Coupling Coordination Between New Urbanization and Economic Development Level in Wuhan

Abstract

Based on the statistical data of Wuhan from 2000 to 2022, this paper constructs an evaluation system for the coordinated development of new urbanization and the economy. It uses the entropy weight method and the coupling coordination degree model to comprehensively measure the relationship between the two. Then, the temporal variation characteristics of the coupling coordination degree between them are analyzed. Finally, Geodetector is employed to analyze the driving factors. The results show that (1) during the study period, the overall urbanization indices of population, economy, society, and space in Wuhan showed an upward trend, while the development trends of the subsystems of the economy were different. Among them, the economic structure developed relatively steadily; the economic environment showed an overall upward trend. The economic scale grew steadily from 2000 to 2019 but significantly decreased after 2019 due to the impact of the COVID-19 pandemic. (2) The comprehensive evaluation index of new urbanization and the economy in Wuhan showed a fluctuating upward trend. The levels of urbanization and economic development were constantly improving. Urbanization lagged behind economic growth from 2000 to 2008, developed synchronously during 2009–2019, and surpassed economic development between 2020 and 2022. (3) The coupling coordination degree has changed from severe dissonance to quality coordination severe dissonance to quality coordination. Its development process is affected by policy and the social environment. (4) According to the analysis of the geographic detector, the following indicators have a high impact: the share of the urban population, the consumer price index, and the proportion of the employed population in secondary and tertiary industries. Based on the analysis results, corresponding countermeasures and suggestions are proposed from three aspects in order to provide references for the coordinated development of urbanization and the economy: urbanization rate, employment, and consumption levels.

1. Introduction

Since the 18th CPC National Congress, China’s new urbanization construction has made significant achievements, with the urbanization rate and quality greatly improved and the economic strength of cities increasingly strengthened. The new urbanization places greater emphasis on human-centricity, collaboration, inclusiveness, and sustainability, which imposes higher requirements on urbanization development [1]. By the close of 2023, China’s population experienced a 66.16% increase in the urbanization rate, marking a 14.33% rise from the end of 2011. This rate met the objectives of the 14th Five-Year Plan in advance, transitioning from swift expansion to a focus on high-quality development. High-quality development refers to a people-centered development model that fulfills the populace’s growing aspirations for a better life, encompassing holistic enhancement across economic, social, cultural, and ecological dimensions [2]. The report from the 20th CPC National Congress emphasized that high-quality development is the primary objective in constructing a contemporary socialist country comprehensively [3]. Urbanization is not only the pathway to modernization but also a powerful engine for the economy. Coordinated development significantly reflects the superior development of contemporary cities. The progression of urbanization in China faces numerous challenges, including uneven economic growth, a lack of infrastructure, rising housing stress, and traffic jams, among others [4], which somewhat obstructs the sustainable growth. The challenge of aligning urbanization with urban economic growth to attain superior urban development in the current development framework is now a tangible issue to confront.

In this regard, many scholars have conducted relevant research on the relationship between urbanization and economy. The development of foreign urbanization is relatively recent. The research results on urbanization are also relatively abundant. The classic research theories include the urban–rural dual economic theory proposed by development economists [5] and the endogenous economic growth theory [6]. Riccardo et al. employed economic complexity metrics to reveal the relationship between a country’s economic development in terms of commodity production and export and the process of urbanization [7]. James et al. redefined urbanization as being generated by two different mechanisms, i.e., natural and residual growth, and studied the effect of the type of urbanization on economic growth [8]. With the promotion of the global urbanization process, the third world and developing countries and other regions where the urbanization process is accelerating and urbanization problems are being highlighted have become the research hotspots of foreign scholars [9,10], and they have put forward “urbanization without industry” [11,12] and “urbanization without growth” [13,14]. Chinese academic research on the relationship between urbanization and economic growth demonstrates two aspects. One is to study the interaction mechanism between the two. Gu Chaolin, Chen Mingxing, Lu Dadao, and others have conducted earlier studies on urbanization and economic and social development [15,16]. Gu Chaolin studied China’s urbanization dynamics over 25 years of reform and opening up, asserting that dual-track industrialization between urban and rural sectors coupled with population mobility propel urbanization processes [15]. Chen Mingxing and Lu Dadao et al. analyzed the spatial pattern of the relationship between urbanization and economic development in China by using an enhanced quadrant mapping framework and found that the inter-provincial pattern showed obvious east–west spatial heterogeneity [16]. In recent years, Zhang Wenzhang et al. analyzed the intrinsic promotion of urbanization on economic growth from the perspective of urbanization and the agglomeration effect and resource allocation [17]. Wang Wei et al. incorporated aging factors into the urban–rural dual economy three-phase generation overlapping model to explore the aging impact mechanism of urbanization and economic growth [18]. Cai Xianjun et al. analyzed the economic growth effect of government-driven urbanization based on the perspective of withdrawing counties and establishing districts [19]. The second approach is to apply econometric methods to measure the level of urbanization development and analyze the spatial and temporal characteristics of urbanization, economic growth, and other factors. The most commonly used models are the coupling coordination degree model, the panel regression model, and vector autoregression (VAR). Zhang Mingdou et al. measured the urbanization quality and economic development level of prefecture-level and above cities in China from 2006 to 2015 and analyzed the coupling coordination degree between the two, as well as the spatial clustering characteristics, showing that the eastern region was higher than the central and western regions [20]. Using the panel regression model and mediation effect model, Wang Shaoxian revealed that both human capital matching and new urbanization exert positive influences on high-quality economic development [21]. Based on the perspective of high-quality development, Su Xufeng et al. used the coupling coordination degree model to measure the coupling coordination levels of demographic, economic, spatial, social, and green urbanization systems in Northwest China [22]. Ma Huiqiang et al. took 31 provinces in China as the study subject, analyzed the temporal and spatial evolution characteristics of the coupling coordination relationship of basic public services, urbanization, and regional economy systems and the driving mechanism from the perspective of system science, and found that the degree is obviously spatially differentiated. This is the result of the integrated effect of multiple driving mechanisms, such as infrastructure, resources, economy, government, and market [23].

By analyzing the relevant literature both domestically and internationally, it can be found that the research focus of foreign scholars is mainly concentrated on theory and method, and Chinese scholars mainly focus on the regional level of provinces and watersheds, as well as the eastern coastal areas, with less emphasis on cities in the central region. Since the implementation of the Rise of Central China Strategy, the central region has achieved remarkable socio-economic progress, with its share of the national GDP increasing significantly. However, persistent challenges remain, including imbalanced regional development, inadequate growth momentum, and relatively low levels of inland openness. Strategically positioned as a pivotal hub for central China’s revitalization, Wuhan demonstrates exceptional geographical advantages, robust economic foundations, and well-developed waterway transportation networks. As a national central city, it has experienced rapid urbanization and maintains industrial dominance in steel and automotive sectors, constituting a vital component of China’s economic framework. Nevertheless, Wuhan faces dual pressures of industrial transformation amidst shifting global economic patterns and intensifying environmental constraints. The COVID-19 pandemic’s severe impact has further compounded economic vulnerabilities. Additionally, emerging industries and the concentration of academic talent in its world-class university cluster present transformative opportunities. Therefore, it is necessary to assess the coordination status of new urbanization and economic development in Wuhan in recent years to provide theoretical support for policy formulation. This will help boost the development of the central region of China.

The systemic interplay between new urbanization and economic advancement necessitates multivariate indicator frameworks, which cannot be measured solely by a single indicator such as the urbanization rate and GDP. Establishing composite assessment models through mathematical models enables the empirical evaluation of these multidimensional processes, addressing current methodological limitations stemming from the absence of standardized evaluation protocols. Taking Wuhan as the research object, this paper constructs the evaluation system of economy from three aspects of economic scale, economic structure, and economic environment. And it constructs the evaluation index system of new urbanization from three aspects of population urbanization, economic urbanization, and social urbanization. It studies the coupling coordinated relationship between new urbanization and the economy of Wuhan during the period of 2000–2022, applies Geodetector to analyze the impact factors, and puts forward countermeasures and suggestions. This paper aims to promote the coordinated and healthy development of new urbanization and the economy.

2. Materials

Wuhan has a total administrative area of 8569 square kilometers, with a built-up area of 925.97 square km in 2022. The total resident population of Wuhan has continued to grow under the strong support of national policies. The trend of population inflow has become more obvious, and the rate of urbanization has been increasing (

Table 1. Major development policies of Wuhan since 2000.

Year	Related Policies
2005	Wuhan was included in the Rise of Central China
2007	Wuhan City Circle was designated as a pilot area for the “two-type society”
2008	Organized and compiled the Spatial Planning of Wuhan City Circle
2010	The State Council approved the Donghu Hi-tech Zone as the second national demonstration zone of independent innovation in China after Zhongguancun Science Park.
2011	National E-commerce Demonstration City
2014	The Wuhan City Circle Regional Development Plan (2013–2020) was approved
2015	Wuhan was positioned by the state as a pilot national innovative city and a pilot zone for comprehensive innovation reform In July of the same year, Wuhan City Circle became the first pilot area for science and technology financial reform and innovation in China
2016	National Center City
2017	The Wuhan Pilot Free-Trade Zone in the Donghu Hi-Tech Zone was opened
2018	The Wuhan Economic–Technological Development Zone (WEDZ) was approved to be established
2022	The Development Plan of Wuhan Metropolitan Area was approved
2023	The Three-Year Action Program for the Development of Wuhan Metropolitan Area (2023–2025)

). By the end of 2023, the population density of Wuhan was 1607 persons per square km, the urbanization rate of resident population reached 84.79%, and the resident population was 13,774,400 persons, an increase of 5,725,900 persons, or 41.57%, compared with that of 2000 (Figure 1). At present, the main urban areas have basically all completed urbanization, and the distant urban areas of Caidian, Huangpi, Xinzhou, and Jiangxia are the main incremental spaces for urbanization.

3. Methods

3.1. Research Methods

3.1.1. Data Normalization

Due to the varying quantification standards of different indicators, in order to facilitate a comparison between the data, it is necessary to normalize the data and adjust the value between 0 and 1, including the boundary values 0 and 1. The coefficients of the indicators in this indicator system are positive, so there is no need to calculate the positive and negative indicators separately. The equation is as follows:

$$X_{ij}={\displaystyle \frac{X_{ij}^{\prime }-X_{min}}{X_{max}-X_{min}}}$$

(1)

In Equation (1), $X_{ij}^{\prime }$ represents the raw data for the j-th indicator in the i-th year.

$X_{max}$ is the maximum value of the j-th indicator.

$X_{min}$ is the minimum value of the j-th indicator.

3.1.2. Entropy Weight Method

In this paper, the large amount of data makes it difficult to determine weights from subjective experience; thus, the entropy weight method was chosen to determine the weights of the evaluation indices for Wuhan. The entropy weight method is an objective assignment method. It determines weights based on the dispersion measure of the data and reduces the bias of subjective factors. However, this methodology demonstrates susceptibility to outliers and lacks interpretability regarding the weight allocation mechanism [24,25].

The calculation steps are as follows.

Equation (2) is used to calculate the weight of the j-th indicator in year i:

$$Y_{ij}={\displaystyle \frac{X_{ij}^{\prime }}{{\sum }_{i=1}^m{X}_{ij}^{\prime }}}$$

(2)

(i = 1, 2, …, n; j = 1,2, …, m)

Equation (3) is used to calculate the entropy value of the j-th indicator:

$$e_j=-k\sum _{i=1}^m{Y}_{ij} ln{Y}_{ij},k={\displaystyle \frac{1}{\ln m}}$$

(3)

When $Y_{ij}=0$, $Y_{ij}\ln Y_{ij}=0$.

Equation (4) is used to calculate the weight of the j-th indicator:

$$w_j={\displaystyle \frac{r_j}{{\sum }_{i=1}^n{r}_j}},r_j=1-e_j$$

(4)

In these equations, m represents the number of years and n represents the number of indicators.

3.1.3. Calculation of the Composite Indices

After utilizing entropy-calculated metric weights, the comprehensive indices of new urbanization and economic development are separately calculated using the following formula:

$$U_1={\sum }_{i=1}^m{w}_i{x}_i,U_2={\sum }_{i=1}^n{w}_j{x}_j$$

(5)

In Equation (5), $U_1$, $U_2$ represent the new urbanization system and the economic system, respectively, $x_i$ and $x_j$ are the normalized values of the indicators of the new urbanization and the economic system, respectively, $w_i$ and $w_j$ are the weights, and m and n are the indicators of the new urbanization system and the economic system.

3.1.4. Coupling Coordination Degree Model

The coupling coordination degree model is a specific application of the coupling coordination theory, which demonstrates the inter-relationships between two or more systems. It is theoretically grounded in system theory and cybernetics, employing the quantification of inter-system interaction intensities and synchronization levels to holistically evaluate systemic performance robustness and stability profiles. In this paper, it is used to study the mutual influence phenomenon between new urbanization and the economy in Wuhan.

The equation is as follows:

$$C=\sqrt{{\displaystyle \frac{U_1{U}_2}{\left(U_1+U_2\right)\left(U_1+U_2\right)}}}$$

(6)

$$T=\alpha U_1+\beta U_2$$

(7)

$$D=\sqrt{CT}$$

(8)

In these equations, C represents the coupling degree between the comprehensive development level of new urbanization and the economic development level; T is the comprehensive coordination index of new urbanization and economic development; and α and β are the weights of urbanization and the economic system, where α + β = 1. In this paper, we assume that both are equally important, assigning a weight of 0.5 to each. T reflects the coordination between the systems; the larger the value of T, the more coordinated the systems are. The closer the value of D is to 1, the more effectively the two systems can collaborate and interact, leading to better overall operational performance. Referring to the existing research data [26,27], the coupling coordination degree is divided into grades (

Table 2. Coupling coordination degree grade classification.

Interval	Style	Interval	Style
0.90~1.00	Quality coordination	0.40~0.49	On the verge of dissonance
0.80~0.89	Good coordination	0.30~0.39	Mild dissonance
0.70~0.79	Intermediate coordination	0.20~0.29	Moderate dissonance
0.60~0.69	Elementary coordination	0.10~0.19	Severe dissonance
0.50~0.59	Bare coordination	0.00~0.09	Extreme dissonance

).

3.1.5. Geodetector

Geodetector is the tool for detecting spatial differentiation and revealing the driving forces of it [28]. The stratification of independent or dependent variables can be geospatial, temporal, or attribute-based. When the independent variable is a numerical quantity, it needs to be discretized into a type quantity. In this paper, K-means clustering is used to discretize the independent variable. Factor detection is employed to analyze the individual drivers of the coupling coordination degree. Geodetector usually provides p-values to determine the reliability of the results. When the p-value is less than a set level of significance (e.g., 0.01), the effect of the factor is considered significant.

The equation is as follows:

$$q=1-{\displaystyle \frac{{\sum }_{h=1}^L{N}_h {\sigma }_h^2}{N{\sigma }^2}}$$

(9)

In Equation (9), the value of q represents the explanatory power of the driving factor. The value range of q is [0, 1]; the larger the value of q, the stronger the explanatory power. H = 1, …, L, represents the stratification of variable Y or factor X; $N_h$ and N denote the number of samples in the stratum and the entire region, respectively; and ${\sigma }_h^2$ and ${\sigma }^2$ are the variance of Y values in stratum h and the whole region, respectively.

3.2. Indicator Systems and Data Sources

3.2.1. Construction of the Indices Systems

Based on the principles of science, system, reliability, truthfulness, and operability, and drawing on the evaluation indices researched in related papers [20,23,29,30,31,32], indices systems of Wuhan were constructed (

Table 3. Indices system of Wuhan.

Objective Level	Primary Indicators	Secondary Indicators	Attributes	Weights
New urbanization	Population urbanization	X1 Share of urban population (%)	+	8.08%
		X2 Population density (persons/square kilometer)	+	10.77%
		X3 Share of employed population in secondary and tertiary industries (%)	+	7.74%
	Economic urbanization	X4 GDP per capita (yuan)	+	11.21%
		X5 Ratio of output value of tertiary and secondary industries (%)	+	10.11%
		X6 Ratio of non-agricultural output value (%)	+	3.36%
	Social urbanization	X7 Annual per capita consumption expenditure of urban residents (yuan)	+	12.25%
		X8 Number of sanitary beds per 1000 people (units)	+	11.32%
		X9 Number of students enrolled in general higher education institutions (persons)	+	4.2%
	Spatial urbanization	X10 Built-up area (square kilometers)	+	12.48%
		X11 Road area per capita (m2)	+	3.54%
		X12 Green coverage rate of built-up area (%)	+	4.96%
Economy	Economic Scale	X13 GDP per capita (yuan)	+	9.9%
		X14 Total social fixed investment per capita (yuan)	+	9.75%
		X15 Per capita total retail sales of social consumer goods (yuan)	+	9.43%
		X16 Per capita fiscal revenue (yuan)	+	10.12%
	Economic Structure	X17 Industrialization level (%)	+	3.54%
		X18 Economic density (billion yuan/square kilometer)	+	7.96%
		X19 Share of output value of secondary industry (%)	+	3.82%
		X20 Share of output value of tertiary industry (%)	+	6.21%
	Economic Environment	X21 Import and export (%)	+	7.06%
		X22 Marketization level (%)	+	13.07%
		X23 Per capita disposable income of urban permanent residents (yuan)	+	10.6%
		X24 Consumer price index (%)	+	8.56%

). This universal indicator system, with its multi-dimensional structure, provides a transferable analytical framework for urban economic research across different cities.

The evaluation indicators of the development level of new urbanization are divided into four major aspects. Among them, population urbanization reflects the process of population concentration in cities and towns. Three indices are selected: the share of urban population, population density, and the share of population employed in secondary and tertiary industries. Economic urbanization reflects the transformation of the economic structure into non-agriculturalization with an increase in GDP and non-agricultural industries. Three indices are selected: GDP per capita, the ratio of output value of tertiary and secondary industries, and the ratio of non-agricultural output value. Social urbanization reflects changes in lifestyles, with indicators selected from three dimensions: education, healthcare, and consumption levels. Spatial urbanization reflects the shift from rural to urban territories, with indicators selected from three dimensions: built-up area, roads, and greenery.

The level of economic development is a comprehensive concept that covers a number of dimensions, including economic scale, economic structure, and the economic environment. The economy scale selects indicators from four aspects: GDP per capita, consumption, investment, and income. Economic structure reflects the changes in the output value of one, two, or three industries so that the data related to the output value of the industries are selected. The economic environment can be divided into the international and domestic environments. The international environment is evaluated in terms of exports and imports, while the domestic environment is evaluated in terms of the marketization level, per capita disposable income, and the consumer price index.

3.2.2. Data Sources

In this paper, the relevant economic and urbanization data of Wuhan from 2000 to 2022 are used as samples, with the data sourced from the Wuhan Statistical Yearbook [33] and the China Urban Construction Statistical Yearbook [34] from 2001 to 2023. Some missing data were obtained through mean interpolation.

4. Results

4.1. Results of Subsystems Analysis

4.1.1. New Urbanization Subsystem Analysis Results

Wuhan’s demographic, economic, social, and spatial urbanization indices have shown an overall upward trend from 2000 to 2022 (Figure 2). From 2000 to 2009, population urbanization, social urbanization, and spatial urbanization developed simultaneously. During this period, the economic urbanization index was higher and dominated. This indicates that the economy improved with the support of major strategies, such as the Rise of Central China. Economic growth became the main factor driving urbanization. From 2010 to 2020, social urbanization dominated. This suggests that the living standards of urban residents significantly improved. From 2021 to 2022, the development of urbanization subsystems was relatively smooth. The population urbanization index was higher during this period. Since 2010, population urbanization has consistently been higher than spatial urbanization. This indicates that a large number of foreigners were attracted during this period. The urbanization rate was high, and population density increased. However, urban spatial development relatively lagged behind.

4.1.2. Economic Subsystem Analysis Results

From 2000 to 2022, Wuhan exhibited distinct development trajectories across three economic dimensions: economic scale, economic structure, and the economic environment (Figure 3). The economic scale demonstrated steady growth between 2000 and 2019. Notably, its growth rate accelerated during the 2010–2019 period compared to the preceding decade (2000–2010). However, post-2019 witnessed a marked decline in the economic scale index, signaling economic stagnancy or contraction in Wuhan. In contrast, the economic structure maintained relative stability with minimal fluctuations throughout the study period. This was due to Wuhan’s well-developed manufacturing industry, such as the automobile industry, optoelectronic information, etc., and strong policy support. The change of industrial structure is not obvious. Meanwhile, the economic environment displayed periodic volatility but overall showed an upward trend. The total amount of imports and exports, the income of the population, and the level of consumption gradually rose.

4.2. Comprehensive Evaluation Index Analysis

Utilizing entropy-calculated metric weights, the comprehensive evaluation indices for new urbanization and economic development in Wuhan from 2000 to 2022 were calculated. The index values range between 0 and 1, with values closer to 1 indicating higher development levels and those approaching 0 reflecting poorer performance. The following conclusions can be drawn (Figure 4).

Analyzing the trend of economic development, it showed a fluctuating upward trajectory. The growth rate from 2012 to 2019 was higher than that from 2000 to 2008. In 2011, the Twelfth Party Congress of Wuhan put forward the goal of “building a national central city and rejuvenating Wuhan”. Wuhan has demonstrated accelerated economic expansion alongside strengthened industrial competitiveness in recent years. This is due to the strategic leadership of the central region, the construction of national central cities, the vigorous development of key emerging industries, and the advancement of advanced manufacturing. However, in 2019, Wuhan, as the hardest-hit area of the pandemic, suffered a significant impact regarding economic development. The economic activities were almost stagnant. Transportation and logistics were blocked. In the face of severe pressure to prevent and control the pandemic, enterprises stopped work and production; there were many business difficulties, and both the secondary and tertiary industries were seriously affected. This led to a reduction in residents’ income, a sharp drop in consumption and investment, and severe GDP losses. Consequently, the combined evaluation index of economic size and economic development declined during this period.

Analyzing the trend of new urbanization, it can be concluded that the urbanization has been growing steadily. From 2000 to 2011, the growth rate was slower, increasing from 0.052 in 2000 to 0.412 in 2011, with an average growth of 0.032 per year. The growth rate accelerated from 2012 to 2021, increasing from 0.461 in 2012 to 0.920 in 2021, with an average annual increase of 0.051. After the 18th National Congress (2012), Wuhan carried out large-scale urban construction and upgrades. It enhanced public service facilities, particularly in healthcare, education, eldercare, and social security. As a result, the quality of life in the city has significantly improved, which has attracted a significant migrant population. Consequently, the total resident population has continued to grow, and the level of urbanization has been rising steadily. In 2022, the comprehensive evaluation index of urbanization remained basically flat. At this stage, the urbanization rate of Wuhan’s resident population reached 84%. It is gradually stabilizing.

From the comprehensive evaluation index of each system, it can be seen that the overall development trend of new urbanization and the economy in Wuhan continues to be positive. From 2000 to 2008, the economic development of Wuhan was higher than the urbanization development. The urban infrastructure construction was weak, and the urbanization development level lagged behind the economic development level. From 2009 to 2019, Wuhan’s urbanization and economic levels basically showed synchronous development. Post-2019, the urbanization development level of Wuhan was higher than the economic development level. This was due to the fact that the economy was most obviously affected by the COVID-19 pandemic, which was intuitively reflected in the shrinkage of GDP, consumption and expenditure, and industrial output. But the level of urbanization development covers four aspects, demographic, economic, social, and spatial, and except for the economic urbanization, the population, infrastructure configuration, and construction of urban spatial development were not obviously affected by the epidemic.

4.3. Characterization of the Time-Series Variation in the Coupling Coordination Degree

Using the coupling coordination degree model, we calculated the degree of Wuhan and made a graph showing the trend (Figure 5).

From the perspective of the coupling degree, between 2000 and 2003, the change in the coupling degree was larger. There was a small decline from 2000 to 2001 and an upward trend from 2001 to 2003. Since 2003, the coupling degree has become stable, remaining above 0.9. This indicates that the coupling interaction relationship has become more significant.

In terms of the change in the coupling coordination degree, it rose from 0.125 to 0.962 from 2000 to 2022, undergoing an evolutionary process from serious dissonance to high-quality coordination. This indicates that the new urbanization and economic system promote each other and develop steadily and synergistically. It can be divided into the following three stages.

From 2000 to 2007, Wuhan’s new urbanization and economic system went through four stages of development, serious dislocation, moderate dislocation, mild dislocation, and near dislocation, with an average annual increase of 0.048. This period was still in the dislocation stage, but the degree of dislocation has gradually eased, and the overall development trend is positive. Since 2000, a series of major policies have been implemented in Wuhan, such as the Rise of Central China strategy and the construction of a pilot area for comprehensive reform of the “two-type society”. This has attracted many national and regional infrastructure projects to settle in Wuhan, spurring rapid growth in the modern service industry and advanced manufacturing sectors. Urban development has been planned at the metropolitan area level, strengthening regional spatial coordination.

From 2008 to 2016, the development trend of Wuhan’s coupling coordination degree continued to be good, with an average annual increase of 0.034. There was bare coordination in coupling coordination during 2008–2009, with primary coordination in 2010–2012, intermediate coordination in 2013, and effective coordination in 2014–2016, suggesting a rise in coupling coordination and a positive evolution of both urbanization and economic systems. The 2008 Wuhan City Circle Spatial Plan took Wuhan as the core and formed the development axis for urban and industrial agglomeration in the three directions of north, south, and west. It concentrated demographic and industrial distribution along primary development corridors, utilizing transport networks as economic catalysts while strengthening Wuhan’s industrial pillars spanning automotive manufacturing, steel production, petrochemical complexes, tech innovation hubs, and professional service clusters. In 2010, Wuhan Donghu New Technology Development Zone became the second national independent innovation demonstration zone, gathering a large number of enterprises and research institutions. During the 12th Five-Year Plan period (2011–2015), Wuhan focused on the construction of a national central city and the revitalization of Wuhan. The total economic output exceeded CNY one trillion, and the industrial structure was optimized. The development of advanced manufacturing, high-tech industry, modern service, and quality was improved. Fundamental changes to the urban landscape were made, and large-scale city construction was pushed forward. The income of residents has steadily increased.

From 2017 to 2022, the degree reached 0.9 or above, achieving high-quality coordination. From 2017 to 2019, it increased year by year, and urbanization and the economic system developed together. According to the Wuhan City Master Plan (2017–2035), at the regional level, centered on a one-hour commuting radius, the Wuhan metropolitan development strategy drives regional integration through coordinated infrastructure and industrial synergy. At the city level, an open, multi-centered, and networked urban spatial structure will be established. In this stage, Wuhan promotes comprehensive environmental improvement and upgrading, optimizes public culture and sports infrastructure, adds many subway lines, and significantly improves the city’s quality. At the same time, the Wuhan Area of Hubei Pilot Free-Trade Zone will be established. It develops sufficient resources, provides policy support, attracts major domestic and foreign well-known enterprises, and drives the continuous improvement of Wuhan’s economic level. After 2019, the pandemic broke out and coupling coordination first fell and then rose, with 2021 having the highest coupling coordination degree at 0.987. Wuhan integrated normalized epidemic control with economic and social development, reshaped the urban governance system, accelerated post-epidemic revitalization, and promoted rapid economic and social recovery.

4.4. Impact Factor Analysis

This paper selects all indicators in the indices system as detection factors and performs a factor analysis using Geodetector. In order to improve the accuracy of the analysis results, in this paper, K = 4, K = 6, and K = 8 were taken in the cluster analysis. The analysis results are shown in

Table 4. Detection results of impact factors with different values of K.

Indicators	K = 4		K = 6		K = 8
	q-Value	p-Value	q-Value	p-Value	q-Value	p-Value
X1	0.932	0.000	0.977	0.000	0.986	0.000
X2	0.771	0.005	0.950	0.000	0.977	0.000
X3	0.925	0.000	0.955	0.000	0.966	0.000
X4	0.892	0.000	0.898	0.000	0.962	0.000
X5	0.688	0.012	0.655	0.137	0.656	0.556
X6	0.529	0.069	0.653	0.054	0.678	0.068
X7	0.910	0.000	0.925	0.000	0.948	0.000
X8	0.827	0.000	0.892	0.000	0.894	0.000
X9	0.869	0.000	0.887	0.000	0.923	0.000
X10	0.906	0.000	0.909	0.000	0.929	0.000
X11	0.869	0.000	0.878	0.000	0.920	0.000
X12	0.897	0.000	0.931	0.000	0.935	0.000
X13	0.892	0.000	0.898	0.000	0.962	0.000
X14	0.871	0.000	0.942	0.000	0.954	0.000
X15	0.866	0.000	0.955	0.000	0.946	0.000
X16	0.847	0.000	0.927	0.000	0.923	0.000
X17	0.364	0.256	0.514	0.611	0.528	0.635
X18	0.858	0.000	0.899	0.000	0.903	0.000
X19	0.580	0.054	0.622	0.147	0.622	0.606
X20	0.681	0.005	0.895	0.000	0.908	0.000
X21	0.127	0.614	0.201	0.628	0.286	0.861
X22	0.705	0.000	0.708	0.062	0.709	0.365
X23	0.778	0.000	0.920	0.000	0.966	0.000
X24	0.908	0.000	0.963	0.000	0.975	0.000

.

According to the results of factor detection, the share of the urban population is the primary influence factor, with exports and imports being the weakest. This shows that population urbanization is the key. The total amount of foreign imports and exports has a relatively small impact on Wuhan’s economy, and the domestic market is the main market.

Among the analysis results of different K values, the q-values of the consumer price index and the share of the employed population in secondary and tertiary industries in total employed population are all in the top five. They are the main factors affecting the coupling coordination degree. The consumer price index (CPI), which gauges fluctuations in the price levels of goods and services consumed by residents, has played a multifaceted role in Wuhan’s socio-economic development. For one thing, since 2010, the city has pioneered the compilation of a “Low-Income CPI” and implemented a price-linkage mechanism, institutional safeguards that protect vulnerable populations from inflationary pressures while maintaining social equity. This provides a fundamental safeguard for population migration during rapid urbanization. For another, changes in the consumption structure have promoted the development of the tertiary industry, leading to increased employment opportunities and the upgrading of urban functions. The share of the employed population in secondary and tertiary industries reflects changes in the structure of the economy and the overall situation of the job market. Wuhan has a solid industrial base and a relatively developed service sector. The size of the workforce in the secondary and tertiary industries continues to increase, and the ability of new industries and new forms of business to absorb employment has been strengthened, providing important support for economic development and the improvement of people’s livelihoods.

5. Conclusions

Based on the statistical yearbook information and related data of Wuhan, this paper analyzes the temporal and spatial differentiation characteristics of the coupling coordination degree between new urbanization and the economy. It uses the entropy weight method, coupling coordination degree model, and Geodetector. The results of the study are as follows:

(1)

The population, economic, social, and spatial urbanization indices of Wuhan as a whole all show an increasing trend. However, the development trends are different in the economy subsystems. Among these, the economic structure has developed relatively smoothly, the economic environment as a whole shows an upward trend, and the economic scale grew steadily in 2000–2019 but decreased significantly due to the impact of the pandemic after 2019.

(2)

The comprehensive evaluation index of new urbanization and economic development in Wuhan from 2000 to 2019 showed a fluctuating upward trend overall, indicating that both the urbanization and the economy of Wuhan are increasing. However, in 2020, the urbanization and the economy of Wuhan declined due to the impact of the pandemic. Urbanization lagged behind economic growth from 2000 to 2008, developed synchronously during 2009–2019, and surpassed economic development between 2020 and 2022.

(3)

The coupling coordination degree of new urbanization and economic development in Wuhan experienced a development course from severe dissonance to quality coordination in 2000–2022. The degree steadily increased in 2000–2019 and had big ups and downs in 2020–2022. Its development process is influenced by policies and endogenous dynamics.

(4)

According to the analysis using Geodetector, the main driving factors include the share of the urban population (%), the consumer price index (%), the share of the employed population in secondary, and tertiary industries (%).

Based on the results of the factor analysis, the following suggestions are provided in Wuhan.

Initially, the share of the urban population must be improved. First, the reform of the registered residence system must be deepened, and the restrictions on settlement, such as those for enterprise employee settlement, employment and entrepreneurship settlement, relocation settlement, and integral settlement must be relaxed. The population inflow policy must be adjusted and improved to promote the smooth flow of population factors. Second, raising the level of urbanization in potential areas must be focused on, such as the Tianhe air–railway hub, Aerospace New City, and other key sectors.

Secondly, the proportion of the employed population in the secondary and tertiary industries must be increased. First, the driving force of industry on employment must be enhanced, effectively integrating industrial stock resources. The construction of the East Lake Independent Innovation Demonstration Zone must be accelerated and its leading role leveraged. Focusing on national high-tech zones and economic development zones, cooperation pilots in innovation parks with unique characteristics must be explored to expand the availability of industrial employment and job chances. Policy support and the implementation of various employment and entrepreneurship subsidies must be provided. This would address the labor demand of key enterprises and help key groups such as rural migrant workers, poverty-eradicating populations, the unemployed, and those with employment difficulties to find employment.

Thirdly, consumption potential must be stimulated. The release of the consumption potential of urban residents can directly lead to an increase in the purchase of goods and services, promote the prosperity of several industries, such as retail, catering, and entertainment, and stimulate domestic demand, which in turn promotes the growth of the urban economy. The consumption of bulk commodities should be encouraged, such as automobiles, home appliances, and furniture. Diverse consumption scenarios should be introduced, in addition to expanding service consumption, developing digital consumption, and accelerating the construction of a high-standard market system.

The coupled coordinated relationship between urbanization and economy is a dynamic and complex process, and its research content and framework are still being enriched and improved. Compared with other studies, this paper spans a long period of time and has a richer system of indicators. It studies the relationship between these two systems over the past two decades and scientifically and objectively analyzes the driving factors behind them. This enables local governments to systematically identify development gaps, optimize resource allocation, and drive industrial upgrading, thus providing precise support for policy regulation and urban development. Insufficiently, this method fails to effectively predict future economic development changes. The digital twin and time network model can be used to predict the regional economic development trend in subsequent research [35]. In addition, this paper only focuses on the spatial and temporal changes of the coupled coordination and lacks spatial comparative research, which still needs to be improved upon.