J. Service Science & Management, 2009, 2: 71-79
Published Online June 2009 in SciRes (www.SciRP.org/journal/jssm)
Evaluation and Analysis: Development Trend of
China’s Logistics Industry under Supply Chain
Globalization Environments
Juping Shao1,2, Tianyun Ma3, Shaohua Dong2, Xianghua Meng1
1School of Management, Ludong University, Yantai, Shandong Province, China; 2Department of Logistics Engineering, University
of Science and Technology, Beijing, China; 3School of Civil Engineering, Ludong University, Yantai, Shandong Province, China.
Received February 20th, 2009; revised April 21st, 2009; accepted May 25th, 2009.
ABSTRACT
First in this paper a systematic and comprehensive hybrid index evaluation system of regional logistics competitiveness
is designed according to the characteristics of China’s regional logistics system under supply chain globalization envi-
ronments, and systematic analysis and discussion of the connotation of the various factors in the index evaluation sys-
tem are made. Then based on hierarchy analysis thought and fuzzy decision-making principles, the development trend
of China’s regional logistics industry is assessed systematically and comprehensively. With the result of the above as-
sessment, the key factors and the gradual evolution process of promoting regional logistics industry competitiveness
under supply chain globalization environments are discussed. Also, in this paper it points out that enhancing the
strength of urban logistic enterprises will promote the competitiveness of regional logistics industry. And the logistics
competitiveness of a few major economic zones in China is discussed with conclusion that discrepancy exists in terms of
China’s provincial capital city’s logistics development. At last, development strategies for regional logistics are put
forward aimed at the west regions of China which have weak competitiveness in logistics industry.
Keywords: supply chain globalization environment, regional logistics, developmental trend, evaluation and analysis
1. Introduction
From the late 1990s, a new round of international indus-
trial transfer, which is characterized by the transfer of
manufacturing industry from developed countries to
China as well as other eastern Asian countries, has been
on the increase with the rise of knowledge economy and
the acceleration of global economy. This has accelerated
the globalization of supply chains, and hence has made
regional logistics more demanding [1]. The level of lo-
gistics industry development has become an important
indicator, which is used to measure the quality of the
regional investment environment, but also becomes an
accelerator to the regional economy. To enhance the ca-
pability of regional logistics system under supply chain
globalization environments and to improve the invest-
ment environment so that to attract more investment
capital, each region should accelerate the construction of
infrastructure investment, based on the scientific and
rational planning of the regional logistics development,
and integrate and optimize the traditional logistics indus-
try and improve the concentration of regional logistics
industry, which plays an important role in enhancing the
regional comprehensive competitiveness and the sus-
tainable development of regional economy under supply
chain globalization environments.
Based on the statistical data of China’s four munici-
palities and 27 provincial capital cities related to the lo-
gistics industry in 2007 and a tentative construction of
the assessment index system for regional logistics de-
velopment, applying the thought of hierarchy analysis
[2] , fuzzy pattern recognition principles and fuzzy con-
sistent judgment matrix [3,4,5,6], the article offers the
hybrid index hierarchy fuzzy decision-making method to
synthetically analyze and evaluate the development trend
of Chinese regional logistics.
2. The Construction of Evaluation Index and
the Data Standardization Processing
2.1 The Construction of Evaluation Index
The competitiveness of area logistics is the joint force
from the interplay of various factors. According to the

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG 72
characteristics of regional logistics and following some
principles about evaluation index, the paper summarizes
the evaluation index system into 12 index of first class
i
M
(for i=1,2,….,12), including such elements as eco-
nomic situation, the logistics volume, the logistics indus-
try practitioners, the logistics facilities and equipments,
the logistics industry costs, postal communications status,
foreign investment, the standard of education, science
and technology, trade status, information status, geo-
graphical situation and industrial policy environment.
Those first class index elements include 22 second class
index which is indicated by (represent the jth sec-
ond-degree index about the ith first class index in the kth
evaluated region), and all these elements compose a three-
tier system of mixed indicators, as shown in Figure 1.
k
ij
S
(1) Economic situation 1
M
: including the monthly
average wage of all workers and the employment staff in
per 10,000 people. These indicators comprehensively
reflect the socio-economic basis of the regional logistics
development.
(2) The logistics volume 2
M
: mainly includes the
goods turnover per capita. The indicator reflects the de-
mand of the situation and the scale in the regional logis-
tics services.
(3) The logistics industry practitioners 3
M
: mainly
includes Logistics industry practitioners in per 10,000
employment staff. The indicator reflects the needing
situation of the human resources in the regional logistics
industry development.
(4) The logistics facilities and equipments 4
M
: mainly
includes per capita area of the road, per 10,000 people
the number of having transport vehicles, per capita in-
vestment of the logistics industry, per 10,000 people the
number of having public transport vehicles. These indi-
cators reflect the infrastructure conditions of a regional
logistics industry development from different angles.
(5) The logistics industry costs 5
M
: mainly includes
per 10,000 people the output of logistics industry, per
10,000 people the increase amount in the inventory, and
the two indicators reflect the effectiveness of the regional
logistics industry from different perspectives.
(6) Postal communications status 6
M
: mainly in-
cludes per 10,000 people the number of owning Mobile
Phone, per 10,000 people the number of having Internet,
per 10,000 people the number of having sub-post office.
These indicators reflect the information infrastructure
status of the regional logistics development from differ-
ent perspectives.
(7) Attract foreign investment status7
M
: mainly in-
cludes per 10,000 people the amount of having foreign
capital investment, the indicator reflects the vitality and
attractive situations of the regional logistics industry
development.
(8) The standard of education, science and technology
8
M
: mainly includes per 10,000 people the number of
having college students in school, per capita the amount
of education expenditure spending, logistics and infor-
mation industry technology professionals in per 10,000
employment staff, these indicators reflect trained per-
sonnel resources status of the regional logistics industry
development from different perspectives.
(9) Trade status 9
M
: mainly includes per capita the
wholesale/retail trade amount of year-end inventory, per
capita total import/export amount of goods, the two in-
dicators reflect the needs conditions and needs scale of
the regional logistics service from trade perspectives.
(10) Information Condition 10
M
: indicates by infor-
mation index, the information index is an important in-
dicator, which reflects the competitiveness of a region in
the information age. It is comprehensively calculated by
20 indicators of six aspects, which includes the devel-
opment and utilization of resources, information network
construction, the application of information technology,
Figure 1. Regional logistics system evaluation index system

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG73
information products and services, information human
resources and the development environment of informa-
tion.
(11) Geographical condition11
M
: geographic location
is obviously one of the important factors influencing the
development of the logistics industry.
(12) Industrial policy environment12
M
: the local in-
dustry system, industrial policies and market economy
atmosphere and the idea and consciousness of the local
people have a wide impact on the development of logis-
tics industry, so industrial policy environment also af-
fects the development of the logistics industry as one of
the important factors.
2.2 Determine Evaluation Index Set
According to AHP, Figure 1 shows the evaluation index
system, which consists of the target layer
A
, middle
layer (first class index) i
M
,and the bottom layer (sec-
ond-degree index) (represent the jth second-degree
index about the ith first class index in the kth evaluated
region).
k
ij
S
A
is the set of first class index i
M
, of which
the notation is .
12
, ,......,M M{AM }
m i
M
(for
i=1,2,…,m) is the set of second-degree index (for
, and is the number of second-degree
index in the ith first class index) , and use the
set
k
ij
S
1, 2,
,
i
..., i jn
{
i
n
...,
12
,...
ii
kk }
in
k
i
M
SSSto represent. Then
1
m
A
Mi
i


 ,
ij
M
Mij

 (1)
,
xy
kk
ijijx y
SS jj  
1, 2,....,
x
i
jni n (2) 1, 2,....,
y
j
2.3 Handle the Mixed Indicator k
ij
S
Let’s suppose that the number of evaluated region is n
and the number of first class index is m. For an evaluated
region k, ()
ij
k
f
x () is the jth value of the
second-degree index in the ith first class index
1, 2,,k
k
ij
S
n
i
M
.
Now define the target characteristic matrix of the ith first
class index by (())
ij i
k
in
Xfx
n

.
We compute quantitative indexes by basic date. As for
the qualitative index in the article, the set of fuzzy lan-
guage is defined as, in which,
EG=extremely good, VG=very good, G=good, F=fair,
P=poor. The definite value is determined by experts giv-
ing a mark according to actual circumstance. Fuzzy
value is indicated with (0, 1). In the article, the “geo-
graphic situation” and the “industrial policy environ-
ment” are two qualitative indicators in first class index,
and the definition of evaluation indicators for the as-
sessment as VG value of 0.95, evaluation indicators as-
sessed as G value 0.85, evaluation indicators assessed
value of 0.75 for F and evaluation indicators for the as-
sessment of P value was 0.65, for the VP to inform the
evaluation index value of 0.55. The final value of each
qualitative index is the average points of all the experts’
points.
L = {EG,VG,G,F,P}
2.4 The Data Standardization Processing
To eliminate the effect of different indexes unit, and to
integrate quantitative indexes and qualitative indexes, we
need to process all indexes data so that they are stan-
dardization data.
For each index,
k
ij
S()
ij
k
x
 is the standardization
value of the jth second-degree index about the ith first
class index in the kth evaluated region .When the index
original data is ()
ij
k
f
x, the definition of standardization
value ()
ij
k
x
 is determined by the following equation
() ()
()
1, 2,....,
1, 2,....,
1, 2,,
ij ij
ij
kk
k
i
f
xfx
xs
im
jn
kn






(3)
In the equation,
2
1
(() ())
ij ij
n
kk
k
f
xfx
sn


 (4)
1
()
()
ij
ij
n
k
kk
f
x
fx n

 (5)
From Formula (3), the standardization evaluation ma-
trix of all indexes is obtained. This is written as follows:
(())
ij i
k
in
Rx 
n

.
Applying Formulae (3), (4) and (5), the original data
of China’s four municipalities and 27 province capital
cities can be processed and standardized. The processing
results are shown in Table 1.
3. Fuzzy Subset of Index Weight
To avoid the problem of poor uniformity of judgment
matrix in the process of computing weight in AHP, we
use fuzzy consistent judgment matrix G which exist in
fuzzy consistent relations to obtain weight. Suppose that

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG 74
Table 1. The results of data standardization processing
Note: The source of statistical original data is rooted in the reference literature [7], [8] and [9] which were computed simply. Because there were a
large number of statistical indexes and original data, but the paper length is limited, so only part of the results of data standardization proc-
essing was shown in table1 in the article.
i

(for ) is first class indexes weight, and 1,...,im
ij

(for，and ) is second-degree
index weight; We have
1, ..,im1, 2,....,i jn
1
j

11
1
i
n
m
ii
ij




(6)
Computing the index weight process is as follows:
Step 1 Establish optimal choice relationship matrix
()
ii
p
qnn
F 


The value of
p
q

in this matrix separately is 0.5 (the
importance of the two indexes is on the same level), 0.0
(one index is less importance than another), 1.0 (one
index is more importance than another). The relative
importance degree of the index is given by the experts
beforehand.
According to the relevant data and the experts’ judg-
ment, establish the optimal choice relationship matrix
F
of the first class indexes are shown as follows:
0.511111111111
00.51011100000
000.5001100000
0110.511111111
00100.51100000
000000.5100000
0000000.500000
01101110.51111
011011100.5111
0110111000.500
01101110010.51
011011100100.5
F



























In addition, according to the actual situation of evalua-
tion indexes design, the second class indexes which are
related with a first class index are of same importance,
that is, the value of
p
q

in optimal choice relationship
matrix ()
ii
p
qnn
F 

 is 0.5. Thus the optimal choice
relationship matrix of the second class index is omitted.
Step 2 Establish fuzzy consistent judgment matrix
()
ii
p
qnn
Gr


Region 11

12

21

31

41

42

43

44

ij

Peking 2.29 0.70 -0.63 -0.21 0.36 0.09 -0.34 3.25 …
Tianjin 0.91 -0.82 2.70 -0.19 -0.03 -0.38 -0.59 0.09 …
Shanghai 2.70 -0.06 3.79 0.01 1.76 0.86 0.37 1.47 …
Nanjing 0.30 1.29 0.09 -0.40 2.28 0.98 2.97 -0.31 …
Hangzhou 1.47 0.20 0.24 -0.29 1.91 3.42 1.62 0.19 …
Hefei -0.76 0.00 -0.15 -0.31 0.45 -0.99 -0.29 -0.49 …
Fuzhou 0.01 -0.05 -0.21 -0.36 0.25 -0.82 -0.07 0.10 …
Nanchang -0.77 -0.44 -0.46 -0.22 -0.35 -1.19 0.25 -0.39 …
Jinan -0.35 2.15 1.27 -0.36 0.82 -0.27 0.05 -0.73 …
Zhengzhou -0.72 1.76 0.16 -0.31 -0.37 -1.17 1.51 -0.43 …
Wuhan -0.74 0.75 -0.21 -0.18 -0.06 -0.88 0.56 -0.39 …
Changsha -0.42 0.24 -0.14 0.58 -0.47 -0.98 0.33 -0.25 …
Guangzhou 1.19 2.16 0.85 -0.24 0.20 0.34 2.51 -0.70 …
Chongqing -0.38 -0.73 -0.68 -0.12 -1.47 0.64 -0.66 -0.50
k … … … … … … … … …

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG75
1
,1,2,
0.5
2
i
n
p
pk i
k
pq
pq
i
rp
rr
rn





From the literature [10] we know that G meets fuzzy
consistent relationship. Thus, according to Formula (7)
and optimal choice relationship matrix
F
, we could
establish fuzzy consistent relationship matrix of the
first class index as follows:
G
n
(7)
0.50.792 0.875 0.542 0.8330.917 0.9580.583 0.6250.750.667 0.708
0.7920.50.583 0.250.542 0.6250.667 0.292 0.3330.458 0.375 0.417
0.8750.583 0.50.167 0.458 0.5470.5830.208 0.250.375 0.292 0.333
0.5420.250.167 0.50.7920.875
G
0.9170.542 0.5830.708 0.625 0.667
0.833 0.5420.4580.7920.50.5830.6250.250.2920.4170.3330.375
0.9170.625 0.5470.875 0.5830.50.542 0.1670.2080.333 0.250.292
0.9580.667 0.5830.917 0.6250.542 0.50.1250.1670.292 0.2080.25
0.5830.292 0.2080.542 0.250.167 0.1250.50.5420.667 0.5830.625
0.6250.333 0.250.583 0.292 0.2080.1670.542 0.50.6250.542 0.583
0.750.4580.375 0.708 0.4170.333 0.2920.667 0.6250.50.4170.458
0.6670.375 0.2920.625 0.333 0.250.2080.583 0.5420.417 0.50.542
0.7080.417 0.3330.667 0.3750.292 0.250.625 0.5830.458 0.542 0.5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Step 3 Computes the largest eigenvalue of G, after
Normalization of the corresponding vector, we can get
i

and ij

.
Applying the tool of MATLAB or SPSS, we can eas-
ily obtain the greatest eigenvalue max 0.6148

 about
G , and the largest eigenvalue corresponding eigenvector
as follows:
 
max 0.40190.27760.24980.33450.29190.28790.28950.23820.24710.28390.25170.2712
T

 
After eigenvector max


normalized, we get the weight about first class index as follows:
 
0.1170.081 0.0730.0980.0850.0840.0850.0700.0720.0830.0740.080
T
 
The weights about second-degree index are shown in
the Table 2.
4. Comprehensive Evaluation
Suppose is the first class index evaluation value ()
k
i
ux
of the kth evaluated region, is the evaluation (())
kk
Ai
Uux
value for overall objective
A
of the different first class
index of the kth evaluated region, so and ()
k
i
ux (())
kk
Ai
Uux
can be computed by following:
1
( )( )1,2,...,
i
ij
n
kk
iij
j
uxx im 


 (8)
Table 2. The weights about second-degree index
k
ij
S 11
s
12
s
21
s
31
s
41
s
42
s
43
s
44
s
51
s
52
s
61
s
ij

0.5 0.5 1 1 0.25 0.25 0.25 0.25 0.5 0.5 0.33
k
ij
S 62
s
63
s
71
s
81
s
82
s
83
s
91
s
92
s
101
s
111
s
121
s
ij

0.33 0.33 1 0.33 0.33 0.33 0.5 0.5 1 1 1

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG 76
1
(()) ()
m
kk k
Ai ii
i
Uux ux 

 (9)
applying Formulae (8) and (9), we can get the overall
objective vector of Chinese
evaluated 31 regions. Sorting each components of the
vector from large to small, we get the sort order of
different region logistics development trend, as shown in
Table 3.
12
(,, ,)
k
AA AA
UUUUU
n
U
5. Analysis of the Evaluation Results
We could roundly analyze to the evaluation results
shown in the Table 3 as the following:
(1) Urban logistics industry competitiveness are
closely related with the economic situation of the whole
city, logistics facilities and equipment, logistics industry
costs, attractiveness of foreign investment, trade and
information etc.. Competitive cities are superior to weak
competitiveness cities in these indexes in Table 3. In
addition, in the process of evaluation, the use of fuzzy
consistent judgement matrix to calculate the weights of
these indexes is also larger than other. Therefore, the
various decision-making which are about the regional
logistics industry development should be focused on
these indexes. It is necessary to point out that the re-
gional economic conditions are closely related to the
level of the regional logistics industry development. The
regional logistics industry development has a strongly
pulling effect for the regional economic development,
and the regional economic development has a reverse
effect on the regional logistics system, which can pro-
mote its development. Thus the two aspects are interde-
pendent and mutually prerequisite.
(2) It is a step-by-step process that the development of
the urban logistics industry and enhancing the overall
competitive strength of the city. Because it involves
many factors, and in particular the construction of logis-
tics infrastructure needs huge amount of investment,
based on their own status of the logistics industry com-
petitive strength which compared with surrounding areas,
every region should think carefully, and rationally ana-
lyze and make a strategic decision. In working out vari-
ous policy measures about the regional logistics devel-
opment planning, firstly, it must be identified that their
own strengths and weaknesses of the logistics industry,
and it should have a systematic and in-depth analysis to
these factors such as production conditions, supply and
demand conditions, and support industries and so on,
which are related with logistics industry development so
that it can be located accurately that the development of
the urban logistics industry. At the same time, it should
pay attention to the coordination between the regions and
attach importance to the complementary and sharing of
logistics resources in the same economic, and avoid the
mechanical and blind and redundant construction of lo-
gistics projects in the same economic region. If that's the
case, it might make these logistics projects no joint
forces and have no characteristics or competitive advan-
tages, even idle.
(3) Logistics enterprises are the main part of urban lo-
gistics industry, therefore the key measures and strate-
gies of promoting the competitiveness of the logistics
Table 3. Sort order of different region logistics competence
Region k
A
U Region k
A
U Region k
A
U
Shanghai 3.500 Zhengzhou 0.081 Yinchuan -0.241
Peking 3.185 Chengdu 0.072 Lanzhou -0.283
Guangzhou 1.355 Harbin 0.045 Nanning -0.309
Hangzhou 0.957 Changsha 0.014 Haikou -0.331
Nanjing 0.548 Xi’an 0.003 Guiyang -0.417
Tianjin 0.498 Changchun -0.007
Jinan 0.444 Taiyuan -0.116
Shenyang 0.382 Chongqing -0.119 *Urumchi 0.010
Shijiazhuang 0.337 Kunming
－0.154 *Xining -0.148
Fuzhou 0.135 Hefei －0.164 *Lhasa -0.082
Wuhan 0.103 Nanchang -0.236 *Hohhot -0.009
Note: The statistical original data of partial indexes of Xining, Lhasa, Urumchi and Hohhot were incomplete, so the result of sort order about these
cities have windages in Table 3.

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG77
industry is to increase the strength of urban logistics en-
terprises. The evaluation results indicate that if the com-
petition of city is strong, the number and overall strength
of its logistics business are also strong. It is necessary to
give priority to cultivate some logistics enterprises which
have characteristics, brand effects and strong exemplary
role in urban development of the logistics industry. The
world famous logistics companies such as UPS, FedEx,
DHL, and APL are positioning their own different char-
acteristics, thereby forming its own unique, differentiated
competitive advantage. Therefore, local governments
should not only innovate in logistics management
mechanism, but also strengthen macro guidance to the
logistics enterprises, and make efforts to cultivate logis-
tics enterprise groups which have different core business
capabilities. All of these are of great significance to
promote the regional logistics competitiveness.
(4) The evaluation results show that the Beijing-Tian
jin-Hebei Economic Area with Beijing and Tianjin as the
representative, the Yangtze River Delta Economic Area
with Shanghai and Nanjing as the representative, and the
Pearl River Delta Economic Zone with Guangzhou and
Shenzhen as the representative are relatively developed
and have stronger competitive power in the logistics in-
dustry. This is mainly because these three economic
zones have stronger economic strength, and the devel-
opment of the logistics industry has a stronger economic
base. In addition, the geographical position and macro-
economic environment of these three economic zones are
better, and these provide unique favorable conditions for
the development of the logistics industry. We discuss
these three economic zones respectively as follows:
1) Beijing-Tianjin-Hebei Economic Area: The Bei-
jing-Tianjin-Hebei Economic Area is located in the
heartland of the around Bohai sea economic circle, and it
is one of the most intensive areas of the Chinese city
zones, industrial parks and port area. In the coastline of
Beijing-Tianjin-Hebei Economic Area, Tianjin port is in
the middle, and the Huanghua Port, Jingtang Port and
Qinhuangdao Port respectively are in the left and right,
the throughput of Tianjin and Qinhuangdao Port are
more than 100 million tons. Around the four major ports,
there are vertical and horizontal cutting railway and
highway traffic net. Through these transportation net-
work, Beijing-Tianjin-Hebei Economic Area and its sur-
rounding areas are closely related. The Beijing Interna-
tional Airport and Tianjin international airport have be-
come the Beijing-Tianjin-Hebei Economic Areas’ inter-
national air cargo centre. Therefore, the Beijing-Tianjin-
Hebei Economic Area has developed economy and tal-
ents. It is relatively perfect in logistics infrastructure.
Also the Beijing-Tianjin-Hebei Economic Area is the
heartland of China and northeast Asia’s junction, and it
connect the north and northwest China, and face the Pa-
cific, therefore, it has geographical superiority to develop
modern logistics industry in the Beijing-Tianjin-Hebei
Economic Area. Also because of the 2008 Beijing
Olympic Games, the Beijing-Tianjin-Hebei Economic
Area has brought further development and new opportu-
nities and has injected new vitality for the logistics in-
dustry. The logistics industry of the Beijing-Tianjin-He
bei Economic Area is expected to achieve greater devel-
opment.
2) The Yangtze River Delta economic zone: The Ya-
ngtze River Delta economic zone is located in the en-
trance of the Yangtze river to the sea. It is one of the
largest core economic zones in China. There are 600 km
coastline and many ports like Shanghai, Ningbo, Hong
Kong, Nanjing, Zhenjiang which can reach more than
160 countries and regions by sea in the Yangtze River
Delta economic zone. The air and land transport are also
highly developed, the Shanghai Pudong Airport and
Hongqiao Airport have become the international air
cargo centre of the Yangtze River Delta economic zone.
Advanced highway and the railway network are also
excellent in China. In the Yangtze River Delta economic
zone, the integrated transport system has been prelimi-
narily formed through the common development of the
various modes of transportation such as highways, wa-
terways, rail, air, pipeline and other transportation mode,
coupled with favorable natural conditions and obvious
geographical advantages, the Yangtze River Delta Eco-
nomic Zone has become one of the most dynamic eco-
nomic regions of China’s logistics industry development.
3) The Pearl River Delta Economic Zone: The Pearl
River Delta Economic Zone is the first known to the
Chinese economic region, one of the earliest beneficial
areas of the policy of reform and opening-up in China.
The obvious geographical advantages and preferential
policies have brought unprecedented prosperity. In the
economic area, we can find intensive industries, capi-
tal-intensive and talent-intensive. Like the Yangtze River
Delta economic zone, the superiority of transportation
system is prominent in the Pearl River Delta Economic
Zone. There are five big ports like Guangzhou Port,
Shenzhen Port, Zhanjiang Port, Shantou ports and Zhu-
hai port. It has five big airports such as Hong Kong,
Shenzhen, Guangzhou, Zhuhai and Macao. Beijing-
Guangzhou, Beijing-Kowloon, and Beijing-Zhuhai
Railway all pass through Pearl River Delta Economic
Zone. And its internal, high-speed transportation network
is also developed. The PRD has formed the three-dimen-
sional, international and all-round development traffic
patterns, and the logistics industry has become the pow-
erful backing of the regional economic development in
the Pearl River Delta Economic Zone.
(5) The evaluation results show that: Imbalance marks
the development of the logistics industry in the provin-

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG 78
cial capital cities of China. The development of the lo-
gistics industry has a strong gap between the Chinese
northwest and southwest cities and the cities in the three
major economic regions. In the three major economic
regions, the urban logistics industry is more competitive,
while in the northwest and south-western cities, the lo-
gistics industry is less competitive, especially in the
north-western cities, logistics industry is in the weak
position. The natural and social environments jointly
lead to the imbalance of logistics industry development,
and also the unbalanced problems of economic devel-
opment urgently need to be solved in China.
In China’s western regions there are 10 provinces,
municipalities, and autonomous regions. It has a total
land area of about 5.4 million square kilometres, ac-
counting for 56% of China’s total land area, but the geo-
graphical location disadvantage is obvious, with its frag-
ile ecological environment, low industrial intensity, and
economic underdevelopment. Also its logistics infra-
structure construction is lagging behind. Although there
are the Eurasian continental bridge, the Southern Xing-
jian Railway, the Lanzhou-Kunming railway, the Lan-
zhou-Xingjian double-track railway in these regions, and
in recent years some of the high-level road network con-
struction has provided a solid foundation for the western
China logistics industry development, however, com-
pared with the economically developed eastern and
south-eastern coastal areas who own three-dimensional,
international and all-round development traffic patterns,
the gap is still large, and the gap is expanding year by
year. At the same time, as the regional logistics industry
main part, the logistics enterprises have a lot of problems
such as shortage of funds, single mode of services, in-
flexibility mode of operation, lack of understanding of
logistics services, small enterprises scale, the low level
of information processing methods, and backward
knowledge of modern logistics, shortage of logistics
personnel and so on, all of which have made it hard for
many of the western region logistics enterprises to achieve
greater development in short term. Essentially, it is the
main reason that the regional economy is underdeveloped,
which leads to the issues of western logistics industry de-
velopment backwardness. Based on the above analysis,
some suggestions on the development of the logistics in-
dustry in the west regions can be made as follows:
1) In the long run, we should improve and protect the
ecological environment, and create a good environment
for the economy and sustainable development of society.
In the western regions, especially in the north-west re-
gions, great importance should be attached to the protec-
tion of the ecological environment from strategic per-
spective, and great effort should be made to change the
phenomena of high input, low output and, the excessive
cost of raw materials and energy so as to achieve the
benign circulation of regional economic development
and improvement of the ecological environment. This
will substantially benefit the development of regional
logistics and relevant industries.
2) Continue to enhance the construction of logistics
infrastructure in the western region such as railways,
highways, airports, river ports, communication and so on
in order to provide good hardware environment for the
regional economic development.
3) In order to create logistics demand, it is crucial that
logistics industrial intensity be improved. In the west
regions we should strengthen urban industrial technology,
promote industrial upgrading, improve the industrial
intensity. PRD model has provided a useful example for
the western regions to improve their industrial intensity.
4) The reasonable logistics system planning is neces-
sary. Based on the planning, gradually standardize re-
gional logistics market, integrate and coordinate the re-
gional logistics resources, improve the technical level
and efficiency of the logistics operation, seek the process
of high value-added logistics, the aim is to reduce re-
gional logistics costs and increase market competitive-
ness. At the same time, the western regions need to
strengthen the cooperation and exchange with the other
three major economic regions in the development of the
logistics industry, and borrow their successful experi-
ences.
5) Pay attention to the construction of the soft envi-
ronment during the development of regional economy
and regional logistics industry, which includes the con-
version of concept, the upgrading of the ability of inde-
pendent innovation, system innovation and the introduc-
tion and training of human resources, so as to enhance
the development of the inherent strength and power.
In short, the development of the logistics industry and
the improvement of competitiveness in the west regions
involve many disadvantageous factors, which makes it
hard and a long way to go to attain the current status of
the developed regions in east China.
6. Concluding Remarks
In this paper a systematic and comprehensive hybrid
index evaluation system of regional logistics competi-
tiveness is designed according to the characteristics of
China’s regional logistics system under supply chain
globalization environments, and systematic analysis and
discussion of the connotation of the various factors in the
index evaluation system are made. Also a comprehensive
evaluation of the development trend of logistics industry
of China’s four municipalities, and 27 provincial capital
cities have been done on base of hierarchy analysis
thought and fuzzy pattern recognition principles accord-

JUPING SHAO, TIANYUN MA, SHAOHUA DONG, XIANGHUA MENG 79
ing to 2007 Statistical Yearbook of the National Bureau
of Statistics data. The results showed that:
1) Urban logistics industry competitiveness is close-
ly related with the economic situation of the whole city,
logistics facilities and equipment, logistics industry costs,
attractiveness of foreign investment, trade and informa-
tion etc.
2) Overall, the regional logistics industry in China has
made gratifying development in recent years, but the
development level of logistics industry in the provincial
capital cities in China remain seriously unbalanced. The
Beijing-Tianjin-Hebei Economic Area with Beijing and
Tianjin as the representative, the Yangtze River Delta
Economic Area with Shanghai and Nanjing as the repre-
sentative, and the Pearl River Delta Economic Zone with
Guangzhou and Shenzhen as the representative are rela-
tively developed and have stronger competitive power in
the logistics industry, but in the cities in northwest and
southwest regions, the logistics industry is less competi-
tive. And especially in those cities in the northwest re-
gions, logistics industry is in the weakest position.
3) The regional economic development is increasingly
dependent on the development level of the regional lo-
gistics industry system. To enhance the competitiveness
of the regional logistics industry has an important strate-
gic significance for improving the ability to cope with
the rising cost and boosting the regional economic de-
velopment.
7. Acknowledgement
The authors would like to thank the referees for their
helpful suggestions. This research works was supported
by the Natural Science Foundation of Shandong Prov.
China under Grant No.Y2008H08 and the Soft Science
Foundation of Shandong Prov. China named Logistics
Service Innovation Tactics and Pattern of Productive
Service Enterprise and the Dr Foundation of Shandong
Prov. China under Grant No. 2008BS014 and the Excel-
lent Teachers of General Institutions of Higher Learning
of shandong province international cooperation training
Program and the Innovative Team Construction of Lu-
dong University under Grant No.22480301.
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