上海市旅游住宿业房价空间分异规律及其影响因素

doi:10.13249/j.cnki.sgs.2022.08.007

摘要/Abstract

摘要：

以上海市主城区住宿业为研究对象，采用Arc GIS10.3、GeoDa分析软件，通过绘制等价格圈，研究房价空间分异规律及其影响因素。结果表明：① 上海市住宿业客房等价格圈圈层结构明显，在迪士尼度假区和南京东路–陆家嘴区域形成价格峰值，以此为中心，客房等价圈呈现中心–外围的渐次梯度分布特征。② 一级等价圈围绕市中心、副中心、一级商业中心、主题街区、核心景区、高校科技园区等圈层分布；二级等价圈主要沿城市核心交通枢纽、交通干道，以及区级行政中心周围分布；三级等价圈主要沿主城区边界向外围扩展分布，在传统工业区、物流园区等形成“价格洼地”。③ 在中心城区、迪士尼度假区、虹桥商务区、闵行环高校科创带等典型区域形成“多中心”“单中心”“带状”“组团式”相对价格高值区。④ 房价与企业到旅游吸引物、交通枢纽、商业中心、行政中心、高校园区、会展中心距离呈显著负相关，此外还受到企业规模、网络评分、经营周期等内部因素的综合影响。

关键词: 住宿业, 等价格圈, 住宿业房价, 上海市

Abstract:

Taking the lodging industry in the main urban area of Shanghai as the research object, the spatial distribution law and influencing factors of room prices are studied by drawing equal price circles through Arc GIS and GeoDa software. The results show that: 1) The price circle structure of lodging rooms in Shanghai is obvious. The price peak is formed in the Disney Resort and the Lujiazui of Nanjing East Road, and presents the characteristics of gradual gradient distribution from the center to the periphery. 2) The first level equivalent circle is distributed around the city center, sub center, first level business center, theme block, core scenic spot, university science and technology park and other circles; The second equivalent circle is mainly distributed along the urban core transportation hub, transportation trunk road and around the district administrative center; The third level equivalent circle is mainly distributed to the periphery along the boundary of the main urban area, forming a “price depression” in traditional industrial areas and logistics parks. 3) In the central urban area, Disney Resort, Hongqiao Business District, Minhang University Science and innovation belt and other typical areas, “multi center, single center, ribbon and group” high-value price areas will be formed. 4) Room price is significantly negatively correlated with the distance from enterprises to tourism attractions, transportation hubs, business centers, administrative centers, University Parks and Convention and exhibition centers. In addition, it is also affected by the comprehensive impact of internal and external factors such as enterprise scale, network score, business cycle and so on.

Key words: lodging industry, equal room price circle, room price of lodging industry, Shanghai

中图分类号:

K901

高杨, 王朝辉, 乔浩浩, 殷鹏. 上海市旅游住宿业房价空间分异规律及其影响因素[J]. 地理科学, 2022, 42(8): 1391-1401.

Gao Yang, Wang Chaohui, Qiao Haohao, Yin Peng. Spatial Differentiation and Influencing Factors of Room Prices in Tourism Lodging Industry in Shanghai[J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(8): 1391-1401.

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影响因素维度	影响因素	量化标准	数据来源
内部影响因素	企业规模	客房数量	去哪儿网（ https://www.qunar.com/）
	经营周期	开业到目前的时间	去哪儿网（ https://www.qunar.com/）
	网络评分	综合评分	去哪儿网（ https://www.qunar.com/）
外部影响因素	商业条件	距市级商业中心最短距离	《上海市商业网点布局规划（2013—2020年）》（ https://ghzyj.sh.gov.cn/）
	交通条件	距火车站、高铁站最短距离	上海交通出行网（ http://www.jtcx.sh.cn/）
	展会场馆格局	距会展中心最短距离	上海展会网（ http://www.shexpo.me/）
	旅游吸引物	距景区旅游景点最短距离	上海旅游网（ http://www.962020.com/）、上海文旅推广网（ https://chs.meet-in-shanghai.net/）
	高等学校分布	距离高校科技园区最短距离	中国学位与研究生教育信息网（ http://www.cdgdc.edu.cn/）
	行政中心驻地	距离市（区）行政驻地最短距离	市（区）政府网站（ https://www.shanghai.gov.cn/）

解释变量	回归系数	稳健概率	VIF
企业规模	0.1824	0.0000	1.7123
经营周期	-0.0277	0.0217	1.1681
网络评分	0.0542	0.0002	1.1121
商业条件	-0.0683	0.0000	2.9366
交通条件	-0.0761	0.0000	3.3684
展会场馆格局	-0.0392	0.0339	4.2635
旅游吸引物	-0.0788	0.0010	3.0014
高等学校分布	-0.0428	0.0139	2.0453
行政中心驻地	-0.0643	0.0281	3.9059