Spatio-temporal evolution of port opening in China's 40 years of reform and opening-up period
Spatio-temporal evolution of port opening in China's 40 years of reform and opening-up period
Xiaoshu Cao? 0 1 2
Shengchao LiID 0 1 2
0 Editor: Jing Zhao, University of Shanghai for Science and Technology , CHINA
1 School of Geography and Planning, Sun Yat-Sen University , Guangzhou, Guangdong , China
2 Funding: This research was funded by National Natural Science Foundation of China , No. 41671160, to X. Cao
In the past 40 years of reform and opening-up, China has developed from an economically closed country to a country that is highly dependent on foreign trade. From the perspective of spatiotemporal evolution, we analyze how port opening promoted China's reform and opening-up process. First, the port development process is divided into four periods. In the start-up period, the pilot open port policy created a platform for foreign cooperation and exchange. During the expansion period, port openings promoted the continuous optimization of the trade structure. In the cooperation period, port openings corresponded with the adjustment of China's overall industrial structure. During the optimization period, port openings provided guarantees for the implementation of a national development strategy. Second, we analyze the distribution of ports and their relationship with cross-border logistics and passenger flow. Based on data of foreign trade and passenger flow, a port openness degree measurement model includes port logistics intensity, passenger flow intensity and port city foreign-trade volume is constructed. There are significant types, geographical differences and grade differences of ports' openness.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Competing interests: The authors have declared
that no competing interests exist.
The definition of port of entry by the General Administration of Customs of China is ports,
airports, stations, cross-border passages, etc., for people, commodities, goods and vehicles
directly crossing the national border or the customs boundary. There are five types of ports:
seaports, riverports, airports, roadports and railports. They are divided into first class ports of
entry and second class ports of entry [
]. In the past 40 years of reform and opening-up, China
has developed from an economically closed country to a country that is highly dependent on
foreign trade. The dependence on foreign trade has increased from 9.65% in 1978 to 33.88% in
2018. In 2006, it reached as high as 64.24%. As national gateways, ports of entry are
increasingly important for China?s opening and connecting functions [
]. Research on port of
entry has focused on international trade and economic development, international
transportation and supply chains [
], and port characteristics [
]. Research on China?s ports of
entry mainly focuses on the geographical environment and development level of the border
ports system [
], the port spatial structure in different regions [
], the port
development model [
], the function of specific ports and their regional cooperation [
the relationship between the ports and the hinterland [
], and the historical
development of a port?s development process and its impact on the regional economy [
general, the studies on China?s port system are mainly macro descriptions of the current state.
There are few studies on the spatiotemporal evolution of ports of entry. Research subjects are
mainly coastal ports, and there are few comprehensive studies on multiport types. Therefore, it
is necessary to comprehensively analyze the relationship between various types of ports and
the country?s opening to the outside world from the perspective of spatiotemporal evolution.
This paper first analyzes the interaction between the port development process and China?s
opening up policy from a time perspective, and then analyzes port distribution and its
relationship with cross-border logistics and passenger flow from a spatial perspective.
The degree of openness refers to the degree to which a country or region?s economy is open
to the outside world. It is a multilevel comprehensive index covering foreign trade, foreign
investment, foreign economic cooperation and exchanges. The study of openness degree
originated from measuring foreign trade dependence. Early studies mostly used foreign trade
dependence as a measure of openness [
]. In many studies, the narrow sense of openness
degree is equivalent to the foreign trade dependence. However, the broad sense of openness
degree refers not only to foreign trade dependence but also to the dimensions of financial
openness, investment openness, production openness, technology openness, and openness to
immigrants. Based on national restrictions on imports and exports, the World Bank divided
countries into four levels according to their openness degree [
]. Sachs and Warner
established the SW (Sachs & Warner) indicator system, which includes comprehensive tariff rates,
nontariff barriers, socioeconomic patterns, monopoly, and smuggling factors to measure the
degree of national economic openness [
]. Lemer first estimated bilateral trade intensity and
then used the average of the difference between the predicted and actual values as the trade
openness indicator [
]. Stewart used the gravity model as a basis to predict trade flows, and
he used the difference between actual and predicted trade flows as an indicator of trade
]. Based on international trade theory, Dollar used the exchange-rate distortion index
to reflect the openness to foreign trade [
]. Studies on openness have been continuously
improved, and it is still a widely-used method to reflect the degree of openness through the
dependence on foreign trade. This method is used because the data on foreign trade and GDP
are more accessible and have better comparability among different regions. Therefore, the
measure of port openness should also follow the criteria of data availability and comparability.
The second part of this study describes the data sources and analysis methods. In the third
part, based on spatiotemporal data, we analyze the development pattern of China?s ports of
entry and the formation process of the port open regional system in the past 40 years of reform
and opening-up, and we discuss the spatiotemporal evolution of the ports of entry. The fourth
part is based on the port?s foreign trade logistics intensity, international passenger flow
intensity and the amount of port city foreign trade?which is how the port?s openness measurement
model is constructed?and so we obtain the port?s comprehensive openness degree. The fifth
part is the conclusion.
Data and methodology
The customs import and export data is from the enterprise import and export database of
the China Customs Administration in 2015. The data includes all types of foreign-trade
2 / 20
enterprises in mainland China, and the quantity of import and export goods. Other data
comes from the 2016 China Statistical Yearbook, the China?s Ports of Entry 2016 Yearbook
and the statistical yearbooks of 31 provinces (including municipalities and autonomous
For the purposes of the data, in cases where a city has multiple ports, if they are the same
type of ports, then they are combined into one port. This is also a common practice in
government statistics. For example, Guangzhou City has three sea ports: Lianhuashan, Guangzhou
and Nansha, which are combined together as the Guangzhou sea-ports; Shenzhen City has six
road ports: Futian, Huanggang, Luohu, Shatoujiao, Shenzhen Bay and Wenjindu which are all
combined together as the Shenzhen road-port.
Principal component analysis
The principal component analysis method uses the idea of dimensionality reduction to
perform linear transformation, and it converts multiple indicators that are originally related to
each other into a few comprehensive indicators or principal components. Each principal
component is irrelevant, and each principal component is a linear combination of original
variables that can reflect most of the information of the original variables?the information
contained therein does not overlap [
]. In this way, multiple factors that reflect the port
openness degree (POD) can be attributed to several principal components, which helps simplifies
The port openness measurement is an area that scholars have rarely studied, and there is no
mature measurement standard yet. Referring to the foreign trade dependence measurement
method commonly used in the study of the country?s openness [
], according to the
characteristics of the port?s openness, we built a model suitable for port openness measurement.
Ports of entry are a country?s doors to the outside world. Their function is to connect internal
and external markets, transport foreign trade goods, transport inbound and outbound
passengers and serve the foreign trade of the hinterland cities. Therefore, the POD should be
examined from the port foreign trade logistics intensity (FLI), port international passenger intensity
(IPI) and port city foreign trade amount (CFA). In this paper, principal component analysis is
used to calculate the POD of 207 ports through a model containing 7 indicators[
(Table 1). Through these indicators including the number of countries or regions, the volume
of goods, and the number of passengers passing through, the broadness and intensity
characteristics of the port opening are reflected[
Spatial correlation analysis
We use local Moran?s I and global Moran?s I to analyze the spatial correlation of port
openness. Global Moran?s I is a description of the spatial characteristics of an attribute value over
port export logistics volume (PEL)
port import logistics volume (PIL)
port external market coverage (EMC)
port outbound passengers (POP)
port inbound passengers (PIP)
port city export trade amount (PCE)
port city import trade amount (PCI)
the entire region. The local Moran?s I is used to explore whether a single region has a high
or low spatial agglomeration of observations, and the contribution of each unit of the
regional space to the global spatial autocorrelation. The global Moran?s I is complementary
to the local Moran?s I. The former reflects the spatial agglomeration of the attributes, while
the latter mainly analyzes the regional heterogeneity. The global Moran?s I equation is as
nPPin?1 PPjn?1 wij?xi
? in?1 jn?1 wij? P
Since the global Moran?s I failed to reflect the regional heterogeneity characteristics, in
order to further reflect the local spatial characteristics of the port?s openness, the local Moran?s
I was introduced:
In the above equations, n is the number of research ports; xi and xj are the original values of
sample i and sample j, respectively; x is the sample mean; wij is the spatial weight matrix. Using
the Geo DA software, the K-nearest matrix is used as the spatial weight matrix to calculate the
global and local Moran?s I. When I is positive, there is a positive spatial agglomeration,
otherwise it means a negative spatial agglomeration; when Ii is positive or negative, respectively, the
local spatial unit similarity value tends to be agglomerated or distributed, and can be visualized
with LISA map[
The cities evolution tree model was proposed by Wang and was applied to study the
evolution law of Chinese cities. The cities evolution tree draws on evolutionary theory in
biology and expresses the multidimensional data generated by urban evolution in a simple
and clear visual form. The theoretical basis for the construction of an evolutionary tree is
the ergodic theorem of physics: Individual evolution constitutes group evolution, and
individual evolution will follow the regularity exhibited by group evolution. The evolution tree
is also a visualization method, that establishes the mapping relationship between attribute
state space and a space-time pattern. In this study, the K-means clustering algorithm was
used to cluster the ports according to the seven indicators required for POD measurement,
and to arrange the branches and leaves so as to form a ports evolution tree. Each of the
branches represents a type of port, and each leaf represents a port; these are arranged
according to the POD value.
Spatial stratified heterogeneity (SSH) is one of the basic characteristics of geographical
distribution, and the difference of spatial distribution is often influenced by many factors. Exploring
its differentiation mechanism is an important part of geography research. Geodetector is a tool
for measure of spatial stratified heterogeneity and attribution of spatial patterns. The core idea
is to use the difference between the sum of the variances in the classification layer and the total
variance of the whole region to detect the spatial differentiation of the dependent variable and
the ability of the independent variable to explain the spatial differentiation of the dependent
4 / 20
]. The model is as follows:
In the above equations, L is the strata of the variable Y or factor X. Nh and N are the number
of cells in strata h (h = 1, 2, . . .) and the whole region, respectively. s2h and ?2 are the variances
of the strata h and the Y value of the whole region, respectively. The value range of q is [
The larger the value, the more obvious the spatial differentiation of Y. If the stratification is
generated by the independent variable, the larger q value is, the stronger the explanatory
power of the independent variable X on the attribute Y is, and vice versa. The geodetector q
statistic can be used to measure spatial differentiation, detect interpretation factors and analyze
the interactive relationship between variables. In this study, the dependent variable Y is POD,
and the factor X contains 7 indicators (Table 1).
The spatiotemporal evolution of China?s ports of entry
To better understand the POD of China?s ports of entry, it is necessary to analyze their
spatiotemporal evolution. We divide the process into four stages according to the port opening
policy and divide the ports into four port open regional systems based on geographical location.
Before the reform and opening-up in 1978, China had 51 national first class ports of entry
open to the outside world. Among them, water-ports (including seaports and riverports) were
mainly concentrated in the eastern coastal areas and along the Heilongjiang River, railports
and roadports were concentrated along the border areas, and airports were only distributed in
six regional central cities. Due to the small number of ports of entry and the uneven spatial
distribution, China?s foreign economic ties and foreign trade development had been hindered. In
the 40 years since opening-up, China?s ports of entry have undergone tremendous changes.
The reform and opening up policies have played a decisive role in the development of ports. In
line with the policy changes, we divide the opening process into four periods (Fig 1).
The first period, from 1978 to 1984, was a startup period characterized by pilot policy
programs. The Third Plenary Session of the 11th Central Committee of the Chinese Communist
Party proposed the reform and opening up policies, marking the end of a long-term closure of
the Chinese economy. China seized the opportunity of the industrial upgrading of the ?four
Asian tigers? and the secondary transfer of labor-intensive industries, and began to participate
in international industrial cooperation. During this period, China established special
economic zones such as Shenzhen, Zhuhai, Shantou and Xiamen and opened 22 coastal ports.
Relying on the comparative advantage of China?s cheap labor resources, the labor-intensive
export processing industry has developed rapidly. The pilot port openings during this period
provided a platform for foreign cooperation and exchanges, and supported China?s most
critical and difficult period for economic restructuring. In these 7 years, China?s foreign trade had
an average annual growth rate of 24.11%, and 34 ports were newly opened, which brought the
total to 84. The newly opened ports were mainly seaports and riverports in the eastern coastal
provinces, airports in the central and eastern provinces, and relatively few roadports and
The second period, from 1985 to 2002, was an expansionary period characterized by policy
guidance. In 1985, the State Council promulgated the ?Several Provisions on Port Opening?
], which clearly guided and expanded port opening from the national policy level. In 1992,
Deng Xiaoping?s Southern Talks marked the further expansion of China?s opening up. China
5 / 20
Fig 1. The changes in the number of ports of entry in the 40 years of reform and opening-up.
has seized the opportunity of the labor-intensive part of the manufacturing industry in
developed countries to shift outwards and gives priority to the development of export-oriented
manufacturing and high-tech industries. Taking the opening of Pudong as an opportunity,
China implemented a series of policies in Shanghai to encourage opening up. The opening up
of the ports also expanded inland from the coast, and the inland provinces have with
conditions, gradually opened up airports and riverports. Foreign capital began to flow into the
mainland on a large scale, foreign trade continued to grow, and the trade structure was
continuously optimized. China?s economy rose rapidly and its overall national strength has
increased substantially. These cumulative changes led China to become a member of the
World Trade Organization and to participate fully in economic globalization. In these 18
years, China?s foreign trade has had an average annual growth rate of 24.71%, while 157 ports
were newly opened, bringing the total to 241.
The third period, from 2003 to 2007, was the period of cooperation characterized by
institutional openness. With the accession to the World Trade Organization, China?s opening up
shifted from partial opening to institutional openness. During this period, China began to
upgrade its industrial structure. The Chinese government proposed a strategy of developing a
modern service industry and advanced manufacturing in the coastal areas, developing strategy
of the Bohai Rim region, revitalizing of the old industrial bases in the Northeast, and
developing the western region. The eastern, central and western regions were opened up according to
the industrial gradient. The core goal of port openings during this period was to coordinate
with China?s overall industrial restructuring and ensure the implementation of its WTO
commitments. This coordination not only enhanced China?s comprehensive national strength but
also promoted the improvement of the socialist market economic system. In these 5 years,
6 / 20
China?s foreign trade had an average annual growth rate of 26.81%, and 19 ports were opened,
bringing the total to 260.
The fourth period, from 2008 to the present, is an optimization period characterized by
comprehensive opening. The 17th National Congress of the Communist Party of China
(NCCPC) put forward a comprehensive opening strategy of "deepening the opening up of the
coastal areas, speeding up the opening up of the central areas, and optimizing the opening of
the border areas. " After the 18th NCCPC, in order to adapt to economic globalization, China
formulated a more proactive open strategy and paid more attention to the balance, security
and efficiency of opening up. After the Third Plenary Session of the 18th NCCPC, China
proposed building a new open economic system, expanding the opening of the inland borders,
and promoting exchanges and complementary advantages in inland and coastal areas. Full
openness is also an important condition for the implementation of national strategies, such as
the Silk Road Economic Belt, the 21st Century Maritime Silk Road, and the Yangtze River
Economic Belt. In the 9 years from 2008 to 2016, China?s foreign trade had an average annual
growth rate of 5.12%, and 42 ports were newly opened, bringing the total to 302.
Four ports open regional systems
China has six maritime neighbors and has 14 land borders. Most of the ports of entry are
located along the border and coastal areas, with a small portion located inland and along
major rivers. Based on the spatial location, China?s ports of entry can be divided into four
open regional systems: Coastal Ports, Ports Along the Yangtze River, Border Ports and Inland
]. Period I, mainly coastal and river ports were opened; in Period II the number of
border ports increased rapidly; in Period III, the overall growth rate slowed down; and in
Period IV the number of ports in each region increased steadily (Fig 2).
The Coastal Ports include the ports of 11 provinces of Liaoning, Hebei, Tianjin, Shandong,
Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi and Hainan (except for riverports
in Jiangsu, and border ports in Liaoning and Guangxi). The coastal areas have the most
developed economies, the densest populations, and the highest openness degree in China. There are
currently 140 ports in the coastal area, a six-fold increase over 1978. It had the fastest growth
rate in Period I, far exceeding the national average growth rate over the same period. This is in
line with the situation in which the coastal areas were first opened to the outside world.
Seaports are the most important of all port types. At the beginning of the reform and opening-up
period, the framework of the seaport system was already in place. After 40 years of
development, there are now 81 seaports. A total of 15 riverports in the Coastal Ports are concentrated
in the Pearl River basin of Guangdong and Guangxi. There are 29 airports in the coastal areas,
which is 7 times more than that in 1978.
The Border Ports include the ports in the 9 border provinces of Liaoning, Jilin,
Heilongjiang, Inner Mongolia, Gansu, Xinjiang, Tibet, Yunnan and Guangxi (except for the coastal
ports in Guangxi and Liaoning). Most of the provinces along the border are far from the
ocean. In the process of reform and opening-up, their development lagged the eastern coastal
areas. Therefore, the opening process of the border ports has also lagged behind the coastal
ports. In 1978, there were 27 border ports, slightly more than the number of coastal ports in
the same period. Period II was the fastest growth period of the border ports, when 49 ports
were added. Now, there are 116 border crossing ports, which is four times higher than in 1978.
China has opened ports of entry with 12 of its 14 neighboring countries. Since China and
Afghanistan have a short border and China has not yet established diplomatic relations with
Bhutan, China has not opened a port with either country. For the provinces perspective,
border ports are concentrated in Heilongjiang (25), Xinjiang (20), Inner Mongolia (18), Jilin (17)
7 / 20
Fig 2. The changes in ports of entry distribution in the 40 years of reform and opening-up.
and Yunnan (18), accounting for 84% of the total. In terms of port types, roadports, railports
and airports are widely distributed in various provinces, and riverports are concentrated in the
Heilongjiang River Basin (16) and the Lancang River Basin (2).
The Ports Along the Yangtze River collectively includes 37 ports in the provinces along the
Yangtze River (except the coastal ports). There are currently only two types of airports (15)
and riverports (22). The Yangtze River Basin is one of the most important economic centers of
China. After the reform and opening-up, a number of riverports and airports along the
Yangtze River were quickly opened to the outside world. The riverports were mainly opened in
Period I; the riverports and airports both had some growth in the latter three periods. Due to
the lack of land ports and the relatively simple port types, the Ports Along the Yangtze River
needs to be improved.
8 / 20
The Inland Ports include the ports in Beijing, Henan, Shanxi, Shaanxi, Ningxia and
Qinghai. These areas do not border the sea, are not along big rivers, and do not border other
countries, it is difficult to trade with foreign countries. So far, only the capitals and central cities of
the provinces have opened airports, and Zhengzhou and Beijing have railports. With the
implementation of the Belt and Road Initiative, these regions are expected to open new ports
as part of the new international transportation corridor.
Openness degree of ports of entry
Results of POD
Kaiser Meyer Olkin (KMO) and Bartlett?s tests were used to assess the sampling adequacy
before running PCA. When the sampling adequacy is greater than 0.5, the data set is suitable
for running PCA [
]. The original data were normalized using SPSS 24 software. The
results of PCA are shown in Tables 2?4. In Table 2, the sampling adequacy is 0.625>0.50.
Three components with eigenvalue larger than 1.00 were generated. The variable loadings
larger than 0.30 or less than 0.30 are significant. In Table 4, all loadings with absolute values
less than 0.8 were suppressed.
According to the component matrix obtained by PCA, multiplied by the data matrix
obtained by the normalization to obtain a component score matrix. Since some of the scores
have negative values, the matrix needs to be transformed. The transformed data order and
eigenvalues are unchanged. The transformation formula is:
In Eq 4, x? is the transformed new value, which is between 0 and 1; x is the original value,
and xmax and xmin are the maximum and minimum values in the original data column,
respectively. Taking the variance contribution of the rotated component as the weight, the POD
score of each port is calculated (Table 5).
Comparative analysis between different ports
Based on the results of POD, FLI, IPI and CFA, global Moran?s I and local Moran?s I were
calculated, and the scatter plots of Moran?s I and LISA (Figs 3 and 4) were drawn. The results of
Tables 5 and 6 were analyzed with reference to Figs 3 and 4.
FLI. The following characteristics can be seen from the scores of the port?s FLI (Tables 5
and 6, Figs 3 and 4). ? The FLI generally has a positive spatial clustering, that is, ports with
high (low) FLI values are concentrated together. High-High agglomeration is distributed in
the Yangtze River Delta, Pearl River Delta and Bohai Rim region. Low-Low agglomeration is
concentrated in the border areas. The agglomeration in other areas is not significant. ? The
highest FLI in all of the ports is the Shanghai Seaport, which is 0.215 and is much higher than
the other ports. ? The FLI distribution is extremely uneven. There are 7 ports? FLI are higher
than 0.1, accounting for 3.38% of the sample and 41 in the range of 0.01?0.1, accounting for
19.81% of the sample. The trade volume of the first 7 ports accounted for 50.1% of the total,
indicating that a small number of ports concentrated most of the country?s foreign trade
logistics. ? The FLI of more than 76.8% ports is less than 0.01, that is, their foreign trade logistics
flow is less than 1% of the Shanghai Seaport, indicating that the foreign trade flow of most
ports is relatively small.
The results show the following: ? the FLI average values of the four port open regional
systems are respectively: Coastal Ports (0.025) > Ports Along the Yangtze River (0.011) > Border
Ports (0.005) > Inland Ports (0.002). The seaports concentrate most of the foreign trade
logistics flow and are the main channel for China?s foreign trade. Other types of port logistics
volume are relatively low. ? Overall, the volume of import logistics is greater than the volume of
export logistics. This is in line with the role of China as the world?s factory. The northern ports
have a higher logistics volume than the southern ports. This volume is related to the northern
import and export of bulk cargo such as coal, iron and ore, which is in line with the industrial
distribution of the south and the north. ? The 4 seaports of Shanghai, Qingdao and Tangshan
Rizhao constitute the first group, and their volume is above 270 million tons, far exceeding
Note: Only the top 10 of 207 ports are shown. See all POD scores and metadata in supporting information S1 Table.
10 / 20
those of other ports. Except for the Weifang Seaports (6 tons), the foreign trade logistics
volume of other shipping ports is more than 70,000 tons. The average volume of seaports is 56.48
million tons, with a median of 14.54 million tons. ? The average foreign trade logistics
volume of riverports is 10.18 million tons, with a median of 2.31 million tons. The 5 riverports of
Suzhou, Wuxi, Nantong, Zhenjiang and Nanjing all have more than 20 million tons of logistics
volume, all of which are in the Yangtze River Delta. Among them, the Suzhou Riverport has
the largest logistics volume, reaching 135.23 million tons. Riverports with the largest logistics
volume in the Pearl River Delta region are Foshan, Jiangmen, Zhongshan, and Dongguan.
Their foreign trade logistics volume are all less than 7 million tons, and their overall scale is
smaller than that in the Yangtze River Delta region. The Daxinganling Riverport has a volume
of 16.44 million tons, which is the riverport with the highest volume in the Heilongjiang River
Basin and the Lancangjiang River Basin. The volume of other riverports in these regions is less
than 410,000 tons each. ? In the airports, the volume of Shanghai, Beijing and Guangzhou far
exceeds that of other airports. ? Among the railports, the 4 major border-crossings of the
China Railway Express train of Hulunbeier, Xilingol, Mudanjiang and Bortala have the largest
volume. The Shenzhen Roadport and Yili Roadport are the largest roadports, with volume of
more than 22 million tons, which is equivalent to the volume of medium-sized seaports.
IPI. The scores of the IPI are shown in Tables 5 and 6. The IPI mainly has the following
characteristics: ? The IPI generally has a positive spatial clustering. High-High agglomeration
is distributed in the Pearl River Delta region. Low-Low agglomeration is distributed in a small
number of border areas and the middle and lower reaches of the Yangtze River. The
agglomeration in other areas is not significant. ? The IPI average values of the four port open regional
systems are respectively: Coastal Ports (0.013) > Inland Ports (0.009) > Ports Along the
Yangtze River (0.0014) > Border Ports (0.001). ? Shenzhen and Zhuhai, the 2 roadports connected
to Hong Kong and Macao have the largest IPI, and the IPI is greater than 0.3. They are
followed by the 3 airports of Shanghai, Beijing and Guangzhou. ? The distribution of IPI is very
uneven. Only 3 of them are larger than 0.1, and 196 of them are less than 0.01, indicating that
most of the international passenger flow is concentrated in a few ports.
It can be seen from the IPI of different regions and types of ports that the overall
international passenger flow is concentrated in the roadports and airports in the eastern coastal areas.
The roadports on the China-Vietnamese and China-Myanmar borders, and the inland
provincial capital city airports also have a large passenger flow.
CFA. The following characteristics can be seen from the scores of the port?s CFA (Tables 5
and 6, Figs 3 and 4). ? The CFA generally has a positive spatial clustering. High-High
agglomeration is distributed in the Yangtze River Delta, Pearl River Delta and Bohai Rim region.
LowLow agglomeration is concentrated in the border areas. The agglomeration in other areas is not
significant. ? The CFA average values of the four port open regional systems are: Inland Ports
(0.031) > Coastal Ports (0.027) >Ports Along the Yangtze River (0.014) > Border Ports (0.001).
? The four port cities of Shanghai, Shenzhen, Suzhou and Beijing have the largest foreign trade
volume. They are the central cities of China?s 3 most developed urban agglomerations (the
Yangtze River Delta, the Pearl River Delta and the Beijing-Tianjin-Hebei region). ? The
distribution of CFA is very uneven; it shows the scale of operations of port cities is quite different.
Comprehensive POD. Integrating the FLI, IPI and CFA, the POD (Tables 5 and 6, Figs 3
and 4) is obtained, which mainly draws the following conclusions. ? The POD generally has a
positive spatial clustering. High-High agglomeration is distributed in the Yangtze River Delta,
Pearl River Delta and Bohai Rim region. Low-Low agglomeration is concentrated in the
border areas. The agglomeration in other areas is not significant. ? The POD average score of the
four port open regional systems are: Coastal Ports (0.066) > Ports Along the Yangtze River
(0.045) > Inland Ports (0.027) > Border Ports (0.004). ? The POD of the port is a power law
11 / 20
Fig 3. Moran?s I scatter plot of POD, FLI, IPI and CFA.
distribution. The highest POD of all ports is the Shanghai Seaport at 0.699. There are 21 ports
with POD higher than 0.1, accounting for 10.1% of the sample. There are 112 ports with a
POD of less than 0.01, accounting for 54% of the sample, which indicates that only a few ports
have a high degree of openness. ? The POD of a few ports is much higher than other ports,
reflecting the hub role of these ports. ? The high POD ports are mainly seaports with vast
hinterlands and roadports connected to Hong Kong and Macao. The airports and riverports in
the Pearl River Delta and Yangtze River Delta regions are mostly at medium levels. Most of the
border ports and inland ports have low POD.
Ports evolution tree
Using the K-means clustering algorithm, the ports are divided into 7 types. A total of 207 ports
are arranged on the evolution tree, and each branch represents a type of ports. The ports on
12 / 20
Fig 4. LISA scatter plot of POD, FLI, IPI and CFA.
each branch are arranged according to the POD value. The ports far from the trunk have a
high POD value, and the ports near the trunk have a low POD value (Fig 5). Shanghai seaport
is the only Type I port, and it is a national hub port and the most open port in China. The
Type II ports are regional hub ports, including the 3 seaports of Tianjin, Qingdao and Ningbo.
Fig 5. Ports evolution tree.
The import and export passenger and cargo services of these ports are well developed, and the
openness degree is second only to Shanghai seaport. The Type III ports are ports connecting
Hong Kong and Macao, including six ports in the Pearl River Delta. They are the connecting
channels between mainland China and Hong Kong and Macao. The Type IV ports are large
ports for bulk minerals, and they include two seaports, Tangshan and Rizhao. They are China?s
main import and export ports for coal and various minerals. The Type V ports are ports that
are close to the large hub ports, including the five ports of Shanghai Airport, Shanghai
Railport, Tianjin Airport, Ningbo Airport and Qingdao Airport. These ports have similar
geographical locations to Type I and Type II ports, and have higher openness degree. The Type VI
ports are medium- and large-scale ports, including 12 ports. The passenger and cargo volume
of such ports is also large, but it is significantly less than that of Type I and Type II ports. The
Type VII ports are small ports. This type includes 178 ports. The passenger and freight traffic
and the number of countries with which foreign trade is conducted by such ports is relatively
small, so that the openness degree of these ports is relatively low.
14 / 20
Impact factor analysis
We use geodetector to analyze the seven factors and the POD. Since the geodetector is suitable
for the influence of the type variable on the dependent variable, seven factors are discretized in
spss24.0 before calculation[
As shown in Table 7, the q value of each factor represents the degree to which the factor
explains the spatial distribution of the POD. The PCE factor has the largest q value, followed
by POP and PIP. PCE has a significant impact on the distribution of POD, indicating that the
difference in export volume between different cities is large, and exports can significantly affect
POD. The p value of PIL is the smallest, indicating that the difference in the amount of
imported goods at the port has little effect on the spatial differentiation of POD.
Geographical distribution characteristics are often the result of a combination of factors, so
to explore the spatial differentiation of POD should consider multi-factor interaction. The
interaction detector in geodetector can well explain the interaction of multi-factors with
dependent variables. Among the 7 factors discussed in this study, the q values of the
interaction of the two factors are all greater than the q value of the single factor. Among them, 18
pairs of factors enhance each other, and 3 pairs are nonlinear enhancement (Table 8). This
shows that the spatial distribution difference of POD is determined by a combination of
factors, and the explanatory power of a single factor is relatively weak.
The results of ecological detector show that there are significant differences between some
factors in terms of the effect on the spatial distribution of POD. As shown in Table 9, Y
indicates a significant difference between the two factors, and N indicates that there is no
significant difference. There is a significant difference between PCE and all other factors; there is a
significant difference between POP and PIL, EMC, PCE and PCI; PIP also has significant
differences with PIL, EMC, PCE and PCI.
Discussion and conclusion
Port development is an important part of China?s reform and opening-up process. In the past
40 years, it has experienced four periods of startup, expansion, cooperation and optimization.
In the startup period, the pilot open port policy provided a platform for foreign cooperation
Notes: " denotes factors enhance each other; ? denotes nonlinear enhancement.
15 / 20
and exchange. During the expansion period, the port?s opening-up process was expanded
from the coastal ports to the inland ports, and the trade structure was continuously optimized.
The experience gained in these ports helped China?s accession to the World Trade
Organization and its full participation in economic globalization. In the cooperation period, the port
opening process was coordinated with China?s overall industrial restructuring, which
enhanced China?s overall national strength, guaranteed the implementation of its WTO
commitments, and improved the market economic system. During the optimization period, the
port opening policy paid more attention to the balance, security and efficiency of opening up
to the outside world, promoting the complementary advantages of inland and coastal areas,
and providing guarantees for national strategies such as the Silk Road Economic Belt, the 21st
Century Maritime Silk Road, and the Yangtze River Economic Belt. As gateways for China?s
opening-up to the outside world, the ports of entry followed the progress of the reform and
opening-up, and each period had different development priorities. The port regional systems
of the coast, the border, the river and the inland have been completed and the port system is
still developing and improving.
The function of ports of entry is to connect internal and external markets, transport foreign
trade goods, transport inbound and outbound passengers and facilitate foreign trade of the
hinterland cities. Our measurement of the openness degree of ports of entry is also carried out
in terms of a port?s foreign trade logistics intensity, international passenger intensity and
foreign trade. The results show that the POD has significant type differences, geographical
differences and quantitative differences. ? The POD generally has a positive spatial clustering.
High-High agglomeration is distributed in the Yangtze River Delta, Pearl River Delta and
Bohai Rim region. Low-Low agglomeration is concentrated in the border areas. The
agglomeration in other areas is not significant. ? Among the four ports open regional systems, the
POD of Coastal Ports is the highest followed by the Ports Along the Yangtze River, the Inland
Ports, and the Border Ports, respectively. ? Generally, the ports with high POD are
concentrated in the eastern coastal areas and are mostly seaports. Low-POD ports are scattered in
inland and border areas and are mostly roadports and railports. The polarization and
difference in POD of different ports is obvious. The overall POD reflects a power law distribution.
? The FLI of the seaports and riverports is the highest. The FLI in the Bohai Rim region is
higher than those of the Yangtze River Delta region and the Pearl River Delta region. The
overall difference in FLI is obvious, indicating that China?s foreign trade logistics is concentrated
in a few coastal ports. ? The overall difference in IPI is obvious. The IPI of the roadports
connected to Hong Kong and Macao in the Pearl River Delta region is the highest, followed by the
airports of the 3 first-tier cities?Beijing, Shanghai, and Guangzhou?and then the airports of
the inland provincial capital cities. ? The largest port cities in terms of foreign trade are the
core city of the Yangtze River Delta, the Pearl River Delta and the Beijing-Tianjin-Hebei
region. ? The analysis of the ports evolution tree shows that ports can be divided into 7 types.
Type I ports are the national hub, Type II ports are the regional hub, Type III ports are the
16 / 20
connecting Hong Kong and Macao, Type IV ports are the bulk mineral, Type V ports are
ports close to the hub ports, Type VI ports are medium scale ports, and Type VII ports are the
small ports. Type I to IV ports are large-scale ports with the highest openness degree. Type V
ports also have high openness degree due to better geographical advantages; Type VI and Type
VII ports have relatively small port sizes and low openness degree. ? The results of
geodetector analysis show that PCE can significantly affect the spatial differentiation of POD, while PIL
has little effect on the spatial differentiation of POD. The spatial stratified heterogeneity of
POD is determined by a combination of factors, and the explanatory power of a single factor is
relatively weak. The results of ecological detector show that there are significant differences
between some variables in terms of the effect on the spatial distribution of POD.
In summary, the eastern coastal ports have the highest openness degree, the openness of
other types of ports is generally low, and the gap between them is patent. The seaports are
close to the places of consumption and production, and international transportation is
convenient, so the high-POD ports are mainly distributed in the coastal areas. Roadports and
railports on the border usually only connect to a single country, and their openness is generally
not high. Compared with the seaports, the roadports, railports, and airports have relatively low
logistics volumes, and their POD are generally not high. The FLI, IPI and CFA are the
responses to the broadness and intensity of the POD. Only a combination of these three can
improve the comprehensive openness of the ports.
This paper analyzes the opening process of various types of ports from the perspective of
time and space evolution, the interaction between the port development process and China?s
opening up policy from the perspective of time, and the distribution characteristics of ports
and their relationship with cross-border passenger and cargo flows from a spatial perspective.
In the context of economic globalization, international trade and cross-border logistics have
developed rapidly, and the important role of ports has been highlighted. However, what
followed was the unbalanced development of different regions and different types of ports, which
hindered the coordinated development of the regional economies. This study starts from the
spatial pattern of the ports and analyzes their degrees of openness in detail. It will help to solve
the current dilemma of unbalanced port development. It can provide a theoretical basis for the
balanced development of ports and the promotion of foreign economic and trade exchanges.
At the same time, this study may have the following shortcomings. We only considered the
ports openness degree, and we did not fully describe the direction of its opening up, that is,
which countries and regions are specifically connected. The study only describes the
international passengers and logistics flow in general, and does not analyze the types of goods and
passengers. The Belt and Road Initiative was proposed 5 years ago, and China?s opening-up
situation has undergone new changes. Due to the lack of timeliness data, it has not been
discussed in detail. These issues will continue to be explored in future studies.
S1 Table. Metadata and all POD scores.
S2 Table. Details for the combination of similar ports.
Conceptualization: Xiaoshu Cao, Shengchao Li.
Data curation: Shengchao Li.
17 / 20
Formal analysis: Shengchao Li.
Funding acquisition: Xiaoshu Cao.
Investigation: Shengchao Li.
Methodology: Shengchao Li.
Project administration: Shengchao Li.
Resources: Shengchao Li.
Software: Shengchao Li.
Supervision: Shengchao Li.
Validation: Shengchao Li.
Visualization: Shengchao Li.
Writing ? original draft: Shengchao Li.
Writing ? review & editing: Shengchao Li.
18 / 20
19 / 20
1. General Administration of Quality Supervision Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China. Codes for Ports and Other Locations of the Peoples Republic of China . 2016 .
2. Brunet-Jailly E . The State of Borders and Borderlands Studies 2009 : A Historical View and a View from the Journal of Borderlands Studies . Eurasia Border Review . 2010 ; 1 ( 1 ): 1 - 15 .
3. Johnson C , Jones R , Paasi A , Amoore L , Mountz A , Salter M , et al. Interventions on Rethinking 'The Border' in Border Studies. Political Geography . 2011 ; 30 ( 2 ): 61 - 9 . https://doi.org/10.1016/j.polgeo. 2011 . 01 .002
4. Song C , Ge Y , Liu Y , Zhou S , Wu X , Hu Z , et al. Undertaking Research on Belt and Road Initiative from the Geo-Relation Perspective. Geographical Research . 2018 ;(01): 3 - 19 . https://doi.org/10.11821/ dlyj201801001
5. Rodrigue J-P , Notteboom T. The terminalization of supply chains: reassessing the role of terminals in port/hinterland logistical relationships . Maritime Policy & Management . 2009 ; 36 ( 2 ): 165 - 83 . https://doi. org/10.1080/03088830902861086 WOS: 000208055600005 .
6. Rodrigue J-P , Notteboom T. Comparative North American and European gateway logistics: the regionalism of freight distribution . Journal of Transport Geography . 2010 ; 18 ( 4 ): 497 - 507 . https://doi.org/10. 1016/j.jtrangeo. 2010 . 03 .006 WOS: 000278836900002 .
7. Tavasszy L , Minderhoud M , Perrin J-F , Notteboom T. A strategic network choice model for global container flows: specification, estimation and application . Journal of Transport Geography . 2011 ; 19 ( 6 ): 1163 - 72 . https://doi.org/10.1016/j.jtrangeo. 2011 . 05 .005 WOS: 000299148900011 .
8. Chen X , Wang S , Shi C , Wu H , Zhao J , Fu J . Robust Ship Tracking via Multi-view Learning and Sparse Representation . Journal of Navigation . 2019 ; 72 ( 1 ): 176 - 92 . https://doi.org/10.1017/ S0373463318000504 WOS: 000454299200011 .
9. Dinu O , Dragu V , Rusc? F , Ilie A , Oprea C . Intermodal Transport and Distribution Patterns in Ports Relationship to Hinterland . IOP Conference Series: Materials Science and Engineering. 2017 ; 227 ( 1 ): 012 - 38 . https://doi.org/10.1088/ 1757 -899x/227/1/012038 WOS: 000409221600038 .
10. Ha M-H , Yang Z , Notteboom T , Ng AKY , Heo M-W. Revisiting port performance measurement: A hybrid multi-stakeholder framework for the modelling of port performance indicators . Transportation Research Part E: Logistics and Transportation Review . 2017 ; 103 : 1 - 16 . https://doi.org/10.1016/j.tre. 2017 . 04 .008 WOS: 000404324800001 .
11. Hilmola O-P , Henttu V. Border-Crossing Constraints , Railways and Transit Transports in Estonia. Research in Transportation Business & Management. 2015 ; 14 : 72 - 9 . https://doi.org/10.1016/j.rtbm. 2014 . 10 .010 WOS: 000214956500009 .
12. Monios J , Wilmsmeier G. Port-Centric Logistics , Dry Ports and Offshore Logistics Hubs: Strategies to Overcome Double Peripherality? Maritime Policy & Management. 2012 ; 39 ( 2 ): 207 - 26 . https://doi.org/ 10.1080/03088839. 2011 .650720
13. Notteboom TE , Rodrigue J-P. Port Regionalization : Towards a New Phase in Port Development . Maritime Policy & Management . 2005 ; 32 ( 3 ): 297 - 313 . https://doi.org/10.1080/03088830500139885
14. Cong Z , Yu T , Tianfu Y. The Investigation of the Frontier Ports Economy of the East of Northeast . Economic Geography . 2010 ;(12): 1937 - 43 . https://doi.org/10.15957/j.cnki.jjdl. 2010 . 12 .010
15. Guo L. Distribution of Ports in China . Acta Geographica Sinica . 1994 ;(05): 385 - 93 . https://doi.org/10. 11821/xb199405001
16. Hu Z. Frontier Advantage Theory and Border Port Construction . Urban Problems . 1993 ;(03): 30 - 3 +2. https://doi.org/10.13239/j.bjsshkxy.cswt. 1993 . 03 .011
17. Xia Q. China Port: Developing External Portal . International Economic Cooperation . 1994 ;(10): 10 - 3 .
18. Xu L , Yang Y , Yaxiong Y . On the Characteristics and Development Path of Northwest Border Ports . Journal of Northwest Normal University(Social Sciences) . 2017 ;(03): 76 - 85 . https://doi.org/10.16783/j. cnki.nwnus. 2017 . 03 .010
19. Yu X , Fang C , Luo K , Chuanglin F , Kui L. Comprehensive Evaluation of the Advantage Value of Geopolitical Strategy of Frontier Port Cities Under the Background of the Silk Road Economic Belt . Arid Land Geography . 2016 ;(05): 967 - 78 . https://doi.org/10.13826/j.cnki.cn65- 1103 /x. 2016 . 05 .006
20. Zhang G , Zhao L , Zhang H , Ling Z , Hongbo Z. The Distribution and Feature of the Chinese Frontier Port System . Jilin Normal University Journal (Natural Science Edition) . 2003 ;(03): 57 - 9 . https://doi.org/10. 16862/j.cnki.issn1674- 3873 . 2003 . 03 .019
21. Chen S. A Study on Spatial Structure of the Open Ports in Heilongjiang Province . World Regional Studies. 2002 ;(03): 50 - 6 . https://doi.org/10.3969/j.issn. 1004 - 9479 . 2002 . 03 .008
22. Huang X. A Spatial Analysis of Boundary Trade Port of Guangxi To Vietnam . World Regional Studies. 2001 ;(02): 91 - 5 . https://doi.org/10.3969/j.issn. 1004 - 9479 . 2001 . 02 .014
23. Wang W , Wang C , Chengjin W. Spatial Evolution of Coal Transportation of Coastal Ports in China . Acta Geographica Sinica . 2016 ;(10): 1752 - 66 . https://doi.org/10.11821/dlxb201610008
24. Zhang B , Bo B , Bin B . Construction of the Logistics System of the Sino-Vietnamese Trading Ports in the Process of Implementing Yunnan's Gateway Strategy . Journal of Yunnan University of Nationalities (Social Sciences) . 2013 ;(02): 108 - 12 . https://doi.org/10.13727/j.cnki. 53 -1191/c. 2013 . 02 .020
25. Deng F , Zhang X , Yang D , Liu H , Xiaolei Z , Degang Y , et al. Mathematical Analysis of Spatial Development Mode of Port Region in Xinjiang. Arid Land Geography . 2006 ;(03): 422 - 6 . https://doi.org/10. 13826/j.cnki.cn65- 1103 /x. 2006 . 03 .026
26. Liang Z , Chen C , Cai C. Research on Development Strategy of the Sino-Russian Border City of Manzhouli . World Regional Studies. 2012 ;(02): 97 - 104 . https://doi.org/10.3969/j.issn. 1004 - 9479 . 2012 . 02 . 012
27. Wang J , Cheng Y , Mo H. The Spatio- Temporal Distribution and Development Modes of Border Ports in China . Sustainability. 2014 ; 6 ( 12 ): 7089 - 106 . https://doi.org/10.3390/su6107089 WOS: 000344355700032 .
28. Wang L , Liu L , Li L . Opening to Outsides along Border of Northeast China and Developing of Border Economy . Economic Geography . 1999 ;(05): 21 - 3 + 127 . https://doi.org/10.15957/j.cnki.jjdl. 1999 . 05 .005
29. Feng G , Ding S , Sibao D. Retrospect and Prospect of the Cross-Border Cooperation Study . World Regional Studies . 2005 ;(01): 53 - 60 . https://doi.org/10.3969/j.issn. 1004 - 9479 . 2005 . 01 .009
30. Gu X , Womack B . Border Cooperation between China and Vietnam in the 1990s . Asian Surv . 2000 ; 40 ( 6 ): 1042 - 58 . https://doi.org/10.1525/as. 2000 . 40 .6.01p0116g
31. Song Z , Che S , Wang Je , Zheng L , Shuyun C , Jiao'e W , et al. Spatiotemporal Distribution and Functions of Border Ports in China . Progress in Geography. 2015 ;(05): 589 - 97 . https://doi.org/10.11820/ dlkxjz. 2015 . 05 .007
32. Wei H , Sheng Z. Logistics connectivity considering import and export for Chinese inland regions in the 21st-Century Maritime Silk Road by dry ports . Maritime Policy & Management . 2018 ; 45 ( 1 ): 53 - 70 . https://doi.org/10.1080/03088839. 2017 .1403052 WOS: 000428749000005 .
33. Guo J , Han Z , Zenglin H. Review and Prospect of the Research on Spatial Connection between Port and City . Progress in Geography. 2010 ;(12): 1490 - 8 . https://doi.org/10.11820/dlkxjz. 2010 . 12 .004
34. Wang Y , Li F , Gu Y , Tong Y , Fuxiang L , Yi G , et al. Research on the Relationship of Ports and Port-Cities in Northeast Border of China base on Relative Concentration Index . Modern Urban Research . 2014 ; (07): 55 - 60 . https://doi.org/10.3969/j.issn. 1009 - 6000 . 2014 . 07 .009
35. Zhang L , Zhang L , Li D , Long Z , Dan L . An Empirical Study of the Influence of Port Development on the Development of Border Port Towns--Exemplified by Erlianhot . Journal of Minzu University of China (Philosophy and Social Sciences Edition) . 2016 ;(01): 109 - 16 . https://doi.org/10.15970/j.cnki. 1005 - 8575 . 2016 . 01 .015
36. Zhang P-y, Ma Y-j, Yu Z-h . Border Port Manzhouli: Urban Function and Space Development. Chin Geogr Sci . 2002 ; 12 ( 4 ): 315 - 20 . https://doi.org/10.1007/s11769-002-0035-7 WOS: 000206553300005 .
37. Zhou Y , Zhang L , Li Z. The Foreign-oriented Hinterland of Chinese Port-cities . Scientia Geographica Sinica . 2001 ;(06): 481 - 7 . https://doi.org/10.13249/j.cnki.sgs. 2001 . 06 .001
38. Dai A . On Trading Ports Along Western Border Areas in Modern China . Fudan Journal(Social Sciences Edition) . 2005 ;(04): 71 - 9 . https://doi.org/10.3969/j.issn. 0257 - 0289 . 2005 . 04 .009
39. Fang S. The Opening of the Ports to the Outside World and the Formation of the Economic Zone in the Late Qing Dynasty: A Case Study of Lingnan and its Influence in China . Journal of Yunnan University (Social Sciences Edition) . 2006 ;(04): 41 - 52 + 95 . https://doi.org/10.3969/j.issn. 1671 - 7511 . 2006 . 04 .007
40. Mao L. Evolution of the Shipping Lines and the Harbor Potential of the Southeastern Treaty Ports in the Late Qing Period . Journal of Historical Science . 2005 ;(12): 37 - 43 . https://doi.org/10.3969/j.issn. 0583 - 0214 . 2005 . 12 .009
41. Leamer E . Measures of Openness. Trade Policy Issues and Empirical Analysis . 1988 : 147 - 200 .
42. Openness Edwards S., Productivity and Growth: What Do We Really Know? Econ J. 1998 ; 108 ( 447 ): 383 - 98 . https://doi.org/10.1111/ 1468 - 0297 . 00293
43. Sachs J , Warner A . Economic Reform and the Progress of Global Integration . Harvard Institute of Economic Research Working Papers. 1995 ; 35 ( 1 ): 1 - 118 . https://doi.org/10.2307/2534573
44. Stewart TP , Johanson DS . Policy in Flux: The European Union's Laws on Agricultural Biotechnology and Their Effects on International Trade . Drake Journal of Agricultural Law . 1999 ; 4 : 243 .
45. Dollar D. Outward-Oriented Developing Economies Really Do Grow More Rapidly: Evidence from 95 Ldcs , 1976 - 1985 . Econ Dev Cult Change. 1992 ; 40 ( 3 ): 523 - 44 . https://doi.org/10.1086/451959
46. Dems?ar U , Harris P , Brunsdon C , Fotheringham AS , McLoone S. Principal Component Analysis on Spatial Data: An Overview . Ann Assoc Am Geogr. 2013 ; 103 ( 1 ): 106 - 28 . https://doi.org/10.1080/ 00045608. 2012 .689236
47. Chen W , Pan R , Wang X , Runqiu P , Xinyi W. Spatial-Temporal Evolution and Its Driving Mechanism of Economic Opening Rate of Provinces in China . Geography and Geo-Information Science . 2016 ; (03): 53 - 60 . https://doi.org/10.3969/j.issn. 1672 - 0504 . 2016 . 03 .011
48. Veenstra AW , Mulder HM , Sels RA . Analysing Container Flows in the Caribbean . Journal of Transport Geography . 2005 ; 13 ( 4 ): 295 - 305 . https://doi.org/10.1016/j.jtrangeo. 2004 . 07 .006
49. Fremont A . Global Maritime Networks: The Case of Maersk. Journal of Transport Geography . 2007 ; 15 ( 6 ): 431 - 42 . https://doi.org/10.1016/j.jtrangeo. 2007 . 01 .005 WOS: 000251779900003 .
50. Anselin L , Florax RJGM , Rey SJ . Econometrics for Spatial Models : Recent Advances: Springer, Berlin, Heidelberg; 2004 . 1 -25 p.
51. Anselin L , Syabri I , Kho Y. GeoDa: An Introduction to Spatial Data Analysis . Geographical Analysis . 2006 ; 38 ( 1 ): 5 - 22 . https://doi.org/10.1111/j.0016- 7363 . 2005 . 00671 .x
54. Wang J-F , Liu X-H , Peng L , Chen H-Y , Driskell L , Zheng X -Y. Cities evolution tree and applications to predicting urban growth . Population and Environment . 2012 ; 33 ( 2 ): 186 - 201 . https://doi.org/10.1007/ s11111-011-0142-4 WOS: 000304167400005 .
Wang JF , Li XH , Christakos G , Liao YL , Zhang T , Gu X , et al. Geographical Detectors-Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China . Int J Geogr Inf Sci . 2010 ; 24 ( 1 ): 107 - 27 . https://doi.org/10.1080/13658810802443457
Wang J-F , Zhang T-L , Fu B-J. A measure of spatial stratified heterogeneity . Ecol Indic . 2016 ; 67 : 250 - 6 . https://doi.org/10.1016/j.ecolind. 2016 . 02 .052
55. China Association of Port-of-Entry. China's ports-of-entry yearbook . Beijing: China Customs Press; 2001 .
56. Kaiser HF . A second generation little jiffy . Psychometrika . 1970 ; 35 ( 4 ): 401 - 15 . https://doi.org/10.1007/ BF02291817