北京市主城区餐馆空间分布格局研究

A Study on the Spatial Distribution Pattern of Restaurants in Beijing's Main Urban Area

文章通过数据挖掘技术从互联网获取到北京市主城区的餐馆数据及其属性信息,运用GIS空间分析方法,从空间分布、人均消费等级和网络口碑等级3个方面对北京市主城区餐馆的空间分布格局进行了详细地描述和分析。研究发现,餐馆整体上呈现"一主两副多中心",从城市中心向外围递减的分布格局,不同人均消费等级和网络口碑等级的餐馆呈现"中间多两头少"的纺锤形分布特征。同时,构建了17个指标,从人口分布因素、区域经济水平、交通便捷度、公共服务设施便捷度、旅游资源、互联网用户情感这6个方面对餐馆空间分布格局的影响因素进行了梳理。文章从互联网获取相关数据及居民情感信息,并将其应用到了城市规划实例中,为商业地理和城市地理的研究提供了有益借鉴。同时,文章对餐馆空间分布格局和影响因素的研究,也对城市规划、旅游行业、餐馆经营和互联网电子商务行业的发展起到积极作用。

In this paper,we aimed to analyze the space distribution pattern of restaurants in Beijing＇s main urban area and to interpret the factors that influenced the characteristics of the restaurants＇ spatial distribution. We explored and analyzed the spatial distribution of the restaurants using methods including data mining technology,geographic information system（GIS） spatial analysis,and statistical and econometric approaches. First,through data mining technology,we found the restaurants of the Beijing main urban area and their attributes from the Internet. Then,we divided the restaurants into five categories of different per capita consumption levels according to the attributes of the price per person.When the price per person of a restaurant was lower than 20 yuan,it was classified as a low- grade restaurant; if the price per person was lower than 50 yuan and higher than 20 yuan,it was classified as a low-to middle-grade restaurant; middle- grade restaurants＇ price per person was lower than 100 yuan and higher than 50 yuan; middle- to high-grade restaurants＇ price per person was lower than 200 yuan and higher than 100 yuan; and high-grade restaurants＇ price per person was higher than 200 yuan. We also divided restaurants into three grades of Internet word of mouth（IWOM） levels according to the attributes of the user ratings. When the user ratings of a restaurant were lower than 1,was classified as low quality,if the user ratings were lower than 4 and higher than 1,a restaurant was classified midrange,and high-quality restaurants＇ user ratings were lower than 5 and higher than 4. Afterwards,we detailed,described,and analyzed the overall spatial distribution characteristics,the different per capita consumption levels,and different IWOM levels of the restaurants in Beijing＇s main urban area using the geographic information system（GIS） spatial analysis method. Our study showed that the distribution pattern of restaurants in the main urban area of Beijing can be characterized as one primary and two secondary zones with multiple centers as a whole,with the number decreasing from the city center to the periphery. The distribution of the restaurant consumption and the IWOM levels was a spindle shape,the characteristics of which can be summarized as having more factors located in the middle and fewer at the ends. Finally,we put forward 17 indicators from six major systems,the population distribution,the regional economy,transportation convenience,infrastructure convenience,tourism resources,and Internet users＇ emotions,to explore and the factors that influenced the spatial distribution of the restaurants. Generally,we creatively acquired the relevant data and residents＇ emotional information from the Internet and applied it to a city planning instance,which was a useful reference for studying commercial and urban geography. Meanwhile,the results of this paper pertaining to the spatial distribution pattern of restaurants and influencing factors could play a positive role in the development of urban planning,the tourism industry,restaurant management,and Internet e-commerce.