables and Data

Based on the current analysis of the connotation of resilient cities and the availability of data and considering the essential components of cities, we believe that the urban economy, society, ecology, infrastructure, and institutions are integrated into a highly complex coupled system [32]. Figure 2 illustrates a conceptual model of the evolution of urban resilience. Cities can be affected by external shocks and disturbances. External shocks and disruptions include natural and man-made disasters and other possible risks [33]. The city responds to external shocks and disturbances by absorbing them, adapting to them, and making structural adjustments to maintain a stable and balanced condition. It has been established that the economic system plays a crucial and irreplaceable function in the urban system and contributes to the healthy growth of cities [25]. The level of urban social development is closely related to people’s basic livelihoods [12]. For cities, improvements in the urban ecological environment increase resilience, improve their defensive capabilities against outside human-made or natural disasters, and facilitate their overall development processes [12]. For most municipal systems to operate effectively, the infrastructure must be in good condition [34]. The institutional resilience of cities means that through the establishment of rules and regulations, long-term safety management mechanisms that balance stability and flexibility quickly adjust their structure and function to prevent the frequent return of urban risks [35]. Therefore, this paper uses economic, social, ecological, infrastructural, and institutional resilience to evaluate the resilience of China’s seven megacities. The improvement of urban resilience is inextricably linked to the advancement of the resilience of the subsystems.

Urban growth is intrinsically driven by a city’s economic subsystem. A city’s economic growth directly influences investments, construction, and public safety. GDP per capita and GDP growth rate are suitable measures of a city’s economic situation [36]. GDP per capita can measure a city’s economic development level, and the GDP growth rate can measure the speed of economic progress. When attempting to reflect changes in the structure and quality of the economy, total fixed asset investment is crucial. Investments are one of the “troikas” factors promoting economic growth on a macro level [37]. Changes in local financial revenues reflect the dynamics of the economic environment. Local financial revenue levels can also indicate a city’s economic development, whether it be favorable or negative. The amount of money spent on science and technology and education shows the value that cities place on these fields. Economic growth and changes in the industrial structure are strongly related and have a cause-and-effect relationship [38]. Therefore, we choose GDP per capita, GDP growth rate, total fixed assets investment, local financial revenue, science and technology expenditure, education expenditure, and proportion of tertiary industry to measure economic resilience.

The social subsystem mainly includes employment, social environment, and health care. Urban dwellers’ standard of living will rise with an increase in per capita disposable income, which encourages social stability. The unemployment rate is an indicator of the extent of labor employment: it measures the amount of idle labor capacity and indicates the percentage of full employment [39]. Both social security and medical expenditures are welfare expenditures. The social security system plays a vital role in regulating income distribution and raising the welfare level of the population [40]. Population mortality is a useful indicator of a region’s population density and, to some extent, indicates the quality of healthcare and the population’s state of health. College students embody a city’s talent and supply capacity and provide an irreplaceable strategic resource for achieving sustainable development. Therefore, we choose the per capita disposable income of urban residents, unemployment rate, proportion of social security expenditure in financial expenditure, proportion of medical and health expenditure in financial expenditure, population mortality, and number of college students per 10,000 people to measure social resilience.

The ecological subsystem directly affects human living circumstances and physical health while also providing a vehicle for human survival and economic development in cities. To encourage the efficient and effective use of resources and to uphold a superb ecological environment, a high rate of waste and wastewater treatment is necessary. Also, the physical and mental health of humans might benefit from clean air. The ratio of days with good air quality is a reliable indicator of a city’s air quality. The per capita public green area is an essential indicator of urban residents’ living conditions and quality of life [11]. Therefore, this paper uses the ratio of industrial solid wastes comprehensively utilized, ratio of consumption wastes treated, ratio of centralized wastewater treated, ratio of days with good air quality, and per capita public green area to measure ecological resilience.

The infrastructure subsystem provides the physical basis for urban development. Infrastructure is a key component of a city’s resilience of its social and natural systems. By altering the layout of industries, spurring economic expansion, and facilitating population mobility, the development of urban transportation infrastructure can have an impact on the development of cities [41]. The postal sector is an essential part of the modern service industry. It is vital in boosting the effectiveness of resource allocation and promoting the growth of e-commerce. A considerable rearrangement of the industrial structure has also been brought about by the growth of the network economy, which has pushed development in the direction of sophisticated, information-based development. Urban municipal facility construction is a necessity for achieving urban functions as well as an unavoidable means of advancing modernization. Therefore, we choose the length of urban rail transit line, per capita road area, revenue from postal services, level of internet penetration, and investment in municipal public infrastructure construction to reflect infrastructure resilience.

The institutional subsystem is an essential guarantee of sustainable urban development. Institutional factors can significantly impact the economic, social, and ecological management of cities and the operation of facilities. The proportion of the registered urban population to the total population can indicate how urbanization is progressing and how well the household registration system reform is working. Basic pension insurance enables participants to provide for their primary livelihood in old age. Participants’ essential medical expenses are covered by basic medical insurance, which also increases the person’s risk tolerance. Participating in unemployment insurance also entitles one to a specific amount of unemployment benefits to safeguard their life in the event of unemployment. Basic pension insurance, basic medical insurance, and unemployment insurance can reflect the state of the urban pension institution, medical institution, and unemployment protection institution, respectively. Per capita financial expenditure is the disbursement of financial resources by the government to provide public goods and services to satisfy the basic requirements of society. Considering the availability of data, we choose proportion of registered urban population to the total population, proportion of employees joining urban basic pension insurance, proportion of employees joining urban basic medical care system, proportion of employees joining unemployment insurance, and per capita financial expenditure to measure the institutional resilience of cities.

This paper used seven megacities in China as the case study. Urban resilience evaluation index system is shown in

Table 1. Urban resilience evaluation indicator system.

Subsystem	Indicator	Unit	Direction
Economic resilience	GDP per capita	Yuan (RMB) per person	+
	GDP growth rate	%	+
	Total fixed assets investment	Hundred million yuan	+
	Local financial revenue	Ten thousand yuan	+
	Science and technology expenditure	Ten thousand yuan	+
	Education expenditure	Ten thousand yuan	+
	Proportion of tertiary industry	%	+
Social resilience	Per capita disposable income of urban residents	Ten thousand yuan	+
	Unemployment rate	%	-
	Proportion of social security expenditure in financial expenditure	%	+
	Proportion of medical and health expenditure in financial expenditure	%	+
	Population mortality	‰	-
	Number of college students per 10,000 people	person	+
Ecological resilience	Ratio of industrial solid wastes comprehensively utilized	%	+
	Ratio of consumption wastes treated	%	+
	Ratio of centralized wastewater treated	%	+
	Ratio of days with good air quality	%	+
	Per capita public green area	m2	+
Infrastructure resilience	Length of urban rail transit line	km	+
	Per capita road area	m2	+
	Revenue from postal services	Ten thousand yuan	+
	Level of internet penetration	%	+
	Investment in municipal public infrastructure construction	Ten thousand yuan	+
Institutional resilience	Proportion of registered urban population to the total population	%	+
	Proportion of employees joining urban basic pension insurance	%	+
	Proportion of employees joining urban basic medical care system	%	+
	Proportion of employees joining unemployment insurance	%	+
	Per capita financial expenditure	Ten thousand yuan per person	+

. The data came from the 2011–2022 China Urban Statistical Yearbook and the 2011–2022 China Urban Construction Statistical Yearbook. In addition, the 2010–2022 provincial and municipal statistical yearbooks and statistical bulletins on economic and social development by province and municipality were included.

3.3. Methods

3.3.1. Improved Entropy Method

Comprehensive evaluation methods include subjective and objective weighting evaluation methods. In practice, the choice depends on the weights that need to be calculated. The entropy approach of the objective weighing evaluation method is employed in this work via the principle of information entropy to compute the weights, enabling an accurate and objective assessment of the resilience of megacities. To achieve comparisons between years, this paper improves the entropy method by adding a time variable to rationalize the results [24,42].

(1) Standardization of indicator: given there are n years, s cities, and z indicators, the jth evaluation indicator for the city i in the year a is ${\mathrm{X}}_{\mathrm{aij}}$:

The positive indicator is calculated as follows:

$${\mathrm{X}}_{\mathrm{aij}}^{\prime }=\left({\mathrm{X}}_{\mathrm{aij}}-{\mathrm{X}}_{\mathrm{jmin}}\right)/\left({\mathrm{X}}_{\mathrm{jmax}}-{\mathrm{X}}_{\mathrm{jmin}}\right)+0.0001$$

(1)

The negative indicator is calculated as follows:

$${\mathrm{X}}_{\mathrm{aij}}^{\prime }=\left({\mathrm{X}}_{\mathrm{jmax}}-{\mathrm{X}}_{\mathrm{aij}}\right)/\left({\mathrm{X}}_{\mathrm{jmax}}-{\mathrm{X}}_{\mathrm{jmin}}\right)+0.0001$$

(2)

where ${\mathrm{X}}_{\mathrm{aij}}^{\prime }$ (i = 1, 2, …, s; j = 1, 2, …, z) is the standardized value of the jth evaluation index of the ith city, ${\mathrm{X}}_{\mathrm{jmax}}$ is the maximum value of the jth evaluation indicator, and ${\mathrm{X}}_{\mathrm{jmin}}$ is the minimum value of the jth evaluation indicator.

(2) Determining the weighting of the indicator:

$${\mathrm{Y}}_{\mathrm{aij}}={\mathrm{X}}_{\mathrm{aij}}^{\prime }/{{\displaystyle \sum }}_{\mathrm{a}}{{\displaystyle \sum }}_{\mathrm{i}}{\mathrm{X}}_{\mathrm{aij}}^{\prime }$$

(3)

where ${\mathrm{Y}}_{\mathrm{aij}}$ is the proportion of the ith city to the index under the jth indicator.

(3) The entropy of the jth indicator (${\mathrm{e}}_{\mathrm{j}}$) is calculated as:

$${\mathrm{e}}_{\mathrm{j}}=-\mathrm{k}{{\displaystyle \sum }}_a{{\displaystyle \sum }}_{\mathrm{i}}{\mathrm{Y}}_{\mathrm{aij}}\ln \left({\mathrm{Y}}_{\mathrm{aij}}\right)$$

(4)

where k > 0, k = $\frac{1}{\ln \left(ns\right)}$.

(4) The information utility value for indicator j is calculated as:

$${\mathrm{g}}_{\mathrm{j}}=1-{\mathrm{e}}_{\mathrm{j}}$$

(5)

(5) The weight of the jth indicator (${\mathrm{w}}_{\mathrm{j}}$) is calculated as:

$${\mathrm{w}}_{\mathrm{j}}={\mathrm{g}}_{\mathrm{j}}/{{\displaystyle \sum }}_{\mathrm{j}}{\mathrm{g}}_{\mathrm{j}}$$

(6)

(6) The weight for subsystem resilience is calculated as:

$${\mathrm{W}}_{\mathrm{j}}^{\prime }={{\displaystyle \sum }}_{\mathrm{j}=1}^{\mathrm{m}}{\mathrm{w}}_{\mathrm{j}}$$

(7)

where m indicates the number of indicators included in the subsystem resilience.

(7) The resilience values for each subsystem in the city are calculated as follows:

$${\mathrm{RES}}_{\mathrm{ai}}^{\mathrm{s}}={{\displaystyle \sum }}_{\mathrm{j}=1}^{\mathrm{m}}\left({\mathrm{w}}_{\mathrm{j}}{\mathrm{X}}_{\mathrm{aij}}^{\prime }\right)$$

(8)

where ${\mathrm{RES}}_{\mathrm{ai}}^{\mathrm{s}}$ denotes the city i subsystem resilience value in year a.

(8) The comprehensive urban resilience assessment value is calculated as follows:

$$\mathrm{RES}={{\displaystyle \sum }}_{\mathrm{j}=1}^{\mathrm{m}}{\left({\mathrm{RES}}_{\mathrm{ai}}^{\mathrm{s}}\right)}_{\mathrm{j}}{\mathrm{w}}_{\mathrm{j}}$$

(9)

3.3.2. Kernel Density Estimation Methods

Kernel density estimation is a nonparametric estimation method that fits a distribution as a function of the characteristics of the data itself. It provides the unmatched advantage of conventional statistics while avoiding errors brought on by artificially set function forms. The kernel density estimation method begins by estimating the probability of a random variable and then uses a continuous density profile to explain the random variable’s distribution pattern. This approach is now frequently employed to examine the dynamic evolution of regional economic and ecological disparities [43]. The formula is as follows.

$$\mathrm{f}(\mathrm{x})=\frac{1}{nh}{{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{n}}\mathrm{k}\left(\frac{{\mathrm{X}}_{\mathrm{i}}-\mathrm{x}}{\mathrm{h}}\right)$$

(10)

where ${\mathrm{X}}_{\mathrm{i}}$ denotes the observation value, X denotes the observations’ mean, $\mathrm{k}\left(\frac{{\mathrm{X}}_{\mathrm{i}}-\mathrm{x}}{\mathrm{h}}\right)$ denotes the Gaussian kernel function, n denotes the number of sample observations, and h denotes the bandwidth. The larger the value of h, the smoother the estimated kernel density function and the larger the fit bias. This paper selects the optimal bandwidth based on the principle of minimum variance.

3.3.3. Double Fixed Effects Panel Model

In most cases, a Hausman test is necessary before deciding whether to employ a fixed-effects model or a random-effects model. The original hypothesis of the Hausman test is to use a random-effects model, and the alternative hypothesis is to use a fixed-effects model. To explore the factors influencing the resilience of China’s seven megacities and to control for each city’s heterogeneity and time-varying characteristics, we constructed the following double fixed-effects panel model after testing. In order to prevent bias in the estimation findings due to the removal of critical variables and to more precisely estimate the influencing factors of urban resilience, a set of control variables ${\mathrm{X}}_{\mathrm{it}}$ were included in the model.

$${\mathrm{Res}}_{\mathrm{it}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1{\mathrm{Ind}}_{\mathrm{it}}+{\mathsf{\alpha }}_2{\mathrm{Pop}}_{\mathrm{it}}+{\mathsf{\alpha }}_3{\mathrm{Ope}}_{\mathrm{it}}+{\mathsf{\alpha }}_4{\mathrm{Mar}}_{\mathrm{it}}+{\mathsf{\alpha }}_5{\mathrm{Mai}}_{\mathrm{it}}+{\mathsf{\alpha }}_6{\mathrm{X}}_{\mathrm{it}}+{\mathsf{\mu }}_{\mathrm{i}}+{\mathrm{v}}_{\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(11)

where ${\mathrm{Res}}_{\mathrm{it}}$ denotes the level of urban resilience in the city i in year t and ${\mathrm{Ind}}_{\mathrm{it}}$ denotes the upgrading coefficient of industrial structure in the city i in year t, which is defined as shown in Equation (12). ${\mathrm{Pop}}_{\mathrm{it}}$ denotes the total population in the city i in year t, ${\mathrm{Ope}}_{\mathrm{it}}$ denotes the actual utilization of foreign capital in the city i in year t, ${\mathrm{Mar}}_{\mathrm{it}}$ denotes the total retail sales of consumer goods per capita in the city i in year t, and ${\mathrm{Mai}}_{\mathrm{it}}$ represents the investment in urban maintenance in the city i in year t. ${\mathrm{X}}_{\mathrm{it}}$ denotes a set of control variables, ${\mathsf{\mu }}_{\mathrm{i}}$ is an individual fixed effect, ${\mathrm{v}}_{\mathrm{t}}$ is a time-fixed effect, and ${\mathsf{\epsilon }}_{\mathrm{it}}$ is a random error term.

Coefficient of industrial upgrading: during the urbanization process, the industrial structure is upgraded as evidenced by the tertiary industry gaining significance while the primary sector’s share is comparatively declining. As a result, the following industrial structural upgrading coefficients were created utilizing the Lan and Chen research methodology [44] to assess the degree of industrial structural upgrading.

$$\mathrm{R}={{\displaystyle \sum }}_{i=1}^3{\mathrm{y}}_{\mathrm{i}}\times \mathrm{i}={\mathrm{y}}_1\times 1+{\mathrm{y}}_2\times 2+{\mathrm{y}}_3\times 3,1\le \mathrm{R}\le 3$$

(12)

where $y_i$ is the share of the output value of industry i in total output value. The value of R ranges from 1 to 3, with R closer to 1 indicating a lower level of industrial structure development and R closer to 3 indicating a higher level of industrial structure development.

The control variables in the econometric model include the level of economic development, which is represented as GDP per capita [45]. The level of human capital is measured using the number of college students per 10,000 people in the city [46]. The level of transport infrastructure is represented as the per capita road area [47].

4. Results

4.1. Evolutionary Characteristics of Resilience in China’s Megacities

4.1.1. Temporal Evolution of Urban Resilience

In this paper, the entropy method is used to determine the weights of the indicators, and the weights of the indicators with big (small) relative changes are relatively large (small), overcoming the arbitrariness of subjective assignment. The weights of each indicator are shown in

Table 2. Indicator weights of urban resilience.

Subsystem	Indicator	Weights
Economic resilience (0.2391)	GDP per capita	0.0395
	GDP growth rate	0.0218
	Total fixed assets investment	0.0377
	Local financial revenue	0.0271
	Science and technology expenditure	0.0439
	Education expenditure	0.0283
	Proportion of tertiary industry	0.0407
Social resilience (0.2080)	Per capita disposable income of urban residents	0.0332
	Unemployment rate	0.0306
	Proportion of social security expenditure in financial expenditure	0.0423
	Proportion of medical and health expenditure in financial expenditure	0.0445
	Population mortality	0.0236
	Number of college students per 10,000 people	0.0338
Ecological resilience (0.1383)	Ratio of industrial solid wastes comprehensively utilized	0.0352
	Ratio of consumption wastes treated	0.0223
	Ratio of centralized wastewater treated	0.0232
	Ratio of days with good air quality	0.0246
	Per capita public green area	0.0331
Infrastructure resilience (0.2180)	Length of urban rail transit line	0.0415
	Per capita road area	0.0410
	Revenue from postal services	0.0496
	Level of internet penetration	0.0453
	Investment in municipal public infrastructure construction	0.0407
Institutional resilience (0.1966)	Proportion of registered urban population to the total population	0.0586
	Proportion of employees joining urban basic pension insurance	0.0357
	Proportion of employees joining urban basic medical care system	0.0358
	Proportion of employees joining unemployment insurance	0.0358
	Per capita financial expenditure	0.0307

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The average resilience values of seven Chinese megacities and their five subsystems’ average resilience values for 2010–2021 are obtained by standardizing the data according to the improved entropy method, as shown in

Table 3. Average urban resilience and subsystem resilience values from 2010 to 2021.

Year	Urban Resilience	Subsystem Resilience
		Economic	Social	Ecological	Infrastructure	Institutional
2010	0.1813	0.0233	0.0596	0.0493	0.0340	0.0150
2011	0.2625	0.0364	0.0700	0.0756	0.0418	0.0387
2012	0.3331	0.0568	0.0676	0.0870	0.0595	0.0622
2013	0.3957	0.0970	0.0846	0.0751	0.0699	0.0690
2014	0.4450	0.0916	0.0929	0.0850	0.0814	0.0939
2015	0.4879	0.1157	0.0995	0.0918	0.0946	0.0863
2016	0.5338	0.1382	0.1046	0.0867	0.0979	0.1064
2017	0.5811	0.1492	0.1042	0.0839	0.1180	0.1258
2018	0.6363	0.1630	0.1207	0.0810	0.1350	0.1366
2019	0.7152	0.1880	0.1292	0.0905	0.1559	0.1516
2020	0.7684	0.1807	0.1393	0.1020	0.1784	0.1680
2021	0.7815	0.1993	0.1478	0.1037	0.1786	0.1521
Mean	0.5101	0.1199	0.1017	0.0843	0.1038	0.1005

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As shown in Table 3, the overall resilience level of China’s megacities shows an upward trend between 2010 and 2021. The study’s findings essentially show that in recent years, China’s megacities have been bolstering their urban infrastructure and enhancing their public services. The combination of these factors has led to a significant increase in the resilience of megacities. The average value of economic resilience for the seven megacities shows a fluctuating upward trend from 2010 to 2021. From 2010 to 2021, the trend was upward, except for a slight decline in 2014 and 2020. The average values of social resilience, ecological resilience, infrastructural resilience, and institutional resilience all show a fluctuating upward trend from 2010 to 2021. The trend increases in most years; however, a few years show a decrease trend compared to the year before. Figure 3 depicts the trend of the seven Chinese megacities’ overall urban resilience from 2010 to 2021.

The overall resilience for all seven megacities shows an upward trend between 2010 and 2021, with very few years showing a downward trend. The most significant increase in overall urban resilience in 2021 compared to 2010 is in Chongqing. The overall resilience value for Chongqing rose from 0.1259 in 2010 to 0.9043 in 2021, an overall increase of 0.7784. This is followed by Shanghai, Beijing, Chengdu, Tianjin, and Shenzhen, with increases of 0.6780, 0.6660, 0.6354, 0.5561, and 0.4631, respectively, between 2010 and 2021. The smallest increase in overall urban resilience in 2021 compared to 2010 is in Guangzhou, with an overall increase of 0.4241.

4.1.2. Evolution of the Resilience Contribution of Megacity Subsystems

China’s megacities’ resilience shows an upward trend from 2010 to 2021 in terms of urban resilience and the absolute change in the resilience of each subsystem. Exploring the contribution of each subsystem resilience to the city’s overall resilience evolves over time so that an understanding of the subsystem resilience that has a greater impact on the city’s overall resilience in different years is formed. That is, the subsystem resilience that dominates the overall urban resilience in a given year becomes evident. The term “contribution” refers to the proportion of economic, social, ecological, infrastructural, and institutional resilience to the city’s overall resilience. There are differences in the variation in the resilience indices of the subsystems, as shown in Figure 4.

As shown in Figure 4, with respect to the 2010–2021 period, the contribution of urban ecological resilience to overall urban resilience shows a decreasing trend, and the contribution of urban institutional resilience to overall urban resilience shows an increasing trend. Regarding the rate of change in different dimensions of resilience, the contribution of urban ecological resilience to overall urban resilience decreased most significantly after 2010, from 29.06% in 2010 to 13.33% in 2021. The rising trend in the contribution of urban institutional resilience to overall urban resilience is most evident after 2010, rising from 6.30% in 2010 to 19.26% in 2021. In addition, the contribution of urban economic resilience to overall urban resilience from 2010 to 2021 shows an upward trend, from 13.43% to 25.57%. The contribution of social resilience to overall urban resilience during the 2010–2021 period shows a downward trend, from 31.84% to 19.04%, respectively. Between 2010 and 2021, the contribution of urban infrastructure resilience to overall urban resilience shows an upward trend, from 19.37% in 2010 to 22.8% in 2021.

Figure 5 depicts the trend of the contribution of subsystem resilience to overall urban resilience for Chinese megacities in 2010, 2015, and 2021. The seven megacities’ economic resilience shows an increasing trend in contribution to the overall resilience of the cities. Possible reasons for this are the gradual increase in the level of economic development of megacities in recent years. In the new era’s urbanization process, increasing attention is being paid to economic growth. The contribution of social resilience to overall urban resilience tends to decrease for six megacities out of the seven megacities, the exception being Chongqing, which shows an increasing trend. A possible reason for this is that Chongqing has placed more emphasis on social development in recent years, resulting in the city’s social resilience growing from 2010 to 2021. The contribution of ecological resilience to the overall urban resilience of six megacities out of the seven megacities shows a decreasing trend, the exception being Guangzhou, while the contribution of ecological resilience to the overall urban resilience of Guangzhou shows an increasing trend. A possible reason is that megacities focus more on economic development rather than on the ecological environment. The cities where the contribution of infrastructure resilience to overall urban resilience increases during the 2010–2021 period are Shanghai, Shenzhen, Guangzhou, and Chengdu. Cities with decreasing contributions of infrastructure resilience to overall urban resilience include Beijing, Chongqing, and Tianjin. The infrastructure resilience in all seven megacities shows an increasing trend between 2010 and 2021. The fact that each city places a varied amount of significance on infrastructure accounts for the varying contributions of infrastructure resilience to the overall resilience of the cities. The contribution of institutional resilience to overall urban resilience tends to increase for six megacities, with the exception of Guangzhou, whose institutional resilience to its overall urban resilience tends to decrease. A possible reason is that Guangzhou attaches less importance to various types of social security than other cities.

Regarding the rates of change in resilience for different cities and different subsystems, Shanghai has the most pronounced upward trend in the contribution of institutional resilience to overall urban resilience and the most pronounced downward trend in the contribution of social resilience to overall urban resilience from 2010 to 2021. Beijing has the most pronounced upward trend in the contribution of institutional resilience to overall urban resilience and the most pronounced downward trend in social resilience to overall urban resilience from 2010 to 2021. Shenzhen has the most pronounced upward trend in the contribution of economic resilience to overall urban resilience and the most pronounced downward trend in the contribution of ecological resilience to overall urban resilience from 2010 to 2021. Chongqing has the most pronounced upward trend in the contribution of institutional resilience to overall urban resilience and the most pronounced downward trend in the contribution of ecological resilience to overall urban resilience from 2010 to 2021. Guangzhou has the most pronounced upward trend in the contribution of economic resilience to overall urban resilience and the most pronounced downward trend in the contribution of institutional resilience to overall urban resilience from 2010 to 2021. Chengdu and Tianjin have the most pronounced upward trend in the contribution of institutional resilience to overall urban resilience. Chengdu has the most pronounced downward trend in the contribution of ecological resilience to overall urban resilience during the 2010–2021 period. Tianjin has the most pronounced downward trend in the contribution of infrastructure resilience to overall urban resilience during the 2010–2021 period.

4.2. Evolution of the Kernel Density Distribution

To explore in depth the evolutionary pattern of resilience in Chinese megacities, a kernel density analysis was conducted on the overall resilience of Chinese megacities in 2010, 2012, 2014, 2016, 2018, and 2021. The dynamic evolution of resilience in megacities is tracked using this method. The kernel density curves are shown in Figure 6.

As shown in Figure 6, the kernel density curve gradually shifts to the right over time, indicating that the urban resilience of China’s megacities is generally increasing. A possible reason is that from 2010 to 2021, the seven megacities had the advantage of attracting the concentration of production factors such as labor, capital, and technology and achieved significant economic growth. In addition, megacities have been constantly upgrading their social and public services, strengthening their infrastructure, and improving institutional security. While paying attention to the above aspects, the protection of the ecological environment should not be neglected. The combination of these factors raises the overall resilience of megacities. Second, the trend toward multiple peaks in the kernel density curve becomes progressively more pronounced, implying that the resilience values of megacities have diverged on multiple levels through time. Again, the kernel density curve evolves from ‘high and narrow’ to ‘flat and wide’, with a declining peak and increased width, showing an increase in the degree of variance in the resilience of megacities. The disparity in the level and rate of growth of each subsystem’s resilience in the seven megacities between 2010 and 2021 may be the cause. For example, Guangzhou and Shenzhen, for instance, have a slower growth tendency for institutional resilience than the other five megacities. While the other five megacities have a greater increase in infrastructure resilience, Tianjin and Shenzhen exhibit a more modest development. All seven megacities’ ecological resilience exhibits some volatility. The combination of these factors has resulted in differences in the overall resilience of megacities.

4.3. Analysis of the Influencing Factors of Urban Resilience in Megacities

The model passed the 1% significance level test according to the Hausman test, which employed a p-value of 0.0000. The original hypothesis is thus rejected, indicating that the fixed-effects model is better than the random-effects model. To better understand the influencing factors and provide more reference to improve urban resilience, this research introduces a double fixed-effects panel model to analyze the influencing factors. The results are shown in

Table 4. Influencing factors of urban resilience in different subsystems.

Variables	(1) Overall	(2) Economic	(3) Social	(4) Ecological	(5) Infrastructure	(6) Institutional
Industry structure	13.937 *** (5.62)	13.374 (1.66)	26.846 * (1.91)	7.332 (0.77)	15.265 (1.26)	76.554 *** (5.90)
Population	−0.895 (−0.94)	−2.123 (−0.53)	1.741 (0.32)	−1.538 (−0.37)	6.865 (1.59)	−13.895 *** (−2.77)
Openness	0.238 (0.97)	3.046 *** (3.85)	−1.527 (−0.97)	−0.365 (−0.37)	0.917 (1.02)	0.306 (0.44)
Market capacity	1.693 ** (2.44)	1.718 (0.71)	3.311 (0.76)	2.517 (0.80)	6.886 ** (2.52)	2.501 (0.88)
Urban maintenance	0.051 ** (2.11)	−0.009 (−0.14)	−0.032 (−0.26)	0.195 ** (2.21)	0.013 (0.12)	0.340 *** (3.45)
Constant	−31.630 *** (−4.61)	−28.620 (−1.15)	−73.343 * (−1.97)	−17.066 (−0.68)	−51.885 (−1.53)	−145.383 *** (−4.38)
Control	Yes	Yes	Yes	Yes	Yes	Yes
R2-adjust	0.963	0.961	0.632	0.492	0.891	0.864
City FE	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes

Notes: t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01.

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According to the estimation results in Table 4, (1) industry structure, market capacity, and urban maintenance positively affect the overall resilience of cities, and their results pass the significance test. This situation shows that the continuous upgrading of the industrial structure can contribute to the city’s overall resilience. In addition, the increase in market capacity and urban maintenance improves the city’s overall resilience. (2) Openness significantly impacts economic resilience. Openness plays a benefit role in economic development by bridging the capital gap in China’s megacities, promoting the optimization of industry structure, boosting exports, and absorbing employment. (3) Industry structure has a significant positive impact on social resilience. Upgrading the industry structure allows for a more efficient and rational allocation of resources, which affects the relationship between supply and demand in society and thus the level of social resilience. Urban maintenance has a significant positive impact on ecological resilience. Urban maintenance funds are mostly utilized for building and maintaining public facilities as well as urban utilities. Market capacity may have a significant positive impact on infrastructure resilience. Due to the close association between market capacity and a city’s level of economic development, regions with high levels of economic development frequently upgrade their urban infrastructure. (4) In essence, institutional resilience is an exogenous property of institutions. Institutional resilience is the ability of an institution to accommodate, adapt, generate, and ultimately sustain itself in the face of uncertainties or unknown variables in its operation [48]. Factors significantly impacting institutional resilience include industry structure, population, and urban maintenance. The industry structure and urban maintenance significantly contribute to the increase in institutional resilience. In contrast, the amount of population significantly negatively affects the rise of institutional resilience.

5. Conclusions and Discussion

5.1. Conclusions

Strengthening urban resilience is essential in promoting urban development from scale expansion to quality improvement. This paper evaluates and analyzes the urban resilience of seven Chinese megacities for the 2010 to 2021 period from a multidimensional perspective. The dimensions include economic resilience, social resilience, ecological resilience, infrastructure resilience, and institutional resilience. The main conclusions are as follows: (1) The overall resilience of all seven megacities shows an upward trend between 2010 and 2021, with very few years showing a downward trend. Chongqing has shown the greatest overall resilience growth between 2010 and 2021. In comparison to 2010, Guangzhou’s overall resilience has increased at the slowest rate. (2) In terms of the average resilience contribution of megacity subsystems in China, the contribution of urban ecological resilience to overall resilience decreased most significantly after 2010, from 29.06% in 2010 to 13.33% in 2021. The rising trend in the contribution of urban institutional resilience to overall resilience is most evident after 2010, rising from 6.30% in 2010 to 19.26% in 2021. However, the contribution of each megacity subsystem’s resilience to overall resilience varies from year to year. (3) The kernel density curve evolves from ‘high and narrow’ to ‘flat and wide’, with a declining peak and increased width, showing an increasing degree of variance in the resilience of megacities. (4) Industry structure, market capacity, and urban maintenance positively affect the overall resilience of cities, and their results pass the significance test. The factor that significantly impacts economic resilience is the level of openness. Factors that impact cities’ social and ecological resilience are industry structure and urban maintenance, respectively. Market capacity has a significantly positive effect on infrastructure resilience. Factors significantly impacting institutional resilience include industry structure, population, and urban maintenance.

Our study extends the literature by evaluating the resilience of China’s seven megacities from a multidimensional perspective and exploring their influencing factors. Future analysis may address the following limitations. First, this paper is at a preliminary stage in exploring the resilience of China’s megacities. Megacities are complex mega-systems, and cities are affected by many factors in their development. However, no academic consensus exists on urban resilience’s meaning and evaluation criteria. Future research needs to explore the meaning and structure of megacity resilience from multiple and compounding viewpoints to make the findings more reliable. Second, as time goes on, the primary factors influencing urban resilience will change. Future research on resilience processes over long time series should be strengthened to highlight the different temporal stages of urban resilience. In addition, there is a need for further expansion of the dimensions used to measure urban resilience, such as the cultural dimension. Culture is the city’s soul and vital to its resilient development. Combining the city’s intrinsic culture with the concept of resilient urban development is worthy of in-depth research in the future. Finally, the study was conducted on seven megacities in China, limiting the analysis’s granularity. To make the research’s findings more useful, it might be considered in the future to focus on the districts or counties of megacities. Future study can therefore expand the granularity of analysis, raise the reliability of assessment results, and better understand the evolution, pattern, and mechanism of the role of multiscale urban resilience.

5.2. Discussion

Urban resilience has grown in importance as a research area for urban planning and sustainable development in China as its urbanization has advanced. This paper builds on prior research to evaluate the resilience of seven Chinese megacities from a multidimensional perspective. It also provides an in-depth analysis of the evolutionary characteristics of resilience, and thereby a fixed-effects panel model is used to explore its influencing factors.

The findings indicate that from 2010 to 2021, China’s seven megacities’ overall resilience increased. The trend of our results is almost identical to that of Yang et al. [49], with the difference that their study area only includes Zhengzhou, Nanjing, and Dalian in China. The findings of our study effectively confirm that China’s megacities have been strengthening their urban infrastructure, reinforcing institutional safeguards for social and public services, and accelerating the pace of industry transformation in recent years. Additionally, compared to 2010, the overall resilience increased the most in 2021 in Chongqing and the least in 2021 in Guangzhou. This is mostly attributable to Chongqing’s strong overall levels of institutional, economic, social, and ecological resilience. The increase in resilience of all subsystems in Chongqing was positive. From 2010 to 2021, Guangzhou’s institutional resilience increased less than the other six megacities. In particular, after 2016, Guangzhou’s institutional resilience was at the lowest level among the seven megacities. Guangzhou’s overall urban resilience is constrained by institutional resilience. In addition, the results show temporal heterogeneity in the resilience variation across individual megacity subsystems with respect to the city’s overall resilience. This finding is consistent with Mu et al. [50], the difference being that they assessed the resilience of China’s Beijing-Tianjin-Hebei urban agglomeration from four dimensions: economic resilience, social resilience, infrastructure resilience, and ecological resilience. However, the level of urban resilience relies on more than just the hard power of the city, but also the coordination and administration ability of the institutional organization is essential. The deviation between the overall resilience of the seven megacities is increasing yearly. The possible reasons are that each megacity has its unique characteristics and a different focus in the development process. Regional variations exist in the functional positioning and development stages [49]. This leads to differences in the resilience of the seven megacity subsystems over 2010 to 2021. For example, Shanghai and Chongqing have increased economic resilience more, while Chengdu and Shenzhen have grown less. Social resilience increased more in Chongqing and Chengdu, while it increased less in Beijing and Guangzhou. Ecological resilience increased more in Beijing and Guangzhou while increasing less in Shenzhen and Tianjin. As for infrastructure resilience, Chengdu increased the most, while Tianjin increased the least. Shanghai’s institutional resilience increased the most, while Guangzhou increased the least. From 2010 to 2021, the trends in the resilience of each megacity subsystem are different, resulting in differences in the overall resilience of the seven megacities.

Moreover, industry structure, market capacity, and urban maintenance have a significant positive effect on overall resilience. The influencing factors for different dimensions of resilience are various, consistent with the findings of existing studies on urban resilience [51,52]. Optimizing and upgrading the industrial structure are objective requirements for improving the efficiency of economic resource allocation and a prerequisite for achieving stable and sustainable economic development. In recent years, megacities have been restructuring their industrial structures to make them more rational and advanced. Market forces refer to the efficient allocation of regional factors of production, territorial combinations, and their operation by the market economic development that drives urban growth [11,53]. Urban maintenance funds are used to construct and maintain urban infrastructure and public utilities to boost the city’s economy and improve living conditions for its citizens. Therefore, upgrading the industry structure, expanding market forces, and investing in urban maintenance can all increase a city’s overall resilience.

The concept of ‘resilience’ was applied to mechanical engineering to describe the capacity of a metal to recover its shape when subjected to an external force. Since then, it has been progressively incorporated into research on urban resilience [4]. Urban resilience has been examined in many types of literature from various perspectives [9,10,15], with a variety of findings that relate to the study region [11,14]. Only a few studies, meanwhile, have examined China’s megacities from a multidimensional perspective that takes economic, social, ecological, infrastructural, and institutional resilience into account. As some of the most economically developed regions in China with a high population density, megacities face particular risks and challenges as they develop [48,54]. For example, there is a risk of natural disasters due to climate change as well as the complexity of the economic environment. Therefore, it is crucial to assess the resilience of megacities and research the factors that affect them. Our findings add to the accumulating evidence about the evolutionary mechanism of megacity resilience in China and provide insight into the influential factors of urban resilience. The construction of the indicator system and the analysis of the influencing factors in this paper are replicable and generalizable. They can provide references for similar studies in megacities in developing and developed countries.

There are higher requirements for enhancing megacities’ resilience and preventing and responding to various unexpected risks. While our analysis has primarily been exploratory, the results are relevant as strategic options for megacity resilience enhancement. Specific recommendations are as follows: (1) Megacities should aggressively adjust their industry structure and promote their optimization and upgrading. The upgrading of the industry structure positively impacts the overall resilience of cities, social resilience, and institutional resilience. In adjusting the industry structure, the market characteristics of each city should be taken into account, and full understanding of their strengths and weaknesses to attain scientific and rational development should occur. (2) Improving the market capacity of megacities and increasing funding for urban maintenance is recommended. The impact of increasing market-based capacity on developing China’s megacities is significant and far-reaching. It can change the mechanisms for the flow and combination of various factors in urban development. Thus, the base of megacity development is fundamentally changing. A higher investment in urban maintenance can help the urban economy grow and improve the living environment for city dwellers. (3) Megacities should focus on the joint collaborative development of multidimensional resilience. It is crucial to pay attention to both strong social development and high-quality economic development. Also, attention must be paid to issues such as building institutional resilience, bolstering infrastructure development, and environmental protection. Megacities’ sustainable growth is a multifaceted, cooperative process of progress. The subsystems must also be more resilient if megacities are to become more resilient.