区域旅游流空间结构的高铁效应及机理——以中国京沪高铁为例

doi:10.11821/dlxb201502004

Abstract

Abstract:

Transportation is one of the most important factors affecting spatial structure of tourist flow. Taking Beijing-Shanghai High-speed Rail (Hereinafter referred to as the HSR) as an example, the paper firstly explores the features and HSR effects of spatial structure of regional tourist flow with the help of social network analysis method. And then it points out the changes of the accessibility in regional transportation. After analyzing the following various influencing factors, e.g. the initial endowment of regional tourist resources, the hospitality facilities, the density of regional tourism transportation network, the location, etc., the paper discusses about the mechanism of HSR effect of spatial structure in regional tourist flow. The results are shown as follows: (1) The HSR effects of spatial structure in regional tourist flow are manifested as the "Matthew effect", the "filtering effect", the "diffusion effect" and the "overlying effect"; (2) The "Matthew effect" of HSR is manifested under the obvious interaction of the location condition, the initial endowment of tourist resources, hospitality capacity, tourist transportation network density and the "time-space compression"; the "filtering effect" of HSR is manifested in those tourism nodes without favorable location condition, endowment of tourist resources, hospitality capacity, tourist transportation network density, and obvious "time-space compression"; For those tourist nodes that boast favorable advantages in terms of location condition, endowment of tourist resources, hospitality capacity, tourist transportation network density and obvious "time-space compression", they will become diffusion sources. HSR will strengthen the aggregation effects of tourist flow in those diffusion sources, and thereafter, will diffuse to the peripheral tourist areas, manifesting the mode of "aggregation-diffusion"; HSR has resulted in the multiplicity phenomenon in terms of tourists' traveling spatial range for those from large-scale spaces. However, the "overlying effect" is only generated in those tourist nodes with favorable location condition, endowment of tourist resources, hospitality capacity, tourist transportation network density, and obvious "time-space compression".

Key words: tourist flow, spatial structure, HSR effect, mechanism, Beijing-Shanghai HSR

Degen WANG, Tian CHEN, Lin LU, Li WANG, August Lew ALAN. Mechanism and HSR effect of spatial structure of regional tourist flow: Case study of Beijing-Shanghai HSR in China[J].Acta Geographica Sinica, 2015, 70(2): 214-233.

Figures/Tables 11

Fig.1

Tab. 1

Changes of network centrality of tourist flow of Beijing and Shanghai before and after HSR opening"

北京旅游流网络								上海旅游流网络
旅游节点		高铁前			高铁后			旅游节点	高铁前			高铁后
	程度中心性			中间中心性		程度中心性		中间中心性	程度中心性		中间中心性	程度中心性		中间中心性
	外向			内向			外向	中间中心性	内向		外向	内向	外向	内向
D2	0.00	3.85	0.00	0.00	0.00	0.00		D27	3.85	11.54	0.46	7.69	3.85	0.00
D3	0.00	6.95	0.00	0.00	4.85	0.00		D26	3.85	7.70	0.00	7.69	7.69	0.19
D4	0.00	3.85	0.00	0.00	3.70	0.00		D25	11.54	11.54	0.92	5.64	9.12	0.39
D6	0.00	3.85	0.00	0.00	3.70	0.00		D24	3.85	7.69	0.00	3.85	0.00	0.00
D7	0.00	3.85	0.00	0.00	3.70	0.00		D22	7.69	11.54	0.92	9.74	13.96	2.68
D5	0.00	0.00	0.00	0.00	0.00	0.00		D21	0.00	3.85	0.00	0.00	3.85	0.00
D8	15.23	3.85	0.77	15.39	3.85	0.46		D20	0.00	0.00	0.00	0.00	0.00	0.00
D9	0.00	3.85	0.00	0.00	4.15	0.00		D19	0.00	3.85	0.00	0.00	3.85	0.00
D10	0.00	3.85	0.00	0.00	4.15	0.00		D18	0.00	3.85	0.00	0.00	7.69	0.00
D11	0.00	3.85	0.00	0.00	4.50	0.00		D17	0.00	3.85	0.00	7.69	3.85	0.00
D12	0.00	3.85	0.00	3.85	7.69	0.00		D16	0.00	0.00	0.00	0.00	0.00	0.00
D13	3.85	3.85	0.15	7.69	11.54	0.92		D15	0.00	3.85	0.00	3.85	4.15	0.00
D14	0.00	3.85	0.00	0.00	4.52	0.00		D14	0.00	3.85	0.00	0.00	7.69	0.00
D15	0.00	3.85	0.00	0.00	4.15	0.00		D13	0.00	3.85	0.00	19.23	26.92	9.85
D16	0.00	0.00	0.00	0.00	0.00	0.00		D10	0.00	0.00	0.00	3.85	3.85	0.00
D17	0.00	3.85	0.00	3.85	3.85	0.15		D11	0.00	0.00	0.00	0.00	0.00	0.00
D18	0.00	0.00	0.00	0.00	3.85	0.00		D12	0.00	3.85	0.00	3.85	7.69	0.08
D19	0.00	0.00	0.00	0.00	3.85	0.00		D8	0.00	3.85	0.00	15.39	7.69	3.65
D20	0.00	0.00	0.00	0.00	0.00	0.00		D9	0.00	0.00	0.00	0.00	3.85	0.00
D21	0.00	0.00	0.00	0.00	3.85	0.00		D5	0.00	0.00	0.00	0.00	0.00	0.00
D22	0.00	3.85	0.00	7.69	7.70	0.35		D7	0.00	3.85	0.00	0.00	0.00	0.00
D24	0.00	0.00	0.00	0.00	3.85	0.00		D6	0.00	0.00	0.00	0.00	0.00	0.00
D25	0.00	0.00	0.00	0.00	3.70	0.00		D4	0.00	0.00	0.00	3.85	0.00	0.00
D26	0.00	0.00	0.00	3.85	3.85	0.00		D3	0.00	3.85	0.00	3.85	4.52	0.00
D27	0.00	3.85	0.00	3.85	11.54	0.11		D2	0.00	0.00	0.00	0.00	3.85	0.00
D28	0.00	3.85	0.00	0.00	11.54	0.00		D1	0.00	3.85	0.00	11.54	26.92	4.23
D23	0.00	3.85	0.00	0.00	3.85	0.00		D30	0.00	0.00	0.00	0.00	3.85	0.00
-	-	-	-	-	-	-		D29	0.00	3.85	0.00	0.00	4.52	0.00

Tab. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig.6

Fig.7

Fig.8

Tab. 2

Fig. 9

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城市	高铁旅游需求位序	旅游资源禀赋位序	旅游接待能力位序	交通密度位序	高铁运行时间	动车运行时间
天津	5/4	12/12	7/12	3/3	0.40/3.99	0.93/8.90
沧州	20/25	25/26	22/23	19/19	0.75/3.40	1.80/8.10
德州	27/24	18/20	24/25	13/13	1.10/3.10	2.50/7.30
济南	2/3	20/21	6/6	9/9	1.40/2.95	3.30/6.50
泰安	4/2	14/15	11/10	11/11	1.60/2.60	3.80/6.10
枣庄	13/2	8/8	23/24	10/10	2.10/2.00	5.10/4.80
徐州	19/18	23/24	18/18	14/14	2.30/1.80	5.50/4.40
宿州	17/20	26/27	27/28	17/17	2.50/1.60	6.00/3.90
蚌埠	26/26	22/23	26/27	12/12	2.80/1.40	6.60/3.30
滁州	24/19	21/22	25/26	21/21	3.15/1.00	7.50/2.40
南京	1/7	4/3	5/5	6/6	3.30/0.87	7.80/2.00
镇江	22/21	16/17	21/22	4/4	3.50/0.68	8.30/1.60
常州	21/6	19/18	15/15	5/5	3.70/0.50	8.80/1.10
无锡	16/10	9/7	13/13	8/8	3.80/0.37	9.00/0.85
苏州	6/5	2/2	3/3	2/2	3.90/0.25	9.30/0.57

Mechanism and HSR effect of spatial structure of regional tourist flow: Case study of Beijing-Shanghai HSR in China

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