Tropical Geography ›› 2021, Vol. 41 ›› Issue (5): 956-967.doi: 10.13284/j.cnki.rddl.003381

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Spatial Pattern and Influencing Factors of the Consumer Service Industry in Shenzhen Based on Multisource Big Data

Na Wang1,2(), Jiansheng Wu1,3(), Zifeng Peng2   

  1. 1.Key Laboratory for Urban Habitat Environmental Science and Technology, School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    2.Information Center of Planning & Land & Real-Estate of Shenzhen, Shenzhen 518040, China
    3.Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • Received:2021-01-13 Revised:2021-03-21 Online:2021-09-22 Published:2021-09-22
  • Contact: Jiansheng Wu;


The consumer service industry directly provides residents with material and spiritual living consumption services and products to meet residents' consumption needs. The reasonable spatial layout of the consumer service industry is of great significance for improving residents' quality of living, optimizing the urban spatial structure, and alleviating urban problems. Based on consumer service point of interest (POI) data, mobile phone signaling data, and population data from Shenzhen, using the nearest neighbor index, kernel density, and entropy index methods, this study analyzes the spatial pattern of the overall and different types of consumer service industry as well as the spatial characteristics of the degree of mixing in the consumer service industry in Shenzhen. Using the Geodetector method, this study also detects the impacts of seven factors, including population, traffic, economy, and space dimensions, on the overall and different types of consumption service industry as well as analyzing the impacts of population age structure on the spatial pattern of this industry and its types. This study is expected to provide a theoretical and decision-making basis for urban planning and development in Shenzhen and other cities. The results show that: 1) The spatial distribution of the consumer service industry in Shenzhen is unbalanced and is concentrated in the central and western regions. The consumer service industry presents the spatial characteristics of two core areas and three belt areas. The two core areas are the Dongmen business area in Luohu District and the Huaqiangbei business area in Futian District. The three belt areas consist of the Luohu-Futian belt, Nanshan-Baoan belt, and Longhua belt. The spatial distribution of the consumer service industry has developed along strips and is mainly concentrated in the areas around the main roads and rail lines. 2) The spatial agglomeration characteristics of the overall and different types of consumer service industry are remarkable and differentiated in Shenzhen. The spatial distribution characteristics of most types of consumer services are similar to those of the overall consumer service industry. The development of industry in some areas has resulted in differences in the spatial distribution of certain categories. 3) The balance of the consumer service industry is better in the Luohu, Futian, Nanshan District and worse in the other Districts. The high balanced areas are the edge areas outside the two core areas, rather than the two core areas with the highest POI density. 4) Population density factors are the most important factors affecting the spatial pattern of the consumer service industry, followed by traffic factors. The influence of economic and spatial factors is relatively low. 5) The population of people aged 19-35 has the greatest impact on the density of the consumer service industry. Age groups have different impacts on the spatial distribution of different types of consumer service industries because of specific needs. These results are consistent with the spatial planning of urban functional zoning and industrial development layout in the Shenzhen Urban Master Plan (2010-2020). Combining these results and current urban development activities, this study provides suggestions for optimizing the spatial layout of the consumer service industry in Shenzhen.

Key words: consumer service industry, spatial agglomeration, influence mechanism, Shenzhen City, multisource big data

CLC Number: 

  • F719