浙江省县域入境旅游时空跃迁特征及驱动机制

doi:10.11821/dlyj201606014

摘要/Abstract

摘要：

县域旅游是支撑中国旅游产业发展的重要基础单元,也是未来入境旅游发展的新方向,当下对县域入境旅游研究的缺失阻碍着对小尺度入境旅游地发展的认知和重视。以浙江省县域为研究对象,借助空间变差函数模拟了浙江县域入境旅游空间格局的演变特征。进一步通过LISA时间路径、时空跃迁测度了各县市入境旅游时空跃迁特征及类型,并将分位数回归与时空跃迁类型相嵌套,建立了四种时空跃迁驱动机制模式。结果表明：浙江省县域入境旅游具有明显的空间集聚特征,“一杭独大”特征显著,且空间自组织性逐年增强,区域入境旅游核心县市扩散效应不断增加,核心县市辐射区域差异逐渐缩小,空间差异主要体现在局部方向;浙江省县域入境旅游空间格局的演化具有较强的正向空间整合性,县域类别之间存在一定的转移惰性,东南—西北区域的入境旅游落后县市具有相对动态的局部空间特征,常山县在空间依赖方向上具有最大的波动性,岱山县在空间依赖方向上具有最大的稳定性;产业—结构驱动、经济—服务制约、贸易—产业驱动、区位—资源制约四种驱动模式呈现出自东北至西南逐渐由同向发展到同向制约的演化过程,此外四种模式背后隐含着不同的影响机理。

关键词: 县域, 入境旅游, 格局演变, 时空跃迁, 驱动机制

Abstract:

County-scale tourism has been recognized as one of the important base units that supports the tourism industry development in China and has also been regarded as the new direction of inbound tourism in the future. The lack of research on county-scale inbound tourism hinders people's cognition and attention to the development in small scale inbound tourism destination. With the help of ESTDA analytical framework and spatial variation function, the spatial correlation characteristics of county-scale inbound tourism in counties of Zhejiang province are simulated. Then the space-time evolution characteristics and types of inbound tourism are measured in each county by means of LISA time path and the space-time transition. In this way, nesting the quantile regression model and space-time evolution type is achieved, which also promotes the construction of space-time transition driving mechanism model. The result shows that the county-scale inbound tourism in Zhejiang has the obvious feature of spatial aggregation—with Hangzhou playing a dominant role. Moreover, the spatial self-organizing feature is increasingly reinforced while its spatial differences are gradually lessened, the latter of which can be reflected at the local level. On the one hand, the revolution pattern of county-scale inbound tourism in this province is feature by significantly positive space integration; on the other hand, there is a degree of transfer inertia between counties. Apart from that, it is shown that the inbound tourism of the backward counties located in the northwest and southeast parts has a relatively dynamic local spatial feature. To be more specific, Changshan county has the most significant volatility in the spatial dependence while the Daishan county has the best stability. In addition, the space-time transition driving patterns of county-scale inbound tourism in Zhejiang are divided into four categories (driving the industry-structure driving pattern, the economy-service restriction modes, the trade-industry driving pattern and the location-resource restriction modes), which present an obvious evolution process which starts from synthetic development and then gradually turns into synthetic restriction from northeast to southwest area. There are less driving areas and more restricted areas at low quantile level, while more driving areas and less restricted areas at high quantile level. And the four main patterns imply different influence mechanisms.

Key words: county-scale, inbound tourism, pattern evolvement, space-time transition, driving mechanism

张子昂, 黄震方, 曹芳东, 王坤, 陈晓艳. 浙江省县域入境旅游时空跃迁特征及驱动机制[J]. 地理研究, 2016, 35(6): 1177-1192.

Zi'ang ZHANG, Zhenfang HUANG, Fangdong CAO, Kun WANG, Xiaoyan CHEN. The space-time transition characteristics and its driving mechanism of county-scale inbound tourism in Zhejiang province[J]. GEOGRAPHICAL RESEARCH, 2016, 35(6): 1177-1192.

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年份	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
Moran's I	0.193	0.243	0.252	0.271	0.232	0.255	0.286	0.274	0.265	0.291
Z检验	2.355	2.914	3.015	3.228	2.794	3.057	3.410	3.280	3.177	3.454
P值	0.019	0.004	0.003	0.001	0.005	0.002	0.001	0.001	0.001	0.001

	年份	变程(km)	块金值C₀	基台值	块金系数	拟合模型	决定系数
入境旅游发展	2004	100.8	0.431	3.307	0.130	Exponential	0.670
	2005	117.0	0.473	3.388	0.139	Exponential	0.779
	2006	198.3	1.283	3.398	0.378	Exponential	0.775
	2007	114.3	0.495	3.165	0.156	Exponential	0.791
	2008	128.4	0.556	3.323	0.167	Exponential	0.860
	2009	144.6	0.424	3.061	0.138	Exponential	0.846
	2010	173.1	0.381	2.971	0.128	Exponential	0.857
	2011	191.7	0.450	2.885	0.156	Exponential	0.870
	2012	206.7	0.289	2.882	0.100	Exponential	0.810
	2013	102.9	0.295	2.748	0.107	Exponential	0.838

	年份	全方向			南—北		东北—西南			东—西			东南—西北
	年份	D		R²		D	R²		D	R²	D	R²	D	R²
入境旅游发展	2004	1.883	0.761		1.964	0.763	1.787	0.467		1.838	0.724		1.971	0.752
	2005	1.862	0.800		1.954	0.809	1.776	0.423		1.818	0.689		1.935	0.631
	2006	1.881	0.807		1.932	0.822	1.78	0.544		1.862	0.651		1.929	0.882
	2007	1.887	0.794		1.802	0.841	1.783	0.433		1.864	0.634		1.981	0.821
	2008	1.875	0.851		1.880	0.850	1.804	0.505		1.850	0.723		1.955	0.866
	2009	1.884	0.845		1.905	0.871	1.827	0.622		1.839	0.754		1.979	0.858
	2010	1.877	0.866		1.858	0.805	1.778	0.512		1.847	0.733		1.989	0.814
	2011	1.868	0.883		1.950	0.656	1.749	0.409		1.841	0.751		1.997	0.801
	2012	1.885	0.835		1.954	0.652	1.802	0.305		1.884	0.590		1.975	0.867
	2013	1.886	0.802		1.948	0.714	1.796	0.438		1.848	0.710		1.952	0.846

	HH_t₊₁	HL_t₊₁	LH_t₊₁	LL_t₊₁
HH_t	Ⅳ(0.750)	Ⅱ(0.000)	Ⅰ(0.150)	Ⅲ(0.100)
HL_t	Ⅱ(0.214)	Ⅳ(0.572)	Ⅲ(0.000)	Ⅰ(0.214)
LH_t	Ⅰ(0.385)	Ⅲ(0.000)	Ⅳ(0.538)	Ⅱ(0.077)
LL_t	Ⅲ(0.000)	Ⅰ(0.150)	Ⅱ(0.050)	Ⅳ(0.800)

分位数/OLS回归	截距项	PGDP	STR	REC	TRA	FECO	RES
OLS	0.001	-0.097^***	1.285^***	-0.214^***	-0.004	0.126^***	-0.147^***
0.1	-0.006	-0.042^***	0.228^***	-0.088^***	0.008^***	-0.005	0.013^***
0.2	0.002	-0.021^***	0.356^***	-0.129^***	0.003^***	-0.013	0.021^***
0.3	-0.001	-0.015^**	0.425^***	-0.118^***	0.002^**	-0.023	0.012^***
0.4	-0.001	-0.010	0.510^***	-0.127^***	0.002^*	-0.007	0.005^***
0.5	0.005	-0.014	0.636^***	-0.149^*	0.002	0.021	-0.011
0.6	0.009^***	-0.083^***	1.175^***	-0.323	-0.017^**	0.354^***	-0.036^***
0.7	0.010^***	-0.066^***	1.187^***	-0.281	-0.019^**	0.285^**	-0.037^**
0.8	0.010^***	-0.034^**	1.393^***	-0.310	-0.017^***	0.134	-0.043
0.9	0.014^**	0.006	1.500^***	-0.325	-0.031^**	0.196^*	-0.066^***