基于互联网数据的住宿业竞争力及其空间格局——以武汉主城区高端酒店为例

doi:10.18306/dlkxjz.2018.10.010

Abstract

Abstract:

The rapid development of the Internet provides a new breakthrough point for urban geography research by using Internet data and technology to study urban physical space problems. Based on customer reviews and comments of online-to-offline (O2O) platform, real-time traffic data, and points of interest (POI) data of web-map, this study set up a competitiveness evaluation index system of high-end hotels and calculated the high-end hotel competitiveness and ranking of Wuhan urban area, then emphatically analyzed its spatial patterns using GIS tools. The results indicate that: (1) With most hotels in the middle and few in the top and bottom rankings, the competitiveness distribution line indicates a general concentrated structure. Price, popularity, business, and commerce services in the surroundings are the main factors that widen the competitiveness levels between hotels. (2) The overall spatial structure is featured by a mixture of point clustering and linear spread that basically concentrate in Wuchang and Hankou town areas within the second ring road. (3) As the competitiveness grades go down, hotels are more likely to locate toward the outskirt of the city, showing a circling spatial structure. (4) The spatial distribution model of Wuhan high-end hotels can be summarized as seven types of hotel spatial layout, such as super-high-end hotels located in the newly-developing business district in the central activity zone (CAZ), middle-leveled high-end hotels located in the traditional business district in the CAZ, and middle-leveled high-end hotels located around traffic gateways, and so on.

Key words: internet data, high-end hotels, competitiveness, spatial structure, Wuhan City

Juan WANG, Yajuan Li, Li LV, Jing HU, Xiang ZHANG. Hotel competitiveness evaluation and spatial pattern based on Internet data: A case study of high-end hotels of Wuhan urban area[J].PROGRESS IN GEOGRAPHY, 2018, 37(10): 1405-1415.

Figures/Tables 10

Fig.1

Fig.2

Tab.1

Evaluation index system of Wuhan high-end hotel competitiveness"

一级指标(权重)	二级指标(权重)	指标说明
X₁酒店价格(0.191)	X_1-1房间起售价格(0.191)	反映酒店的档次和消费水平
X₂酒店人气(0.108)	X_2-1酒店点评数(0.108)	酒店的总点评数
X₃酒店区位(0.247)	X_3-1距离交通门户平均耗时(0.166)	酒店距离机场、火车站的平均耗时
	X_3-2 2 km内最近地铁站距离(0.063)	酒店附近最近的地铁站到酒店的距离,2 km内无地铁站的此项得分为0
	X_3-3 2 km内热门景点数(0.018)	酒店2 km内可达的热门景点数,包括旅游景点、城市公园、购物商圈等
X₄酒店满意度(0.304)	X_4-1五星好评占总评论数比例(0.06)	五星好评数与全部点评数的比值
	X_4-2房间评分(0.075)	消费者对某酒店房间的打分
	X_4-3设施评分(0.009)	消费者对某酒店设施的打分
	X_4-4环境评分(0.013)	消费者对某酒店环境的打分
	X_4-5位置评分(0.031)	消费者对某酒店位置的打分
	X_4-6服务评分(0.027)	消费者对某酒店服务的打分
	X_4-7卫生评分(0.089)	消费者对某酒店卫生的打分
X₅酒店周边商业服务(0.045)	X_5-1 1 km内购物中心/商业街数(0.035)	酒店1 km缓冲区内购物中心/商业街的数量
	X_5-2 1 km内大型超市数(0.007)	酒店1 km缓冲区内大型超市的数量
	X_5-3 500 m内品牌便利店数(0.003)	酒店500 m缓冲区内购品牌便利店的数量
X₆酒店周边商务服务(0.051)	X_6-1 1 km内商务大厦数(0.028)	酒店1 km缓冲区内商务大厦/写字楼的数量
	X_6-2 1 km内企事业单位数(0.011)	酒店1 km缓冲区内企事业单位的数量
	X_6-3 1 km内金融机构数(0.012)	酒店1 km缓冲区内金融机构的数量
X₇其他因素(0.054)	X_7-1酒店所属集团排名(0.038)	HOTELS杂志公布的“2016年度全球酒店集团排名”,若未上榜,则此项得分为0
	X_7-2酒店客房数(0.01)	酒店拥有的房间数
	X_7-3开业或装修时间(0.006)	酒店最近一次装修时间,开业后未重新装修的即为开业时间

Tab.1

Fig.3

Fig.4

Fig.5

Tab.2

Fig.6

Fig.7

Fig.8

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酒店等级	酒店个数	最大值	最小值	平均值	标准差
第一等级	17	80.584	56.729	62.080	6.110
第二等级	62	56.073	47.408	51.382	2.512
第三等级	65	47.353	40.705	44.123	2.017
第四等级	53	40.225	32.220	36.473	2.459
第五等级	37	32.048	18.256	27.781	3.793
总计	234	80.584	18.256	43.034	10.028

Hotel competitiveness evaluation and spatial pattern based on Internet data: A case study of high-end hotels of Wuhan urban area

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