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Spatial-temporal Evolution of Multi-airports’ Homogenization in China Yangtze River Delta
Available online at www.sciencedirect.com
ScienceDirect Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
13th COTA International Conference of Transportation Professionals (CICTP 2013)
Spatial-temporal Evolution of MultiChina Yangtze River Delta Yonglei Jianga* , Lu Wangb, Xiaolin Jianga, Jing Lua a
College of Transportation Management, Dalian Maritime University, , Dalian, 116026, Chin a b China Academy of Civil Aviation Science and Technology, Beijing, 100028, Chin a
Abstract The continuous increase of civil aviation demand acts as a spur not only for the government to enlarge inves tment on infrastructure construction, but also for the airport and airlines to improve service to compete for the market share. As a result, the development of airports in the region has experienced a trend of homogenization. This paper aimed to analyze th e integrated endow proportion method are employed to calculate the homogenization degree, and then the trends and characteristics of airports are analyzed systematically. Further, the homogenization of each airport is taken as the variable to implement the cluster analysis, and the development classes of airports are gained. © TheAuthors. Authors. Published by Elsevier © 2013 2013 The Published by Elsevier Ltd. B.V. Selection and/or peer-review under responsibility ChineseTransportation Overseas Transportation Association (COTA). Selection and peer-review under responsibility of ChineseofOverseas Association (COTA). Keywords: Airport homogenization; tempo-spatial evolution; similarity coefficient; cluster analysis
1. Introduction Recently, the consumption capacity of China citizen s and their demand level of service keep increasing while the national economic and inco me level imp roves continuously. Under this circu mstance, considering the characteristics of celerity and co mfort, the civil aviation is gradually becoming one of the ci especially for the long-haul trips. The average annual increase rate of civil aviation passenger transportation and cargo transportation have reached 14.1% and 12.9% respectively fro m 2005 to 2010, which is on the top list of the five t airports had increased to 175. Acco
-Five-
* Corresponding author. Tel.: +86-411-84723203; fax: +86-411-84724241. E-mail address: [email protected]
1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of Chinese Overseas Transportation Association (COTA). doi:10.1016/j.sbspro.2013.08.159
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
1403
covered. The opening of a large nu mber o f civil airports will en large the cover rate of civil aviation, and improve the accessibility of civ il av iation. However, the opening and operating of a large scale of airports will result that mu ltip le airports exist in a developed region. And the region can be described as a mu lti -airport reg ion. In this region, in order to develop itself, each airport will inevitably encounter problems such as hinterland overlap, airline similarity, and the identical construction of cargo/passenger flows. And all these problems will induce the -throat competit ion for survival and development. To grasp the homogenization degree and trends of each airpo rt in a mu lti-airport region is urgent and necessary for the operation and development of each airport . 2. Literature review ce of mu lt iairport reg ions and the development, competition, integration among airports has attracted the notice of some scholars. Co mpared with the Multi-airport regions abroad, Fang and Gao (2004) pointed out that the distribution of civ il airports in Yangtze River Delta is over-concentrated, and the airports in Yangtze River Delta will meet problems like limited market scale and difficu lty in allocation of resources. Chen and Fu (2005) analy zed the difficult ies of airport integration in Pearl River Delta Region, and emp loyed production function to analyze the Zhang and Hu (2006) took notice of the problems o f high density of airports in global urban agglo merat ion and unreasonable resource allocation of airports; they suggested that the integrated operation of mult i-airport system can be applied to solve the problems. And the reason, benefits, and development mode of the integrated operation were analyzed and exp lore d further. Zhou et al (2011) discussed whether the mult i-airport system is reason and operation mode of these regions were also explored. And other similar studies are qualitative analysis of merits and faults of mult i-airport system in a region (Zhang, 2007; Liu, 2008; Wei &Xia, 2008; Hu, 2011 ). In conclusion, the existing researches gradually attach importance to the fierce co mpetit ion and difficu lty of resource integration service, which may be one of in mu ltithe main reasons of negative effects of multi-airport system. Considering the trends of resource integration of regional mu lti-airport system, this paper took Yangtze River Delta as examp le to analyze the spatial-temporal evolu of this paper is as follows: the secession 3 describes the methods using in computing the homogenizat ion trends and characteristics of mu lti-airport system. The secession 4 takes the airports in Yangtze River Delta as examp le. Finally the secession 5 is the conclusion. 3. Methodol ogy In order to analyze the spatial-temporal trend of service ho mogenization of regional mu lt i-airport system, we implement the methodology as follow: Firstly, imp roved similarity coefficient (Wei et al, 2010) was selected to . Secondly, the integrated endow compute the homogenization degree of e proportion method (Guo, 2002) was applied to compute the value of comprehensive homogenizat ion index of each couple of airports . Finally, taking the co mprehensive homogenization degrees between each airport and other airports as the evaluation variable, the hierarchy analysis (Nie, 2003) was emp loyed to classify regional airports and analyze the different evolution characteristics of multi3.1. Improved similarity coefficient
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Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
The homogenization of regional airports is main ly related to the service supplied by the airports and the distances between each couple of airports, so we take the similarity coefficient to evaluate the ho mogenization degree of civil airports, the computational formula is as follow: Sijmt
n
(
ij
( xikmt
x mt jk ) /
k 1
d Max ij
ij is
n
( xikmt ) 2
k 1
d ij (d Max
d Min )
1
Where,
n
(1)
2 ( x mt jk ) )
k 1
d ij
0
d ij
0
(2)
S ijmt is the similarity coefficient value of the mth index between airport i and j during the t th period;
the distance weight between airport i and j, which can be calculated by equation (2);
th xikmt ( x mt jk ) is the m
index s share of airport i (j) of the k th leg during the tth period; d ij is the distance between airport i and airport j.
S ijmt is between 0 and 1, and the bigger imp lies the higher similarity degree of the two
The value of mt
airports. S ij
0 means the services of airport i and airport j are totally different under the mth index during the
S ijmt
t th period;
1 means the services of airport i and airport j are totally same under the mth index during the tth
m
0.5 means the services of airport i and airport j shows the trend of service homogenization under period; Sij the mth index during the tth period. 3.2. Integrated endow proportion method The similarity of each index of each couple of airports can be calculated by e quation (1), but the comprehensive homogenization of t wo airports is preferred to measure the t rend of service ho mogenizat ion of each couple of airports in a region. We take the comprehensive weighted evaluation method to evaluation the homogenization between airports. And the approach is as follow: (1) Differential-driven method is applied to compute the weight of mth index (equation (3)): m (3) w m, c r m rk ij
ij
ij
k 1
Where, r m ij
m
1
m 1k
( S ijk
S ij ) 2 , S ij
1
1 m
m
th S ijk are the deviation and mean of the value of the m index between
k 1
airport i and airport j respectively. (2) Then the function-driven method is employed to calculate the weight of mth index (equation (4)): wijm, g
Sijm
m k 1
Sijk
(4)
1405
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
(3)
Finally, after solving the equation (5), the co mprehensive weight wijm m
the comprehensive homogenization of each couple of airports Sij
k 2 wijm, g can be gained, and
( wijk Sijk ) .
k 1
m
Max
k1wijm,c
k ,c ij
k ,g ij
(k1w
k2 w
)S
k ij
k 1
s.t.
k1
0, k 2
k1
k2
k1
(
m
1 wijk ,c S ijk ) 2
k 1
k2
(5)
0
(
m
wijk ,c S ijk ) 2
k 1
(
m
wijk , g S ijk ) 2
k 1
1 k1
3.3. Hierarchical cluster In a closed region, the service homogenization of each airport and other airports shows different characteristics and trends, so we take the co mprehensive similarity coefficient as a variable to imp ly hierarchical cluster method. 4. Analysis of spatial-temporal evolution of airports in Yangtze River Delta 4.1. Study region and data There are 16 civil av iation airports opening and operating in Yangtze River Delta at the end of 2010, and 5 of them are regional hubs which locate in cities of Shanghai(2 airports), Hangzhou, Ningbo and Nanjing, the others are local airports locates in Lianyungang, Xuzhou, Yancheng, Nantong, Changzhou, Wu xi, Zhoushan, Yiwu, Quzhou, Taizhou and Wenzhou. Of the 16 airports, Hangzhou Xiaoshan Airport has the highest class (4F), while the airport class of Yancheng, Yiwu, Qu zhou and Taizhou is the lowest (4C). The information of each airport in Yangtze River Delta is shown in Table 1. T able 1 Information of airports in Yangtze River Delta Designed Capacity
Airport
Opening(Year)
Class
Lianyungang
1985
4D
>20
Local
Xuzhou
1997
4D
100
Local
Yancheng
2000
4C
30
Local
Nantong
1993
4D
150
Local
Changzhou
1986
4E
490
Local
Nanjing
1997
4E
4,000
Regional
Wuxi
2004
4E
1,000
Local
Shanghai (Hongqiao)
1963
4E
4,000
Regional
Shanghai(Pudong)
1999
4E
6,000
Regional
Data Source:
(10 thou visitors/year)
T ype
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Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
Hangzhou
2000
4F
2,000
Regional
Zhoushan
1997
4D
40
Local
Ningbo
1990
4E
>380
Regional
Yiwu
1993
4C
100
Local
Quzhou
1993
4C
10
Local
T aizhou
1987
4C
60
Local
Wenzhou
1990
4D
600
Local
In order to analyze the homogenization situation between airports in Yangtze River Delta, we collect data of flight number, passenger volume and cargo volume of main domestic legs between airports of Yangtze River Delta and other airports in China from 2003 to 2010. 4.2. Homogenization trends of airports in Yangtze River Delta Firstly, the flight nu mber, passenger volume, cargo volu me of main do mestic legs fro m 15 airports of Yangtze River Delta (Pudong Airport and Hongqiao Airport are seen as a single one) and the distance between each couple of airports are collected annually. And three kinds of similarity coefficients of each co uple of airports are calculated with equation (1). Secondly, the co mprehensive weighted method is used to compute the weights of three kinds of similarity coefficients, which are 0.43, 0.28 and 0.29 respectively. Finally, according to the values of co mprehensive similarity coefficients of airports in Yangtze River Delta, the ho mogenizat ion situations (the value of similarity coefficient is above 0.5) of each couple of airports are gained and shown in Fig. 1.
(a) 2003
(b) 2004
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
(c) 2005
(d) 2006
(e) 2007
(f) 2008
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Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
(g) 2009
(h) 2010
Fig.1 the spatial-temporal development of airport homogenization
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
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According to the characteristics shown in Fig.1 (a) ~ (h), we div ided the process of airports homogenization in Yangtze River Delta into three stages: (1) Preliminary Stage (2003~2004) The airport homogenization had experienced two kinds of trends since 2003. On one hand, the number of airports with homogenization trends was rising, and most of them are located in the most develop ed cities firstly, such as Shanghai, Hangzhou and Ningbo. Then, the airports located in the neighbor cities gradually shows the characteristics of service homogenization. On the other hand, the airports with shorter distances (Ningbo, Hangzhou and Taizhou) were developing homogenized. Considering the economic develop ment, we found that: although as a whole economic entity, the Yangtze River Delta were boosting very fast, the development rate of Huhangyong zone (the zone of Shanghai, Hangzhou and Ningbo) and South Jiangsu were on the top list while other cit ies kept a slow step. In addition, the price of civil aviat ion was co mparatively h igh and its market was limited. In order to increase respective market share, the airports in these most developed cities compete fiercely, and the services supplied by airports were inevitably homogenized. (2) Extension Stage (2005~2008) economy and the further deregulation of Ch ina civil aviation, the civ il aviation experienced a period of high-speed development. As a double-edged sword, the fast ation gradually spread from the airports in the core economic circle of Yangtze River Delta to ones in the neighbor cities in Zhejiang Province. At the same time, the homogenizat ion of a couple of airports had spread from between neighboring airports to between regional airports. The airports with most serious homogenization trend were located in Shanghai, Hangzhou, Wu xi and Ningbo; each one owned the homogenization characteristics with at least 5 other airports. During this period, the fu rther reform and loosing of China civil aviation market access and price deregulation act as a spur for the development of airports and airlines. In order to grasp the market and enlarge the profit margin, the airports and airlines actively cooperated to improve the civ il a viation service. However, the airport density of Yangtze River Delta is ext remely high and the hinterland of each airport overlaps each other heavily. with each other. (3) Network Stage (2009~2010) In this stage, the regional economic developed widely, especially the cities in the fringes of Yangtze River Delta, so did civil airports in North Yangtze River Delta. And the service ho mogenization between fringe airports and those between airports of core economic circle of Yangtze River Delta finally combined together to form a homogenization network. 4.3. Results of Cluster Analysis It is necessary to analyze the homogenization classes of each airport after the spatial-temporal analysis of homogenizat ion characteristics. We take the comprehensive similarity coefficients of each airport in 2010 as the evaluation variable to clustering the development types of airports in Yangtze River Delta. In 2010, there are 15 airports operating in Yangtze River Delta, according to the clustering result, the development of 15 airport cit ies can be divided into 5 classes (Fig. 2).
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Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411 H angzhoou u Hangzhou N inggb bo Ningbo SShanghai hanghai N annjjing Nanjing C hangzhoou u Changzhou W uxi Wuxi W enzhoou u Wenzhou T aizhoou u Taizhou Y iw u Yiwu wu X uzhoou u Xuzhou L ianyungang Lianyungang N annttong Nantong Y ancheng Yancheng Q uzhoou u Quzhou Z hoou ushan Zhoushan
Fig.2 Clustering result of the homogenization development of airports in 2010
(1) 1st Class: Hangzhou, Ningbo, Shanghai, Nanjing, Changzhou & Wuxi. The 6 airport airports locate in Huhangyong Zone and South Jiangsu which is the highest develop ed region. These airports maintain a large nu mber of passenger/cargo volume and airlines, and the distances between each other are comparat ively short, so the hinterlands of each airport overlap heavily. In conclusion, these airports own the highest degree of service homogenization. (2) 2nd Class: Wenzhou, Taizhou and Yiwu. These 3 airports locate on the fringe of core econo mic cycle of Yangtze River Delta. A lthough the ir city scales are small, due to the economic level and the advantage of geographical location, the airports develops fast and turns out to be homogenizing with neighboring airports. (3) 3rd Class: Xuzhou & Lianyungang. These two airports locate at the north of Yangtze River Delta, which is far away fro m other airports and the urban economiy i is behind other cities. Thus they do not have any trend of homogenization. (4) 4th Class: Nantong, Yancheng & Quzhou. These 3 airports locate at the middle ground between the core economic cycle and the fringe reg ion. The 3 airports barely show the homogenizat ion trends with any other airports except the regional hubs in the neighbor cities. (5) 5th Class: Zhoushan. Zhoushan is a city with the geographical feature of islands and th e structure of its urban economy is different fro m cit ies in mainland. According to these reasons, the service supplied by Zhoushan airport is widely different from other airports. 5. Conclusion This paper employed imp roved integrated similarity coefficient and hierarch ical cluster analysis to explore the spatialion of
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
1411
airports has experienced a obvious trend, and spread from the most developed economic cycle to the peripheral cities, which is related to the urban economic level and distances between each couple of airports. Considering the homogenizat ion degree, the development of airports can be divided into 5 classes. And each class of airports needs to be paid different kinds of attentions, and different develop ment strategies should be worked out specially. Acknowledgment This work was supported by National Natural Science Foundation of Ch ina 51108053 and 51208079, the Trans-Century Train ing Program Foundation for Talents from the Ministry of Education of Ch ina and Liaoning Excellent Talents in University LJQ2012045, the Key Projects of Philosophy and Social Sciences fro m the Depart ment of Education (11JZD049), the Fundamental Research Funds for the Central Un iversities (3132013079).
References Chen Qingye, Fu Lina (2005). Empirical analysis of airports integration in Greater Pearl River Delta. SUN YATSEN UNIVERSITY FORUM, 25(1): 65-69. Fang Yungen, Gao Jinhua (2004). Analysis on Status Quo of Airports in Yangtze Delta and Relevant Proposals. Journal of Civil Aviation University of China, 22(5):32-37. Guo Yajun (2002). Integrated evaluation theory and method. Beijing Science Press: 81-98. Hu Yihong, Zhu Daoli(2011). Study on Airport Cluster in Yangtze River Delta based on complex networkds theory and customer choince theory. Shanghai Management Science, 33(3): 106-110. Liu Xiaoming, Xia Hongshan(2008). A Literature Review of the Study on Airport Choice. Application of Statistics and Management, 27(5): 897-904. Ni Pengfei Liu Gaojun Song Xuantao (2003). Cluster Analysis on Chinese Urban Competitiveness, China Industrial Economy,7: 12-16. Wei Suqiong,Chen Yanhua,Gen Jinghuan (2010). Empirical study on industrial isomorphism comparing Fujian and T aiwan provinces by the similar coefficient and R/S. Geographical Research, 29(3): 491-499. Wei Wei, Xia Hongshan (2008). Integrating Airport Group Resources in the Yangtze River Delta and Promoting Corrdinated Development . Journal of Transport Information and Safety, 26(4): 120-124. Zhang Ning(2007). The problems of the Multi-airport s integration based on the optimization and allocation of transport resource. Integrated Transport, 6: 16-20. Zhang Yue, Huaqing (2006).Regional airports integration: the development strategy and trends of airport industry. Integrated Transportation, 5: 25-30. -airport Compound Zhou Huiyan, Shi Lina, Zhang Xu, Xu Zhenling (2011). On Coordinated Development of Chin System.Journal of Nanjing University of Aeronautics and Astronautics (Social Sciences), 13(2): 48-52.
ScienceDirect Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
13th COTA International Conference of Transportation Professionals (CICTP 2013)
Spatial-temporal Evolution of MultiChina Yangtze River Delta Yonglei Jianga* , Lu Wangb, Xiaolin Jianga, Jing Lua a
College of Transportation Management, Dalian Maritime University, , Dalian, 116026, Chin a b China Academy of Civil Aviation Science and Technology, Beijing, 100028, Chin a
Abstract The continuous increase of civil aviation demand acts as a spur not only for the government to enlarge inves tment on infrastructure construction, but also for the airport and airlines to improve service to compete for the market share. As a result, the development of airports in the region has experienced a trend of homogenization. This paper aimed to analyze th e integrated endow proportion method are employed to calculate the homogenization degree, and then the trends and characteristics of airports are analyzed systematically. Further, the homogenization of each airport is taken as the variable to implement the cluster analysis, and the development classes of airports are gained. © TheAuthors. Authors. Published by Elsevier © 2013 2013 The Published by Elsevier Ltd. B.V. Selection and/or peer-review under responsibility ChineseTransportation Overseas Transportation Association (COTA). Selection and peer-review under responsibility of ChineseofOverseas Association (COTA). Keywords: Airport homogenization; tempo-spatial evolution; similarity coefficient; cluster analysis
1. Introduction Recently, the consumption capacity of China citizen s and their demand level of service keep increasing while the national economic and inco me level imp roves continuously. Under this circu mstance, considering the characteristics of celerity and co mfort, the civil aviation is gradually becoming one of the ci especially for the long-haul trips. The average annual increase rate of civil aviation passenger transportation and cargo transportation have reached 14.1% and 12.9% respectively fro m 2005 to 2010, which is on the top list of the five t airports had increased to 175. Acco
-Five-
* Corresponding author. Tel.: +86-411-84723203; fax: +86-411-84724241. E-mail address: [email protected]
1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of Chinese Overseas Transportation Association (COTA). doi:10.1016/j.sbspro.2013.08.159
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
1403
covered. The opening of a large nu mber o f civil airports will en large the cover rate of civil aviation, and improve the accessibility of civ il av iation. However, the opening and operating of a large scale of airports will result that mu ltip le airports exist in a developed region. And the region can be described as a mu lti -airport reg ion. In this region, in order to develop itself, each airport will inevitably encounter problems such as hinterland overlap, airline similarity, and the identical construction of cargo/passenger flows. And all these problems will induce the -throat competit ion for survival and development. To grasp the homogenization degree and trends of each airpo rt in a mu lti-airport region is urgent and necessary for the operation and development of each airport . 2. Literature review ce of mu lt iairport reg ions and the development, competition, integration among airports has attracted the notice of some scholars. Co mpared with the Multi-airport regions abroad, Fang and Gao (2004) pointed out that the distribution of civ il airports in Yangtze River Delta is over-concentrated, and the airports in Yangtze River Delta will meet problems like limited market scale and difficu lty in allocation of resources. Chen and Fu (2005) analy zed the difficult ies of airport integration in Pearl River Delta Region, and emp loyed production function to analyze the Zhang and Hu (2006) took notice of the problems o f high density of airports in global urban agglo merat ion and unreasonable resource allocation of airports; they suggested that the integrated operation of mult i-airport system can be applied to solve the problems. And the reason, benefits, and development mode of the integrated operation were analyzed and exp lore d further. Zhou et al (2011) discussed whether the mult i-airport system is reason and operation mode of these regions were also explored. And other similar studies are qualitative analysis of merits and faults of mult i-airport system in a region (Zhang, 2007; Liu, 2008; Wei &Xia, 2008; Hu, 2011 ). In conclusion, the existing researches gradually attach importance to the fierce co mpetit ion and difficu lty of resource integration service, which may be one of in mu ltithe main reasons of negative effects of multi-airport system. Considering the trends of resource integration of regional mu lti-airport system, this paper took Yangtze River Delta as examp le to analyze the spatial-temporal evolu of this paper is as follows: the secession 3 describes the methods using in computing the homogenizat ion trends and characteristics of mu lti-airport system. The secession 4 takes the airports in Yangtze River Delta as examp le. Finally the secession 5 is the conclusion. 3. Methodol ogy In order to analyze the spatial-temporal trend of service ho mogenization of regional mu lt i-airport system, we implement the methodology as follow: Firstly, imp roved similarity coefficient (Wei et al, 2010) was selected to . Secondly, the integrated endow compute the homogenization degree of e proportion method (Guo, 2002) was applied to compute the value of comprehensive homogenizat ion index of each couple of airports . Finally, taking the co mprehensive homogenization degrees between each airport and other airports as the evaluation variable, the hierarchy analysis (Nie, 2003) was emp loyed to classify regional airports and analyze the different evolution characteristics of multi3.1. Improved similarity coefficient
1404
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
The homogenization of regional airports is main ly related to the service supplied by the airports and the distances between each couple of airports, so we take the similarity coefficient to evaluate the ho mogenization degree of civil airports, the computational formula is as follow: Sijmt
n
(
ij
( xikmt
x mt jk ) /
k 1
d Max ij
ij is
n
( xikmt ) 2
k 1
d ij (d Max
d Min )
1
Where,
n
(1)
2 ( x mt jk ) )
k 1
d ij
0
d ij
0
(2)
S ijmt is the similarity coefficient value of the mth index between airport i and j during the t th period;
the distance weight between airport i and j, which can be calculated by equation (2);
th xikmt ( x mt jk ) is the m
index s share of airport i (j) of the k th leg during the tth period; d ij is the distance between airport i and airport j.
S ijmt is between 0 and 1, and the bigger imp lies the higher similarity degree of the two
The value of mt
airports. S ij
0 means the services of airport i and airport j are totally different under the mth index during the
S ijmt
t th period;
1 means the services of airport i and airport j are totally same under the mth index during the tth
m
0.5 means the services of airport i and airport j shows the trend of service homogenization under period; Sij the mth index during the tth period. 3.2. Integrated endow proportion method The similarity of each index of each couple of airports can be calculated by e quation (1), but the comprehensive homogenization of t wo airports is preferred to measure the t rend of service ho mogenizat ion of each couple of airports in a region. We take the comprehensive weighted evaluation method to evaluation the homogenization between airports. And the approach is as follow: (1) Differential-driven method is applied to compute the weight of mth index (equation (3)): m (3) w m, c r m rk ij
ij
ij
k 1
Where, r m ij
m
1
m 1k
( S ijk
S ij ) 2 , S ij
1
1 m
m
th S ijk are the deviation and mean of the value of the m index between
k 1
airport i and airport j respectively. (2) Then the function-driven method is employed to calculate the weight of mth index (equation (4)): wijm, g
Sijm
m k 1
Sijk
(4)
1405
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
(3)
Finally, after solving the equation (5), the co mprehensive weight wijm m
the comprehensive homogenization of each couple of airports Sij
k 2 wijm, g can be gained, and
( wijk Sijk ) .
k 1
m
Max
k1wijm,c
k ,c ij
k ,g ij
(k1w
k2 w
)S
k ij
k 1
s.t.
k1
0, k 2
k1
k2
k1
(
m
1 wijk ,c S ijk ) 2
k 1
k2
(5)
0
(
m
wijk ,c S ijk ) 2
k 1
(
m
wijk , g S ijk ) 2
k 1
1 k1
3.3. Hierarchical cluster In a closed region, the service homogenization of each airport and other airports shows different characteristics and trends, so we take the co mprehensive similarity coefficient as a variable to imp ly hierarchical cluster method. 4. Analysis of spatial-temporal evolution of airports in Yangtze River Delta 4.1. Study region and data There are 16 civil av iation airports opening and operating in Yangtze River Delta at the end of 2010, and 5 of them are regional hubs which locate in cities of Shanghai(2 airports), Hangzhou, Ningbo and Nanjing, the others are local airports locates in Lianyungang, Xuzhou, Yancheng, Nantong, Changzhou, Wu xi, Zhoushan, Yiwu, Quzhou, Taizhou and Wenzhou. Of the 16 airports, Hangzhou Xiaoshan Airport has the highest class (4F), while the airport class of Yancheng, Yiwu, Qu zhou and Taizhou is the lowest (4C). The information of each airport in Yangtze River Delta is shown in Table 1. T able 1 Information of airports in Yangtze River Delta Designed Capacity
Airport
Opening(Year)
Class
Lianyungang
1985
4D
>20
Local
Xuzhou
1997
4D
100
Local
Yancheng
2000
4C
30
Local
Nantong
1993
4D
150
Local
Changzhou
1986
4E
490
Local
Nanjing
1997
4E
4,000
Regional
Wuxi
2004
4E
1,000
Local
Shanghai (Hongqiao)
1963
4E
4,000
Regional
Shanghai(Pudong)
1999
4E
6,000
Regional
Data Source:
(10 thou visitors/year)
T ype
1406
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
Hangzhou
2000
4F
2,000
Regional
Zhoushan
1997
4D
40
Local
Ningbo
1990
4E
>380
Regional
Yiwu
1993
4C
100
Local
Quzhou
1993
4C
10
Local
T aizhou
1987
4C
60
Local
Wenzhou
1990
4D
600
Local
In order to analyze the homogenization situation between airports in Yangtze River Delta, we collect data of flight number, passenger volume and cargo volume of main domestic legs between airports of Yangtze River Delta and other airports in China from 2003 to 2010. 4.2. Homogenization trends of airports in Yangtze River Delta Firstly, the flight nu mber, passenger volume, cargo volu me of main do mestic legs fro m 15 airports of Yangtze River Delta (Pudong Airport and Hongqiao Airport are seen as a single one) and the distance between each couple of airports are collected annually. And three kinds of similarity coefficients of each co uple of airports are calculated with equation (1). Secondly, the co mprehensive weighted method is used to compute the weights of three kinds of similarity coefficients, which are 0.43, 0.28 and 0.29 respectively. Finally, according to the values of co mprehensive similarity coefficients of airports in Yangtze River Delta, the ho mogenizat ion situations (the value of similarity coefficient is above 0.5) of each couple of airports are gained and shown in Fig. 1.
(a) 2003
(b) 2004
Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
(c) 2005
(d) 2006
(e) 2007
(f) 2008
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Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411
(g) 2009
(h) 2010
Fig.1 the spatial-temporal development of airport homogenization
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According to the characteristics shown in Fig.1 (a) ~ (h), we div ided the process of airports homogenization in Yangtze River Delta into three stages: (1) Preliminary Stage (2003~2004) The airport homogenization had experienced two kinds of trends since 2003. On one hand, the number of airports with homogenization trends was rising, and most of them are located in the most develop ed cities firstly, such as Shanghai, Hangzhou and Ningbo. Then, the airports located in the neighbor cities gradually shows the characteristics of service homogenization. On the other hand, the airports with shorter distances (Ningbo, Hangzhou and Taizhou) were developing homogenized. Considering the economic develop ment, we found that: although as a whole economic entity, the Yangtze River Delta were boosting very fast, the development rate of Huhangyong zone (the zone of Shanghai, Hangzhou and Ningbo) and South Jiangsu were on the top list while other cit ies kept a slow step. In addition, the price of civil aviat ion was co mparatively h igh and its market was limited. In order to increase respective market share, the airports in these most developed cities compete fiercely, and the services supplied by airports were inevitably homogenized. (2) Extension Stage (2005~2008) economy and the further deregulation of Ch ina civil aviation, the civ il aviation experienced a period of high-speed development. As a double-edged sword, the fast ation gradually spread from the airports in the core economic circle of Yangtze River Delta to ones in the neighbor cities in Zhejiang Province. At the same time, the homogenizat ion of a couple of airports had spread from between neighboring airports to between regional airports. The airports with most serious homogenization trend were located in Shanghai, Hangzhou, Wu xi and Ningbo; each one owned the homogenization characteristics with at least 5 other airports. During this period, the fu rther reform and loosing of China civil aviation market access and price deregulation act as a spur for the development of airports and airlines. In order to grasp the market and enlarge the profit margin, the airports and airlines actively cooperated to improve the civ il a viation service. However, the airport density of Yangtze River Delta is ext remely high and the hinterland of each airport overlaps each other heavily. with each other. (3) Network Stage (2009~2010) In this stage, the regional economic developed widely, especially the cities in the fringes of Yangtze River Delta, so did civil airports in North Yangtze River Delta. And the service ho mogenization between fringe airports and those between airports of core economic circle of Yangtze River Delta finally combined together to form a homogenization network. 4.3. Results of Cluster Analysis It is necessary to analyze the homogenization classes of each airport after the spatial-temporal analysis of homogenizat ion characteristics. We take the comprehensive similarity coefficients of each airport in 2010 as the evaluation variable to clustering the development types of airports in Yangtze River Delta. In 2010, there are 15 airports operating in Yangtze River Delta, according to the clustering result, the development of 15 airport cit ies can be divided into 5 classes (Fig. 2).
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Yonglei Jiang et al. / Procedia - Social and Behavioral Sciences 96 (2013) 1402 – 1411 H angzhoou u Hangzhou N inggb bo Ningbo SShanghai hanghai N annjjing Nanjing C hangzhoou u Changzhou W uxi Wuxi W enzhoou u Wenzhou T aizhoou u Taizhou Y iw u Yiwu wu X uzhoou u Xuzhou L ianyungang Lianyungang N annttong Nantong Y ancheng Yancheng Q uzhoou u Quzhou Z hoou ushan Zhoushan
Fig.2 Clustering result of the homogenization development of airports in 2010
(1) 1st Class: Hangzhou, Ningbo, Shanghai, Nanjing, Changzhou & Wuxi. The 6 airport airports locate in Huhangyong Zone and South Jiangsu which is the highest develop ed region. These airports maintain a large nu mber of passenger/cargo volume and airlines, and the distances between each other are comparat ively short, so the hinterlands of each airport overlap heavily. In conclusion, these airports own the highest degree of service homogenization. (2) 2nd Class: Wenzhou, Taizhou and Yiwu. These 3 airports locate on the fringe of core econo mic cycle of Yangtze River Delta. A lthough the ir city scales are small, due to the economic level and the advantage of geographical location, the airports develops fast and turns out to be homogenizing with neighboring airports. (3) 3rd Class: Xuzhou & Lianyungang. These two airports locate at the north of Yangtze River Delta, which is far away fro m other airports and the urban economiy i is behind other cities. Thus they do not have any trend of homogenization. (4) 4th Class: Nantong, Yancheng & Quzhou. These 3 airports locate at the middle ground between the core economic cycle and the fringe reg ion. The 3 airports barely show the homogenizat ion trends with any other airports except the regional hubs in the neighbor cities. (5) 5th Class: Zhoushan. Zhoushan is a city with the geographical feature of islands and th e structure of its urban economy is different fro m cit ies in mainland. According to these reasons, the service supplied by Zhoushan airport is widely different from other airports. 5. Conclusion This paper employed imp roved integrated similarity coefficient and hierarch ical cluster analysis to explore the spatialion of
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airports has experienced a obvious trend, and spread from the most developed economic cycle to the peripheral cities, which is related to the urban economic level and distances between each couple of airports. Considering the homogenizat ion degree, the development of airports can be divided into 5 classes. And each class of airports needs to be paid different kinds of attentions, and different develop ment strategies should be worked out specially. Acknowledgment This work was supported by National Natural Science Foundation of Ch ina 51108053 and 51208079, the Trans-Century Train ing Program Foundation for Talents from the Ministry of Education of Ch ina and Liaoning Excellent Talents in University LJQ2012045, the Key Projects of Philosophy and Social Sciences fro m the Depart ment of Education (11JZD049), the Fundamental Research Funds for the Central Un iversities (3132013079).
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