Analysis of the Characteristics and Spatial Pattern of the Catering Industry in the Four Central Cities of the Yangtze River Delta

Abstract

The development of the catering industry in big cities is of great significance for countries to improve the quality of development and improve people’s living standards. In recent years, the urban catering industry has effectively promoted the process of urbanization, and it is significant to study the development characteristics and spatial distribution of the catering industry for the urban pattern. Taking the four central cities (Shanghai, Hangzhou, Nanjing, and Hefei) of China’s Yangtze River Delta (YRD) urban agglomeration as examples, first, the point-of-interest (POI) data of various catering facilities in the city’s main urban area were crawled from the Amap (AutoNavi map) open platform through Python. Second, for the first time, three quantitative indicators were constructed to characterize the development and urbanization of the urban catering industry, namely cuisine localization index (CLI), cuisine diversity index (CDI), and cuisine geographical preference index (CGPI). Third, the overall spatial characteristics of the catering industry in the four central cities and administrative districts were obtained using the methods of kernel density and spatial autocorrelation analysis. The spatial distribution of the catering industry development in each city is displayed through GIS visualization, and its influencing factors are discussed preliminarily through geographically weighted regression (GWR) model. The research shows that: (1) the four central cities in the YRD have formed core catering areas with different agglomeration levels. Different cuisines in the city have the characteristics of partial spatial overlap. (2) In the four central cities of the YRD, there is a significant positive spatial correlation between the catering industry as a whole and individuals. Hangzhou and Hefei have higher CLI (0.38), but the cuisine structure is relatively simple. The CLI of Shanghai and Nanjing is at a low level, but the overall cuisine structure is relatively balanced. (3) The catering industry in the four central cities has a high degree of agglomeration, a wide range of agglomeration, and many agglomeration points. Only Shanghai cuisine, Jiangsu and Zhejiang cuisine, Anhui cuisine, Fujian cuisine, Shandong cuisine, and Hunan cuisine have significant positive correlations in space, and the correlations weaken in turn. (4) The influence intensity of the influencing factors on CLI and CDI is in the order of degree of openness, regional economic level, market vitality, population concentration level, industrial structure. The spatial pattern of catering in a city is greatly affected by the regional economy and population density. This study can provide a reference for research on the spatial distribution of the catering industry in similar urban agglomerations around the world.

Spatial differences and underlying mechanisms in electronic word of mouth in the foodservice industry: A case of Sanya, China

“…The spatial distribution and influencing factors of the foodservice industry have previously been studied from the perspective of tourism, mainly in the context of single foodservice formats such as hotels [ 11 ], tourist restaurants [ 12 ], fast food chains [ 13 ], and high-end restaurants [ 14 ]. As the availability of spatial data has increased, scholars have begun to use qualitative methods to study the spatial characteristics and influencing factors of the foodservice industry, which include transportation accessibility [ 15 ], economic development [ 16 ], population density [ 16 , 17 ], infrastructure [ 18 , 19 ], locational factors [ 20 ], market demand [ 21 ], supplier density [ 22 ], commercial land prices [ 23 ], size and cost [ 24 ], and restaurant type [ 25 ].…”

“…The kernel density estimation, cold hotspot analysis, spatial clustering and other methods have been used in these studies [ 15 , 26 ]. Quantitative analysis methods such as correlation analysis, geodetector software, and geographically weighted regressions have been used to explain the impacts of various factors on the spatial pattern in the foodservice industry [ 16 , 21 , 27 ]. Recently, the Online To Offline (O2O) model has dramatically changed the spatial distribution of restaurants in China.…”

Evolution Characteristics and Causes—An Analysis of Urban Catering Cluster Spatial Structure

“…For example, joint promotion and mutual support among enterprises within catering clusters can enhance the visibility and brand image of the entire cluster [22]. Moreover, research has shown that the spatial relationships of urban and community catering clusters [23,24], the agglomeration process of catering clusters [25], and the variations in cluster size of different catering clusters [13] all contribute to regional economic development, including the creation of employment opportunities and tax revenue [8,14,26]. Catering clusters that are not severely affected by competition can elevate the visibility and appeal of the entire region, enticing more diners to patronize restaurants and bolstering the growth of the overall catering industry.…”

“…Currently, scholars have explored various aspects of catering clusters using POI data, specifically the identification of catering clusters [23,31], the spatial distribution characteristics of catering clusters [16,32], the guidance of catering clusters for urban planning [33,34], the economic benefits of catering clusters [35,36], and the competition and cooperation of catering clusters [37,38] and the network relationships of catering clusters [39,40]. The emergence of POI data enables a clearer and more accurate analysis of the distribution of restaurant establishments, the development patterns of catering clusters, and the mechanisms of cluster evolution, whether viewed from a macro or micro perspective.…”

Analysis of the Aggregation Characteristics and Influencing Elements of Urban Catering Points in Small Scale: Methods and Results

“…The current literature on the aggregation characteristics of urban commercial formats, including catering, can be divided into two main aspects. The first aspect concerns the spatial distribution of the urban commercial formats that can be identified through various methods and indicators such as KDE, Moran's I, Getis-Ord G*, and DBSCAN [5][6][7][8][9]. On this basis, analyses of different urban commercial formats' location choices have also been conducted.…”