高级别景区对旅游发展的影响及其空间效应研究

doi:10.18306/dlkxjz.2022.08.002

Abstract

Abstract:

Building high-quality tourist clusters and creating multi-site scenic tour routes and loops are important breakthroughs in promoting the development of global tourism. Based on the data of "5A" scenic spots—the highest-level scenic spots—selected from 288 prefecture-level cities in China from 2006 to 2018, this study divided these sites into three categories: natural, humanistic, and comprehensive. With the help of ArcGIS and Stata, this study explored the spatial distribution characteristics of the "5A" scenic spots and quantitatively analyzed the impact and spatial effects of high-level scenic spots on tourism development of cities by using a dynamic spatial panel model. The study found that: First, "5A" scenic spots distribution showed spatial imbalance, agglomerated mainly in the eastern and central regions. Resource endowments differ great across regions, and the number of comprehensive scenic spots is seriously insufficient. Second, high-level scenic spots can significantly promote the development of tourism in cities, and have significant effects of spatial cooperation and spatial competition. Specifically, high-level scenic spots in adjacent cities of the same province have a spatial competitive effect on the cities' tourism development, and the main competition range is 0-400 km; while high-level scenic spots in adjacent cities across provinces have a spatial cooperation effect on the cities' tourism development, and the optimal cooperation range is 200-400 km. In the meantime, competition mainly occurs between the same type of scenic spots, and cooperation mainly occurs between different types of scenic spots. Finally, comparing the spatial distribution of scenic spots within each province, this study found that the scenic spots in the same province are mainly natural or humanistic "5A" scenic spots, which means that there may be competition between similar scenic spots within the same province due to their homogeneity. The conclusions of this research provide empirical evidence for the spatial allocation and spatial optimization of tourism resources.

Key words: high-level scenic spots, tourism development of cities, spatial competition, spatial cooperation, China

GONG Qinlin, ZOU Donghan, ZHOU Yi, ZHU Shengjun. Influence of high-level scenic spots on tourism development and its spatial effect[J].PROGRESS IN GEOGRAPHY, 2022, 41(8): 1364-1377.

Figures/Tables 7

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Tab.1

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References 38

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变量	邻接空间权重W₁		省内邻接空间权重W₂		省外邻接空间权重W₃
变量	模型1	模型2	模型3	模型4	模型5	模型6
y_t_-1	0.5138^***	0.1502^***	0.3403^***	0.0262^**	0.4987^***	0.0617^***
y_t_-1	(48.908)	(9.759)	(26.388)	(1.970)	(43.107)	(3.844)
scenery_t_-1	3.2730^***	4.7991^***	4.1024^***	5.2097^***	3.4671^***	4.9345^***
scenery_t_-1	(36.314)	(24.074)	(26.268)	(23.238)	(37.239)	(24.148)
W*y	0.0877	0.0356	0.4236^***	0.2470	-0.1924^***	-0.0492
W*y	(1.511)	(0.430)	(3.459)	(1.402)	(-3.019)	(-0.577)
W*scenery_t_-1	-0.1231	0.1115	-6.0577^***	-6.1736^***	0.9484^***	1.1322^***
W*scenery_t_-1	(-0.939)	(0.475)	(-6.588)	(-4.543)	(6.127)	(4.870)
trans_t_-1		0.0739^**		-0.2583^***		0.1790^***
trans_t_-1		(2.294)		(-5.618)		(5.323)
open_t_-1		0.8396^***		0.6581^***		0.8071^***
open_t_-1		(8.503)		(5.930)		(7.408)
gover_t_-1		0.1343^***		0.0211		0.0947^*
gover_t_-1		(2.655)		(0.450)		(1.884)
serv_t_-1		0.0612^***		0.0786^***		0.0822^***
serv_t_-1		(3.503)		(3.799)		(4.181)
常数	0.8040^***	-1.8372^**	0.7477^***	-0.0105	1.0697^***	-1.1005
常数	(9.390)	(-2.504)	(4.898)	(-0.013)	(12.779)	(-1.526)
年份	是	是	是	是	是	是
Hansen检验(P值)	0.0675	0.5814	0.8514	0.9938	0.0366	0.6069
AR1检验(P值)	0.0143	0.0265	0.0118	0.0150	0.0076	0.0177
AR2检验(P值)	0.2106	0.3572	0.2173	0.3223	0.1936	0.3267
N	3456	3456	3456	3456	3456	3456

变量	空间权重W_0-200		空间权重W_200-400		空间权重W_400-600		空间权重W_600-800
变量	同省模型7	跨省模型8	同省模型9	跨省模型10	同省模型11	跨省模型12	同省模型13	跨省模型14
y_t_-1	-0.0199	0.0925^***	-0.0300	-0.0814^***	-0.1078^***	0.0163	-0.0709^***	-0.5202^***
y_t_-1	(-1.503)	(5.780)	(-1.569)	(-4.457)	(-6.126)	(0.584)	(-5.092)	(-14.303)
scenery_t_-1	5.8985^***	4.4332^***	5.3637^***	5.0842^***	6.0389^***	4.6601^***	4.7913^***	6.3399^***
scenery_t_-1	(26.030)	(23.010)	(16.166)	(20.683)	(24.679)	(18.471)	(15.514)	(18.458)
W*y	0.6698^***	-0.0074	0.8103^***	-0.0890^***	0.0617	-1.0366^***	0.0893	-2.6609^***
W*y	(3.065)	(-0.108)	(3.411)	(-3.110)	(0.286)	(-3.041)	(0.023)	(-6.087)
W*scenery_t_-1	-7.8432^***	0.7883^**	-4.1389^*	9.2122^***	-1.9783	7.9239^***	-3.4645	1.4521
W*scenery_t_-1	(-4.854)	(2.247)	(-1.919)	(8.767)	(-1.229)	(6.240)	(-0.082)	(0.543)
控制变量	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
年份	是	是	是	是	是	是	是	是
Hansen检验(P值)	0.9577	0.3690	0.7979	0.6289	0.8589	0.1456	0.9406	0.6100
AR1检验(P值)	0.0109	0.0128	0.0795	0.0377	0.0292	0.0083	0.0119	0.0080
AR2检验(P值)	0.3302	0.3401	0.4551	0.3413	0.4346	0.2338	0.4126	0.4832
N	3456	3456	3456	3456	3456	3456	3456	3456

变量	省内邻接空间权重 W₂(模型15)	跨省邻接空间权重 W₃(模型16)
scenery_t_-1	0.9812^***	0.9871^***
scenery_t_-1	(477.624)	(767.137)
Diff_scenery_t_-1	0.0040	-0.0037^*
Diff_scenery_t_-1	(1.358)	(-1.819)
W*scenery	-0.0407^***	-0.0073^**
W*scenery	(-8.371)	(-2.570)
W*Diff_scenery	0.0258^***	0.0038^**
W*Diff_scenery	(3.641)	(1.985)
控制变量	Yes	Yes
年份	是	是
Hansen检验(P值)	0.1768	0.9025
AR1检验(P值)	<0.001	<0.001
AR2检验(P值)	0.8501	0.9464
N	6912	6912

Influence of high-level scenic spots on tourism development and its spatial effect

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