The Driving Path of China’s Urban Resilience Enhancement in the Digital Economy Era

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Introduction
In recent years, Chinese society is still in a period of rough growth in the pursuit of urbanization, and cities are still not well-equipped to respond to crises.Under the impact of uncertainty risks, cases of catastrophic consequences, such as loss of life and property, failure of urban function, and imbalance of social order have occurred repeatedly, making urban security development disturbed and impacted by many uncertain factors [1][2][3].Terefore, China has successively proposed the construction of sponge cities, climateresilient cities, and other pilot projects to improve the level of urban resilience development and, in 2020, for the frst time from the national strategic level, to make clear requirements for the construction of resilient cities so that the construction of resilient city rises to promote the modernization of the national governance system and governance capacity is an important focus point.A resilient city is a city that has the ability to withstand, adapt, and quickly recover in an inverted environment, and it is a new paradigm of urban security development.We need to plan from the strategic height of integrated development and safe development, promote the institutionalization and standardization of resilient city construction, reduce uncertainty and vulnerability in the development process, and achieve sustainable urban development.
Since the 21st century, the resilience theory has been introduced into the economic and social felds and urban systems, and concepts such as "resilient city" or "urban resilience" have emerged [4].Since the concept of resilient cities was introduced, the United Nations, the World Bank, and the Rockefeller Foundation, among others, have conducted a lot of research studies on resilient cities [5,6], but there is still no consensus on the scientifc defnition of resilient cities [7].With the deepening of people's awareness and understanding of the concept of resilience, the connotation of resilience has been developed, and scholars have begun to integrate resilience with urban studies, thereby opening up new horizons for the urban emergency management research [8].And with the rapid growth of global urbanization and the rapid accumulation of various risks, this topic has quickly become an academic hotspot [9], and the research results have had an important impact on the modern urban planning and construction concepts.However, diferent research felds have diferent focuses on urban resilience research, resulting in the lack of a unifed approach to measuring urban resilience.However, taken together, the evaluation index system of urban resilience is divided into fve main dimensions: ecological, infrastructural, community, institutional, and economic [10,11].In addition, the quantitative measures of urban resilience by scholars in diferent felds difer, mainly in the following three methods: indicator evaluation, resilience time function evaluation, and model simulation [12].Commonly used numerical calculation methods for index evaluation include the following: structural equation method, entropy weight method, hierarchical analysis method, and principal component analysis method.In terms of theoretical and empirical research studies, the research studies on urban resilience in China at this stage mainly focuses on the evaluation of urban disaster resilience [7] and the comprehensive evaluation of urban resilience [13,14].And some scholars also empirically analyze the dynamic changes and infuencing factors of urban resilience in each province and city from the perspective of time and space [15,16].Compared with the policies, implementing agencies, and multisectoral coordination mechanisms for building a resilient city in developed countries [17,18], China started late in the application of building a resilient city, and there are many defciencies.In planning and construction, there is a lack of applied governance research and policy guidance for urban resilience [19].In cognition, society as a whole and individual residents lack scientifc knowledge of urban resilience.In terms of driving factors, there is a lack of research on the impact of confguration efects of multiple driving factors on urban resilience [20].To this end, it is of great practical signifcance to scientifcally explore the spatial and temporal evolution characteristics of China's urban resilience development level and identify the driving factors of urban resilience development, in order to optimize China's urban development pattern and to realize the modernization of urban governance system and governance capacity.
In the face of the increasing prominence of urban safety and development issues, the rise of the digital economy has prompted various parts of China to sound the call to build digital cities, creating favorable conditions and solutions for fostering new advantages in urban development.Jing [21] proposed a theoretical framework of the digital economy for the high-level development of urban resilience in the context of new opportunities for digital economy development in the new era.Tan et al. [22] proposed that, in the process of highlevel urban resilience enhancement, the digital economy is the focal point for promoting safe urban development.Terefore, due to its innovative nature and industrial spillover efect, the digital economy plays an increasingly important role in promoting the upgrading of urban economic structure, production efciency, green development, and improving people's living standards and is an inevitable trend for the high level of resilient urban development in China.Te data related to the "White Paper on the Development of China's Digital Economy" released by the China Academy of Information and Communication Research in 2021 show that the scale of China's digital economy continued to expand in 2020, and the scale of digital industrialization and industrial digitization accounted for 20% and 80% of the digital economy, respectively, and the new digital economy gradually formed around the world has become a driving force to promote enterprise development and a stabilizer to cope with the downward pressure of the economy.Terefore, promoting the development of the digital economy and using the infuence of the digital economy to enhance the efciency of national governance and urban resilience is an important issue that needs to be addressed nowadays.In view of this, based on the urban resilience practices of 31 provinces, autonomous regions, and municipalities directly under the central government in China, this paper proposes the following two questions in light of the current shortcomings of urban resilience research studies in China: what are the development trends, regional diferences, and spatial relationships of urban resilience in each province in China?What condition confgurations exist to drive urban resilience improvement?
In order to answer the abovementioned questions, this study searched for the infuencing factors of urban resilience enhancement based on the conditions of China's digital economy development and constructed a comprehensive evaluation index of urban resilience based on the urban resilience practice of 31 Chinese provinces, autonomous regions, and municipalities directly under the central government, calculated the urban resilience index using the entropy value method, and then explored the spatial and temporal diferences and driving paths of urban resilience among provinces and municipalities.In this paper, given that the efects of diferent factors on the urban resilience index are not independent, they can afect the improvement of urban resilience by linkage matching to produce diferent confguration paths.Terefore, from the perspective of confguration analysis, this paper used fuzzy set qualitative comparative analysis (fsQCA) to explore the infuence mechanism of the conditional confguration of urban resilience drivers.Te answers to the abovementioned questions can help make up for the shortcomings in the current urban resilience practice process, can provide a reference for local governments to formulate policies related to building a resilient city, and can help society as a whole and individual residents to understand the 2 Discrete Dynamics in Nature and Society development trend and spatial and temporal diferences of urban resilience in a scientifc and reasonable manner.In addition, the answers to the abovementioned questions can broaden the perspective of urban resilience-related research studies, address the shortcomings of traditional statistical analysis, provide a new research perspective for understanding the complex interactions among the drivers of urban resilience [23], and provide useful references for promoting the comprehensive modernization of urban governance capacity and governance system.Te marginal contributions of this paper are as follows: First, due to the regional resource endowment status, development foundation, and other factors, the development of urban resilience in China is still characterized by obvious geographical diferences.As an integrated, dynamically evolving development system, urban resilient development varies signifcantly by regional development context when faced with uncertain perturbations.In view of this, this paper analyzed the spatial pattern and drivers of urban resilience development in China based on a spatiotemporal analysis.It is expected to provide some cognitive basis and guiding signifcance for the development of urban resilience in China.Second, given that the urban resilience index is a comprehensive evaluation system, this paper constructed the urban resilience evaluation system from the perspectives of ecological resilience, economic resilience, social resilience, infrastructure resilience, and institutional resilience.It is expected to provide a useful reference for future research studies on urban resilience.Tird, the qualitative comparative analysis method was introduced to identify the infuence mechanism of urban resilience from the perspective of group analysis, which breaks through the traditional analysis methods based on independent variables and oneway linear infuence relationships and provides a new research perspective for the study of urban resilience driving paths.

Study Design and Data Selection
2.1.Region Selection.With the deepening of the reform and opening-up policy, China has gradually developed into the world's second-largest economy, its international infuence is increasing, and its economic and social development has entered a new normal.However, with economic and social development, China still faces many difculties and challenges such as the severe ecological and environmental situation, unbalanced regional development, and the difcult task of industrial transformation and upgrading [24].In the face of uncertain disturbance factors, the development level of urban resilience will be afected by the regional development background, leading to diferences in the infuencing factors of urban resilience in diferent regions.Terefore, this paper selected 31 Chinese provinces, autonomous regions, and municipalities directly under the central government as the case subjects of the study based on the previous studies (given the availability of data, the study cases do not include Taiwan Province of China and Hong Kong and Macau special administrative regions) [16].Studying the spatial and temporal distribution and drivers of urban resilience in each province of China will help to improve the overall level of urban governance, thus further contributing to the modernization of the national governance system and governance capacity.Te study region is shown in Figure 1.

Research
Framework.Te research study mainly includes two parts: the spatial and temporal diference analysis and the confguration analysis of driving factors of urban resilience.Spatial characterization of urban resilience: frst, we selected appropriate urban resilience evaluation indicators based on the previous studies; second, the urban resilience index was calculated by using the entropy method.Finally, according to the urban resilience index, the spatial distribution characteristics of urban resilience was analyzed by drawing a spatial distribution map with ArcGIS software, and the spatial autocorrelation test of urban resilience was conducted with Stata software, and we aimed to provide an efective reference for the analysis of infuencing factors of urban resilience enhancement in China.
Confguration analysis of urban resilience driving factors: frst, the infuencing factors of urban resilience were selected based on the literature review; second, the QCA was applied to study the sustainable and high-quality development paths to improve the regional urban resilience from the perspective of confguration path, and multiple driving paths to improve urban resilience were confrmed.Combined with the research ideas of spatiotemporal diference analysis and confguration analysis of urban resilience, a research framework model is constructed, as shown in Figure 2.

Outcome Variables.
Studies on urban resilience evaluation indices have shown that the urban resilience index is a comprehensive evaluation system and that there are interactions between the subsystems [25][26][27][28].Drawing on existing research results [29], we build an urban resilience evaluation index consisting of fve subresilience systems: ecological resilience, economic resilience, social resilience, infrastructure resilience, and institutional resilience, including a total of 33 secondary indicators, taking into account the actual situation of urban development in China.Among them, ecological resilience emphasizes the ability to resist risks such as degradation of natural resources, defciencies in ecological governance systems, reduction of public green spaces, and natural disasters, for which eight indicators, including precipitation, were selected for evaluation.Economic resilience emphasizes a city's ability to quickly recover its industrial structure and adjust its economic recovery in a timely manner in the face of unknown economic pressures and shocks, for which six indicators, including GDP per capita, were used for evaluation.Social resilience is an important guarantee for the stable development of the city and the happy life of its residents, for which seven indicators such as per capita disposable income were chosen for evaluation.Infrastructure resilience emphasizes the ability to protect residents' daily lives, withstand Discrete Dynamics in Nature and Society disaster risks, and return to normal operation in a timely manner after a disaster, and it is an important vehicle for urban development, for which eight indicators such as for the number of beds in medical institutions per 10,000 people were selected for evaluation.Institutional resilience emphasizes the ability of city macroinstitutional development to handle risks, for which four indicators were selected for evaluation.Te abovementioned data were obtained by manually searching the statistical yearbooks of 31 provinces, autonomous regions, and municipalities directly under the Central Government of China through China's economic and social big data research platform.
To efectively avoid the randomness of subjective weighting, we used the entropy method to calculate the urban resilience index of 31 provinces, autonomous regions, and municipalities directly under the Central Government of China from 2016 to 2020.Te specifc calculation steps were borrowed from the study of Liu et al. [30], and the maximum-minimum processing method with the best processing efect was selected to standardize the data to make them comparable.Te formula of the urban resilience index is as follows, and the indicators of urban resilience at all levels are shown in Table 1.
where URI represents the urban resilience index, a i represents the weight of each secondary indicator, and X i represents the standardized secondary indicators.

Condition
Variables.Tis paper drew on the research experience of Zhu and Sun [31] to fnd the infuencing factors of urban resilience in terms of government factors, market factors, and technical factors.And with reference to the research experience of Guo and Huang [32], six   conditional variables, such as digital services, input strength, industrial development, market potential, infrastructure, and talent pool, were selected, which not only refect the level of China's digital economy but also are highly correlated with the infuencing factors of urban resilience.Te conditional variables were defned by drawing on the research experience of relevant scholars and combining the research topic and data availability of this paper.We selected the overall index of online government service capability published by the e-Government Research Center of the Central Party School of China to measure the level of digital services, and the data for the remaining measurement condition variables were obtained from the National Bureau of Statistics and the China Statistical Yearbook.Te conditional variables defnitions are specifed in Table 2.

Analysis on Spatiotemporal Evolution and Spatial
Characteristics of Urban Resilience Index.To explore the spatiotemporal evolution and spatial distribution characteristics of the urban resilience index in each province of China, this paper used ArcGIS software to map the spatial distribution of the urban resilience index.Te spatial distribution map of the urban resilience index for 2016, 2018, and 2020 is shown in Figure 3. Te natural breakpoint method was used to classify the urban resilience index into the following fve levels: excellent (marked dark in Figure 2), good, medium, average, and poor (marked light in Figure 3), and then, the spatial distribution characteristics were analyzed [33].
As can be seen from Figure 3, the overall urban resilience index of each province from 2016 to 2020 shows a diferentiated spatial distribution pattern of good in the east, middle in the center, and low in the west.Te overall level of urban resilience development moves upward, showing a relatively concentrated spatial distribution pattern, with relatively few cities with excellent urban resilience index and mainly distributed in the developed eastern coastal provinces.Te number of provinces with less than a medium urban resilience index is higher, mainly concentrated in the central and western regions.Te regional range of the urban resilience index for average and poor levels gradually decreases during the sample study period, and the regional range of the city resilience index for medium levels gradually increases.Specifcally, the provinces with excellent levels of urban resilience index in 2016 and 2018 were Guangdong, Zhejiang, Jiangsu, Shandong, Beijing, and Shanghai, mainly concentrated in the eastern region of China.In 2020, the provinces with excellent levels of urban city resilience index were Guangdong, Jiangsu, and Beijing.Although the number of provinces with excellent level of urban resilience index decreased slightly, the number of provinces with medium and above level urban resilience index increased.And the urban resilience index in central and western regions shows a better upward trend.Tis is mainly because this paper adopts the natural breakpoint method to classify the urban resilience level of each region with a fxed division ratio.And compared with the provinces with excellent urban resilience index, the growth rate of urban resilience index in the provinces below the medium level is relatively fast.Te abovementioned results also refect that the disparity between regions in China's urban resilience index is gradually decreasing and the diferentiated distribution is weakening.

Global Moran Index.
In order to study the spatial relationship of urban resilience, this paper used Stata15.0 statistical software to test the spatial autocorrelation of the urban resilience index.Spatial autocorrelation is a method for analyzing the similarity of attribute values in spatial adjacency or spatial adjacent regions [34,35].Te currently recognized global Moran index is represented as follows [35][36][37]: where Moran , sI represents the Moran index, x i represents the urban resilience index of the i th region, n represents the number of regions, and W ij represents the spatial weight coefcient matrix.
As can be seen from Table 3, the global Moran index of the urban resilience index is signifcantly positive for the years 2015 to 2020.Te Moran index passes the signifcance test at the 1% level in 2016, 2017, and 2020 and at the 5% level in 2018 and 2019.Te results indicate that there is a strong positive spatial autocorrelation and a strong spatial agglomeration pattern in the urban resilience index of Chinese provinces.Te largest value of the Moran index is 0.225 in 2020, indicating that the urban resilience agglomeration phenomenon is the most obvious and the spatial spillover efect is the most obvious in Chinese provinces in 2020.Overall, the urban resilience Moran index from 2016 to 2020 shows a fuctuating upward trend, with a large overall fuctuation, but the upward trend is not obvious.In 2012, China raised the topic of "resilient city" construction and has been exploring the path of a resilient city construction that fts the characteristics of Chinese cities.However, due to the late introduction, insufcient improvement of relevant policies, and low penetration of implementation measures in various regions, the overall urban resilience Moran index has not shown a rapid growth trend, while China's economy continues to develop positively.It also refects that, now and in the future, enhancing urban resilience should 6 Discrete Dynamics in Nature and Society Discrete Dynamics in Nature and Society attract sufcient attention from Chinese provinces, and the sustainable development path of urban resilience enhancement should be adhered to.

Local Moran Index.
Te local Moran index autocorrelation can be tested by the local Moran index [38].Its formula is as follows: where coupled with the implementation of policies such as integrated urban environment and cross-regional collaborative governance in recent years, the ecosystem resilience has generally improved, and the overall regional urban resilience is higher.Tere is a tendency for the spatial distribution pattern of central and western cities to transition to highvalue areas.Low-low agglomeration areas, mainly located in central and western cities in China, have an overall low urban resilience due to economic, transportation, resource, and environmental constraints, but the number of low-low agglomeration provinces is gradually decreasing from 2016 to 2020.From the macrolevel, this is mainly due to the impact of policies such as the strategic goal of common prosperity, the "Belt and Road" initiative and the construction of a resilient city, as well as the improvement of regional transportation networks such as high-speed rail and highways, which further promote the synergistic political, economic, and cultural development of provinces nationwide.At the same time, in recent years, afected by natural disasters, Chinese provinces have increased infrastructure investment in response to earthquakes, freezing, foods ,and other disasters, and the resilience of infrastructure systems has generally improved.From the microlevel, since the implementation of the regional synergistic development strategy, the central and western regions have developed rapidly, especially the provinces of Hunan, Hubei, and Sichuan, relying on the natural transportation, resource, and industrial advantages of the Yangtze River Economic Belt, and have vigorously developed their own advantageous industries such as electronic information, life medical care, high-end equipment manufacturing, and ecological food, and the industrial economy has steadily risen.Te good industrial development and the steady rise of the economy have also created more employment opportunities in Hunan, Hubei, and Sichuan, attracting more people to the cities and signifcantly increasing the level of urbanization.Te rising level of urbanization has led to an increase in the overall income levels and educational attainment of residents and an increase in the urban public infrastructure such as hospitals and schools.As a result, urban resilience has generally increased in the central and western regions.In general, the resilience of cities in central and western China has generally improved, for example, the urban resilience index of Sichuan Province has surpassed that of some provinces.

Data Calibration.
When fsQCA is used for analysis, it converts the condition and outcome variables into fuzzy sets, thus satisfying the Boolean logic of QCA [40].Terefore, drawing on the study of Rihoux and Ragin [41], we set three anchor points for the calibration of the variable data: a full membership (fuzzy score � 0.75), a full nonmembership (fuzzy score � 0.25), and a crossover point (fuzzy score-� 0.5).Te localization points and calibrated fuzzy values of each variable are shown in Table 4.

Truth Table Construction.
After calibrating the data, the software was used to calculate and obtain the truth table.Sixty-four combinations could be obtained from the six condition variables, and when using fsQCA, we could set the consistency and case frequency thresholds to flter out the solutions that met the requirements.Referring to the mainstream practice, we selected the rows with an original consistency threshold of below 0.8 and a frequency threshold of 1 for deletion and obtained the truth table, as shown in Table 5.No contradictory confguration appears in the truth table.Tus, the current data could be used for analysis in the following step [42].

Necessary Condition Analysis.
After calibrating the data, we analyzed the data to determine the necessary conditions using fsQCA software.Te results are shown in Table 6.As can be seen from Table 7, the consistency of the condition variables is all less than 0.9 and is not a necessary condition for the outcome variables, so no further verifcation of the necessity of these condition variables is required.

Conditional Confguration Analysis.
Ten, according to the research purpose, the confguration analysis of the condition variables was carried out to study the adaptation path of urban resilience enhancement.As the study consisted of small and medium caseloads, the mainstream approach was adopted, and we chose to set a consistency threshold of 0.8, a PRI consistency of 0.7, and a frequency threshold of 1 [43].Tree types of solutions, the complex solution, parsimonious solution, and the intermediate solution, are usually obtained through sufciency confguration analysis.Regarding the presentation mode of confguration analysis results proposed by Ragin and Fiss, the intermediate solution of the report was selected, and the simple solution was used as an auxiliary explanation [44].Te analysis results of fsQCA3.0software are shown in Table 7. From the consistency index, it can be seen that there are fve frst-order equivalent confgurations that constitute sufcient conditions for the high urban resilience index.In addition, the consistency of the solution is 0.946, implying that 94.6% of the cases satisfying the 5 driving paths would exhibit the high urban resilience index, and the coverage of the solution is 0.7292, implying that the 5 development paths explain 72.9% of the cases.Both the consistency and coverage of the solutions indicate that each confguration has substantial explanatory power for the improvement of urban resilience in China, and together, they explain the high urban resilience index.Te detailed description of each confguration is as follows: (1) Digital Industry Driven Path.Te frst combination path shows that in cities with high talent reserves, government service capacity and market potential will better drive highquality urban development and improve the urban resilience index if their digital industry development level is high.Among them, government digital services, market potential, and talent reserve are the core conditions, and industrial development is the marginal antecedent condition.Promoting the orderly digital transformation of the real economy is an important measure to achieve stable and orderly economic growth in China.Te deep integration of the digital economy and the real economy can enhance the innovation power of the real economy, expand the development space of the real economy, promote the    Discrete Dynamics in Nature and Society optimization of the institutional environment of the real economy, accelerate the green transformation of the real economy, and thus can improve the quality of economic supply of the city.Terefore, under this path, the integration of the real economy and digital economy can provide a special path for the digital industry development to achieve the goal of perfecting the quality of the urban supply system and improving the urban resilience index.Comparing the fve confgurations of the high urban resilience index, it can be found that the coverage index of C1 is signifcantly greater than C2, C3, C4, and C5.It explains 58% of the outcome variable, covering eight cases, and is a more common path for the digital economy to drive the improvement of urban resilience in China.
(2) Technology Factor Driven Path.Te second combined path shows that cities with high digital technology conditions can fnd urban development momentum and can promote the improvement of urban resilience through integration with government service capacity and market potential.Te second combined path shows that cities with high digital technology conditions can fnd urban development momentum through integration with government service capacity and market potential to achieve the goal of promoting increased urban resilience.When a city is subjected to severe shocks and natural persecution, a large number of human resources and excellent infrastructure services are inevitably needed to maintain the normal function of the city, and a high human reserve and infrastructure are conducive to enhancing urban resilience by strengthening the city's resilience and recovery, selfregulation, and creativity.Xu and Deng [45] mentioned that after an external shock to urban economies, highly qualifed digital talents can fully release the market consumption demand through their stronger creativity and can gain room for maneuver for urban economic development by stabilizing the market domestic demand, so as to play a role in protecting the urban economy.At the same time, a good government digital service environment is conducive to the formation of a highly orderly resource operation (3) Government Input and Talent Pool Driven Path under Market Factors.Te third path suggests that in cities with low levels of digital infrastructure development, high digital industry development and market potential, combined with excellent human resources and government investment, can contribute to generating a high urban resilience index.A high talent pool means that the city has the potential for a good digital economy, which can drive the traditional industry to achieve digital transformation and stimulate the market to fully release consumer demand.Talent resource is the main force in achieving high-quality development in China and is the backbone of the process of promoting urban resilience enhancement [31].Adequate government investment in science and technology research and development provides sufcient fnancial support for the digital construction of the city, which can attract more scientifc talents, help break the barriers to the fow of talent elements, reserve scientifc and technical service talents for the city, and enhance the innovation power of the social.Under this path, digital talents guide the progress of technology and economy in the market through their strong creativity, so as to efectively stimulate market demand.In the benign development pattern of "internal circulation" and "double circulation" in China, sufcient consumption potential can stimulate the endogenous power of economic growth, release the purchasing power of all people, stimulate the vitality of urban markets, promote the technical progress of the macroeconomic system as a whole, improve the economic supply level of urban systems, and thus enhance the ability of cities to resist risks.
(4) Technology Factor and Government Factor Driven Path.
Te fourth combination path is dominated by the technical factor and government factor, both of which have a common purpose to jointly promote the resilience of Chinese cities. Trough its powerful creativity, the new-age digital technology strengthens disaster resilience and promotes the optimization of industrial structure, thus enhancing urban vitality and improving urban resilience.Urban resilience enhancement should break through the traditional technical capacity framework and rely on new products, technologies, and concepts in the development process of digital economy and integrate digitalization, informatization, intelligence, and other related technologies and development models into urban construction to help enhance the ability of cities to withstand risks and disasters.Te digital development of the government helps to guide the generation of new business models and formats, improve the intelligence of social development, widely apply digital products to all aspects of social construction, strengthen the informatization and intelligence of the whole city, and further improve the mobility of the city to cope with risks.Terefore, the high innovation of digital technology, which signifcantly enhances the level of industrial technology, provides good technical conditions for urban resilience enhancement, and the high social service of government digital service, which signifcantly enhances urban intelligence, provides a solid political guarantee for urban resilience enhancement.
(5) Government Investment and Infrastructure-Driven Path under Market Factors.Te ffth path suggests that in cities with low digital services and talent pool, high digital industry development and market potential, paired with excellent infrastructure and government investment, can yield high urban resilience indices.A disaster warning system is the frst barrier to a resilient city against disasters, preparing cities in advance for shocks and reducing the extent of damage to urban facilities and social order.Having the advanced infrastructure in cities helps to improve the capacity of data storage, analysis, and transmission, so that early warning systems can quickly and accurately analyze possible disasters and complete timely information transmission, thus enhancing the resilience of early warning systems.Te government's adequate investment in science and technology research and development can provide sufcient fnancial support for urban digital construction, which can help promote urban information communication, disaster early warning system, and other infrastructure construction.At the same time, a good market environment can also promote the continuous change of industrial technology, which has a positive efect on the construction of urban infrastructure and the speed of public information dissemination.Terefore, under this path, through market factors and efective investment of government funds, digital infrastructure can be well built and the city's ability to withstand disturbances and shocks from uncertainties will be enhanced.

Robustness Test.
In line with the mainstream practice of QCA, robustness testing is achieved mainly by increasing the level of consistency and adjusting the calibration anchor point of the variables.Terefore, we increased the PRI consistency level from 0.70 to 0.85, and the three confgurations of the new test results were consistent with the original results, except for the lack of confgurations corresponding to C2 and C5 due to the increase in the PRI consistency level.And then, the calibration anchor points of the condition variables were adjusted, and each step of the fsQCA was repeated after the calibration anchor points were adjusted, and the four confgurations of the new test results were consistent with the original results except for the lack of the group corresponding to C2. Tere is no signifcant change in the coverage and consistency of the results of the two robustness tests compared to Table 6, which indicates that the fndings are reliable [46,47].

Discussion
First, in terms of spatial distribution characteristics, there are large regional diferences in China's urban resilience index, which overall shows a strong spatial dependence and differential distribution characteristics.Specifcally, provinces in eastern and coastal China, such as Shandong, Guangdong, Jiangsu, Zhejiang, Shanghai, and Beijing, have higher resilience indexes and show high-high aggregation distribution characteristics.Compared with the eastern region, the urban toughness index in the central and western regions of China is relatively poor and belongs to the low-low agglomeration area of the urban resilience index.Tese results are generally consistent with the fndings of the previous studies [16].Tis is mainly because, since the reform and opening up, the eastern and coastal provinces of China have been the key development areas of China.At the same time, they have a better development base, with good human, industrial, scientifc, technological, cultural, and political resources, and a long-term leading economy.In recent years, the central and western regions have developed rapidly, and the provinces are in a period of rapid economic development and a critical period of urbanization.However, due to the constraints of transportation, resources, environment, and industrial structure, the infrastructure construction and economic development in the central and western regions are still relatively backward, and the room for further improvement of the urban resilience index is still large.Second, from the spatial evolution trend, the spatial pattern of the urban resilience index in the central and western regions shows a gradual growth trend and good development momentum.In recent years, with the continuous promotion of ecological civilization construction, environmental pollution, ecosystem degradation, and frequent disasters in the central and western regions have formed a push-back mechanism for sustainable urban development, making them pay more attention to the ecological civilization construction, and the economic, social, and ecological recovery of each region has continued, and urban resilience has been gradually improved [48].In addition, with the continuous promotion of regional coordinated development strategies such as the rise of central and western development, the regional transportation road networks such as high-speed rail and highways in central and western regions have been further improved, which promotes the synergistic political, economic, and cultural development of provinces nationwide.
Finally, from the perspective of conditional confguration analysis, none of the infuencing factors selected in this study can be considered as necessary conditions for the improvement of urban resilience in China alone.Meanwhile, this study provides 5 driving paths for China's urban resilience improvement.A comparative analysis of the fve driving paths reveals that the digital industry-driven path is the most common path driving urban resilience development across Chinese provinces.Tis is because the continuous upgrading of industrial structure is a key factor in promoting sustainable urban development, and the efective operation of market mechanisms is an important condition for urban development.Tis shows that resilient urban  development needs to create a good market environment while continuously promoting the transformation and upgrading of industrial structures.Tese results are generally consistent with the fndings of the previous studies that industrial upgrading should be promoted in the process of sustainable urban development [23].In addition, there are alternative relationships between diferent drive paths.Although the fve paths are the results of the linkage and matching of diferent infuencing factors, their ultimate impact results in promoting the generation of a high urban resilience index.Tis reveals that each province should fully consider its own resource conditions and play the role of linkage matching between infuencing factors, so as to better serve the construction of resilient cities.First, through the analysis of the spatial and temporal diferences of the urban resilience index, it was found that there were strong spatial agglomeration patterns and spatial diferences in the urban resilience index of Chinese provinces, and the overall trend showed the spatial distribution characteristics of good in the east, middle in the center, and low in the west.Tis also means that it is necessary to analyze the diversity of urban resilience driving paths from the perspective of condition confguration.Second, from the condition confguration analysis, the condition variables could not be used alone as necessary conditions for the urban resilience enhancement in China.Meanwhile, this study provides fve driving paths for urban resilience enhancement in China, which can be specifcally by digital industry-driven path, technology factor-driven path, government input-and talent pool-driven path under market factors, technology factor-and government factor-driven path, and government investment-and infrastructuredriven path under market factors, while it is found that the digital industry-driven path is a more common path to drive urban resilience development in China.Tird, in general, the improvement of the urban resilience in China was the synergetic efect of multiple factors of the digital economy, and each factor was efectively combined through diferent paths to enhance the urban resilience index in China.

Policy Suggestion.
First, give full play to the market potential and optimize the level of urban resilience.C3 and C5 confgurations show that market factors promote urban resilience enhancement by infuencing government and technological factors.Good digital industry can drive the city's technological progress by increasing productivity and innovation capacity.Te advantages of good digital consumption can give full play to the established dynamics of China's large market, and then drive the synergistic progress of industry and urban economy through the pulling power of market consumption to enhance the supply capacity of urban economy.Tis reveals that China should not only efectively play the driving role of the digital economy in the formation of a strong domestic market when enhancing urban resilience but also start to promote the digitalization, intelligence, and networking of traditional industries, as well as specifcally locate the market demand in the process of urban resilience enhancement and open up new product sales markets based on the existing technology accumulation to provide product and technology support for urban resilience enhancement.
Second, the characteristics of urban resilience infuencing factors are fully utilized to better serve the efective development of urban resilience.Urban resilience enhancement should break through the traditional technical capacity framework and rely on new products, technologies, and concepts in the process of social development and integrate digitalization, informatization, intelligence, and other related technologies and development models into urban construction to enhance the capacity of cities in terms of resisting disasters and shocks.We should take advantage of the high innovation of the digital economy to promote the technology level of traditional industries, realize the rapid upgrading of infrastructure, and promote the coordinated progress of the ecological environment, infrastructure, social system, and economic development as a whole, thus improving the ability of the urban system to withstand risks.We should leverage the high social serviceability of digital government to accelerate the level of digitalization, informatization, and intelligent services in cities, and on this basis, continuously improve the modernization of urban governance systems and governance capacity, enhance the function of urban systems, optimize the operation mode of resources, and improve the level of urban resilience with more scientifc public policies and more efcient governance capacity.
Tird, understand the driving path of urban resilience and formulate urban resilience development plans that conform to local characteristics.In the process of promoting urban resilience through digital economy, local governments can refer to the fve driving paths proposed in this study to formulate urban resilience development plans that conform to local characteristics.For example, for cities with good government digital services, market consumption potential, and talent pool, but with marginal conditions for digital industry development, the distinctive path of digital industry development can be adopted to integrate the city's traditional industries with the new-age economy, thereby promoting regional urban resilience enhancement (C1).In cities with low investment conditions for government science and technology R&D, we should actively give play to the innovation of technical conditions, drive the efective integration of technology with government service capacity and market potential, to fnd urban development momentum and to promote a higher level of urban resilience (C2).In areas where market potential and digital industries are less well developed, the city 14 Discrete Dynamics in Nature and Society should give full play to the synergy between government factors and technology factors to jointly promote regional urban resilience enhancement (C4).In addition, by reviewing the fve confguration paths, it is found that optimizing a single factor is not the precondition to drive the urban resilience improvement, indicating that the urban resilience improvement is the result of the interaction of various infuencing factors, which enlightens cities not to be limited to optimizing a single infuencing factor driving the urban resilience improvement, but to pay attention to the linkage matching of government, technology, and market, and clarify the complexity of the digital economy driving the urban resilience improvement, and then, formulate the urban fexible shaping scheme in line with the regional characteristics.
i represents the local Moran index, y i represents the urban resilience index of the i th region, n represents the number of regions, and W ij represents the spatial weight coefcient matrix.Te local Moran scatter plots of the urban resilience index in 2016, 2018, and 2020 are shown in Figure 4. Te local Moran indices for these three years are 0.222, 0.127, and 0.225, respectively, which indicate that the urban resilience index in the Chinese region has a strong spatial autocorrelation and a more stable spatial development pattern.Te local Moran scatter plot reveals that the urban resilience index of most provinces is located in quadrants 1 and 3, and the provincial urban resilience index shows two patterns of diferentiation, with a strong autocorrelation and dependence on the geographic spatial distribution of urban resilience index clustering [39].Comprehensive local Moran scatterplots for 2016, 2018, and 2020 reveal that the highhigh agglomeration type provinces are mainly concentrated in Shandong, Guangdong, Jiangsu, Zhejiang, Shanghai, and Beijing, which are developed provinces in the eastern and coastal regions of China, and this type of provinces have close industrial development exchanges, signifcant urban resilience index difusion efects, and basically form a pattern of synergistic development with neighboring provinces.Tis is because the developed provinces in eastern China and coastal areas have a good foundation for development and have good human, industrial, scientifc, technological, cultural, and political resources, and their economies have been in a leading position for a long time, while the level of economic development directly afects the construction of infrastructure and the maturity of social development,

Figure 3 :
Figure 3: Spatial distribution of urban resilience index.

Table 3 :
Global Moran index of urban resilience index.

Table 6 :
Test of necessity for condition variables.

Table 7 :
Te results of the confguration analysis.
Note. "•" means that the core antecedent condition exists; "•" means that the marginal antecedent condition exists; the existence of factors plays an auxiliary role." " means that the core antecedent condition is missing; " " means that the marginal antecedent condition is missing; "○" means that the existence or nonexistence of the condition variables is irrelevant to the result, which is represented as a blank cell in the table (no graph).
Taking 31 provinces, autonomous regions, and municipalities directly under the Central Government of China as sample cases, this study conducted confguration analysis, explored the temporal and spatial diferences of urban resilience in China and the confguration paths driving urban resilience improvement in the digital economy era, and revealed the complex and diverse interactions between the infuencing factors of urban resilience improvement in China.