Coupling of Urban Economic Development and Transportation System: An Urban Agglomeration Case

Abstract

Urban agglomeration is a new carrier of regional economic development, whose spatial structure can be reflected by the transportation system. The coordination between urban economic development and the transportation system is conducive to promoting balanced urban economic development. As an important urban cluster of China, the Harbin-Changchun urban agglomeration plays an important role in promoting the revitalization of northeast China. Targeting 11 cities of the Harbin-Changchun urban agglomeration, this paper adopts the coupling coordination degree model to study the coordination level of urban economic development and the transportation system. The results show that large differences exist among the cities, with Changchun at the outstanding position. A more developed transportation system exists in the western Harbin-Changchun urban agglomeration, while the east is in a worse condition. The coupling coordination degree of the urban economic development and transportation system shows obvious stratification. Further adjusting the industrial structure, expanding the degree of opening to the outside world, and increasing investment in transportation technological innovation are recommended to promote an integrated development pattern in the Harbin-Changchun urban agglomeration.

1. Introduction

From the perspective of urban economic development worldwide, it is evident that cities are increasingly interconnected, the flow of production factors is accelerating, and urban economic development shows a phenomenon of grouping. An urban agglomeration is based on one or two large cities as the core of the regional economy. A transportation system is a complex dynamic system composed of different modes of transportation. An urban agglomeration is made up of several closely related cities and towns of different sizes, natures, and grades, relying on developed transportation systems and other infrastructure of different sizes and closely related cities formed by the spatial footprint of compact, close economic relations, and coordinated development of regional urban groups [1]. The transportation system is the spatial structure skeleton of urban economic development, an essential bridge for the connection and development between cities. Urban economic development and transportation are mutually dependent and closely related [2]. Therefore, coordinating the relationship between urban economic development and the transportation system has become a topic of common concern for scholars worldwide.

Transportation systems and economic developments are the foundation and premise of each other. Urban mobility significantly contributes to the achievement of the social and economic goals of cities and promotes urban economic growth [3,4,5]. Transportation networks improve the mobility of population and goods, optimize the industrial structure, improve production efficiency, and save transaction costs [6]. The faster the economy develops, the greater the city’s demand for the exchange of external resources, the more vital its aggregation and radiation capacity, and, thus, the more significant the need for transportation systems [7]. Urban economic development affects the demand for transportation system demand and investment in transport infrastructure [8].

Transportation is a derivative demand of urban economic development [9] and is influenced by economic scale, economic structure, and economic quality [10,11,12]. Its evolution is affected by accompanying economic changes and industrial structure [13]. The transportation elasticity coefficient usually describes the relationship between the urban economic development level and passenger volume and freight volume [14,15,16]. The transportation elasticity coefficient (abbreviated as E) is the ratio between the growth rate of the transportation volume and the growth rate of national economic development [17,18]. The relationship between the two is shown in Figure 1. In the early stage of industrialization, the secondary industry developed rapidly, the freight growth was higher than the economic growth rate, and the freight volume elasticity system was more significant than 1; in the middle and late stage of industrialization, the growth rate of the secondary industry slowed down, the demand for freight volume decreased, and the demand for passenger volume increased rapidly. At this time, the passenger volume elasticity coefficient is greater than 1; in the post-industrialization period, knowledge-intensive industries and service industries dominate, increasing passenger volume rapidly and putting forward new service quality and speed requirements. Fouquet nalyzed the data of Britain from 1850 to 2010 [19], and Zhang and Jin compared the passenger volume and freight volume elasticity coefficient between developed and developing countries [20]; the laws shown in Figure 1 are verified.

At the end of the 19th century, Howard designed a group of urban agglomerations, which were composed of pastoral cities around several central cities [21]. Since then, scholars have begun to study the development direction of the region from the perspective of urban agglomeration. In the process of urban agglomeration development, transportation promotes the urban economic development of urban agglomerations by promoting the layout of economic activities along the transportation route [22], and the agglomeration of production factors along the transportation route [23], forming regional economic agglomeration [24]. The extension of the transport network between cities extends the scope of economic agglomeration so that cities that are not adjacent to the urban agglomeration can also share the benefits of economic agglomeration [25].

The coupling relationship between urban economic development and the transportation system is manifested as a benign in-order development process. Coupling is a concept in physics, commonly used to express the matching degree between two or more systems [26]. The higher the coupling degree is, the better the linkage effect between subsystems is, which helps to promote the overall optimization of the system. At the same time, subsystems enable each other and develop in coordination. The measurement methods of coupling coordination economic level between systems include the Node-place model, grey correlation analysis (GCA), and the coupling coordination degree model (CCD). The research methods have their own advantages and disadvantages [27], suitable for different research fields. The Node-place model proposed by Bertolini is important in studying the degree of matching transportation systems with urban economic development [28,29]. Groenemeijer applied the Node-place model to examples [30]. The model takes the station as the core of the transportation network [31,32,33]. After that, the Node-place was expanded in terms of the research scope and evaluation index [34,35,36]. The Node-place model is mainly used to study the matching of public transportation and urban economic development with node attributes such as subway stations, passenger stations, and railway stations [37,38,39]. Grey correlation analysis (GCA) is used to identify the correlation between uncertain factors [40]. It is challenging to deal with indicators’ positive and negative effects [41]. The quantitative calculation results are nonstandard and inconsistent, which makes it easy to produce an ordinal impact [42].

The coupling coordination degree model is often used to evaluate the relationship between two or more systems [43]. A greater degree of coupling coordination indicates that the relationship between subsystems tends to coordinate from disorder to order [44,45,46]. A smaller degree of coupling coordination indicates that the relationship between subsystems tends to be separated and disordered. Compared with other models, the advantage of the coupling coordination model is that it cannot only reflect whether the system promotes each other at a higher level but can measure the development level of each subsystem. At present, the coupling coordination degree model has been widely used in urban economic development and environmental quality evaluation [47,48,49], land use and urbanization [50,51], urban agglomerations, industrial clusters [52,53], and so on. Scholars are studying transportation and regional economy using the coupling coordination degree model [54,55,56]. In particular, Chinese scholars have conducted many studies on the coupling relationship between provincial and municipal urban economic development and transportation in China [57,58].

When developed in synchrony, urban economic development and transportation system can promote each other and the sustainable development of cities. However, in the context of rapid economic and transportation growth, whether the transportation system can meet the needs of urban economic development and boost high-quality urban economic development, as well as the coupling and coordination of urban economic development and transportation systems, need to be further explored. The development level of the transportation system usually uses transportation accessibility, passenger turnover, and freight turnover as evaluation indexes, but the single index cannot fully measure the development level of regional transportation. Therefore, this study improves the evaluation index, on the one hand, from the three aspects of the economic scale, economic structure, and economic quality, combined with the entropy weight method to assign a weight, to comprehensively evaluate the degree of urban economic development. Accordingly, we refer to Jin et al.and Chen et al. to comprehensively evaluate the economic support of urban transportation systems from three aspects: transportation quantity, transportation quality, and transportation potential [59,60]. Previous studies did not specifically study the northeast region of China. The particular geographical location and unique urban economic development characteristics of the northeast region give the Harbin–Changzhou urban agglomeration at the medium level of development in China a strong regional representation. The coupling coordination degree model is more and more widely used. We have tried to improve the evaluation index to optimize the model. Taking urban agglomerations as an example, we comprehensively analyze the coupling coordination degree of transportation and urban economic development, providing specifically the developments of urban agglomerations and transportation planning in other countries or regions.

2. Methods

For a clear understanding of the research procedures, a roadmap of this study is presented in Figure 2. Firstly, the overall level of urban economic development is calculated from three aspects: economic scale, economic structure, and economic quality. Then, the development level of the urban transportation system is considered from three aspects: ‘quantity’, ‘quality’, and ‘potential’. Finally, based on a coupling coordination degree model, the comprehensive coupling level between urban economic development and the transportation system development is explored.

2.1. Quantification of the Overall Urban Economic Development Level

The composition of overall urban economic development is complicated, and it is difficult to comprehensively evaluate the economic development of urban agglomerations simply by using gross domestic product (GDP) as the standard to measure the level of urban economic development. Therefore, this paper adopts a comprehensive evaluation system to comprehensively evaluate the level of urban economic development. Based on research and combined with the actual situation [55,61,62], we constructed an evaluation system of 11 indicators of economic scale, economic quality, and economic structure to measure and evaluate the level of urban economic development. In this paper, the entropy weight law is adopted to avoid the subjectivity of artificial weighting. The specific calculation method is as follows:

First, we standardize the positive and negative indicators in the urban economic development system to facilitate comparability:

$$Z_{ij}=\left\{\begin{array}{c}\frac{x_{ij}-\min \left(x_{ij}\right)}{\max \left(x_{ij}\right)-\min \left(x_{ij}\right)}, if x_j is a positive \\ \frac{\max \left(x_{ij}\right)-x_{ij}}{\max \left(x_{ij}\right)-\min \left(x_{ij}\right)}, if x_j is a negative\end{array}\right.$$

(1)

where $x_{ij}$ is the value of index j (j = 1, 2, …, m) of region i (i = 1, 2, …, n), $\max \left(x_{ij}\right)$ and $\min \left(x_{ij}\right)$ are the maximum and minimum values of $x_{ij}$, respectively, and $Z_{ij}$ is the standardized value.

We use the entropy weight method to empower urban economic development indicators. Firstly, we determine the information entropy of indicator j, where:

$$E_j=-\frac{1}{\ln n}{\displaystyle \sum }_{i=1}^n{p}_{ij}\ln p_{ij}$$

(2)

among them, $p_{ij}$ is the sample index weight, and $p_{ij}=\raisebox{1ex}{$Z_{ij}$}\!\left/ \!\raisebox{-1ex}{${\sum }_{i=1}^n{Z}_{ij}$}\right.$. Notably, we assume that if $p_{ij}=0$, then $\underset{p_{ij}\to 0}{\lim }{p}_{ij}\ln p_{ij}=0$.

According to information entropy, the entropy weight of index j is calculated as follows:

$$w_j=\frac{1-E_j}{{\sum }_{j=1}^m\left(1-E_j\right)}$$

(3)

The calculation formula of the urban economic development level is as follows:

$$F_i={\displaystyle \sum }_{j=1}^m{w}_j\times Z_{ij}$$

(4)

where F_i is the urban economic development level of i city; the higher the score of the urban economic development level is, the higher the level of urban economic development is. $w_j$ is the weight of the j index obtained by the entropy weight method; $Z_{ij}$ is the index value of j item of i city after standardization.

2.2. Quantification of the Transportation System Level

This paper has modified the model according to the actual data and regional characteristics. The road network density is represented as “quantity”, representing the economic support capacity of the transportation system in the region. Time accessibility represents the “quality” of transportation and serves as the index of the convenience of out-of-area contact. Secondly, the transportation location is the high incidence place of the transportation phenomenon in geography. Economic accessibility represents the ‘potential’ of the transportation system, indicating the regional transportation location advantage. The transportation location advantage is closer to the demand of urban economic development. Finally, the comprehensive index of transportation system development level is used to measure the development level of the transportation system of urban agglomeration.

2.2.1. Traffic Network Density

The traffic network density refers to the length of various traffic routes to the area. The greater the density of the regional transportation network, the more it can support the development of the regional economy. The impact of the railway on regional transportation is more reflected in the selection of stations. At the same time, the water traffic in the Harbin-Changchun urban agglomeration is greatly affected by climate and underdevelopment. As the density of air routes is difficult to measure, the road network density is selected in this paper to measure the internal transportation level of the region.

$$R_i=L_i/S_i$$

(5)

where $R_i$ represents the density of the i city’s road, $L_i$ represents the length of the i city’s road, and $S_i$ represents the land area of the i city.

2.2.2. Time Accessibility

Time accessibility refers to the ease of transportation from one city to other cities in the region. This paper selects the time accessibility of road and railway to comprehensively evaluate the urban transportation convenience.

$$A_i={{\displaystyle \sum }}_{i=1}^n\raisebox{1ex}{$T_{ij}$}\!\left/ \!\raisebox{-1ex}{$N$}\right.$$

(6)

where, $A_i$ is the time accessibility of city i and is the shortest time from city i to city j, which is subject to the shortest arrival time of railway (including high-speed railway) and highway use. $T_{ij}$ is the shortest time from city i to city j, and N is the total number of cities.

2.2.3. Economic Accessibility

Economic accessibility is used to measure the urban transportation location conditions. The advantage degree of urban transportation system location is affected by the city’s external economic radiation ability and urban transportation system agglomeration ability. The stronger the two effects of radiation and agglomeration, the greater the urban transportation location advantage. Therefore, this paper uses the gravity model to measure economic accessibility. The measurement method is:

$$H_i=\frac{1}{n-1}{\displaystyle \sum }_{i=1,j=2}^{n-1}\left(\sqrt{P_i{G}_i}\ast \sqrt{P_j{G}_j}\right)/D_{ij}^2$$

(7)

where $H_i$ is the economic accessibility of city i. The greater the economic accessibility, the more obvious the location advantage of the city. $P$ is the total population of the city, $G$ is the GDP of city, $D$ is the straight-line distance between city i and city j, which is calculated by the longitude and latitude of the city government.

2.2.4. Transportation System Development Level

The above methods obtain the traffic network density, time accessibility, and economic accessibility. First, the dimensionless processing is carried out, and then the weighted sum of the indicators is carried out:

$$K_i=a{R}_i^{\prime }+b{A}_i^{\prime }+c{H}_i^{\prime }$$

(8)

where $K_i$ is transportation system development level (TAD), the greater $K_i$ indicating that the regional transportation location advantage is more obvious. a, b, and c are the weights of the road network density, time accessibility, and economic accessibility, respectively. This paper considers that the regional-external and -internal transportation system is equally important, so the weight is a = b = c = 1/3.

2.3. Coupling Coordination between Urban Economic Development and Transportation System

Urban economic development and the transportation system have the coupling relationship of mutual influence and adaptation. The two systems will develop from the disordered state to the orderly state when reaching the critical value. The coupling and coordination of the two systems determine the development trend [63]. The coupling coordination degree model can reflect the measurement model of the coupling coordination degree and state among subsystems [56]. Therefore, this paper uses the coupling coordination degree model to analyze the interactive relationship between urban economic development and transportation system. Therefore, this paper uses the coupling coordination degree model to analyze the interactive relationship between urban economic development and the transportation system. The model is as follows [64]:

$$C_i=2\sqrt{\frac{F_i\times K_i}{{\left(F_i+K_i\right)}^2}}$$

(9)

$$S_i=\alpha F_i+\beta K_i$$

(10)

$$D_i=\sqrt{\left(C_i+S_i\right)}$$

(11)

$D_i$ is the coupling coordination degree of urban economic development and the transportation system, which ranges from 0 to 1. The critical value of coupling coordination degree is 0.5. $F_i$ is the urban economic development level of i city, and $K_i$ refers to the transportation system level of i city. $\mathsf{\alpha }$ and β are the weights of the two subsystems. Generally speaking, we believe that urban economic development and the transportation system are equally important, so the weights are 0.5. The coupling coordination degree is mainly divided into ten types in

Table 1. Classification of coupling coordination degree.

CCD	Coordination Type	CCD	Coordination Type
0.000–0.100	Extreme imbalance	0.501–0.600	Reluctant coordination
0.101–0.200	Severe imbalance	0.601–0.700	Primary coordination
0.201–0.300	Moderate imbalance	0.701–0.800	Intermediate coordinate
0.301–0.400	Slight imbalance	0.801–0.900	Well coordination
0.401–0.500	Approaching imbalance	0.901–1.000	High coordination

CCD stands for the coupling coordination degree.

.

In order to analyze the causes of the coupling coordination type, this paper uses the relative development degree model to evaluate the relative development of transportation subsystem and economic subsystem; the formula is as follows:

$$R_i=\frac{K_i}{F_i}$$

(12)

where, $R_i$ is the relative development degree (RDD) of i city transportation and economic subsystem. According to the concept of traffic first, the construction cycle of transportation infrastructure is long, and transportation construction can effectively promote regional urban economic development. Therefore, this paper divides the relative development degree into three types. When RDD < 0.8, the urban transportation system lags behind urban economic development, which is not conducive to sustainable regional growth. When 0.8 < RDD < 1.2, the city is in a state of simultaneous development of transportation and economy. When RDD > 1.2, the transportation system is ahead of the urban economic development, and the transportation system may appear to be a redundant phenomenon.

3. Study Area and Data

3.1. The Harbin-Changchun Urban Agglomeration

Harbin-Changchun urban agglomeration is an important part of the urban landscape in northeast China. It is located in the national “two horizontal and three verticals” urbanization strategic pattern and the northern end of the vertical axis of the Beijing–Harbin–Guangzhou corridor. It plays an important role in promoting new urbanization construction and urban economic development. The Harbin-Changchun urban agglomeration consists of 11 cities, including Harbin, Daqing, Qiqihar, Suihua, Mudanjiang, Changchun, Jilin, Siping, Liaoyuan, Songyuan, and Yanbian Korean (Yanbian), a core area of about 511,000 m². The core cities of the Harbin–Changzhou urban agglomeration have a high population absorption capacity and high population agglomeration. In 2019, the total population of the Harbin-Changchun urban agglomeration was about 46.19 million. The urban economic development level of the Harbin-Changchun urban agglomeration is medium in 19 urban agglomerations in China. In 2019, the total GDP of the Harbin-Changchun urban agglomeration was CNY 2085.31 billion, accounting for 2.1% of the total GDP of the country and 82.30% of the total GDP of Heilongjiang Province and Jilin Province. Under this background, understanding the characteristics and coupling relationship between urban economic development and the transportation system of the Harbin-Changchun urban agglomeration can provide a reference for optimizing the regional resource allocation and formulating transportation planning in other urban areas.

3.2. Data Presentation

The overall urban economic development levels of 11 cities in the Harbin-Changchun urban agglomeration were quantified. Because Changchun City will be under the jurisdiction of Gongzhuling in 2020, and due to the impact of COVID-19, the economy has experienced outliers, which are incomparable to other years, so this study selected 2019 data to study. The data sources for the variables are described in

Table 2. Data sources for the variables. GDP is gross domestic product.

Variables		Data Sources
Urban economic	Per capita GDP	China City Statistical Yearbook [65]
	GDP growth rate	China City Statistical Yearbook and Statistical yearbooks for each city [66,67]
	General budgetary financial revenue	China City Statistical Yearbook and Statistical yearbooks for each city
	Total import and Export	China City Statistical Yearbook
	Total Retail Sales of Consumer Goods	China City Statistical Yearbook
	Annual per capita disposable income of Urban residents	China City Statistical Yearbook
	Annual per capita disposable income of Rural residents	Statistical yearbooks for each city
	Number of hospital beds per thousand people	China City Statistical Yearbook
	Ratio of value-added of secondary Industry in GDP	China Statistical yearbooks for each city
	Ratio of value-added of three Industries in GDP	Statistical yearbooks for each city
Transportation systems	GDP	Statistical yearbooks for each city
	Total population at the end of the year	China City Statistical Yearbook
	Land area	National Platform for Common Geospatial Information Services
	Road length	National Platform for Common Geospatial Information Services [68]
	The shortest arrival time	12306 China Railway [69]

.

4. Results and Discussion

4.1. Overall Urban Economic Development Level

The index weight of the urban economic development level results is shown in

Table A1. Index weight of urban economic development level.

Variable	Category	Unit	Weight
Economic size 0.587	Per capita GDP	CNY	0.127
	GDP growth rate	%	0.058
	General fiscal revenue	CNY 10,000	0.130
	Import and Export volume	CNY 100 million	0.190
	Total Retail Sales of Consumer Goods	CNY 10,000	0.154
Economic quality 0.189	Per capita disposable income of urban residents	CNY	0.057
	Per capita disposable income of rural residents	CNY	0.063
	Number of hospital beds per thousand people		0.118
Economic structure 0.225	Proportion of added value of secondary industry in total output value	%	0.057
	Proportion of added value of three industries in total output value	%	0.046

in Appendix A. At the same time, we calculated the urban economic development degree of the Harbin-Changchun urban agglomeration (see

Table A2. Urban economic development level of Harbin-Changchun urban agglomeration in 2019. EDD, EOS, EEQ, and EES denote the urban economic development level, economic size, economic quality, and economic structure.

City	Ranking	Urban Economic Development Level	Economic Size	Economic Quality	Economic Structure
Changchun	1	0.700	0.565	0.084	0.052
Jilin	6	0.178	0.090	0.045	0.043
Siping	8	0.113	0.066	0.026	0.021
Songyuan	9	0.083	0.033	0.010	0.040
Liaoyuan	11	0.075	0.043	0.011	0.022
Yanbian	7	0.143	0.089	0.009	0.045
Harbin	3	0.583	0.405	0.145	0.033
Qiqihar	5	0.179	0.103	0.055	0.021
Mudanjiang	4	0.224	0.149	0.049	0.026
Daqing	2	0.625	0.514	0.053	0.057
Suihua	10	0.077	0.048	0.026	0.002

in Appendix A). The natural breakpoint method was adopted to divide the urban economic development level of the Harbin-Changchun urban agglomeration into four levels. The result is shown in Figure 3.

The urban economic development level of Harbin-Changchun urban agglomeration presents a pyramid shape, with only Changchun at the top of the tower and a large number of cities in the low level of development. Except for the core cities, the urban economic development of the central axis of the Harbin-Changchun urban agglomeration is at a lower level in the region. The average score of the urban economic development level of the Harbin and Changchun city group is 0.271, and the highest score of the Changchun city group is 0.700. Songyuan City has the worst level of urban economic development, and its urban economic development degree is only 0.075, indicating an apparent polarization phenomenon.

The level of urban economic development in Harbin-Changchun urban agglomeration is obvious. In Changchun, as the capital of Jilin Province, the level of urban economic development is much higher than in other cities. Economic scale contributes most to the urban economic development of Changchun. The second level of cities is an important old industrial base in northeast China, with a strong foundation for urban economic development, including Daqing and Harbin. The third level cities include Mudanjiang, Qiqihar, Jilin, and Yanbian Korean (Yanbian). The level of urban economic development at the third level has obvious stratification with that at the second level. The fourth-level cities are Siping, Liaoyuan, Suihua, and Songyuan, and the level of urban economic development is at a low level. This level of cities has insufficient domestic demand, a low degree of opening up, and other issues. In conclusion, the spatial distribution of the urban economic development level of the Harbin-Changchun urban agglomeration is not balanced, and the urban primacy effect is obvious. The urban economic development level of Changchun is far higher than that of other cities in the urban agglomeration. The urban economic development level of the main axis of the urban agglomeration development is low (except the core city).

4.2. Transportation System Level

The overall performance of the traffic network density in the Harbin-Changchun urban agglomeration is good, with an average of 1.84 km/km². In the east, the traffic network density is low. Qiqihar’s traffic network density is the highest, reaching 2.02 km/km². Daqing has the lowest traffic network density, at only 1.70 km/km². From spatial distribution, the traffic network density in the midwest is slightly higher than that in the eastern cities. The first reason is that the central and western regions are located in the Sonnen Plain, with flat and low road construction costs and low technical requirements. Secondly, Mudanjiang and Yanbian each have a large area with a relatively low population density and a low demand for transportation. However, with the continuous expansion of the openness of the Harbin-Changchun urban agglomeration, the demand for transportation in the two cities is proliferating.

The time accessibility of the Harbin-Changchun urban agglomeration is 186.6. As an important industrial base, Qiqihar has a high traffic network density and good traffic infrastructure, so the time accessibility is the highest, at 115.2. The time accessibility is greatly affected by high-speed rails. Suihua does not have a high-speed rail, and there are fewer railway lines. The external transportation system is mainly dependent on highway transportation. Therefore, Suihua has poor time accessibility, at 253.6. Suihua to Harbin mainly depends on the He–ha Expressway, which takes 2 h and 40 min. However, in 2019, Heilongjiang planned to build a passenger dedicated line, which will greatly improve the time accessibility of Suihua time.

The economic accessibility of the Harbin-Changchun urban agglomeration is 199; the proportion of each interval is similar, but the polarization phenomenon is obvious. From the perspective of spatial distribution, the time accessibility of the Harbin-Changchun urban agglomeration performs well in the development axis. Changchun and Harbin are at the first level, with a time accessibility of 481 and 480, respectively. From the perspective of the spatial distribution, the time accessibility of the Harbin-Changchun urban agglomeration shows a decreasing distribution of external radiation levels with Changchun–Harbin as the core. High values are mainly distributed in the central circle, including Changchun and Harbin. The economic accessibility value of the Harbin-Changchun urban agglomeration is mainly in the median range, which is mainly distributed in the cities near the central circle, and the low value is mainly distributed in the eastern cities far from the central circle.

The transportation system development level is a comprehensive index reflecting urban transportation system conditions. There are significant differences in the transportation system development level within the Harbin-Changchun urban agglomeration, and the polarization phenomenon is obvious (

Table A3. Transportation system development level of Harbin-Changchun urban agglomeration in 2019.

City	Traffic Network Density	Time Accessibility	Economic Accessibility	Transportation System Development Level
Changchun	1.95	119.8	480.91	0.9160
Jilin	1.91	191.0	253.00	0.5352
Siping	1.79	163.1	148.19	0.4003
Songyuan	1.86	139.8	80.618	0.4797
Liaoyuan	1.82	237.3	126.34	0.2368
Yanbian	1.78	246.1	27.715	0.1014
Harbin	1.74	153.5	479.81	0.6153
Qiqihar	2.02	115.2	99.01	0.7191
Mudanjiang	1.84	201.0	41.09	0.2824
Daqing	1.70	232.2	213.53	0.1882
Suihua	1.78	253.6	242.45	0.2413

in Appendix A). Changchun is the city with the best level of internal and external transportation construction, and its transportation system development level reaches 0.916. The Yanbian transportation system’s performance is poor and its development level is only 0.101, with the difference between Changchun being 0.815.

The first category is excellent transportation conditions; Changchun is the only city of this kind (see Figure 4). Changchun has a large traffic network density and good road network conditions, which are conducive to the flow of materials in the city, reduction in transport costs, and improvement of transport efficiency. At the same time, the time accessibility of Changchun is the fastest, which shows that it can conveniently reach the Harbin-Changchun urban agglomeration and has superior external transportation conditions. The second category is regions with good transportation conditions, including Qiqihar, Harbin, and Jilin. The third category is the general area of transportation conditions, including Siping and Liaoyuan. Liaoyuan’s road network density and transportation capacity are strong, but its lack of a motorway or high-speed rail means that the development of an external transportation system is largely restricted, so the overall transportation system environment performance is decreased. Other cities’ road network density and external transportation system convenience are not prominent in the Harbin-Changchun urban agglomeration. The fourth category is poor transportation conditions, which includes the cities of Mudanjiang, Songyuan, Daqing, Suihua, and Yanbian. Mudanjiang’s and Yanbian’s terrains are more complex, including mountainous areas, and road network coverage is low. At the same time, Mudanjiang and Yanbian are far away from the core city, the economic radiation ability is poor, and the economic accessibility is at a low level.

4.3. Coupling Coordination Degree

The Harbin-Changchun urban agglomeration’s economic development and transportation system have obvious stratification. According to

Table 3. Coupling coordination degree of urban economic development and transportation system in Harbin-Changchun urban agglomeration in 2019.

City	CCD	RDD	Coordination Type	Characteristics
Changchun	0.895	1.308	Well coordination	A
Jilin	0.556	3.007	Reluctant coordination	A
Siping	0.461	3.551	Approaching imbalance	A
Songyuan	0.447	5.750	Approaching imbalance	A
Liaoyuan	0.365	3.156	Slight imbalance	A
Yanbian	0.347	0.711	Slight imbalance	C
Harbin	0.774	1.055	Intermediate coordinate	B
Qiqihar	0.599	4.011	Reluctant coordination	A
Mudanjiang	0.502	1.258	Reluctant coordination	A
Daqing	0.586	0.301	Reluctant coordination	B
Suihua	0.369	3.134	Slight imbalance	A

CCD and RDD denote the coupling coordination degree and the relative development degree. A, B, and C denote the transportation system ahead of urban economic development, urban economic development, and the transportation system level matching, and the transportation system lags behind urban economic development.

, the types of CCD are mainly divided into five categories, namely, slight imbalance, approaching imbalance, reluctant coordination, intermediate coordinate, and well coordination. The coordinated cities mainly include Changchun, Jilin, Harbin, Mudanjiang, and Daqing, and the coupling coordination degree fluctuates between 0.5–0.9. The urban economic development level of these cities has reached a certain height, and the transportation infrastructure can support their urban economic development. Changchun achieves benign coordination, and the coupling coordination degree is 0.895. The transportation system is moderately ahead of the urban economic development, which benefits overall urban economic development. Changchun’s transportation system and economic development achieve a high level of coordination. The coupling coordination degree of Harbin is at the stage of well coordination, at 0.774. Both the transportation system and economic systems are developed to a high level. The transportation system strongly supports Harbin’s urban economic development, and the economy effectively drives the further development of the transportation system. Other cities in the Harbin-Changchun urban agglomeration are imbalanced, and the coupling coordination degree is between 0.3–0.5. The urban economic system and transportation system need to be further improved.

Liaoyuan, Yanbian, and Suihua belong to the slight imbalance stage. This is due to the transportation system advantage being far higher than the urban economic development level, indicating that the urban transportation system development is good, but that there is a low level of urban economic development. The transportation infrastructure construction investment is too much and causes crowding out to other production sector investments, and the transportation system is redundant and not conducive to urban economic development (see Figure 5). The coupling coordination degree of Yanbian is the lowest, at 0.347, which is in the stage of slight imbalance. At this stage, the rapid growth of the urban economy requires the supply of many production factors, and the transportation system conditions cannot meet the actual urban economic development needs. Therefore, it is necessary to increase the transportation system construction in Yanbian and promote the coordinated development of the two systems.

Combined with the relative development index, it can be seen that most cities in the Harbin-Changchun urban agglomeration are at the transportation system development level of most cities in a leading state. From the perspective of spatial distribution, the relative development degree of the Harbin-Changchun urban agglomeration is low in the east but high in the west. The western cities’ transportation system development is ahead of their urban economic development, while the eastern cities’ transportation system development is behind their urban economic development. This is due to differences in geographical conditions and historical development conditions. Yanbian has the most severe imbalance, followed by Mudanjiang. One of the important reasons why Yanbian’s transportation system lags behind urban economic development is the difficulty and high cost of mountain and forest transport infrastructure construction. The government has accelerated the construction of transportation infrastructure, building high-speed rail in Mudanjiang and Yanbian in December 2015. However, in the early stages of transport infrastructure construction, a specific time was needed to adapt to the economic impact, which was not directly reflected in the current period. At the same time, the road network density and economic radiation capacity of the two cities are weak, so the transportation system is still restricting the urban economic development of Yanbian. Transport infrastructure construction should be accelerated to support its urban economic development. The city in the transportation system advance should develop its economy energetically, cause transportation demand, and promote a good match between transportation and economic development. Harbin is in the stage of synchronous development of transportation and economy, so it is necessary to plan the transportation network, optimize the transportation service, and guide the urban economic development.

5. Conclusions and Policy Implication

5.1. Conclusions

A better understanding of the interaction between urban economic development and the transportation system helps to achieve urban economic development. A city group is a collection of urban economic development cities; it is the agglomeration of economic and social factors. This paper attempts to construct an evaluation system for the urban economic development and transportation system of 11 cities in Harbin–Changzhou urban agglomeration, and uses the coupling coordination degree model to analyze the interaction between urban transportation and economic, drawing the following conclusions:

(1) Economic development shows apparent polarization. The economic development level of the Harbin-Changchun urban agglomeration spreads outward with Changchun as the core. Except for Changchun and Harbin, the economic development of the Harbin-Changchun urban agglomeration is at a low level in the region.

(2) There are differences in the level of development of the transportation systems in the Harbin-Changchun urban agglomeration. From the supportability of the transportation system to the urban economic development, namely, the quantitative index, the average road network density is greatly affected by terrain, showing the characteristics of being high in the central and western regions and low in the eastern region. From the perspective of the convenience degree of external communication, namely, the quality index, the spatial distribution of time accessibility is random, and whether the high-speed trains/bullet trains are connected or not has a significant indigenous impact on time accessibility. From the perspective of the transportation location advantage, namely, the potential index, economic accessibility spreads outward, with Harbin-Changchun as the core.

(3) The coupling coordination degree of the transportation system and urban economy in the Harbin-Changchun urban agglomeration is low. Only 54.55% of the cities in the urban agglomeration are at the coordination level, and the economy and transportation of these cities have formed an orderly positive interaction. However, nearly half of urban transportation and economic development are uncoordinated.

(4) From the distribution of coupling coordination types, the Harbin-Changchun urban agglomeration does not form spatial agglomeration, and the distribution of various types is relatively scattered and irregular.

(5) Combined with the relative development index, it is found that most cities in the Harbin-Changchun urban agglomeration area are in a state of transportation advance. Moderately advanced transportation systems can promote economic development, but excessively advanced transportation systems will also hinder urban economic development. The relative development degree between Songyuan and Qiqihar is less than 4, which accumulates the city’s investment in other economic sectors, leading to the coupling coordination degree of the whole city in reluctant coordination.

5.2. Policy Implication

Adjusting the industrial structure and opening it wider to the outside world is recommended. Central cities and surrounding cities may rely on the construction of intercity channels to achieve upstream and downstream industrial agglomeration. For cities whose urban economic development lags behind the development level of transportation systems, politicians can consider expanding the level of opening up, improving urban radiation capacity, and promoting urban economic development.

Investment in transportation science and technology innovation should be increased. For cities with a backward urban economic development of transportation systems, decision-makers can consider increasing investment in transportation technology innovation, reducing the cost of transportation infrastructure construction, promoting the development of the transportation industry, and forming the network structure of urban agglomerations as soon as possible.

The government may reasonably arrange transportation infrastructure network construction to build inter-city transportation integration. Urban agglomeration development requires passenger transportation to achieve “zero distance” transfer and a seamless rapid freight service system. Decision-makers can take the interconnection of the urban infrastructure as the goal, expand the road network coverage, promote the construction of transportation information, and improve the quality of the transportation service.