sustainability

Article
Sustainable Urbanization Synergy Degree
Measures—A Case Study in Henan Province, China
Leilei Jiao, Fumin Deng and Xuedong Liang *
The Economy and Enterprise Development Institute, Sichuan University, Chengdu 610065, China;
2015225025013@stu.scu.edu.cn (L.J.); dengfm@scu.edu.cn (F.D.)
* Correspondence: liangxuedong@scu.edu.cn; Tel.: +86-028-8541-5581

Received: 11 November 2017; Accepted: 19 December 2017; Published: 21 December 2017

Abstract: Sustainable urbanization emphasizes properly handling the relationships between people,
people and society, and people and nature in the process of urban development. However, sometimes
these interactions are difficult to quantify. Through an analysis of the structure and functions
of the sustainable urbanization system, this paper introduced synergetic theory and constructed
a sustainable urbanization synergy system (SUSS) with five subsystems; demographic change,
economic development, spatial structure, environmental quality, and social development; to study
the synergistic development and orderly evolution trend of the sustainable urbanization composite
system. Using sustainable urbanization in Henan province as an example, a mathematical quantitative
model was established to measure the subsystem order degrees and the composite system synergy
degree from 2006 to 2015. The results were consistent with the actual situation and indicated
that over time, sustainable urbanization in Henan developed towards a more harmonious and
orderly state, though the overall synergy degree was not high. It was found that the model was
a sound basis for scientific judgment and effective decision-making when seeking to coordinate
sustainable urbanization.

Keywords: sustainable urbanization; order degree; synergy degree; CRITIC method; Henan province

1. Introduction
Urbanization is an inevitable trend of social development that is booming rapidly in all parts of the
world, especially in developing countries [1], and it has been identified as one of the most important
development strategies in the twenty-first century [2]. Since the implementation of the “Reform and
Opening-Up” policy in the late 1970s, China has been experiencing rapid urban development [3,4],
which has led to an expansion in urban spaces, enlarged city scales, and lifestyle changes, and has
enhanced economic development, improved people’s living standards and resulted in many other
visible benefits [5,6]. However, due to a lack of rational collaborative planning, the rapid and
disordered economic development, industrialization and urbanization processes have resulted in
various environmental and social problems—air and water pollution, resource depletion, reductions in
biodiversity, chaotic and dysfunctional urban space, traffic congestion, disordered urban morphological
structure, social conflicts, unbalanced development and land shortages [7,8]—all of which have
restricted the healthy development, reduced the quality and affected the overall level of urbanization.
To address these challenges, focus needs to be placed on improving the quality of urbanization and
developing sustainable urbanization practices [9,10].
Sustainable urbanization requires that urban development satisfy the ecological, economic,
and societal needs in an urban space [11,12] and also considers the demands of future generations;
that is, sustainable urbanization is focused on the coordinated development of the population,
the economy, urban spaces, the environment, and the overall society under geographical conditions

Sustainability 2018, 10, 9; doi:10.3390/su10010009 www.mdpi.com/journal/sustainability

Sustainability 2018, 10, 9 2 of 19

and development direction restrictions. In other words, sustainable urban development involves a
rational distribution within the urban space, steady economic growth, ecological stability, reasonable
population density, and improved social security. Therefore, to achieve these development goals,
it is necessary to take an ecological, intensive, open, and synergetic sustainable urban development
path [13].
The evaluation of urban development quality and the exploration of evolutionary trends of
sustainable urbanization can be helpful in rational collaborative planning of urbanization [14].
To effectively measure the sustainable urbanization situation, and ensure the coordinated and orderly
operation of a sustainable urbanization composite system, in this paper, synergetic theory and the
CRITIC method are introduced to allow for the measurement of sustainable urbanization and ensure
the sustainable urbanization composite system is coordinated and orderly. The main processes in
this study are as follows. First, an order parameter system for the sustainable urbanization synergy
system is developed based on previous research results, after which, a quantitative analysis model is
established based on synergetic theory. The subsystem order degree and composite system synergy
degree are then analyzed to study the degree of sustainable urbanization within the system.

2. Literature Review

2.1. Research on Sustainable Urban Development

Urbanization and the accompanying social developments have meant that the interrelationships
and interactions between society and the environment have become increasingly complex.
Many studies have focused on sustainable urban development with the aim of finding solutions to
unfavorable urbanization planning so as to provide new urbanization paths, which can be summarized
from three perspectives:

(1) Analyses of the changes brought about by urbanization. Srinivasan et al. [15] studied the
relationship between urbanization and water resource vulnerability in a fast-growing city and
found that some generalizable factors exist in the highly site-specific link between urbanization
and water vulnerability, for which some feasible suggestions on water resource vulnerability
were offered. Shen et al. [16] examined the link between urbanization and resource utilization and
predicted that as there was going to be an increased demand for energy and mineral resources
for China’s continuing urbanization plans up till 2050, the government sector needed to review
and improve existing resource utilization and environmental policies to ensure sustainable urban
development. Li and Ma [17] established environmental quality indices for 30 administrative
regions in China from 2003 to 2011, and employed panel data analyses to explore the relationships
between the urbanization rate, economic development, and environmental change, with the
results revealing an inverted-U-shaped relationship between the urbanization rate and regional
environmental quality changes, and a “turning point” at around a 60% urbanization rate.
Zhang et al. [18] studied the effects of industrial structure, infrastructure development, land
use changes, and income on sustainable urban development, and found that with steady
economic growth, moderate land use changes were the key to sustainable urban development.
Dewan et al. [19] investigated the link between rapid urbanization growth and flood disasters in
Bangladesh and concluded that urbanization had a significant influence on flood occurrences.
(2) Construction of sustainable urban development measurement indices. Measurement indices play
an important role in information extraction and urbanization evaluations, however, due to
different foci and research perspectives, different scholars have utilized different indices.
Overall, in Refs. [20–22], there was a consensus that sustainable urbanization could be assessed
from economic, social, environmental, and resource sustainability perspectives. Moreover,
Jochen et al. [23] outlined thirteen suitability criteria for measuring urbanization expansion,
providing a helpful and useful reference for the systematic assessment of the consistency and
reliability of urban development metrics. To assess the urban sustainability of Chinese megacities,
Sustainability 2018, 10, 9 3 of 19

Huang et al. [24] listed eight indicators from the three dimensions of sustainability such as
an environmental performance index, a human development index, and a Gini coefficient.
Shen et al. [25] examined nine different practices using different indicators based on particular
needs, and proposed a comparative analysis across four dimensions: environmental, economic,
social, and government. Mori and Yamashita [26] selected environmental, economic, and social
indices and established a framework of city sustainability indices to assess the performance of
sustainable urbanization. All of these studies have provided valuable contributions to sustainable
urbanization indicator systems from diverse perspectives.
(3) Sustainable urbanization measures. With the advancement of urbanization, the methods,
techniques, and tools for assessing sustainable performance in the process of urbanization
have made remarkable progress. Zhang [27] proposed a bi-dimensional matrix model for
sustainable urbanization to analyze the performance of economic, social and environmental
issues at different stages of new lifecycles of urban and rural environments, providing a reference
for sustainable urbanization. Li et al. [28] analyzed panel data collected from 2000 to 2008 for
Lianyungang and established a coupling coordination degree model to measure coordination
between urbanization and the environment. Liang et al. [6] constructed a PCA-Grey-TOPSIS
model to measure sustainable urban development capacities by combining principal component
analysis with Grey TOPSIS. Thirteen cities in the Jiangsu province, China were selected as
the study object to measure their sustainable development capacity, from which the model’s
effectiveness and operability were proven. Principal component analysis (PCA) [29] and the
entropy method [30] were used to develop a sustainable urban development system evaluation
model for assessing the performance of sustainable urbanization and a range of evaluation
standards were outlined.

2.2. Summary of Previous Research

From the review and analyses of the existing sustainable urbanization research systems, several
omissions were identified.
Based on previous studies of urban development, it is clear that previous research on urbanization
has tended to primarily focus on one specific activity or one specific aspect of the economy, the
society, or the ecology; therefore, the accompanying research dimensions or perspectives were
relatively singular, and the overall synergistic effectiveness of integral urbanization was ignored.
However, the essence of sustainable urbanization is the coordinated development of the whole system,
with the core purpose being the promotion of harmony between the urban economy, the residents’
lives, the natural resources, and the ecological resources through regional co-ordination, resource
conservation, and other means [6]. Therefore, all aspects related to sustainable urbanization need
to be collectively considered to ensure that the overall development situation is accurately reflected.
Another issue in previous research is that there has been a tendency to employ qualitative analyses to
assess sustainable urbanization performances, and to examine the links between urbanization, natural
resources, and environmental impacts; therefore, as there has been a lack of quantitative research,
the depth and accuracy of the research requires improvement. In addition, most scholars focus on
the macro level, and there have been few studies on sustainable urbanization evolutionary trends or
synergetic system mechanisms.
In view of the above, by introducing synergetic theory and the CRITIC method, this paper
conducted a study of the synergetic degree of the urbanization process from the perspective of
sustainable development, and established a sustainable urbanization synergy degree model. A case
study in Henan province, China was presented, which can provide a scientific reference for guiding
the coordinated development of the level and quality of urbanization in Henan. Accordingly,
the innovations of this paper are presented from the following three aspects:

(1) On the basis of previous research, this paper developed a more comprehensive SUSS that included
demographic change, economic development, space structure, environmental quality, and social
Sustainability 2018, 10, 9 4 of 19

development. For these five subsystems, more accurate order parameters were selected to allow
for the analyses of the subsystems’ evolutionary processes. Through the determination of the
subsystem order degrees, the synergistic development level of the sustainable urbanization
composite system can be more easily analyzed.
(2) Grounded by the principles associated with a comprehensive, integrated index system,
a sustainable urbanization synergy degree measurement model was established. The CRITIC
method was used to obtain the objective weights of each order parameter, and a quantitative
analysis was then carried out using this model in order to reflect the coordination of sustainable
urbanization and understand the urbanization development status and future tendencies.
(3) From the calculation of the order parameter weights, the subsystem order degrees and
the composite system synergy degree, the coordinated development status and the orderly
evolutionary trends of sustainable urbanization system in different years were analyzed from the
perspective of time series.

3. SUSS Analysis
Synergetics was founded in 1976 by the German theoretical physicist Professor Hermann Haken,
and its basic idea is that each subsystem in the living and nonliving open system will generate
synergetic effects through nonlinear interactions under certain conditions, which makes the old
structure develop into a new ordered structural system that has undergone fundamental changes in
time, space, nature, and function. Sustainable urbanization is an open and nonlinear complex system
that encompasses society, economy, environment and other aspects [11,12] and its development process
is a self-organizing system. Healthy and orderly urban development requires each element within the
system to coordinate with and compete with each other, which was the driving force for the overall
evolution of the sustainable urbanization system. Through this drive, the system will gradually reach
an orderly state and develop in a specific direction. Therefore, the complex evolution of SUSS can be
well analyzed by synergistic theory.
In order to carry out this study, a SUSS is created first. There have been many studies on
sustainable urbanization systems. Shen et al. [20] divided the sustainable urbanization system
into four parts: economic, social, environmental and resources. Qiao and Fang [31] analyzed the
urbanization process and pointed out that urbanization is made up of four courses, namely, economic
urbanization, spatial urbanization, demographic urbanization and social urbanization. In Refs. [32,33],
researches also claimed that there were four aspects to be considered when constructing urbanization
evaluation indices: demographic, economic, social, and environmental. The above divisions based
on social structures effectively revealed the governing laws in each urbanization subsystem and the
functional relationships between the subsystems.
The SUSS evolves with the constant exchange of energy and matter with the external environment,
and at the same time, the system’s internal subsystems and factors interact with each other in a
nonlinear way. This study focuses on the regional level to probe into the synergy issues of sustainable
urbanization, so the factors considered are different from those considered by urban planning and
development. To better reflect the evolutionary characteristics of a sustainable urbanization system
and highlight the concept of sustainable development, based on theoretical and practical research
and dynamic models, this paper argues that when studying sustainable urbanization there are five
subsystems which need to be considered: the demographic subsystem, the economic subsystem,
the social subsystem, the spatial subsystem, and the ecological subsystem. The above five core
subsystems, through mutual restriction, coordination, and the interaction between these aspects, will
produce the urbanization synergy effect, that is, “1 + 1 > 2” [34], which can promote the rapid and
healthy development of urbanization. If any subsystem is in a state of being too fast or too slow,
the system will lose its synergism and gradually deviate from the equilibrium state, which is not
conducive to the promotion of sustainable urbanization. Figure 1 shows the operation mechanism of
the SUSS.
Sustainability 2018, 10, 9 5 of 19
Sustainability 2018, 10, 9 5 of 19

Figure 1. A sustainable urbanization synergy system (SUSS).

Figure 1. A sustainable urbanization synergy system (SUSS).
4. The Order Parameter System of SUSS
4. The Order Parameter System of SUSS
Urbanization from the perspective of sustainable development reflects the rational distribution of
urbanUrbanization
space, stablefrom the perspective
economic of sustainable
growth, ecological development
stability, reasonablereflects the rational
population distribution
concentration and
of urban space, stable economic growth, ecological stability, reasonable
harmonious social development. The comprehensive synergy degree measurement for sustainablepopulation concentration
and harmonious
urbanization socialnotdevelopment.
is essential The comprehensive
only to understand the complexity ofsynergy degree
the system measurement
but also for
to illustrate the
sustainableevolution.
synergistic urbanization is essential not only to understand the complexity of the system but also to
illustrate the synergistic
The construction evolution.
of an effective synergistic measurement index system, therefore, is essential to
The construction of
accurately assess the synergy an effective synergistic
degree, which meansmeasurement
that appropriateindex system,
order therefore,
parameters is essential
(indicators that
to accurately
reflect assess the trends
the evolutionary synergy anddegree, which means
urbanization that appropriate
characteristics) need to beorder parameters
identified (indicators
and selected for
that reflect the evolutionary trends and urbanization characteristics) need to
each subsystem. According to synergy theory, variables that determine the system are called order be identified and
selected for each
parameters. subsystem.
The order According
parameter to synergy
is generated by a theory, variables that
single subsystem, whichdetermine the system the
in turn dominates are
called order parameters. The order parameter is generated by a single subsystem,
behavior of each subsystem, reflecting the evolutionary trend of subsystems and composite system. which in turn
dominates
From the behavior
the analysis of each
of the many subsystem,
factors reflecting the
affecting sustainable evolutionary
urbanization trend of subsystems
and following the principlesandof
composite
science, system. From
systematicness, the analysis
operability, of the many
availability, factors affecting sustainable
and representativeness, a diagram ofurbanization and
the relationships
followinginfluence
between the principles
factorsofofscience, systematicness,
sustainable urbanizationoperability, availability,
was constructed, and in
as shown representativeness,
Figure 2.
a diagram of the relationships between influence factors of sustainable urbanization was
constructed, as shown in Figure 2.
Sustainability 2018, 10, 9 6 of 19
Sustainability 2018, 10, 9 6 of 19

+ Environmental
Population - quality +
urbanization + Construction land - - Environmental
Urban road area - +
+ + governance +
+ + +
Urban ecological + + + utilization
Space
land + Science, education

+ + and health
+
Social ++
development + Consumption of Urban planning
Employment
+ ecological
+ resources method
+ population
+ + +Waste production
Urban population
+ +
+ Scientific research
Infrastructure achievements
+
Economic capacity
construction + Medical institution
+ Living security of
Consumption level +
+ residents
+ Agricultural people to be + Environmental
The development of given non-agricultural status investment
the third industry + +
+ + + +
+ + Financial revenue+
Urbanization
+ level
Attract investment + +
Financial +
expenditures Economic growth

Figure 2. The
Figure 2. The relationships
relationships between
between influencing
influencing factors
factors of
of sustainable
sustainable urbanization.
urbanization.

Based
Based on
on the
the inter-relationship
inter-relationship analysis
analysis inin Figure
Figure 22 and
and the
the “China
“China Statistical
Statistical Yearbook”
Yearbook” and
and
the
the “Henan
“HenanStatistical
StatisticalYearbook”
Yearbook”over
overthethe
years, thethe
years, proper order
proper parameters
order werewere
parameters selected and then
selected and
athen
sustainable urbanization
a sustainable synergy synergy
urbanization degree measurement order parameter
degree measurement order system was system
parameter constructed.
was
Table 1 showsTable
constructed. the detailed
1 showsorder parameter
the detailed ordersystem of the system
parameter SUSS. of the SUSS.
The SUSS consists of five subsystems, namely, demographic change, economic development,
Table 1. Sustainable
spatial arrangement, environmental urbanization
quality, and socialorder parameter system.
development, and each subsystem can be
represented by one or more order parameters. The selection logic is as follows:
System Subsystem Order Parameters of Each Subsystem Effect
The demographic change subsystem reflects the changes in rural and urban populations.
Urban unemployment rate (%) −
As urbanization results in high internal migration from rural areas to the cities and towns, there are
Resident population in urban areas (million
upward changes in urban populations. Therefore, the urban population becomes the main factor + by
Demographic persons)
which to measure the scale of urbanization. Although the proportion of urban population has been
change Proportion of urban employment to total
the main indexes to evaluate the level of urbanization, as urbanization and urban scale expansions +
employment (%)
continue, the evaluation of population urbanization should not only be judged using this index.
Population urbanization rate (%) +
Therefore, to avoid the one sidedness of single index evaluations, the urban unemployment rate,
Sustainable Per capita GDP (Yuan) +
the resident population in urban areas, the proportion of urban employed population in the total
urbanization Tertiary Industry Proportion (%) ±
employed population, and the proportion of urban population to total population were selected as
synergy system Disposable income of urban residents (Yuan) +
order parameters for Economic
the demographic change subsystem.
Comparison of consumption levels between
The economic development subsystem is the basic foundation and motivating force− for urban
and rural
urbanization. This subsystem mainly reflects the residents
economic (rural residents
development = 1)
strength, industrial structure
optimization and industrial innovation ability which are closely related to for
Urban fixed asset investment accounted theGDP
development + of
urbanization. When the economic level ratioadvances,
(hundredwithmillion
theyuan)
convergence of occupation structure,
Spatial The urban resident per capita road area (sq. m) +
structure Urban population density (persons/sq. km) −
Sustainability 2018, 10, 9 7 of 19

income level, and education changes, rural residents’ life satisfaction will increase. Based on this,
we selected per capita GDP, the tertiary industry proportion, the disposable income of urban residents,
comparison of consumption level between urban and rural residents, and the urban fixed asset
investment accounted for GDP ratio as the order parameters of this part.

Table 1. Sustainable urbanization order parameter system.

System Subsystem Order Parameters of Each Subsystem Effect

Urban unemployment rate (%) e11 −
Resident population in urban areas (million persons) e12 +
Demographic change Proportion of urban employment to total employment
+
(%) e13
Population urbanization rate (%) e14 +
Per capita GDP (Yuan) e21 +
Tertiary Industry Proportion (%) e22 ±
Disposable income of urban residents (Yuan) e23 +
Economic development
Comparison of consumption levels between urban and
−
rural residents (rural residents = 1) e24
Urban fixed asset investment accounted for GDP ratio
+
(hundred million yuan) e25
The urban resident per capita road area (sq. m) e31 +
Urban population density (persons/sq. km) e32 −
Sustainable urbanization Spatial structure
synergy system Per capita living space of urban residents (sq. m) e33 +
Built-up areas (sq.km) e34 +
Green coverage rate of built-up areas (%) e41 +
Harmless treatment rate of municipal solid waste (%) e42 +
Environmental quality Urban sewage treatment rate (%) e43 +
Environmental governance investment (Hundred
+
million yuan) e44
Public transport standard operating vehicle numbers e51 +
Total amount of patent authorization e52 +
Gas popularization rate (%) e53 +
Social development Medical insurance numbers in cities and towns e54 +
Internet connected computer numbers per 100
+
households in cities and towns e55
Bed numbers in hospital health centers at the end of the
+
year (×104 ) e56
Note: “+” means that the index has a positive effect on the system, and “−” indicates that the index has a negative
impact on the system; “±” means having a positive effect on the system at a reasonable value.

The spatial structure subsystem explains the urban spatial conditions and the residents’ living
conditions. Urban population aggregation accelerates the demand for construction land and the use of
urban space; however, it cannot blindly expand. Sustainable urbanization needs a reasonable spatial
layout that can effectively support the development of the social economy and ensure the stability of
the ecosystem. Therefore, the order parameters selected were; the per capita living space of urban
residents, built-up areas, the urban resident per capita road area to reflect urban resident housing
levels, urban infrastructure construction, and the satisfaction degree of urbanization development.
In addition, the density of the urban population reflects the characteristics of the city’s spatial change
and land structure [14] and indicates whether the population density in the city is crowded or not and
whether the layout of space is reasonable or not. Only a moderate population density can guarantee
the space for survival and life.
The environmental quality and social development subsystems are able to measure the
urbanization development harmony and friendliness degree by considering how ecological governance
and social mechanisms influence various aspects of the residents’ lives. The green coverage rate
of built-up areas can reflect whether the green space degree of urban is narrowing, the harmless
Sustainability 2018, 10, 9 8 of 19

treatment rate of municipal solid waste and the urban sewage treatment rate both reflect the greening
level of urban ecological environments and imply an environmental cost for economic development.
The environmental governance investment explains the level of government investment required
to maintain a sustainable industrial environment. Social development order parameters, such as
transportation, gas supply, social security indicators are available, and measure the level of social
development. Public transport standard operating vehicle numbers reflect the level of urban public
facilities, the total amount of patent authorization can give expression to the level of scientific and
technological innovation, the gas popularization rate indicates the take up of clean energy, the medical
insurance numbers in cities and towns reflect social security popularization levels, the number of
Internet-connected computers per 100 households in cities and towns reflects the informatization level
of urban residents, and the bed numbers in hospital health centers at the end of the year indicates the
level of urban public health.
These five subsystems affect and interact with each other, and their interaction influences the
evolution of the entire urbanization system. The coordinated development of the five subsystems
will help to keep the entire system in an ordered and stable state, so as to promote urbanization
development efficiency and boost the sustainable development of the city.

5. Sustainable Urbanization Synergy Degree Measurement Method

The synergy theory is a useful tool for systems science studies as it can reveal the common
principle of the change in the updating process of the system development [35]. Since it was put
forward by Hermann Haken in 1976, it has been applied in many fields such as logistics systems [36]
and tourism planning [37]. In this paper, the synergy theory is introduced into the study of sustainable
urbanization composite system. Synergy degree is used to measure the degree of coordination and
collaboration between the subsystems within sustainable urbanization system, which can be reflected
by order degrees of order parameters in each subsystem.

5.1. Subsystem Order Degree Measurement Model

Suppose a sustainable urbanization compound system consists of i subsystems, S = (S1 , S2 , · · · , Si ),
i ∈ [1, k] and k ≥ 2. In this research, k = 5, which indicates that the sustainable urbanization system (S)
has five subsystems; a demographic change subsystem (S1 ), an economic development subsystem (S2 ),
a spatial structure subsystem (S3 ), an environmental quality subsystem (S4 ), and a social development
subsystem (S5 ).
The order parameters for subsystem Si are defined as ei = (ei1 , ei2 , · · · , ein ), n ≥ 1, β ij ≤ eij ≤
αij , j ∈ [1, n], with αij and β ij being the upper and lower limits of eij at the critical system stability point.
Generally, there are two kinds of order parameters; (1) the greater the value of the order parameter, the
higher the subsystem order degree; and (2) the smaller the value of the order parameter, the higher the
subsystem order degree. In this case, we suppose ei1 , ei2 , · · · , eim are the first kinds of order parameters
and eim , eim+1 , · · · , ein are the second kinds of order parameters. Therefore, the order degree for the
sustainable urbanization subsystem can be expressed as:

eij − β ij

αij − β ij , j ∈ [1, m ], eij is positive index


ui eij = αij −eij (1)
αij − β ij , j ∈ [ m + 1, n ], eij is negetive index


From Equation (1), it can be known that the order degree of the order parameter of subsystem



ui eij ∈ [0, 1], and the larger ui eij is, the more order parameter eij contributes to the order degree
of the subsystem. In addition, the total contribution of each order parameter to the subsystem is not
only related to the numerical value of the order, but also related to their specific combination form;
that is, the weight of each order parameter. In practice, the geometric mean method or linear weighted
Sustainability 2018, 10, 9 9 of 19

summation method is often used. In this paper, the linear weighting method is used to integrate the
order degree of subsystem, namely:
n
∑ ω j ui


u i ( ei ) = eij (2)
j =1

n
0 ≤ ω j ≤ 1, ∑ ω j = 1.
j =1

We know from Equation (2) that ui (ei ) ∈ [0, 1] and the higher the ui (ei ) value is, the higher the
order degree of subsystem Si . Among them, the weight coefficient ω j indicates the position of the order
parameter eij in the orderly operation of the subsystem, which can be calculated by the CRITIC method.
The CRITIC method is an objective weighting method that not only accounts for the influence of
contrast strength size on the weights, but also accounts the conflict between the indices, which can
effectively determine the index weight by using the product of the internal contrast strength of
evaluation indices and the conflict between the indices [38,39]. According to the definition of the
CRITIC method, c is the information quantity of the order parameter in the evaluation system. Thus,
the amount of information for the j-th order parameter is:
n  
c j = σj ∑ 1 − rkj , j = 1, 2, · · · , n (3)
k =1

where σj is the standard deviation of the j-th order parameter, and it can be used as a measure of
contrast intensity; rkj is the correlation coefficient between the evaluation order parameter k and the
n  
evaluation order parameter j; and ∑ 1 − rkj represents the conflict between the order parameters.
k =1
The larger the value of c j , the greater the information it contains and the greater the corresponding
weight; therefore, the objective weight ω j for the j-th order parameters is:

cj
ωj = , j = 1, 2 · · · , n (4)
∑nk=1 c j

5.2. Sustainable Urbanization System Synergy Degree Measurement Model

It is assumed that, at a given initial time t0 , the order degrees of the five subsystems
of the sustainable urbanization system are u1 0 (e1 ), u2 0 (e2 ), u3 0 (e3 ), u4 0 (e4 ), u5 0 (e5 ) and as the
urbanization system dynamically evolves, the order degree of the five subsystems change to
u1 m (e1 ), u2 m (e2 ), u3 m (e3 ), u4 m (e4 ), u5 m (e5 ) at time tm . Then, the measurement model of urbanization
synergy degree can be defined as follows:
( )1/k
k h i
SD = θ ∏ u i m ( ei ) − u i 0 ( ei ) (5)
i =1

In Equation (5), θ should meet the following conditions:

min ui m (ei ) − ui 0 (ei ) 6= 0

i
θ= , i = {1, 2, 3, 4, 5}. (6)
min(ui m (ei ) − ui 0 (ei ) 6= 0)
i

From Equation (6), when the order degree of the five subsystems all increases from time t0 to tm ,
θ = 1, otherwise, θ = −1. Therefore, the range of the synergy degree value is SD ∈ [−1, 1]. The larger
SD is, the higher the synergy degree of the urbanization system will be; on the contrary, the smaller SD
is, the lower the synergy degree of urbanization system will be. Further, we can know from Equation (6)
 Sustainability 2018, 10, 9 10 of 19

the smaller
Sustainability SD10,is,
2018, the lower the synergy degree of urbanization system will be. Further, we
9 10 ofcan
19
know from Equation (6) that only when ( )− ( ) > 0, where = {1,2,3,4,5}, can the synergy
degree of urbanization system be positive, which means the whole urbanization system is
that only when u1 m (ei ) − u1 0 (ei ) > 0, where i = {1, 2, 3, 4, 5}, can the synergy degree of urbanization
developing in an orderly way from time to . If the synergy degree value is negative in that
system be positive, which means the whole urbanization system is developing in an orderly way from
period, it indicates the inharmonious development of the entire urbanization development system.
time t0 to tm . If the synergy degree value is negative in that period, it indicates the inharmonious
development of the
5.3. Measurement entire urbanization development system.
Steps
5.3. Measurement
To sum up,Steps
the model of sustainable urbanization system synergy degree measurement is
shown in Figure 3. The detailed calculation steps are as follows:
To sum up, the model of sustainable urbanization system synergy degree measurement is shown
in Figure 3. The detailed calculation steps are as follows:

Figure 3. Sustainable urbanization synergy degree measurement model.

Figure 3. Sustainable urbanization synergy degree measurement model.

Step 1: Normalize original data. In order to eliminate the influence of the dimension of the
Step 1: Normalize original data. In order to eliminate the influence of the dimension of the
original data on the measurement results, we firstly need to normalize the data. The normalization
original data on the measurement results, we firstly need to normalize the data. The normalization
process is as follows:
process is as follows: Zsj − Zmin
0
Zsj = , s = 1, 2 . . . m; j = 1, 2 . . . n (7)
Z −−Zmin
=max , = 1,2 … ; = 1,2 … (7)
where Zsj0 represents the normalized data,−Z is the raw data value for variable s, Z
sj max stands for the
where represents the normalized data, is the raw data value
maximum order parameter value for subsystem j, and Zmin is the minimum order parameter for variable , stands
value for
subsystem j.
for the maximum order parameter value for subsystem , and is the minimum order
Step 2:value
parameter Determine the correlation
for subsystem . coefficient for each order h iparameter in the urbanization
Step 2:and
subsystem, Determine the correlation
establish the correlationa coefficient for each
coefficient matrix R= order
rkj parameter
, in the urbanization
n×n
subsystem, and establish the correlation a coefficient matrix = [ ] × ,
Cov (k, j, ) )
ov(
rkj ==p (8)
Var (k))Var ((j)) (8)
ar(
whereCovov(
where (k, j,) )is the covariance
is the of k and
covariance Var(k ). isar(
of j. and the )variance
is the of k and Var
variance of ( j) is
and ( ) is ofthe
the variance j.
Then calculate
variance of . the
Then objective weight
calculate of themweight
the objective based onof Equations
them based(3)onand (4).
Equations (3) and (4).
Sustainability 2018, 10, 9 11 of 19

Step 3: Calculate the order degree values for the urbanization subsystem order parameters ui eij
according to Equation (1). On this basis, the order degree of subsystems is obtained by the aggregation
of Equation (2).
Step 4: Determine the sustainable urbanization synergy degree values using Equation (5).

6. Case Analysis
In this section, the Henan province of China is chosen as the study object to analyze the
development and evolution in its sustainable urbanization. Henan is a large agricultural province in the
central part of China, and has the highest population of all provinces in China. However, urbanization
has been slow, with the quality being lower than the national average primarily because of slow
and low quality urbanization and unbalanced development [40]. The characteristics of industrial
structure in Henan province are as follows: (1) the proportion of agricultural output value is higher
than that of other provinces; (2) industry is dominated by traditional industries and basic industries,
and the level of development of tertiary industry is low; and (3) the size of the economy is larger.
With such a background, the characteristics and causes revealed by an in-depth study of Henan
urbanization mean that corresponding measures are very necessary and urgent to speed up the process
of urban development.
According to the established order parameter system above, we chose Henan province, in China,
as our research object. The original data of this study are derived from the “China Statistical
Yearbook” (2007–2016) [41], the “Henan Statistical Yearbook” (2007–2016) [42], and some of the order
parameter data were converted from the original data by calculation formulas. The Henan sustainable
urbanization order parameter data is shown in Table 2.
The correlation coefficient matrix and the order parameter standard deviation were calculated by
using SPSS software to find order parameters information quantity and weights for the sustainable
urbanization system, the calculation results for which are shown in Table 3.
The order parameter order degrees, the subsystem order degrees, and the sustainable urbanization
synergy degree were determined based on Equations (1), (2), and (5), as shown in Tables 4 and 5.
Sustainability 2018, 10, 9 12 of 19

Table 2. Order parameters raw data.

Demographic Change Economic Development Spatial Structure Environmental Quality Social Development
Year
e11 e12 e13 e14 e21 e22 e23 e24 e25 e31 e32 e33 e34 e41 e42 e43 e44 e51 e52 e53 e54 e55 e56
2006 3.5 3050 16.47 33.1 13,172 31 9810.26 3.4 39.16 10 5305.7 31.75 1679 32.8 46.3 66.32 95.15 12,575 5242 67.2 704 21.24 2.21
2007 3.4 3214 16.59 34.34 16,012 31.3 11,477.05 3.4 44.02 10.81 5902 32.3 1775 34.3 51.9 71.45 114.4 13,071 6998 68.9 726.03 24.96 2.43
2008 3.4 3397 16.72 36.03 19,181 29.7 13,231.11 3.4 48.4 9.9 5967 31.9 1857 35.4 67.3 77.53 109.88 15,661 9133 66.9 840.87 30.88 2.71
2009 3.5 3577 17.94 37.7 20,597 31 14,371.56 3.4 58.8 10.44 4886 32.8 1913 36.3 75.3 83.86 121.32 18,381 11,425 72.9 1970.13 35.21 3.15
2010 3.4 3651 18.18 38.5 24,446 30.6 15,930.26 3.4 60.34 10.25 5178 33.3 2014 36.5 82.5 87.58 132.25 18,912 16,539 73.4 2043.75 41.23 3.18
2011 3.4 3809 20.76 40.57 28,661 32.1 18,194.8 3.2 62.88 10.83 5124 34.1 2098 36.6 84.4 87.77 140.11 20,860 19,259 76.2 2122.26 56.83 3.29
2012 3.1 3991 21.99 42.43 31,499 33.8 20,422.62 3 69.46 11.08 4964 34.7 2219 36.9 86.4 87.82 178.21 21,852 26,833 77.9 2222.2 59.38 3.52
2013 3.1 4123 24.03 43.8 34,211 35.7 21,740.7 2.9 78.25 11.57 4982 34.4 2289 37.6 90 90.88 288.1 22,790 29,482 82 2297.2 66.66 3.66
2014 3.0 4265 27.27 45.2 37,072 37.1 23,672.1 2.7 85.9 11.67 5149 38.18 2375 38.3 92.8 92.51 317.58 25,257 33,366 83.8 2340.03 62.25 3.8
2015 3.0 4441 27.71 46.85 39,123 40.2 25,575.6 2.6 94.46 12.06 5155 38.35 2503 37.7 96 93.58 360.16 27,355 47,766 86 2344.9 60.61 3.73

Table 3. Order parameters information quantity and weights.

Subsystem Order Parameters of Each Subsystem Information Quantity Order Parameters Weights
Urban unemployment rate (%) e11 0.1112 0.421
Resident population in urban areas (million persons) e12 0.0503 0.191
Demographic change
Proportion of urban employment to total employment (%) e13 0.0576 0.218
Population urbanization rate (%) e14 0.0450 0.170
Per capita GDP (Yuan) e21 0.0772 0.197
Tertiary Industry Proportion (%) e22 0.1106 0.283
Disposable income of urban residents e23 0.0592 0.152
Economic development
Comparison of consumption level between urban and rural residents
0.0844 0.216
(rural residents = 1) e24
Urban fixed asset investment accounted for GDP ratio (Hundred
0.0595 0.152
million yuan) e25
The per capita road area of urban residents (sq.m) e31 0.2739 0.206
Density of urban population (persons/sq.km) e32 0.5686 0.428
Spatial structure
Per capita living space of urban residents (sq.m) e33 0.2731 0.205
Built-up area (sq.km) e34 0.2143 0.161
Sustainability 2018, 10, 9 13 of 19

Table 3. Cont.

Subsystem Order Parameters of Each Subsystem Information Quantity Order Parameters Weights
Green coverage rate of built-up area (%) e41 0.0818 0.154
Harmless treatment rate of municipal solid waste (%) e42 0.0920 0.173
Environmental quality
Urban sewage treatment rate (%) e43 0.0920 0.173
environmental governance investment (hundred million yuan) e44 0.2652 0.500
Public transport standard operating vehicle numbers e51 0.0893 0.098
Total amount of patent authorization e52 0.1751 0.194
Gas popularization rate (%) e53 0.1209 0.134
Social development Medical insurance numbers in cities and towns e54 0.2455 0.272
Internet computer numbers per 100 households in cities and
0.1632 0.181
towns e55
Bed numbers in hospital health centers at the end of the year
0.1088 0.121
(×104 ) e56

Table 4. Order degree of the order parameters of each subsystem.

Demographic Change Economic Development Spatial Structure Environmental Quality Social Development
Year
e11 e12 e13 e14 e21 e22 e23 e24 e25 e31 e32 e33 e34 e41 e42 e43 e44 e51 e52 e53 e54 e55 e56
2006 0.0000 0.0000 0.0000 0.0000 0.0000 0.1238 0.0000 0.0000 0.0000 0.0463 0.6117 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0157 0.0000 0.0000 0.0000
2007 0.2000 0.1179 0.0107 0.0902 0.1094 0.1524 0.1057 0.0000 0.0879 0.4213 0.0601 0.0833 0.1165 0.2727 0.1127 0.1882 0.0726 0.0336 0.0413 0.1047 0.0134 0.0819 0.1384
2008 0.2000 0.2495 0.0222 0.2131 0.2316 0.0000 0.2170 0.0000 0.1671 0.0000 0.0000 0.0227 0.2160 0.4727 0.4225 0.4112 0.0556 0.2088 0.0915 0.0000 0.0834 0.2122 0.3145
2009 0.0000 0.3789 0.1308 0.3345 0.2861 0.1238 0.2893 0.0000 0.3552 0.2500 1.0000 0.1591 0.2840 0.6364 0.5835 0.6434 0.0988 0.3928 0.1454 0.3141 0.7716 0.3076 0.5912
2010 0.2000 0.4321 0.1521 0.3927 0.4344 0.0857 0.3882 0.0000 0.3830 0.1620 0.7299 0.2348 0.4066 0.6727 0.7283 0.7799 0.1400 0.4288 0.2657 0.3403 0.8165 0.4401 0.6101
2011 0.2000 0.5457 0.3817 0.5433 0.5969 0.2286 0.5318 0.2500 0.4289 0.4306 0.7798 0.3561 0.5085 0.6909 0.7666 0.7869 0.1697 0.5606 0.3296 0.4869 0.8643 0.7836 0.6792
2012 0.8000 0.6765 0.4911 0.6785 0.7062 0.3905 0.6731 0.5000 0.5479 0.5463 0.9278 0.4470 0.6553 0.7455 0.8068 0.7887 0.3134 0.6277 0.5077 0.5759 0.9252 0.8397 0.8239
2013 0.8000 0.7714 0.6726 0.7782 0.8107 0.5714 0.7568 0.6250 0.7069 0.7731 0.9112 0.4015 0.7403 0.8727 0.8793 0.9010 0.7281 0.6911 0.5700 0.7906 0.9709 1.0000 0.9119
2014 1.0000 0.8735 0.9609 0.8800 0.9210 0.7048 0.8793 0.8750 0.8452 0.8194 0.7567 0.9742 0.8446 1.0000 0.9356 0.9607 0.8393 0.8581 0.6614 0.8848 0.9970 0.9029 1.0000
2015 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.7512 1.0000 1.0000 0.8909 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.8668 0.9560
Sustainability 2018, 10, 9 14 of 19

Table 5. Order degree of all subsystems and synergy degree of the composite system.

Year u1 (e1 ) u2 (e2 ) u3 (e3 ) u4 (e4 ) u5 (e5 ) SD sd

2006 0 0.035 0.271 0 0.002
2007 0.124 0.094 0.148 0.130 0.061 −0.0929 −0.0929
2008 0.173 0.104 0.039 0.245 0.137 −0.1557 −0.0542
2009 0.158 0.189 0.558 0.350 0.446 0.2553 −0.1165
2010 0.267 0.227 0.459 0.435 0.515 0.2928 −0.0752
2011 0.364 0.382 0.577 0.460 0.643 0.4087 0.0893
2012 0.688 0.543 0.707 0.548 0.741 0.5729 0.1424
2013 0.763 0.679 0.751 0.806 0.840 0.6925 0.1028
2014 0.947 0.832 0.828 0.902 0.887 0.8038 0.0996
2015 1 1 0.894 0.983 0.971 0.8945 0.0832
Sustainability 2018,
Sustainability 2018, 10,
10, 99 14 of
15 of 19
19

7. Results Analysis
7. Results Analysis
In order to more intuitively reflect the cooperative evolutionary trend of each subsystem and
In ordersystem,
the overall to morethe
intuitively reflecttrend
development the cooperative evolutionary
is drawn from the data trend of each
in Tables subsystem
4 and and the
5, as shown in
overall system,
Figure 4. the development trend is drawn from the data in Tables 4 and 5, as shown in Figure 4.

1.2
Demographic change
1 subsystem
Economic development
0.8 subsystem
Spatial structure subsystem
0.6

0.4 Environmental quality

subsystem

0.2 Social development

subsystem
0 Composite system synergy
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 degree
-0.2
Composite system dynamic
synergy degree
-0.4

Figure 4. Development trend of the order degree of the sustainable urbanization subsystems and
Figure 4. Development trend of the order degree of the sustainable urbanization subsystems and
synergy degree
synergy degree of
of the
the composite
composite system
system in
in Henan.
Henan.

7.1. Analysis of the Subsystem Order Degree of the Sustainable Urbanization

7.1. Analysis of the Subsystem Order Degree of the Sustainable Urbanization
As can be seen from Table 5 and Figure 4, in 2006–2010, on the whole, the order degrees of the
As can be seen from Table 5 and Figure 4, in 2006–2010, on the whole, the order degrees of the
subsystems of sustainable urbanization fluctuated but steadily increased from 2011 to 2015. From
subsystems of sustainable urbanization fluctuated but steadily increased from 2011 to 2015. From 2006
2006 to 2015, the order degrees of all the subsystems of sustainable urbanization increased to
to 2015, the order degrees of all the subsystems of sustainable urbanization increased to varying
varying degrees, indicating that the five subsystems have the ability for self-organization. Over this
degrees, indicating that the five subsystems have the ability for self-organization. Over this period,
period, the social development subsystem and the spatial structure subsystem order degrees were
the social development subsystem and the spatial structure subsystem order degrees were relatively
relatively higher than the others, and the order degree of the economic development subsystem was
higher than the others, and the order degree of the economic development subsystem was the lowest.
the lowest.
(1) The demographic change subsystem order degree was increasing from 2006 to 2015, with
(1) The demographic change subsystem order degree was increasing from 2006 to 2015, with the
the order degree improvement particularly evident after 2011. Since the 11th Five-Year Plan,
order degree improvement particularly evident after 2011. Since the 11th Five-Year Plan,
Henan province has attached great importance to an orderly population flow and a reasonable
Henan province has attached great importance to an orderly population flow and a reasonable
population distribution. In the past ten years, the urban population has increased by 19.31 million,
population distribution. In the past ten years, the urban population has increased by 19.31
and the urban unemployment rate has decreased to 3%. Further, the secondary and tertiary
million, and the urban unemployment rate has decreased to 3%. Further, the secondary and
industry has increased urban employment opportunities, thereby contributing to the development
tertiary industry has increased urban employment opportunities, thereby contributing to the
of population urbanization. These changes appeared to suggest that the demographic change
development of population urbanization. These changes appeared to suggest that the
subsystem has been developing gradually into an orderly state. However, it is worth noting that
demographic change subsystem has been developing gradually into an orderly state. However,
the phenomenon of disequilibrium exists in Henan population urbanization.
it is worth noting that the phenomenon of disequilibrium exists in Henan population
(2) urbanization.
The improvement of the order degree of the economic development subsystem was the same as
that of
(2) The the demographic
improvement of thechange
order subsystem, but economic
degree of the the fluctuations were small.
development As a large
subsystem agricultural
was the same
as that of the demographic change subsystem, but the fluctuations were small. labor
province, Henan’s economy has been steadily developing during urbanization. The As a force
large
has shifted from primary industry to secondary industry, and with the further
agricultural province, Henan’s economy has been steadily developing during urbanization. increases in the
per capita GDP income level, there has been a gradual shift to the tertiary industry.
The labor force has shifted from primary industry to secondary industry, and with the further At the end
of 2015, the
increases in proportion of the
the per capita GDPtertiary
income industry increased
level, there to 40.2%,
has been leading
a gradual to an
shift increase
to the in
tertiary
the order At
industry. degree of the
the end economic
of 2015, development
the proportion subsystem.
of the Additionally,
tertiary industry the progress
increased to 40.2%,of order
leading
to an increase in the order degree of the economic development subsystem. Additionally, the
Sustainability 2018, 10, 9 16 of 19

degree of sustainable urbanization in Henan has also been driven by the increase in the income of
residents and the increased investment in fixed assets by the government over the past ten years.
In addition, in 2011, the construction of the Central Plains Economic Zone has been brought into
the national 12th Five-Year Plan, which has officially risen to the national strategy, and the pace
of building in Henan’s Central Plains Economic Zone has been greatly accelerated since 2011.
As shown in Figure 4, from 2011, the trend curve became more inclined; however, compared with
the other subsystems, the economic development in Henan province is not sufficient, which is
also in line with Henan’s reality.
(3) The order degree of the spatial structure subsystem first decreased from 0.271 in 2006 to the
minimum value in 2008, and then increased. There were two reasons for this. First, the urban
population growth and urban area expansion were not coordinated. Second, since Henan
province had a large population output, the Beijing Olympic Games and the economic depression
in 2008 caused limited population output, resulting in an increase in population density and
a decline in the urban resident per capita road area. As the population density and the urban
resident per capita road area weights were larger in the spatial structure subsystem, any changes
would have a significant influence on the spatial structure subsystem order degree.
(4) The order degree of the environmental quality subsystem continuously improved. Among them,
the harmless treatment rate of municipal solid waste had risen significantly from 46.3% in
2006 to 96% in 2015—a significant improvement. The urban sewage treatment rate increased
from 66.32% in 2006 to 93.58% in 2015, and environmental governance investment increased by
almost four times over the past years, all indicating that some achievements have been made in
the construction of ecological civilization, and the quality of the urban environment has been
increasingly improved in Henan.
(5) The order degree of the social development subsystem was increasing year on year and was
somewhat higher than that the other subsystems. Due to the varying improvement degrees
in each of the order parameter indices from 2006 to 2015, the system has moved in an orderly
direction, as exemplified in the increase of 18.8% in the gas popularization rate, the threefold
increase in the medical insurance numbers in cities and towns, and the increase to 47,766 in total
amount of patent authorization, all of which demonstrated that urbanization was developing
well. Compared with the other subsystems, and especially from 2009–2015, the social subsystem
had the highest order degree, indicating that more attention had been paid to it.

7.2. Analysis of Synergy Degree of the Sustainable Urbanization Composite System

From the above analysis, it can be known that the premise for a positive synergy degree value
of the sustainable urbanization composite system is that the order degrees of all subsystems at
time tm should be greater than its order degree at the initial time t0 , suggesting that the composite
system is in the state of synergistic evolution. As can be seen in Figure 4, the synergy degree of the
composite system was negative before 2009, which resulted from the disorderly development of the
spatial structure subsystem. From 2009 to 2015, the value of the synergy degree of the sustainable
urbanization composite system was positive and increased steadily, showing that the synergy system
of sustainable urbanization developed to an ordered state as a whole. From a dynamic point of view
(with the base period being one year ahead of each year), the order degrees of all of the subsystems
every year were larger than the previous year after 2010 (Table 5), leading to the positive value of
synergy degree from 2011 to 2015 (Figure 4). However, the synergy degree is negative before 2011,
indicating that the development of each subsystem is not all orderly than that of the previous year.
Sustainability 2018, 10, 9 17 of 19

Taking five years as a time period, the synergy degree of the composite system from 2006 to
2011 is SD0 = 0.4087 from Table 5. The synergy degree from 2010 to 2015 can be calculated using
Equations (5) and (6):
( )1/k ( )1/5
k h i 5 h i
SD1 = θ ∏ ui 2015
( ei ) − u i 2010
( ei ) =θ ∏ ui 2015
( ei ) − u i 2010
( ei ) = 0.5771
i =1 i =1

From a comparison of SD0 and SD1 , the improvement of the synergy degrees of the sustainable
urbanization composite system from 2006 to 2011 and from 2010 to 2015 can be observed.
SD1 > SD0 > 0 suggests that the composite system was in a synergistic development state in these
two stages, but the progress of the synergy degrees from 2010 to 2015 is greater than that from 2006
to 2011. The main reason was that in 2011, the beginning of the 12th Five-Year Plan, Henan first
introduced a series of policies focused on the scientific coordination development road of the new
urbanization, and explored out a sustainable urbanization road. Consequently, it can be seen from
Figure 4 that the order degree improvement trend of all of the subsystems is more obvious from 2011.
The synergistic evolution of a composite system is determined by the synergistic mechanisms
between the demographic, economic, spatial, ecological, and social subsystems. By calculation,
the average synergy degree of the composite system was 0.2753 from 2006 to 2015, which showed
that although the trend was rising, the synergy degree level of the sustainable urbanization system
in Henan province was still not high. From Figure 4, it was found that the economic development
subsystem is the “short board” and determined the lower synergy degree of composite subsystem to a
certain extent.

8. Conclusions
From an analysis of the structure and functions of a sustainable urbanization system, based on the
“China Statistical Yearbook” and the “Henan Statistical Yearbook” from 2007 to 2016 [41,42], this paper
developed a SUSS that had five key subsystems; demographic change, economic development, spatial
structure, environmental quality and social development. Combined with the CRITIC weighted
method, the synergetic theory was introduced and a synergy degree model was used to study the
order degree of all subsystems and the synergetic degree of the composite system. From this study,
the following conclusions were drawn:

(1) To measure the sustainable urbanization synergistic effects, this paper developed a SUSS with
selected subsystem order parameters to examine the concept of sustainable urban development,
the effectiveness and feasibility of which was verified in a pilot case study. The CRITIC method
was used to determine the order parameters weights to avoid subjective preferences, which made
the results more objective and representative.
(2) Sustainable urbanization is a complex system affected by many factors and its development is a
dynamic evolution process based on time series. Through the application of a synergy theory,
the order degree value changes of the five subsystems and the synergy degree value changes of
the composite system can be analyzed so as to scientifically reflect the systematic characteristics
and development status in the process of urbanization.
(3) Through the analysis of the order degree change of each subsystem and the synergy degree
change of the composite system in Henan province from 2006 to 2015, it was found that
although synergistic effects were developing into an ordered state, there was still much room for
improvement, especially in terms of the economic development subsystem, which needs to be
further reinforced.

Sustainable urbanization is a multi-dimensional, multi-structured, complex system that is affected

by many factors. Although the order parameters in this paper were selected from multiple perspectives,
there are still certain limitations. The synergy system does not contain all the elements that influence
Sustainability 2018, 10, 9 18 of 19

the sustainable urbanization synergy degree and the threshold of indicators is not considered in this
paper. In addition, factors that affect the synergy degree vary over time, for study convenience this
paper carried out a static independent analysis of subsystem order parameters, without considering
the internal logical relationships between the order parameters and the effect of order parameter
indices changes on measurement results. Therefore, further explorations on the order parameter index
system and dynamic research will be the focus of the future research work.

Acknowledgments: This research was funded by the Foundation of Academic Leader Training in
Sichuan Province ([2015]100-6).
Author Contributions: The study was designed by Leilei Jiao in collaboration with all co-authors. Data was
collected by Fumin Deng. The first and final drafts were written by Leilei Jiao. The defects of draft were critiqued
by Leilei Jiao and Xuedong Liang. The results were analyzed by Fumin Deng and Xuedong Liang. The research
and key elements of models were reviewed by Fumin Deng. The writing work of corresponding parts and the
major revisions of this paper were completed by Leilei Jiao.
Conflicts of Interest: The authors declare no conflict of interest.

References
1. Kumar, M.P.; Reddy, S. Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at
an Urban Area, Tirupati, India. Sci. World J. 2013, 2013, 268623. [CrossRef]
2. Shen, L.Y.; Zhou, J.Y. Examining the effectiveness of indicators for guiding sustainable urbanization in China.
Habitat Int. 2014, 44, 111–120. [CrossRef]
3. Lu, S.S.; Guan, X.L.; He, C.; Zhang, J.L. Spatio-Temporal Patterns and Policy Implications of Urban
Land Expansion in Metropolitan Areas: A Case Study of Wuhan Urban Agglomeration, Central China.
Sustainability 2014, 6, 4723–4748. [CrossRef]
4. Wang, S.J.; Fang, C.L.; Guan, X.L.; Pang, B.; Ma, H. Urbanization, energy consumption, and carbon dioxide
emissions in China: A panel data analysis of China’s provinces. Appl. Energy 2014, 136, 738–749. [CrossRef]
5. Liu, S.W.; Zhang, P.Y.; Jiang, X.L.; Lo, K. Measuring sustainable urbanization in China: A case study of the
coastal Liaoning area. Sustain. Sci. 2013, 8, 585–594. [CrossRef]
6. Liang, X.D.; Zhang, W.W.; Chen, L.; Deng, F.M. Sustainable Urban Development Capacity Measure—A Case
Study in Jiangsu Province, China. Sustainability 2016, 8, 270. [CrossRef]
7. Yu, A.T.W.; Wu, Y.; Zheng, B.; Zhang, X.; Shen, L. Identifying risk factors of urban-rural conflict in
urbanization: A case of China. Habitat Int. 2014, 44, 177–185. [CrossRef]
8. Tosics, I. The Chinese urban development dilemma: heritage and green areas as victims of rapid urbanization.
Mazowieckie Biuro Planowania Regionalnego W Warszawie 2012, 9, 87–100.
9. Yigitcanlar, T. Smart cities: An effective urban development and management model? Aust. Plan. 2015, 52,
27–34. [CrossRef]
10. Zhou, J.Y.; Shen, L.Y.; Song, X.N.; Zhang, X. Selection and modeling sustainable urbanization indicators:
A responsibility-based method. Ecol. Indic. 2015, 56, 87–95. [CrossRef]
11. Sobczyk, W. Sustainable Development of Middle East Region. Problemy Ekorozw. 2015, 10, 51–62.
12. Dassen, T.; Kunseler, E.; Van Kessenich, L.M. The Sustainable City: An Analytical–Deliberative Approach to
Assess Policy in the Context of Sustainable Urban Development. Sustain. Dev. 2013, 21, 193–205. [CrossRef]
13. Chen, Z.L.; Su, L.C.; Zhang, C. Research on the Synergy Degree of Aboveground and Underground Space
along Urban Rail Transit from the Perspective of Urban Sustainable Development. Sustainability 2016, 8, 934.
[CrossRef]
14. Liu, Y.Q.; Xu, J.P.; Luo, H.W. An Integrated Approach to Modelling the Economy-Society-Ecology System in
Urbanization Process. Sustainability 2014, 6, 1946–1972. [CrossRef]
15. Srinivasan, V.; Seto, K.C.; Emerson, R.; Gorelick, S.M. The impact of urbanization on water vulnerability:
A coupled; human-environment system approach for Chennai, India. Glob. Environ. Chang. 2013, 23,
229–239. [CrossRef]
16. Shen, L.; Cheng, S.K.; Gunson, A.J.; Wan, H. Urbanization, sustainability and the utilization of energy and
mineral resources in China. Cities 2005, 22, 287–302. [CrossRef]
17. Li, S.S.; Ma, Y. Urbanization, Economic Development and Environmental Change. Sustainability 2014, 6,
5143–5161. [CrossRef]
Sustainability 2018, 10, 9 19 of 19

18. Zhang, H.Y.; Uwasu, M.; Hara, K.; Yabar, M. Sustainable Urban Development and Land Use Change—A Case
Study of the Yangtze River Delta in China. Sustainability 2011, 3, 1074–1089. [CrossRef]
19. Dewan, A.M.; Yamaguchi, Y. Effect of land cover changes on flooding: Example from Greater Dhaka of
Bangladesh. Int. J. Geoinform. 2008, 4, 11–20.
20. Shen, L.Y.; Peng, Y.; Zhang, X.L.; Wu, Y.Z. An alternative model for evaluating sustainable urbanization.
Cities 2012, 29, 32–39. [CrossRef]
21. Harris, N. Wastes, the environment and the international economy. Cities 1992, 9, 177–185. [CrossRef]
22. Marcotullio, P.J. Asian urban sustainability in the era of globalization. Habitat Int. 2001, 25, 577–598.
[CrossRef]
23. Jaeger, J.A.G.; Bertiller, R.; Schwick, C.; Kienast, F. Suitability criteria for measures of urban sprawl. Ecol. Indic.
2010, 10, 397–406. [CrossRef]
24. Huang, L.; Yan, L.J.; Wu, J.G. Assessing urban sustainability of Chinese megacities: 35 years after the
economic reform and open-door policy. Landsc. Urban Plan. 2016, 145, 57–70. [CrossRef]
25. Shen, L.Y.; Ochoa, J.; Shah, M.N.; Zhang, X.L. The application of urban sustainability
indicators—A comparison between various practices. Habitat Int. 2011, 35, 17–29. [CrossRef]
26. Mori, K.; Yamashita, T. Methodological framework of sustainability assessment in City Sustainability Index
(CSI): A concept of constraint and maximization indicators. Habitat Int. 2015, 45, 10–14. [CrossRef]
27. Zhang, X.L. Sustainable urbanization: a bi-dimensional matrix model. J. Clean. Prod. 2016, 134, 425–433.
[CrossRef]
28. Li, Y.F.; Li, Y.; Zhou, Y.; Shi, Y.L. Investigation of a coupling model of coordination between urbanization and
the environment. J. Environ. Manag. 2012, 98, 127. [CrossRef] [PubMed]
29. Tavernia, B.G.; Reed, J.M. Spatial extent and habitat context influence the nature and strength of relationships
between urbanization measures. Landsc. Urban Plan. 2009, 92, 47–52. [CrossRef]
30. Shen, L.Y.; Zhou, J.Y.; Skitmore, M.; Xia, B. Application of a hybrid Entropy–McKinsey Matrix method in
evaluating sustainable urbanization: A China case study. Cities 2015, 42, 186–194. [CrossRef]
31. Qiao, B.; Fang, C.G. The dynamic coupling model and its application of urbanization and eco-environment
in Hexi Corridor. J. Geogr. Sci. 2005, 15, 491–499. [CrossRef]
32. Buhaug, H.; Urdal, H. An urbanization bomb? Population growth and social disorder in cities.
Glob. Environ. Chang. 2013, 23, 1–10. [CrossRef]
33. Sato, Y.; Zenou, Y. How Urbanization Affect Employment and Social Interactions. Eur. Econ. Rev. 2015, 75,
131–155. [CrossRef]
34. Haken, H. Synergetics: An Overview. Rep. Prog. Phys. 1989, 52, 515–553. [CrossRef]
35. Haken, H. Basic concepts of synergetics. Appl. Phys. A Solids Surf. 1993, 57, 111–115. [CrossRef]
36. Heuvel, F.V.D.; Donselaar, K.V.; Langen, P.D.; Fransoo, J. Co-Location Synergies: Specialised Versus Diverse
Logistics Concentration Areas. Tijdschrift Voor Economische En Sociale Geografie 2016, 107, 331–346. [CrossRef]
37. Buultjens, J.; Gale, D.; White, N.E. Synergies between Australian indigenous tourism and ecotourism:
Possibilities and problems for future development. J. Sustain. Tour. 2010, 18, 497–513. [CrossRef]
38. Diakoulaki, D.; Mavrotas, G.; Papayannakis, L. Determining objective weights in multiple criteria problems:
The critic method. Comput. Oper. Res. 1995, 22, 763–770. [CrossRef]
39. Kazan, H.; Ozdemir, O. Financial performance assessment of large scale conglomerates via TOPSIS and
CRITIC methods. Int. J. Manag. Sustain. 2014, 3, 203–224.
40. He, L.X.; Chen, B.X. The present situation, causes and Countermeasures of urbanization in Henan province.
China’s Urban Econ. 2010, 9, 259–261.
41. People’s Republic of China National Bureau of statistics. China Statistical Yearbook; China Statistics Press:
Beijing, China, 2007–2016. Available online: http://www.stats.gov.cn/tjsj/ndsj/ (accessed on 11 October 2017).
42. Henan Bureau of Statistics. Henan Statistical Yearbook; China Statistics Press: Beijing, China, 2007–2016.
Available online: http://www.ha.stats.gov.cn/sitesources/hntj/page_pc/tjfw/tjcbw/tjnj/list1.html
(accessed on 11 October 2017).

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