Redirigiendo al acceso original de articulo en 21 segundos...
ARTÍCULO
TITULO

Mining the Spatial Distribution Pattern of the Typical Fast-Food Industry Based on Point-of-Interest Data: The Case Study of Hangzhou, China

Yan Zhou    
Xuan Shen    
Chen Wang    
Yixue Liao and Junli Li    

Resumen

There is a Chinese proverb which states ?Where there are Shaxian Snacks, there are generally Lanzhou Ramen nearby?. This proverb reflects the characteristics of spatial clustering in the catering industry. Since the proverbs are rarely elucidated from the geospatial perspective, we aimed to explore the spatial clustering characteristics of the fast food industry from the perspective of geographical proximity and mutual attraction. Point-of-interest, OSM road network, population, and other types of data from the typical fast-food industry in Hangzhou were used as examples. The spatial pattern of the overall catering industry in Hangzhou was analyzed, while the spatial distribution of the four types of fast food selected in Hangzhou was identified and evaluated. The ?core-edge? circle structure characteristics of Hangzhou?s catering industry were fitted by the inverse S function. The common location connection between the Western fast-food KFC and McDonald?s and the Chinese fast-food Lanzhou Ramen and Shaxian Snacks and the spatial aggregation were elucidated, being supported by correlation analysis. The degree of mutual attraction between the two was applied to express the spatial correlation. The analysis demonstrated that (1) the distribution of the catering industry in Hangzhou was northeast?southwest. The center of the catering industry in Hangzhou was located near the economic center of the main city rather than in the center of urban geography. (2) The four types of fast food were distributed in densely populated areas and exhibited an anti-S law, which first increased but then decreased as the distance from the center increased. Among these, the number of four typical fast foods was the highest within a distance of 4?10 km from the center. (3) It was concluded that 81.6% of KFCs had a McDonald?s nearby within 2500 m, and 68.5% of Shaxian Snacks had a Lanzhou Ramen nearby within 400 m. McDonald?s attractiveness to KFC was calculated as 0.928448. KFC?s attractiveness to McDonald?s was 0.908902. The attractiveness of the Shaxian Snacks to Lanzhou Ramen was 0.826835. The attractiveness of Lanzhou Ramen to Shaxian Snacks was 0.854509. McDonald?s was found to be dependent on KFC in the main urban area. Shaxian Snacks were strongly attributed to Lanzhou Ramen in commercial centers and streets, while Shaxian Snacks were distributed independently in the eastern Xiaoshan and Yuhang Districts. This study also helped us to optimize the spatial distribution of a typical fast-food industry, while providing case references and decision-making assistance with respect to the locations of catering industries.

 Artículos similares

       
 
Haibo Li, Zhonghua Tang and Dongjin Xiang    
Acid in situ leaching (ISL) is a common approach to the recovery of uranium in the subsurface. In acid ISL, there are numerous of chemical reactions among the injected sulfuric acid, groundwater, and porous media containing ore layers. A substantial amou... ver más
Revista: Water

 
Hadis Mohajerani, Mathias Jackel, Zoé Salm, Tobias Schütz and Markus C. Casper    
The aim of this study was to simulate dominant runoff generation processes (DRPs) in a mesoscale catchment in southwestern Germany with the physically-based distributed hydrological model WaSiM-ETH and to compare the resulting DRP patterns with a data-mi... ver más
Revista: Hydrology

 
Noradila Rusli, Nor Zahida Nordin, Ak Mohd Rafiq Ak Matusin, Janatun Naim Yusof, Muhammad Solehin Fitry Rosley, Gabriel Hoh Teck Ling, Muhammad Hakimi Mohd Hussain and Siti Zalina Abu Bakar    
The government enacted the Movement Control Order (MCO) to curb the spread of the COVID-19 pandemic in Malaysia, restricting movement and shutting down several commercial enterprises around the nation. The crisis, which lasted over two years and featured... ver más

 
Artur Krawczyk    
This paper attempts to define a name for an area of science and technology that encompasses the acquisition, processing and application of spatial data in the mining industry. A comparative study of the evolution of spatial data exchange methods between ... ver más

 
Jing Tian, Zilin Zhao and Zhiming Ding    
With the widespread use of the location-based social networks (LBSNs), the next point-of-interest (POI) recommendation has become an essential service, which aims to understand the user?s check-in behavior at the current moment by analyzing and mining th... ver más