高速铁路对中心城市航空客运市场的空间影响——基于人均时间价值视角

doi:10.18306/dlkxjz.2019.11.002

Abstract

Abstract:

The spatial differentiation characteristics of the impact of high-speed rail on China's air passenger market is of important reference value for the coordinated development of the two modes of transportation. Using the standard deviation ellipse and traffic comprehensive utility analysis methods, this study analyzed the development status and spatial competition of the high-speed rail and air passenger transport market. The results show that: 1) The high-speed rail and aviation passenger markets have all formed a spatial pattern with Wuhan as the center. Compared with the high-speed rail, the development of the air passenger market area is more balanced; compared with the central cities of the eastern and western regions, the probability of passengers traveling with high-speed rail in the central cities of central China is higher. 2) The per capita time value is inversely proportional to the superiority distance of high-speed rail. The difference in superiority distance makes the high-speed rail and aviation passenger markets in central cities clearly different spatially. Based on the comprehensive utility perspective of traffic, for travels between most central cities in China, air travel is still the best choice. 3) The impact of high-speed rail on the air passenger transport market shows clear spatial differentiation. Most of the central cities in central China are the most affected, which is a key area for coordinating the development of high-speed railways and aviation. In the western region, due to the location conditions of transportation and the lagging development of high-speed rail, air transportation is dominant, and there is still a market gap in the aviation-dominated areas.

Key words: high-speed rail, aviation, per capita time value, competition and cooperation, spatial differentiation

WANG Shaobo, GUO Jianke, LUO Xiaolong, GU Zongni. Spatial differentiation of the impact of high-speed rail on aviation passenger market in central cities of China[J].PROGRESS IN GEOGRAPHY, 2019, 38(11): 1665-1674.

Figures/Tables 9

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References 27

1	丁金学, 金凤君, 王姣娥 , 等. 2013. 高铁与民航的竞争博弈及其空间效应: 以京沪高铁为例[J]. 经济地理, 33(5):104-110.
	[ Ding J X, Jin F J, Wang J E , et al. 2013. Competition game of high-speed rail and civil aviation and its spatial effect: A case study of Beijing-Shanghai high-speed rail. Economic Geography, 33(5):104-110. ]
2	方叶林, 黄震方, 陈文娣 , 等. 2013. 2001—2010年安徽省县域经济空间演化[J]. 地理科学进展, 32(5):831-839. doi: 10.11820/dlkxjz.2013.05.014
	[ Fang Y L, Huang Z F, Chen W D , et al. 2013. Spatial evolution of county economy in Anhui Province during 2001-2010. Progress in Geography, 32(5):831-839. ] doi: 10.11820/dlkxjz.2013.05.014
3	郭春江 . 2010. 高速铁路与民航客运量分担博弈模型研究[D]. 北京: 北京交通大学.
	[ Guo C J . 2010. Research on the game theoretical model of passenger traffic sharing between high speed railway and civil aviation. Beijing, China: Beijing Jiaotong University. ]
4	郭建科, 王绍博, 李博 , 等. 2016. 哈大高铁对东北城市旅游经济联系的空间影响[J]. 地理科学, 36(4):521-529. doi: 10.13249/j.cnki.sgs.2016.04.005
	[ Guo J K, Wang S B, Li B , et al. 2016. The spatial effect of Harbin-Dalian high-speed rail to the northeast city tourism economic link. Scientia Geographica Sinica, 36(4):521-529. ] doi: 10.13249/j.cnki.sgs.2016.04.005
5	蒋海兵, 祁毅, 李传武 . 2018. 中国城市高速铁路客运的空间联系格局[J]. 经济地理, 38(7):26-33.
	[ Jiang H B, Qi Y, Li C W . 2018. China's city high-speed rail (HSR) passenger spatial linkage pattern and its influence factors. Economic Geography, 38(7):26-33. ]
6	梁雪松 . 2010. 基于双重区位空间的湖南旅游业发展机遇探讨: “武广高铁”开通视阈[J]. 经济地理, 30(5):859-864.
	[ Liang X S . 2010. Disscussion on the development opportunity of tourism industry in Hunan Provience based on the dual locational space-the opening visual threshold of "Wu-Guang high speed railway". Economic Geography, 30(5):859-864. ]
7	孟德友, 冯兴华, 文玉钊 . 2017. 铁路客运视角下东北地区城市网络结构演变及组织模式探讨[J]. 地理研究, 36(7):1339-1352.
	[ Meng D Y, Feng X H, Wen Y Z . 2017. Urban network structure evolution and organizational pattern in Northeast China from the perspective of railway passenger transport. Geography Research, 36(7):1339-1352. ]
8	彭峥, 胡华清 . 2009. 高速铁路对航空运输市场的影响分析[J]. 综合运输, ( 7):70-75.
	[ Peng Z, Hu H Q . 2009. Analysis of impact of high-speed railway on air transport market. Comprehensive Transportation, ( 7):70-75. ]
9	卢婉婉 . 2015. 高速铁路与民航的竞争博弈研究[D]. 北京: 北京交通大学.
	[ Lu W W . 2015. The competition game of high speed railway and civil avition. Beijing, China: Beijing Jiaotong University. ]
10	骆嘉琪, 匡海波, 冯涛 , 等. 2019. 基于两阶段博弈模型的高铁民航竞合关系研究[J]. 系统工程理论与实践, 39(1):150-164.
	[ Luo J Q, Kuang H B, Feng T , et al. 2019. Research on the co-opetition between high speed rail and civil aviation based on two stage game model. System Engineering Theory and Practice, 39(1):150-164. ]
11	孙枫, 汪德根, 牛玉 . 2017. 高速铁路与汽车和航空的竞争格局分析[J]. 地理研究, 36(1):171-187. doi: 10.11821/dlyj201701014
	[ Sun F, Wang D G, Niu Y . 2017. Competition patterns of high-speed rail versus highways and aviation. Geographical Reseach, 36(1):171-187. ] doi: 10.11821/dlyj201701014
12	王姣娥, 胡浩 . 2013. 中国高铁与民航的空间服务市场竞合分析与模拟[J]. 地理学报, 68(2):175-185. doi: 10.11821/xb201302003
	[ Wang J E, Hu H . 2013. Competition and cooperation of high-speed rail and air transport in China: A perspective from spatial service market view. Acta Geographica Sinica, 68(2):175-185. ] doi: 10.11821/xb201302003
13	王绍博, 郭建科 . 2016. 中国风景名胜区交通可达性及市场潜力空间测度[J]. 地理研究, 35(9):1714-1726. doi: 10.11821/dlyj201609010
	Wang S B, Guo J K . 2016. Spatial measure of traffic accessibility and market potential of the national scenic areas. Geographical Research, 35(9):1714-1726. ] doi: 10.11821/dlyj201609010
14	王绍博, 郭建科 . 2017. 我国城市整体交通运输流发展的时空演化及其空间关联性分析[J]. 干旱区资源与环境, 31(2):43-49.
	Wang S B, Guo J K . 2017. Spatial and temporal evolution and spatial correlation analysis of the transportation development in China. Journal of Arid Land resources and Environment, 31(2):43-49. ]
15	王绍博, 罗小龙, 郭建科 , 等. 2019. 高铁网络化下东北地区旅游空间结构动态演变分析[J]. 地理科学, 39(4):568-577.
	Wang S B, Luo X L, Guo J K , et al. 2019. Dynamic evolution of tourism spatial structure under the improvement of the high speed rail network in Northeast China. Scientia Geographica Sinica, 39(4):568-577. ]
16	徐广岩 . 2016. 高速铁路动车组列车客座率预测及盈亏分析[D]. 北京: 北京交通大学.
	Xu G Y . 2016. High speed train load factor forecast and breakeven analysis. Beijing, China: Jiaotong University. ]
17	钟业喜, 黄洁, 文玉钊 . 2015. 高铁对中国城市可达性格局的影响分析[J]. 地理科学, 35(4):387-395.
	Zhong Y X, Huang J, Wen Y Z . 2015. Impact of high-speed railway on spatial pattern of Chinese cities'accessibility. Scientia Geographica Sinica, 35(4):387-395. ]
18	宗芳, 隽志才, 张慧永 , 等. 2009. 出行时间价值计算及应用研究[J]. 交通运输系统工程与信息, 9(3):114-119.
	Zong F, Juan Z C, Zhang H Y , et al. 2009. Calculation and application of value of travel time. Journal of Transportation Systems Engineering and Information Technology, 9(3):114-119. ]
19	Cheng Y H . 2009. High-speed rail in Taiwan: New experience and issues for future development[J]. Transport Policy, 10:1-13. doi: 10.1016/S0967-070X(02)00008-2
20	Concepción R, Raquel E, Juan C M . 2007. Competition of high-speed train with air transport: The case of Madrid-Barcelona[J]. Journal of Air Transport Management, 13(5):277-284. doi: 10.1016/j.jairtraman.2007.04.009
21	Frédéric D . 2011. High-speed rail and air transport competition in Western Europe: A supply-oriented perspective[J]. Transport policy, 18(6):870-879. doi: 10.1016/j.tranpol.2011.06.002
22	Givoni M . 2006. Development and impact of the modern high-speed train: A review[J]. Transport Reviews, 26:593-611. doi: 10.1080/01441640600589319
23	Oskar Fröidh . 2008. Perspectives for a future high-speed train in the Swedish domestic travel market[J]. Journal of Transport Geography, 16(4):268-277. doi: 10.1016/j.jtrangeo.2007.09.005
24	Park Y, Ha H K . 2006. Analysis of the impact of high-speed railroad service on air transport demand[J]. Transportation Research, 42(2):96-140.
25	Vickerman R . 1997. High speed rail in Europe: Experience and tissues for future development[J]. Annals of Regional Science, 31:21-38. doi: 10.1007/s001680050037
26	Yang H, Burghouwt G, Wang J , et al. 2018. The implications of high-speed railways on air passenger flows in China[J]. Applied Geography, 97(8):1-8. doi: 10.1016/j.apgeog.2018.05.006
27	Yang H, Dobruszkes F, Wang J , et al. 2018. Comparing China's urban systems in high-speed railway and airline networks[J]. Journal of Transport Geography, 68(4):233-244. doi: 10.1016/j.jtrangeo.2018.03.015

类别	涉及城市	人均时间价值
第一档	北京、上海、天津	52.90元/h
第二档	南京、杭州、宁波、济南、青岛、武汉、长春、重庆、沈阳、大连、广州、深圳	35.00元/h
第三档	哈尔滨、西宁、福州、厦门、郑州、合肥、石家庄、南昌、长沙、西安	28.00元/h
第四档	昆明、兰州、贵阳、太原、南宁、成都、呼和浩特、乌鲁木齐	17.63元/h

中心城市	高铁日均运行频次	铁路总频次	高铁比重	中心城市	高铁日均运行频次	铁路总频次	高铁比重
福州	337	349	0.97	合肥	278	333	0.83
厦门	311	323	0.96	青岛	146	182	0.80
长沙	702	756	0.93	南昌	286	361	0.79
深圳	588	634	0.93	西安	357	454	0.79
宁波	201	217	0.93	大连	119	160	0.74
南京	657	726	0.90	长春	239	323	0.74
广州	962	1068	0.90	北京	605	824	0.73
武汉	633	703	0.90	石家庄	286	411	0.70
济南	443	500	0.89	西宁	57	84	0.68
成都	416	470	0.89	沈阳	290	447	0.65
上海	748	846	0.88	兰州	162	252	0.64
南宁	332	380	0.87	昆明	141	230	0.61
杭州	497	574	0.87	太原	122	221	0.55
郑州	474	554	0.86	哈尔滨	183	336	0.54
天津	548	641	0.85	呼和浩特	70	137	0.51
重庆	308	366	0.84	乌鲁木齐	46	135	0.34
贵阳	228	272	0.84

类别	绝对优势区/km		高铁、航空竞争激烈区/km	相对优势区/km
类别	高铁	航空	高铁、航空竞争激烈区/km	高铁	航空
第一档	320以内	1020以上	610~880	320~610	880~1020
第二档	400以内	1130以上	680~910	400~680	910~1130
第三档	480以内	1290以上	790~1080	480~790	1080~1290
第四档	520以内	1370以上	880~1230	520~880	1230~1370

城市	高铁绝对优势区	竞争激烈区	相对优势区	航空绝对优势区	城市	高铁绝对优势区	竞争激烈区	相对优势区	航空绝对优势区
北京	0.017	0.026	0.047	0.910	南昌	0.033	0.068	0.108	0.791
成都	0.013	0.017	0.056	0.914	南京	0.041	0.053	0.105	0.801
大连	0.007	0.032	0.031	0.930	武汉	0.027	0.081	0.054	0.838
福州	0.008	0.077	0.113	0.802	南宁	0.015	0.046	0.051	0.888
广州	0.028	0.051	0.050	0.871	深圳	0.017	0.047	0.018	0.918
贵阳	0.012	0.018	0.063	0.907	厦门	0.009	0.072	0.087	0.832
哈尔滨	0.011	0.013	0.009	0.967	天津	0.034	0.047	0.052	0.867
济南	0.050	0.066	0.115	0.769	石家庄	0.055	0.076	0.061	0.808
杭州	0.033	0.042	0.072	0.853	上海	0.033	0.041	0.034	0.892
合肥	0.052	0.093	0.124	0.731	沈阳	0.012	0.014	0.031	0.943
青岛	0.011	0.067	0.069	0.853	太原	0.041	0.053	0.065	0.841
呼和浩特	0.032	0.039	0.082	0.847	乌鲁木齐	0	0	0	1.000
长春	0.012	0.014	0.013	0.961	西安	0.012	0.087	0.085	0.816
宁波	0.026	0.038	0.065	0.871	重庆	0.017	0.045	0.017	0.921
昆明	0.011	0.012	0.028	0.949	西宁	0.012	0.014	0.012	0.962
兰州	0.018	0.021	0.029	0.932	郑州	0.063	0.081	0.123	0.733
长沙	0.017	0.096	0.135	0.752

城市	未通航城市	城市	未通航城市	城市	未通航城市
广州	青岛	哈尔滨	拉萨、兰州、西宁	天津	西宁
长沙	拉萨、石家庄	济南	拉萨	太原	西宁
大连	拉萨、银川、西宁	石家庄	长沙、拉萨、兰州、南昌、西宁	武汉	拉萨
合肥	长春、贵阳、拉萨	兰州	石家庄、宁波、长春	南宁	拉萨、宁波、西宁
郑州	拉萨	南昌	拉萨、长沙、长春	贵阳	长春、西宁
长春	贵阳、合肥、拉萨、兰州、南昌、宁波、银川、西宁	青岛	拉萨	沈阳	拉萨、银川、西宁
呼和浩特	宁波、西宁	宁波	长春、呼和浩特、兰州、南宁、乌鲁木齐、西宁	乌鲁木齐	宁波、拉萨、海口
西宁	大连、贵阳、海口、呼和浩特、哈尔滨、宁波、南宁、沈阳、石家庄、天津、太原

Spatial differentiation of the impact of high-speed rail on aviation passenger market in central cities of China

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