Spatial Characteristics and Influencing Factors of the Coupling and Coordination of High-Quality Development in Eastern Coastal Areas of China

Abstract

China’s pursuit of sustainable and healthy economic growth requires the promotion of high-quality development. While many scholars have studied high-quality development, few have examined the coupling and coordination among its internal systems. The study aims to analyze the influencing factors of high-quality coordinated development, identify problem areas based on the five development statuses, and provide practical recommendations for optimizing the spatial layout of high-quality development in these areas. By applying a coupling coordination model and a geographically weighted regression model, the comprehensive level of high-quality coordinated development in the eastern coastal areas was evaluated. The results revealed that the majority of the eastern coastal region exhibited weak coordination and significant spatial differences in their comprehensive level. The problem cities were predominantly located in the southern and northern coastal areas. An economic foundation and innovation potential have a positive and stable impact on high-quality coordinated development.

1. Introduction

High-quality development denotes an economic development approach that considers the long-term consequences of economic growth and prioritizes enhancing the overall welfare of society alongside the achievement of economic growth [1]. The 19th National Congress of the Communist Party of China pointed out that “China’s economy has shifted from a high-speed growth stage to a stage of high-quality development” [2]. This implies that advancing high-quality development has emerged as the primary concern of China’s present-day progress. Since China’s reform and opening-up policy in 1978, the eastern coastal region has become the strategic focus of national economic development due to its comprehensive and pioneering achievements. The COVID-19 pandemic and profound changes in China’s primary social contradictions have exposed the issues of unbalanced and insufficient economic and social development [3]. Thus, it is crucial for the eastern coastal region to play a leading role in high-quality development and to solve these problems through effective and sustainable means. Meeting the needs of the people’s pursuit of a better life and completing the new tasks and goals assigned by high-quality development should also be a top priority [4].

The existing literature on high-quality development mainly focuses on the following aspects: (1) interpretation of the connotation and path development of high-quality development [1,5,6,7,8]; (2) measurement of the level of quality and analysis of the influencing factors [9,10,11,12]; (3) the relationships between human capital, energy, tourism, scientific and technological innovation, and high-quality economic development [13,14,15,16]. The research methods mainly include entropy analysis, cluster analysis, spatial correlation analysis, regression analysis, and coupled coordinated development analysis [17,18,19,20], and the research regions are mainly on the provincial level [12,17,20]. Most of them consider high-quality development as a long-term and complex systematic project. Different indicators are selected to measure the high-quality development level of the research area, but the subjectivity of indicator selection leads to significant differences in evaluation results.

In addition, current studies of the measurement of the internal system coupling and coordination level, spatial pattern evolution, and the mechanism of high-quality development is still not systematic enough, especially in terms of the city/regional dimension. Coupling refers to the phenomenon in which two (or more) systems or forms of motion mutually influence each other through various interactions. The coupling degree is the degree to which a system or element affects and interacts with another. From the perspective of synergy, the coupling effect and the coupling degree determine the direction and structure of the system when it reaches the critical region, or they determine the trend of the system in going from disorder to order. In 1960, the British economist Boulding applied the development of this system to the analysis of the coordinated development of the economy and environment with the aim of establishing a “circular” economic system that is environmentally friendly and recyclable [14]; subsequently, Norgaad proposed the theory of coordinated development, believing that mutual development between society and ecological systems could be achieved through feedback loops [21].

This study builds a comprehensive evaluation system for high-quality development based on the five concepts of innovation, coordination, green, openness, and sharing. The entropy method and a spatial autocorrelation model are applied to systematically measure and analyze the current situation and spatial patterns of high-quality development in various cities in the eastern coastal region. Moreover, a geographically weighted regression model is used to quantify the factors that influence the level of high-quality and coordinated development in this region. These findings are crucial in guiding practical solutions for fully realizing the potential for high-quality development in the eastern coastal region and for further promoting regional development that is both of a high quality and coordinated.

The structure of this work is organized as follows: the Section 2 outlines the research methods and data sources used in this study; the Section 3 presents the results and an analysis that evaluated the comprehensive level of high-quality coordinated development by using a coupling coordination degree model and analyzed the influencing factors of high-quality coordinated development; the main findings are summarized, and their implications are discussed in the concluding Section 4.

2. Research Methods and Data Sources

2.1. Research Methods

2.1.1. Measurement of the High-Quality Development Level

This article follows the principles of scientific, systematic, accessible, and operational indicator selection to construct the Comprehensive Innovation Development Index $C\left(c\right)$, Coordinated Development Index $X\left(x\right)$, Green Development Index $L\left(l\right)$, Open Development Index $K\left(k\right)$, and Shared Development Index G(g). These indices were selected in consideration of the core concept and main forms of high-quality development and were used to comprehensively evaluate high-quality development. In the construction of the indicator system, the selection of specific indicators was based on the methods that were commonly used by previous researchers for indicator selection and the availability of data [22,23,24]. The specific indicators selected were the following:

$$C\left(c\right)=\sum _{\alpha =1}^m{\alpha }_a{c}_a^{\prime };X\left(x\right)=\sum _{b=1}^m{\beta }_b{x}_b^{\prime };L\left(l\right)=\sum _{c=1}^m{\gamma }_c{l}_c^{\prime };K\left(k\right)=\sum _{d=1}^m{\delta }_d{k}_d^{\prime };G\left(\mathrm{g}\right)=\sum _{e=1}^m{\mathsf{\epsilon }}_e{\mathrm{g}}_e^{\prime }$$

(1)

The formula uses $c_a^{\prime },x_b^{\prime },l_c^{\prime },k_d^{\prime }$, and $g_e^{\prime }$ to represent indicators that describe the characteristics of innovative, coordinated, green, open, and shared development. These indicators are dimensionless values obtained by applying range standardization to the indicator data. Additionally, ${\alpha }_a,{\beta }_b,{\gamma }_c,{\delta }_d$, and ${\mathsf{\epsilon }}_e$ represent the weights of each respective indicator, and they were obtained by using the entropy weighting method. With regards to the development of the indicator system, the specific indicators shown in

Table 1. The comprehensive evaluation index system for high-quality development.

Primary Indicators	Secondary Indicators	Indicator Definitions
Innovative Development	Research and Development (R&D) Expenditure Intensity	R&D Investment/GDP (%)
	Proportion of Scientific and Technical Researchers	Personnel in the Scientific Research and Technical Services Industry/Employed persons (%)
	Patent Applications per 10,000 People	Patent Application Quantity/Annual Average Total Population by Region (pieces/10,000 people)
	Patents Authorized per 10,000 People	Patent Granted Quantity/Average Total Population per Year in the Region (pieces/10,000 people)
	Industrial Enterprises above Designated Size	The Number of Industrial Enterprises above Designated Size
Coordinated Development	The Proportion of the Output Value of the Secondary Industry to GDP	Value of the Secondary Industry/GDP (%)
	Disposable Income of Urban and Rural Residents	Urban Residents’ Disposable Income/Rural Residents’ Disposable Income (%)
	Sharing Level of Regional Income	GDP Per Capita by Province/GDP Per Capita of the Country
	The Proportion of Labor Compensation to GDP	Labor Compensation/GDP (%)
	Binary Disparity Index (-) 1	Binary Disparity Index (%)
Green Development	Wastewater Discharged to GDP (-)	Wastewater Discharged/GDP (%)
	Waste Gas Emissions to GDP (-)	Waste Gas Emission/GDP (%)
	Dust Emissions to GDP (-)	Dust Emission/GDP (%)
	Green Space Area in Parks Per Capita	Park Green Space Area/Annual Regional Average Total Population (Square Meters/10,000 people)
	Urban Centralized Sewage Treatment Rate	Urban Centralized Sewage Treatment Rate
Open Development	Total Import	Total Import (Billion RMB)
	Total Export	Total Export (Billion RMB)
	Foreign-Invested Enterprises	Number of Foreign-Invested Enterprises
	Utilization of Foreign Investment	The Actual Utilization of Foreign Investment (Billion RMB)
	The Proportion of Total Retail Sales of Consumer Goods to GDP	Total Retail Sales of Consumer Goods/GDP (%)
Shared Development	The Public Library Collection Owned per 10,000 People	The Public Library Collection Amount/Annual Regional Average Total Population (Books/10,000 people)
	Hospital Beds per 10,000 People	The Number of Hospital Beds/Annual Regional Average Total Population (Beds/10,000 people)
	Densities of Primary and Secondary Schools	Primary and Secondary Schools/Administrative District Area (Schools/Square Kilometers)
	Unemployment Rate (-)	Unemployment Rate (%)
	Participation Rate of The Basic Pension Insurance	The Number of Workers Participating in the Basic Pension Insurance/Employment (%)

¹ The Binary Disparity Index is the absolute value of the difference between the proportion of the output value of secondary and tertiary industries and the proportion of the labor force in secondary and tertiary industries.

were selected.

On the basis of Equation (1), the Innovative Development Index, Coordinated Development Index, Green Development Index, Open Development Index, and Shared Development Index were further weighted and summed to obtain a high-quality comprehensive development index, as shown in Equation (2).

$$T=1/5\left[C\right(c)+X(x)+L(l)+K(k)+G(g\left)\right]$$

(2)

2.1.2. Coupled Coordination Model

The coupling degree can describe the strength of an interaction between two or more systems, but it is difficult to truly reflect the effect of “synergy” between systems [15], whereas the coordination degree can describe the process of mutual promotion and harmonious development between two or more systems [25]. Therefore, the use of a coupled coordination model can truly reflect the level of high-quality coordinated development. The reader is referred to the studies of Niu, Shen, and Zhang as well as of Yuan, Ou, and Tang for the calculation steps of the relevant model [26,27].

Coupling is a concept in physics that refers to the phenomenon in which two or more systems affect each other through interaction. In current academic research, the coupling degree model of interaction between two or more systems (or elements) is often derived by extending the capacity coupling coefficient model in physics, as shown below:

$$C_n={\{(u_1,u_2\dots u_m)/\mathsf{\Pi }(u_i+u_n)\}}^{1/n}$$

(3)

In Equation (3), $u_i(i=1,2,3,\dots ,m)$ is the comprehensive evaluation coefficient of each subsystem. From Equation (3), a coupling model with five dimensions for high-quality development can be further deduced as follows:

$$C=\{\frac{C\left(c\right)\times X\left(x\right)\times L\left(l\right)\times K\left(k\right)\times G\left(g\right)}{{[C\left(c\right)+X\left(x\right)+L\left(l\right)+K\left(k\right)+G\left(g\right)]}^5}{\}}^{\frac{1}{5}}$$

(4)

However, there are obvious defects in the coupling degree calculated with Equation (4). When the value of one subsystem is 0, regardless of the values of the other subsystems, the value of the entire system is 0, which is seriously inconsistent with the reality of the social and economic system. To overcome the above-mentioned shortcoming, this study introduces a coefficient of variation in the statistical sense to optimize the model, and it further deduces and simplifies the calculation model for the coupling degree with the five dimensions of high-quality development in a synchronous developmental manner, as shown in Equation (5).

$$C=\sqrt{2-5\times \frac{{\left[C\left(c\right)\right]}^2+{\left[X\left(x\right)\right]}^2+{\left[L\left(l\right)\right]}^2+{\left[K\left(k\right)\right]}^2+{\left[G\left(g\right)\right]}^2}{{[C\left(c\right)+X\left(x\right)+L\left(l\right)+K\left(k\right)+G\left(g\right)]}^2}}$$

(5)

Moreover, the coupling model can only comprehensively reflect the strength of coupling among the subsystems, but it cannot reflect the development level of individual subsystems. Therefore, this study further introduces a coordination model to enable a more comprehensive judgment of the degree of coordination among the five dimensions of high-quality development in any specific region. The equation for calculating the coordination degree is

$$D=\sqrt{C\times T}$$

(6)

In Equation (6), C is the coupling degree from Equation (5); T is the high-quality comprehensive development index from Equation (2).

In the above model, the values of the coupling degree C and coordination degree D are both between 0 and 1. When the values of C and D are close to 1, the coupling and coordination degrees are very high, indicating that the entire system is in a stage of coordinated improvement. Conversely, when the values of C and D are close to 0, the coupling and coordination degrees are very low, indicating that the entire system is in a stage of disordered decline.

In order to better explain the coupling and coordination degrees among the five dimensions of high-quality coordinated development, this study divides high-quality coordinated development into 10 types, namely, extremely imbalanced [0–0.100], severely imbalanced (0.100–0.200], moderately imbalanced (0.200–0.300], mildly imbalanced (0.300–0.400], nearly imbalanced (0.400–0.500], barely coordinated (0.500–0.600], mildly coordinated (0.600–0.700], moderately coordinated (0.700–0.800], well coordinated (0.800–0.900], and extremely coordinated (0.900–1.000].

2.1.3. Geographically Weighted Regression Model

Geographically weighted regression (GWR) is a local regression model that can form separately estimated coefficients for each study unit to reflect the degree of influence of a variable on the region when it is located in different geographic locations. Through this, it obtains the spatial differentiation characteristics of the impacts of different factors on the explanatory variables [28,29]. The regression model is as follows:

$$y_i={\beta }_0(u_i,v_i)+\sum _{k=1}^p{\beta }_i(u_i,v_i)x_{ik}+{\mathsf{\epsilon }}_i$$

(7)

where $y_i$ denotes the dependent variable for the ith sample space in China in a given year; $(u_i,v_i)$ denotes the ith sample space’s coordinates; $x_{ik}$ denotes the kth variable; ${\mathsf{\epsilon }}_i$ denotes the error term; ${\beta }_0(u_i,v_i)$ is the intercept term. ${\beta }_k(u_i,v_i)$ is the coefficient of the kth variable.

The function of the geographic location can be calculated as follows:

$$\beta (u_i,v_i)={\left(X^{T}X(u_i,v_i)\right)}^{-1}{X}^{T}W(u_i,v_i)y,W_{ij}=exp(-{(d_{ij}/b)}^2)$$

(8)

where X is the matrix of independent variables; $W(u_i,v_i)$ denotes the spatial weight matrix; b is the bandwidth determined by the Gaussian function; $d_{ij}$ denotes the distance between the ith sample space and the jth sample space. The bandwidth is determined by the minimum AICc method.

2.2. Data Sources

This study takes 112 cities under the administration of 11 provinces and municipalities, namely, Liaoning, Hebei, Beijing, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, and Guangxi, as the research area (considering the accessibility of data, the research area does not include Hong Kong, Macao, Taiwan, and Hainan) to explore the current situation and the potential reasons for high-quality development in the eastern coastal areas of China in 2019. In the comprehensive evaluation index system, the data of indicators such as technology expenditure, the number of scientific and technological research personnel, patent applications, patent authorizations, internet users, the number of students in higher education institutions, the number of employees in primary, secondary, and tertiary industries, the output value of primary, secondary, and tertiary industries, labor compensation, the balance of deposits and loans of financial institutions at the end of the year, the area of built-up areas and green coverage, green space areas, total population, industrial wastewater discharge, total electricity consumption in society, urban sewage centralized treatment rate, the number of employees in water conservancy, the environmental and public facility management industry, total import and export trade, actual utilization of foreign capital, the number of employees in the financial industry, total retail sales of consumer goods, the number of hospital beds, education expenditure, the number of public transportation vehicles, the registered unemployed urban population at the end of the year, the collection of public library books, the urban road area, and other indicators were mainly extracted from the 2020 China Urban Statistical Yearbook compiled by the National Bureau of Statistics of China.

3. Results and Analysis

3.1. The Comprehensive Measurement of the Level of High-Quality Development

Based on the natural break method, this study used ArcGIS 10.0 for mapping analysis (see Figure 1) to explore the spatial differentiation characteristics of the high-quality development index in the eastern coastal region. The main findings are discussed below.

First, the average value of the innovation development index was 0.288, with a standard deviation of 0.256 and a coefficient of variation of 0.891. Figure 1a suggests that, except for the provincial capital cities and sub-center cities, such as Beijing, Tianjin, Shijiazhuang, Shenyang, Dalian, Jinan, Qingdao, Fuzhou, Xiamen, Nanning, etc., which were distributed in a point-like manner, in most cases, the cities with values higher than the average showed a patchy distribution, which was mainly concentrated in the urban agglomerations of the Yangtze River Delta and the Pearl River Delta. The low-value areas were mainly distributed in most parts of Liaoning, most parts of Hebei, most parts of Shandong, the central and northern parts of Jiangsu, Fujian, and most parts of Guangxi. This was mainly due to the insufficient input of innovative factors, weak agglomeration externality, and incomplete construction of innovation platforms, which had not yet formed a regional linkage pattern between the northern and southern coastal regions [30].

Second, the average value of the Coordinated Development Index was 0.464, the standard deviation was 0.169, and the variation coefficient was 0.365. Figure 1b shows that the cities with higher values than the average level in the eastern coastal areas were mainly concentrated in Beijing, Tianjin, the Shandong Peninsula, the Yangtze River Delta, and the Pearl River Delta urban agglomerations, and they were also distributed in the mineral-resource-rich northern coastal areas. The low-value areas mainly appeared in the northern part of Hebei, the eastern part of Shandong, the northern part of Fujian, and most parts of Guangxi.

Third, the average value of the Green Development Index was 0.282, with a standard deviation of 0.136 and a coefficient of variation of 0.483. Figure 1c shows that the cities with higher values were mainly concentrated in the cities along the west coast of the Taiwan Strait and the Pearl River Delta, as well as some regions with superior ecological conditions and strong environmental protection efforts. The lower value areas were mainly distributed in the Yangtze River Delta city cluster, as well as the eastern part of Shandong, the northern part of Jiangsu, the western part of Fujian, and most of Guangxi. The main reason for this was that although the coastal regions had issued a series of policy decisions to ease the contradiction between resource and environmental carrying capacity and social and economic development, the environmental problems characterized by “high investment, high efficiency, and high pollution” caused by the important manufacturing industry agglomeration in the Yangtze River Delta city cluster had become an important factor that restricted the high-quality development of the central coastal region [31].

Fourth, the average value of the Open Development Index was 0.360, with a standard deviation of 0.194 and a coefficient of variation of 0.538. Figure 1d shows that its spatial differentiation characteristics were similar to those of the Innovation Development Index, mostly presenting a dotted distribution centered on cities and sub-centers, such as Beijing, Qingdao, Jinan, Xiamen, and Quanzhou, and a patchy distribution dominated by the urban agglomerations of the Yangtze River Delta and the Pearl River Delta. The low-value areas were mainly concentrated in most of Hebei, eastern Shandong, central-northern Jiangsu, northern Fujian, and most of Guangxi. Deepening the level of opening up both domestically and internationally was an effective way to promote high-quality development in a coordinated manner. With the establishment of free trade zones and the help of relevant preferential policies, the level of two-way opening up in coastal areas, especially in the central coastal region, is increasing, thanks to the early start and additional advantages brought about by the construction of free trade zones. Open development is at a leading level [30].

Fifth, the average value of the Shared Development Index was 0.514, with a standard deviation of 0.194 and a coefficient of variation of 0.377. Figure 1e suggests that its spatial differentiation characteristics were similar to those of the Coordinated Development Index, with high-value areas that were mainly distributed in the Beijing–Tianjin region, the Yangtze River Delta, the Pearl River Delta urban agglomeration, and the mineral-resource-rich northern areas, while the low-value areas were mainly distributed in the southern part of Hebei, most of Shandong, the central and northern parts of Jiangsu, Fujian, and most of Guangxi.

Finally, the Innovative Development, Coordinated Development, Green Development, Open Development, and Shared Development Indexes were added with equal weight to obtain the comprehensive development level of each city. The average value of the comprehensive high-quality development index in the eastern coastal region was 0.381, with a standard deviation of 0.151 and a coefficient of variation of 0.396. In the high-quality development system, the Shared Development Index had the highest mean value, the Green Development Index had the lowest mean value, the Innovation Development Index had the highest coefficient of variation, and the Coordinated Development Index had the lowest coefficient of variation. In addition, the regions in which the comprehensive high-quality development index in the eastern coastal region was higher than the average value were mainly distributed in the Beijing–Tianjin–Hebei region, the Yangtze River Delta region, the Pearl River Delta region, and some resource-based cities in the northern coastal area. The low-value areas were mainly concentrated in most of Hebei, eastern Shandong, northern Jiangsu, northern Fujian, eastern Guangdong, and most of Guangxi, which may have been related to the level of regional economic and social development, government scale, industrial structure, and innovation potential [30]. Taking the northern part of Jiangsu province as an example, to improve its level of high-quality development, it is necessary to implement relevant government policies, improve the construction of infrastructure, strengthen ecological protection, attract foreign investment, and optimize the layout of the manufacturing industry. Enterprises can improve their treatment, improve platform construction, attract high-quality talent, and retain talent.

3.2. Analysis of the Level of High-Quality Integrated and Coordinated Development

By using a model for coupled and coordinated development, the degree of coupling for high-quality development was calculated. The average coupling degree of high-quality development in the eastern coastal areas was found to be 0.900, with a standard deviation of 0.096 and a coefficient of variation of 0.107. The regions with relatively high coupling degrees were mainly concentrated in urban agglomerations, such as those of Beijing–Tianjin–Hebei, the Shandong Peninsula, the Yangtze River Delta, the west bank of the Taiwan Straits, and the Pearl River Delta. On the other hand, the regions with relatively low coupling degrees were scattered and could be found in areas such as Liaoyang, Fushun, Dandong, Huludao, Yingkou, Hezhou, Chongzuo, Yunfu, Laibin, and Guigang (see Figure 2a).

Considering that the coupling degree cannot truly reflect the coupling under different development levels, the coordinated development model was used to calculate the coordination degree of high-quality development. The average coordination index of high-quality development in the eastern coastal areas was 0.577, with a standard deviation of 0.121 and a variation coefficient of 0.210. The high-value areas of the coordination index were mainly distributed in the Beijing–Tianjin–Hebei urban agglomeration, Shandong Peninsula urban agglomeration, Yangtze River Delta urban agglomeration, Pearl River Delta urban agglomeration, and some mineral-resource-rich cities in the northern coastal region. The low-value areas were concentrated in relatively underdeveloped economic areas along the eastern coast (see Figure 2b).

According to the coordination index, high-quality development could be categorized as follows (see Figure 2c): six mildly imbalanced type cities with $0.300<D\le 0.400$, mainly located in the northern part of Guangxi; 18 cities subtly imbalanced with $0.400<D\le 0.500$, mainly distributed in the northern part of Hebei, the northern part of Fujian, and the southern part of Guangxi; 48 barely coordinated cities with $0.500<D\le 0.600$, mainly distributed in underdeveloped areas within economically developed provinces and developed areas within economically developed provinces, such as southern Hebei, central–northern Jiangsu, eastern Shandong, southern Fujian, etc.; 25 mildly coordinated urban areas with $0.600<D\le 0.700$, mostly located in the edge cities of the Yangtze River Delta urban agglomeration, provincial capital cities, and some sub-central cities such as Yantai, Dalian, Jinan, Foshan, and Nanning; nine moderately coordinated cities with $0.700<D\le 0.800$, including Tianjin, Qingdao, Nanjing, Suzhou, Hangzhou, Ningbo, Xiamen, and Zhongshan; two well-coordinated cities with $0.800<D\le 0.900$, both of which are core cities within the Pearl River Delta urban agglomeration, namely, Dongguan and Zhuhai; four extremely coordinated cities with $0.900<D\le 1.000$, including Beijing, Shanghai, Guangzhou, and Shenzhen, whose innovation ability and openness level ranked among the top in the country. Therefore, while the overall level of high-quality coordinated development along the east coast of China was relatively high, there were significant regional differences within the region.

3.3. Analysis of Factors Influencing High-Quality Coordinated Development

Considering the significant importance of high-quality coordinated development in promoting regional balance and collaborative development, this study further investigates the impact mechanism of high-quality coordinated development in coastal areas by using the GWR model. Based on relevant research [19,20,32,33,34], this study selected the economic foundation (GDP per capita), government financial support (proportion of local fiscal expenditure to GDP), innovation potential (density of ordinary institutions of higher education), and agglomeration capacity (number of permanent residents per unit area) as the influencing factors of high-quality coordinated development in the eastern coastal areas.

To comprehensively compare the impacts of these four driving forces on high-quality coordinated development in coastal areas, this study first used the range standardization method to standardize the data of each indicator. The changes in economic development level, government financial support, innovation potential, and agglomeration capacity were taken as independent variables, and the change in coordination degree was taken as the dependent variable, as shown in Equation (3). Based on the “adaptive” kernel function, the AICc was minimized to make the local estimation [35]. The $R^2$ of the ordinary least squared regression model was 0.737, while in the GWR model, the $R^2$ was 0.842, indicating that the parameters estimated by the GWR model were more reasonable (Further information on the specific application of the GWR model can be found in the work of Pang et al. [28]).

As shown in Figure 3, the regression coefficient fluctuations of the factors affecting the high-quality coordinated development in the eastern coastal area in 2019 were significant, indicating heterogeneity and correlation among the research units. In terms of the degree of influence, the economic foundation, innovation potential, government financial support, and agglomeration capacity ranked from strong to weak. The specific analysis is as follows.

First, the economic foundation was a positive leading factor that affects high-quality coordinated development, and it generally presented a pattern of gradually weakening from the central coastal areas to the southern and northern coastal areas. That is, the promotion effect of the economic foundation on the high-quality coordinated development of the central coastal areas was relatively greater, while its promotion effect on the high-quality coordinated development of the southern and northern coastal areas was relatively smaller. Although, against the background of high-quality development, more emphasis is placed on enhancing the comprehensive competitiveness of the social economy and paying attention to the sustainability of the ecological environment, it is undeniable that the regional economic development foundation is still the material prerequisite for deepening high-quality development.

Second, the potential for innovation was the second biggest factor that affected high-quality coordinated development, and the regression coefficient gradually increased from the central coast to the northern and southern coasts, with a strengthening effect. The main reason is that innovation is the first driving force for development and an important factor in ensuring long-term and stable economic growth. However, there was a large gap within the coastal region in terms of innovation input intensity and technology output conversion rate, with the central coastal region significantly outperforming the northern and southern coasts. For example, in 2019, the numbers of patent applications in the central and southern coastal regions reached 700,100 and 643,800, respectively, while the number of patent authorizations in the northern coastal region was only 431,000. To narrow the gap between the northern and southern coasts and the central coastal region and to make up for their shortcomings in innovation capabilities, it is necessary to encourage the establishment of a two-way-flow mechanism for scientific and technological personnel between enterprises and research institutions, as well as to accelerate the integration of industry, academia, and research.

Third, the overall impact of the government’s financial support coefficient was positive, with an average impact coefficient of 0.080. The impact effect showed a general trend of decreasing from the coastal region to the southern region, and decreasing towards the northern region while fluctuating. Government financial expenditure helps to accelerate industrial restructuring and upgrading, improve people’s livelihoods, and promote social equity. Against the background of the new era of development and transformation, the continuous deepening of high-quality development has put forward new and higher requirements for industrial strength, innovation potential, openness, and the construction of an ecological civilization. The realization of these goals depends on the promulgation and implementation of relevant policies. For example, in the process of ecological environmental governance, we must adhere to the role of regional governments, innovate the ecological environmental governance system, and enhance the participation of residents in ecological environmental governance. In the process of industrial transfer and upgrading, we must follow the relevant provisions of policy documents, such as the “Guiding Catalogue for Industrial Transfer” (this policy document was proposed by Ministry of Industry and Information Technology of China) to avoid the illegal transfer of high-pollution and high-energy-consumption industries.

However, it is noteworthy that the negative coefficients of government financial support in some cities indicated that the implementation of their policies did not significantly promote high-quality development. This may be attributed to the fact that strong institutional guarantees and government policy support are essential for achieving high-quality development. Since the reform and opening up, China is still in the stage of gradually transitioning from a planned economy to a market economy with the basic establishment of a socialist market economic system. As such, local governments need to consistently and comprehensively deepen reforms, clearly identify key areas and directions for reforms, and continuously refine relevant institutional measures to ensure sustained and effective promotion of high-quality development.

Fourth, looking at the spatial distribution of the regression coefficients of agglomeration ability, the impact of agglomeration ability on high-quality coordinated development was manifested in two opposing effects. Its positive promotion effect was more significant in regions with good location conditions, a high level of economic and social development, and complete infrastructure, such as the Beijing–Tianjin–Hebei region, the Yangtze River Delta, the west coast of the Taiwan Straits, and the Pearl River Delta urban agglomerations. The negative hindrance effect was more significant in regions with weaker economic strength and greater economic disparities. Specifically, it may have impeded their high-quality coordinated development to a certain extent. The main reason for this is that human capital is an important manifestation of urban competitiveness, and population inflows can, to a certain extent, promote resource integration and local economic and social development [36]. Currently, the trend of factor outflow caused by the “siphon” effect and the tendency of an inflowing population to agglomerate in the central cities of urban agglomerations still continues, but there are differences in the preferences of urban agglomerations for where the inflowing population comes from. For example, some resource-based cities in the northern coastal areas prefer to flow into the Beijing–Tianjin–Hebei urban agglomeration [37].

3.4. Analysis of Factors Influencing High-Quality Coordinated Development

Identifying problem areas is a basic prerequisite for formulating and improving regional policies [38,39,40]. Based on a comprehensive measurement of the state of high-quality development and an analysis of its influencing factors, problem areas were identified. According to the evaluation criteria established by Li et al. [40], if a city met any one of them, it was defined as a problem area. The evaluation criteria included the following: (1) The Innovation Development Index was lower than 60% of the average level in coastal regions; (2) the Coordination Development Index was lower than 60% of the average level in coastal regions; (3) the Green Development Index was lower than 60% of the average level in coastal regions; (4) the Openness Index was lower than 60% of the average level in coastal regions; (5) the Shared Index was lower than 60% of the average level in coastal regions; (6) the comprehensive high-quality development index was 60% lower than the average level of coastal areas; (7) the comprehensive high-quality coordination development index was lower than 60% of the average level in coastal areas.

By using the ArcGIS 10.0 spatial query tool based on the seven aforementioned criteria, extraction and overlay analysis were performed. The results showed that there were 48 cities with a low Innovation Development Index that met the criteria (1), 13 cities with a low Coordinated Development Index that met the criteria (2), 9 cities with a low Green Development Index that met the criteria (3), 22 cities with a low Openness Index that met the criteria (4), 13 cities with a low Shared Index that met the criteria (5), 7 cities with a low comprehensive high-quality development index that met the criteria (6), and 2 cities with a low comprehensive high-quality coordination development index that met the criteria (7). Simply adding up the numbers, the total number of problem areas was 114, but because some of the seven types of problems spatially overlapped, the actual number of problem areas was 61.

The comprehensive analysis of the problem areas can be roughly divided into five categories (Figure 4). First, the problem areas dominated by lagging innovation and development, involving a total of 36 cities, were mainly distributed in Guangxi and Liaoning. There was insufficient innovation investment, and low output, and the other development indicators were also low. Second, the problem areas wree dominated by lagging coordinated development involved the three cities of Dongying, Liuzhou, and Baise, where the “dual structure” of urban and rural development was significant, and the proportion of traditional manufacturing was high. The road of industrial transformation and upgrading is relatively long. Third, the problem areas dominated by lagging green development involved only Fushun and Chongzuo, with inadequate resource continuity, a single industrial structure, and serious damage to the ecological environment. The leading role of innovation and development urgently needs to be improved. Fourth, the problem areas dominated by lagging open development involved a total of 14 cities that were mostly scattered on the provincial border cities, which had a low level of opening up to the outside world, resulting in obviously lagging innovation and coordinated development as their common characteristics. Fifth, the problem areas dominated by lagging shared development involved a total of six cities that were mainly distributed in the north of Guangdong, with some scattered in central Jiangsu and northern Fujian. Although their levels of innovative, coordinated, green, and open development were relatively high, the better and faster achievement of the fundamental goal of sharing development results with everyone is the bottleneck that must be overcome in their process of advancing to the forefront of high-quality development.

Overall, the 61 issues in cities were mainly concentrated in the southern and northern coastal areas. The common problems faced by most regions included weak innovation capabilities, difficulties in industrial transformation and upgrading, and a relatively low level of openness to the outside world. In the new era of high-quality transformation and development, these issues are prominent symptoms that urgently need to be addressed as the eastern coastal regions advance toward a high-quality economic belt.

4. Discussion and Conclusions

4.1. Conclusions

There are significant spatial differences in the development level and comprehensive index for the five systems of innovation, coordination, green development, openness, and sharing among cities along the eastern coast of China. In general, the central coastal areas perform better than the northern and southern coastal areas, and the high-value areas are distributed around urban agglomerations. High-quality coordinated development is mainly characterized by weak coordination and large internal differences. The cities with higher levels of coordinated development are mainly concentrated in the Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations, with a few scattered in provincial capital cities and sub-central cities.

The economic foundation, innovation potential, government financial support, and agglomeration capacity have different degrees of influence on the high-quality coordinated development of coastal areas. The local economic foundation and innovation potential have a more positive and stable impact on high-quality coordinated development. In contrast, the government’s financial support and agglomeration capacity demonstrate two different effects of promotion and inhibition. The higher the level of high-quality coordinated development, the better the regional economic foundation and innovation potential, and the stronger the government’s financial support and regional agglomeration capacity.

The 61 problematic cities with poor high-quality coordinated development are mainly distributed in the southern and northern coastal regions. High-quality development is a long-term and complex systematic project, and promoting coordinated development of innovation, coordination, greenness, openness, and sharing of the five systems requires both top-level design and support from relevant regional policies. In the new era of transformation towards high-quality development, it is necessary to accelerate industrial transformation and upgrading, guide the orderly transfer of some manufacturing industries, continue to increase financial investment in scientific and technological innovation, build an innovation mechanism that links enterprises and research institutes, and stimulate the potential for regional innovation development. By using the improvement of residents’ participation in governance for the ecological environment and the refinement of inter-provincial and inter-city collaborative governance and control mechanisms as a starting point, we must continue to promote the construction of an ecological civilization. In general, targeted regional policies need to be developed to address the specific problems of problem areas.

4.2. Discussion

This study preliminarily explored the patterns, coordination status, influencing factors, and problems of high-quality development in coastal areas. However, due to the difficulty in obtaining data, it is challenging to comprehensively depict the rich connotation of high-quality development, and there may be some deviations in the evaluation results of the indicator system that was constructed. In addition, spatial and temporal dynamic research on high-quality coordinated development is still an important direction that needs to be further explored.

Currently, China’s regional economic development has made remarkable achievements, and the role of the eastern coastal areas in the process of economic transformation and development is self-evident. Relying on their own advantages, the eastern coastal areas have taken the lead in achieving high-quality development, played a role in driving the development of the central and western inland areas, and optimized the spatial layout of China’s high-quality development. However, the research results also show that the unbalanced and insufficient high-quality development of the eastern coastal areas is still significant, with the main manifestation being weak coordination and large internal differences and the “problem cities” with poor high-quality coordinated development being mainly distributed in the southern and northern coastal areas. In view of this, the State Council, national ministries and commissions, etc. should focus on deepening research on the deep-seated contradictions in the economic development of the eastern regions and, by adopting scientific and feasible measures, strengthen the overall planning and guidance at the national level, break regional barriers, optimize resource allocation, and enhance the scientific layout of resources and factors at the national and regional levels.

Local governments should use their developmental positioning and comparative advantages to guide the five development concepts, create development policies, introduce necessary technology, industry, and talent, and promote regional university–enterprise cooperation. They should encourage high-tech companies to cooperate with local universities or research institutions, create high-end industry agglomeration zones and modern service industry pilot zones with strong demonstration and driving capabilities, and promote resource complementarity and regional coordination among the north, central, and south regions of the eastern coastal area [41,42]. Additionally, they should adhere to supply-side structural reform as the main line, supervise and provide services for local policy implementation, and strengthen overall planning for the “weak links” of economic development, including increasing financial support to local governments that lack talent, funds, technology, and industry.

Local governments should also tightly follow the five development concepts, formulate development policies suitable for their local conditions, introduce necessary technology, industry, and talent, promote university–enterprise cooperation, and encourage high-tech companies to collaborate with local universities. This will guide the creation of high-end industry and modern service industry zones, thus forming agglomeration advantages.