With the development of economy and the cluster development of modern service industry, the revitalization plan of northeast area and the upgrading of industrial structure in Liaoning depend on the improvement of its modern service industry. But the cluster development is the mainstream not only in developed countries but also domestic developed areas. Therefore, to speed up the process of modern service industry cluster in Liaoning has certain significances in promoting the development of clustering situation which should be guided reasonably.
Compared with the traditional service industry, modern service industry is modern and informationalized. With the development of science and technology, it is essential to modernize the traditional industry and promote the application of modern information and technology. The development of modern service industry will provide higher-value and high-tech industry. The modern service industry mainly contains the following sectors: modern logistics; information transmission, software and information technology services; financial industry; real estate, etc. [
Code | Category | Item |
---|---|---|
G | Modern logistics | TPL, etc. |
I | Information transmission, software and information technology services | Telecommunications, broadcasting and TV transmission and satellite services, the internet and related services, software and information technology services. |
J | Financial industry | Monetary and financial services, capital market services, insurance and other financial business. |
K | Real estate | Real estate management, property management, real estate intermediary services and other real estate business. |
L | Leasing and commercial services | Financing lease, car rental, engineering machinery leasing, enterprise management service and other business services. |
M | Scientific research and technical services | Professional and technical services, technology promotion and application. |
P | Education industry | Preschool education, primary school, secondary education and higher education, special education, skill training, etc. |
Q | Health and social work | Health care services, social security and other social services activities. |
R | Culture, sports and entertainment | Television and recording studios, culture, art, sports and entertainment industry. |
From GB_T4754-2011.
When talking about the connotation of modern service industrial cluster, there isn’t a unified definition in the world. However, depending on the researches at home and abroad and the connotation of industrial cluster applied extensively, it is concluded that modern service industry cluster is a new organization structure. This new structure can not only bring economies of scope and economies of scale, but also point out the close relationship in a certain space [
The classification of modern service industrial cluster is summarized roughly as the following:
1) original cluster
The regional natural resources or some congenital advantages promote the development of original cluster. During the long endogenous process, the industrial cluster is the main performance in industrial agglomeration or the collection of enterprises, so most scholars defined it as Marshall industrial cluster. This kind mainly focuses on some private small and medium-sized enterprises, which also exists the mutual competition, just like the wholesale and retail.
2) embedded cluster
Embedded cluster is between native cluster and exogenous cluster which is also known as advantage cluster. When they have built their own certain foundation, the government preferential policies or guide will play a role in reinforcing the application of the capital and technology which can promote it to be the leading enterprise in the areas. So this kind of enterprises is almost technology intensive modern service industry and capital intensive modern service industry, which greatly rely on the government guidance, such as financial industry, scientific research and technical services.
3) exogenous cluster
Exogenous cluster enterprises entirely depend on the government’s arrangement, which just own limited factor endowments. And the limited factor endowments refer to the natural resources of local or regional conditions. The typical representative of exogenous cluster is the free trade zone.
4) collaborative cluster
Collaborative cluster is the emerging form of cluster, which is the special competitive cooperation. This kind of cluster will promote the collaborative technology research and the enterprises’ internal competitiveness. It is better to realize common development by forming multiple center enterprises and reinforce the mutual trust.
5) driven cluster
The driven cluster mainly highlights the effect of a giant modern service industrial enterprise, and will lead other enterprises to form industrial clusters.
Based on the scholar’s point of views and the problems preliminarily discussed, it is concluded that they carry out the different index system for the different research angle. But establishing a perfect system of comprehensive evaluation is an important premise. This paper establishes the multi-target appraisal, depending on the current scholars’ researches and the limited useful data.
This paper takes in the basic law of modern service industrial cluster and the precious scholars’ experiences and achievements. It is necessary to point out the research about the service industrial development in Gansu written by Jinmei. Using for reference from the above research and the level of modern service industrial cluster in Liaoning, it establishes the index system and also divided into 18 comprehensive indexes [
Because of the second economic census in 2008 in China and the limitations of statistical data in Liaoning province, this article adopts the statistical data of Liaoning province in 2013. At the same time, the lack of statistical caliber decides this paper to give up external evaluation but to choice the internal evaluation. Besides, the
The evaluation object | First grade indexes | Second grade indexes |
---|---|---|
The comprehensive strength of modern service industry | Development level | GDP |
GDP per capitals | ||
Industrial GDP | ||
Industrial GDP/GDP | ||
Non-agricultural population | ||
Non-agricultural population proportion | ||
The proportion of foreign investment | ||
The investment of residents and other services | ||
The students in high school or above | ||
The proportion of students in high school or above | ||
Economic efficiency | Modern service industry in GDP | |
Modern service industry GDP per capitals | ||
The third industry GDP | ||
Modern service industry employment | ||
The proportion of modern service industry employment | ||
Modern service industry GDP/GDP | ||
The third industry GDP/GDP | ||
Modern service industry in GDP/ the third industry in GDP | ||
Concentration coefficient | The concentration factor of modern service industry |
Jin, M. (2013) The Research of Industry Development in Gansu Province Based on Cluster]. Lanzhou University, Lanzhou, (9), 56-87.
development of modern service industrial cluster in Liaoning is used in the early stage, which requires to take in the industrial cluster data instead of industrial data.
From the factor analysis of development conditions, this paper mainly takes in the following factors: GDP (f1), GDP per capita (f2), industrial GDP (f3), 18 - 60 population (f4), students in high school or above (f5) (
1) factor analysis
Factor analysis calculation is made by SPSS. After the reflection as correlation coefficient matrix and the KMO inspection and Bartlett ball inspection, it shows that the characteristic roots of the first and the second common factor is 4.155 and 0.625. All the three public factors explain 99.718 percent of the original variables. So it abandons the other two public factors which means just little information lost with an ideal analysis effect.
2) the score table of development conditions
From the above-mentioned analysis result (
Depending on the
Region | GDP (billion) | GDP Percapita (Yuan) | Industrial GDP (Billion) | 18 - 60 Population (Thousand) | Students in high school or above (Person) |
---|---|---|---|---|---|
Shenyang | 715.857 | 86850 | 334.9 | 4936.0 | 493.77 |
Dalian | 765.079 | 110600 | 343.9 | 3973.0 | 397.44 |
Anshan | 262.325 | 72606 | 124.6 | 2338.0 | 233.88 |
Fushun | 134.045 | 63922 | 67.5 | 1508.0 | 150.85 |
Benxi | 119.366 | 69118 | 64.1 | 1063.0 | 106.34 |
Dandong | 110.730 | 45596 | 45.8 | 1609.0 | 160.96 |
Jinzhou | 134.493 | 43497 | 58.6 | 2011.0 | 201.17 |
Yingkou | 151.311 | 61937 | 71.2 | 1597.0 | 159.76 |
Fuxin | 61.512 | 34259 | 23.7 | 1309.0 | 130.95 |
Liaoyang | 107.999 | 58236 | 63.9 | 1200.0 | 120.04 |
Panjin | 135.106 | 94052 | 84.0 | 882.0 | 88.23 |
Tieling | 103.127 | 34143 | 47.2 | 2039.0 | 203.97 |
Chaoyang | 100.286 | 33591 | 40.7 | 2262.0 | 226.28 |
Huludao | 77.511 | 29915 | 30.4 | 1829.0 | 182.96 |
From the statistical yearbook of Liaoning province 2014.
Component | Initial eigen values | Rotation sums of squared loadings | ||||
---|---|---|---|---|---|---|
Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | |
1 | 4.155 | 83.106 | 83.106 | 2.181 | 43.621 | 43.621 |
2 | 0.625 | 12.500 | 95.606 | 1.631 | 32.630 | 76.251 |
3 | 0.206 | 4.112 | 99.718 | 1.173 | 23.467 | 99.718 |
4 | 0.013 | 0.255 | 99.974 | |||
5 | 0.001 | 0.026 | 100.000 |
From SPSS.
Region | f1 | f2 | f3 | f | Rank |
---|---|---|---|---|---|
Shenyang | 2.148 | 0.333 | 1.323 | 1.363 | 2 |
Dalian | 1.287 | 1.702 | 1.023 | 1.378 | 1 |
Anshan | 0.575 | 0.598 | −1.146 | 0.184 | 3 |
Fushun | −0.750 | 0.226 | 0.328 | −0.175 | 6 |
Benxi | −0.908 | 0.678 | −0.301 | −0.240 | 8 |
Dandong | −0.295 | −0.515 | −0.011 | −0.305 | 12 |
Jinzhou | −0.532 | −0.929 | 1.447 | −0.206 | 7 |
Yingkou | −0.056 | 0.323 | −1.031 | −0.158 | 5 |
Fuxin | −1.120 | −1.134 | 1.686 | −0.475 | 14 |
Liaoyang | −0.653 | 0.196 | −0.263 | −0.281 | 9 |
Panjin | −1.387 | 1.753 | −0.352 | −0.098 | 4 |
Tieling | 0.618 | −0.978 | −1.032 | −0.302 | 12 |
Chaoyang | 0.735 | −1.107 | −0.975 | −0.281 | 10 |
Huludao | 0.338 | −1.146 | −0.696 | −0.402 | 13 |
From the statistical yearbook of Liaoning province 2014.
Considering the representative and the useful of the data, the factor analysis of economic efficiency of modern service industrial cluster choices the following factors: modern service industry in GDP (f1), modern service industry GDP per capitals (f2), the third industry GDP (f3), modern service industry employment (f4), the proportion of modern service industry employment (f5), modern service industry GDP/GDP (f6), the third industry GDP/GDP (f7).
This part of factor analysis is same with the previous section, so it omits the steps and gives the results directly.
The composite scores ranking in the
Region | f1 | f2 | f3 | f | Rank |
---|---|---|---|---|---|
Shenyang | 1.910 | 0.780 | 0.902 | 1.270 | 2 |
Dalian | 1.271 | 1.862 | 1.053 | 1.460 | 1 |
Anshan | 0.717 | 0.625 | −2.605 | 0.030 | 4 |
Fushun | −0.533 | 0.087 | 0.228 | −0.140 | 6 |
Benxi | −0.460 | 0.369 | −0.145 | −0.070 | 5 |
Dandong | 0.297 | −0.508 | −0.961 | −0.270 | 9 |
Jinzhou | 0.200 | −0.754 | 0.085 | −0.200 | 8 |
Yingkou | 0.230 | −0.299 | 0.410 | 0.060 | 3 |
Fuxin | −0.315 | −1.047 | 0.740 | −0.400 | 13 |
Liaoyang | −0.785 | 0.237 | −0.630 | −0.350 | 12 |
Panjin | −2.182 | 1.681 | 0.276 | −0.180 | 7 |
Tieling | −0.459 | −0.552 | −0.563 | −0.520 | 14 |
Chaoyang | −0.598 | −1.002 | 1.329 | −0.380 | 11 |
Huludao | 0.708 | −1.478 | −0.121 | −0.320 | 10 |
From the statistical yearbook of Liaoning province 2014.
phenomenon implies that economic efficiency of modern service industrial in the northwestern Liaoning province is weak. At the same time, the development of the Anshan, Benxi and Fushun owns the advantages of industrial foundation which can provide the support of capital [
There are kinds of methods used in the research of industrial cluster depending on the precious scholars’ experience. This article mainly brings into the concentration coefficient. In some extent, concentration coefficient is a relative index, according to per capitals output or yield. This method uses a relative index to explain the development of modern service industrial cluster more scientific and more persuasive. In addition, concentration coefficient method is operated simply and the result is intuitive. Its formula is shown as followed:
Note:
CCij: the concentration coefficient of industry i in region j; eij: the output value of industry i in region j; pj: the employment of industry i in region j; n: the number of region. It is easy to get the conclusion that the greater ofthe numerical value of CCij, the more concentrated of this industry. The following
This table analyzes the 9 sectors of 14 regions in Liaoning province. The result indicates that the concentration coefficient is general low which means the concentration ratio in these regions is weak, which also means its development condition and economic efficiency is unapparent. By comparison, Shenyang and Dalian possess the prominent environmental advantage and economic conditions, which lead to the two regions’ concentration coefficient higher than 1. Besides, their low cluster level in Tieling, Huludao and Chaoyang has a close relationship with the relative poor foundation. Many theory and practice prove that the development of modern ser-
Region | Modern logistics | Information transmission, software and information technology services | Financial industry | Real estate | Leasing and commercial services | Scientific research and technical services | Education industry | Health and social work | Culture, sports and entertainment | Modern services industry | |
---|---|---|---|---|---|---|---|---|---|---|---|
Shenyang | 1.16 | 1.79 | 1.59 | 1.33 | 1.57 | 1.04 | 1.50 | 0.97 | 1.53 | 1.27 | |
Dalian | 1.21 | 0.81 | 2.00 | 1.03 | 2.28 | 2.75 | 1.72 | 1.70 | 0.76 | 1.68 | |
Anshan | 0.52 | 0.99 | 0.96 | 1.07 | 1.31 | 0.75 | 0.56 | 0.55 | 0.99 | 0.82 | |
Fushun | 1.22 | 1.34 | 0.76 | 1.13 | 0.26 | 1.59 | 0.91 | 1.77 | 0.86 | 0.95 | |
Benxi | 1.00 | 1.00 | 0.64 | 0.60 | 0.81 | 1.29 | 0.88 | 0.44 | 2.97 | 0.71 | |
Dandong | 0.71 | 1.55 | 0.82 | 0.32 | 1.34 | 0.32 | 0.29 | 0.32 | 1.24 | 0.54 | |
Jinzhou | 0.95 | 1.02 | 0.58 | 1.15 | 0.42 | 0.53 | 0.59 | 0.60 | 0.38 | 0.74 | |
Yingkou | 1.28 | 1.11 | 0.92 | 1.44 | 1.05 | 1.04 | 0.78 | 0.72 | 0.95 | 1.25 | |
Fuxin | 0.96 | 0.56 | 0.48 | 0.78 | 0.36 | 1.04 | 0.75 | 0.52 | 0.81 | 0.57 | |
Liaoyang | 1.76 | 1.48 | 0.83 | 1.03 | 0.57 | 1.30 | 0.67 | 0.59 | 0.77 | 0.92 | |
Panjin | 1.08 | 0.68 | 0.79 | 1.30 | 0.36 | 1.46 | 0.86 | 0.84 | 0.78 | 0.92 | |
Tieling | 1.25 | 0.62 | 0.75 | 1.09 | 0.18 | 0.45 | 0.48 | 0.59 | 0.45 | 0.63 | |
Chaoyang | 0.89 | 0.87 | 0.51 | 0.95 | 0.48 | 0.96 | 0.56 | 0.72 | 0.56 | 0.57 | |
Huludao | 1.37 | 0.94 | 0.50 | 1.60 | 0.33 | 0.55 | 0.60 | 0.77 | 0.83 | 0.74 |
From the statistical yearbook of Liaoning province 2014.
vice industrial cluster not only is affected by some hardware factors like the geographical conditions, the resources endowment, but also influenced by the software factors such as the policy, market economy. Overall, the whole level in the 14 regions is general low, especially those regions whose concentration coefficient is lower than 1. These regions must exist some obstacles to limit the development of the whole region.
According to the above analysis of development condition and the economic efficiency, and the statistical calculation of concentration coefficient, this paper adopts AHP. AHP is also called expert rating or literature reading method, put forward in 1970s by professor Satty from University of Pittsburgh. As a hierarchy weighted decision-making analysis method, it is widely used in systematic analysis which combines the quantity factors with quality factors in a more clear way.
Through the calculation of the judgment matrix and the RI table, we concluded the weighing factor of development condition, the economic efficiency and concentration coefficient [
According to the comprehensive score statistics of modern service industrial cluster (
Comprehensive strength | Development level | Economic efficiency | Concentration coefficient |
---|---|---|---|
Development level | 1 | 1/4 | 1/5 |
Economic efficiency | 4 | 1 | 2 |
Concentration coefficient | 5 | 1/2 | 1 |
From the document consulting and investigation and expert consultation.
n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
RI | 0 | 0 | 0.52 | 0.89 | 1.12 | 1.26 | 1.36 | 1.41 | 1.46 | 1.49 | 1.52 | 1.54 | 1.56 |
Hong, Z.G., Li, Y., Fan, Z.G. and Wang, Y. (2002) The Calculations of AHP and RI. Computer Engineering and Application, (12), 45-47.
Index | Development condition | Economic efficiency | Concentration coefficient |
---|---|---|---|
Weighing factor | 0.09 | 0.54 | 0.36 |
From
Region | Development level | Economic efficiency | Concentration coefficient | Composite scores | Rank |
---|---|---|---|---|---|
Shenyang | 1.36 | 1.27 | 1.27 | 1.26 | 2 |
Dalian | 1.38 | 1.46 | 1.68 | 1.52 | 1 |
Anshan | 0.18 | 0.03 | 0.82 | 0.33 | 4 |
Fushun | −0.17 | −0.14 | 0.95 | 0.25 | 5 |
Benxi | −0.24 | −0.07 | 0.71 | 0.20 | 7 |
Dandong | −0.31 | −0.27 | 0.54 | 0.02 | 11 |
Jinzhou | −0.21 | −0.2 | 0.74 | 0.14 | 8 |
Yingkou | −0.16 | 0.06 | 1.25 | 0.47 | 3 |
Fuxin | −0.48 | −0.4 | 0.57 | −0.05 | 13 |
Liaoyang | −0.28 | −0.35 | 0.92 | 0.12 | 9 |
Panjin | −0.10 | −0.18 | 0.92 | 0.22 | 6 |
Tieling | −0.30 | −0.52 | 0.63 | −0.08 | 14 |
Chaoyang | −0.28 | −0.38 | 0.57 | −0.03 | 12 |
Huludao | −0.40 | −0.32 | 0.74 | 0.06 | 10 |
From Tables 5-7.
Based on the analysis of modern service industrial cluster development in Liaoning, we come to the following conclusion: 1) modern service industrial cluster in Liaoning is underdeveloped; 2) there exists large development gap among 14 districts; 3) modern service has strict requirement for the economy development. Modern service industrial cluster development is a special concept, in which the achieved effect of development cannot always be coincident with the plans and expectations. It needs long-run observation and analysis. However, according to the development trend of current economy, the combination of finance and Internet has been increasingly significant in economy and the two industries are the key areas of modern service. It also needs continuous tracking analysis about whether the primary stage of cluster development and the gradual transformation can be smoothly completed and accomplished or not.
During the process of writing the paper, in spite of large quantities of literatures having been collected, the incompletion of the statistics and inconsistent statistical caliber add obstacles for the data collection and selection. Scholars in the future are expected to analyze the cluster development by using more complete data. Valuable advice to this paper is welcomed. Academic research level can be lifted through more beneficial communications. This paper is not perfect now and needs refinement in the future, but I still feel honored to provide some perspectives for the successors
XuemeiLiu,HeSun,BaixiaLiu, (2015) The Evaluation of the Old Industrial Base Transformation—With the Development of Modern Service Industrial Cluster in Liaoning Province as an Example. Modern Economy,06,1261-1269. doi: 10.4236/me.2015.612119