• Journal of Geo-information Science
  • Vol. 22, Issue 6, 1228 (2020)
Kangmin WU1、1、2、2、3、3, Yang WANG2、2, Yuyao YE2、2、*, and Hongou ZHANG2、2
Author Affiliations
  • 1. 中国科学院广州地球化学研究所,广州 510640
  • 1Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
  • 2. 广州地理研究所,广州 510070
  • 2Guangzhou Institute of Geography, Guangzhou 510070, China
  • 3. 中国科学院大学,北京 100049
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    DOI: 10.12082/dqxxkx.2020.190353 Cite this Article
    Kangmin WU, Yang WANG, Yuyao YE, Hongou ZHANG. A Study on the Influencing Factors and Driving Forces of Spatial Differentiation of Retail Formats in Guangzhou[J]. Journal of Geo-information Science, 2020, 22(6): 1228 Copy Citation Text show less
    Guangzhou and core circle layer, inner circle layer, outer circle layer division
    Fig. 1. Guangzhou and core circle layer, inner circle layer, outer circle layer division
    The general framework for quantitative identification of influencing factors of retail business distribution
    Fig. 2. The general framework for quantitative identification of influencing factors of retail business distribution
    Influencing mechanism of spatial agglomeration of retail
    Fig. 3. Influencing mechanism of spatial agglomeration of retail
    Retail formats and its distribution in Guangzhou in 2014
    Fig. 4. Retail formats and its distribution in Guangzhou in 2014
    Evaluation of influence Factors of Guangzhou Retail Format
    Fig. 5. Evaluation of influence Factors of Guangzhou Retail Format
    评价因子代表性指标指标的计算过程预期作用方向
    人口密度常住人口密度常住人口/社区面积;其中社区面积中剔除了水系以及绿地等非建设用地面积正向
    公共交通便利性地铁站点可达性以各地铁站点为基础数据,以社区为基本评价单元,采用缓冲区赋分评价法得到公共交通便利性;位于地铁站点200 m(直线距离)范围内(9分);位于地铁站点200~400 m范围内(7分);位于地铁站点400~800 m范围内(5分);位于地铁站点800~1500 m范围内(3分);位于地铁站点1500 m范围外(1分)正向
    商务条件办公点集聚空间评价以300 m×300 m为基本研究单元,以研究区商务办公大厦、事业单位POI点等为基础数据计算办公点集聚核密度值正向
    业态丰富度零售熵值以300 m×300 m为基本研究单元,计算格网单元的零售网点熵值正向
    地价租金二手房售价以社区二手房均价与楼栋数为基础数据,以小区楼栋数占社区楼栋总数为小区均价权重,计算小区加权均价,计算社区中所有小区的加权均价的均值负向
    Table 1. Indicators for influencing factors of spatial differentiation of retail formats
    OLSSLMSEM
    系数标准差z统计值p系数标准差z统计值p系数标准差z统计值p
    常数项144.8770***1.4166102.26900.000012.4940***0.301341.46100.000029.3667***0.587649.97830.0000
    人口密度657.4760***17.966036.59560.000038.4481***3.361211.43860.000069.5201***5.545812.53570.0000
    商务条件5.5349***0.0356155.58200.00000.3354***0.008240.78180.00004.3798***0.0380115.27200.0000
    公共交通便利性5.1620***0.258219.99440.00000.2228***0.04824.62330.00001.8038***0.122514.72150.0000
    业态丰度-38.1272***0.7069-53.93360.0000-3.8552***0.1363-28.29190.00007.3926***0.271727.20780.0000
    租金条件-2.8278***0.4429-6.38480.0000-0.10550.0824-1.28020.20050.3857**0.16322.36380.0181
    R-squared: 0.5155 似然估计:-286 235; AIC: 572 482R-squared: 0.9832 似然估计:-213 619; AIC: 427 252R-squared: 0.9903 似然估计:-202 927; AIC: 405865
    Table 2. Regression results of influencing factors on the overall spatial agglomeration and differentiation of retail outlets
    核心圈层内圈层外圈层
    系数标准差z统计值p系数标准差z统计值p系数标准差z统计值p
    常数项106.8000***2.484142.99300.000042.6064***1.246434.18390.000019.3990***0.535836.20560.0000
    人口密度28.1051***7.51073.74200.000259.0739***10.87975.42980.0000129.6830***12.743010.17670.0000
    商务条件2.8623***0.061346.68510.00005.6570***0.084766.82210.00003.4267***0.075145.60560.0000
    公共交通便利性-0.05870.2147-0.27320.78470.7091***0.20873.39710.00070.8652***0.18324.72230.0000
    业态丰度2.2551***0.59783.77260.00028.2634***0.415119.90540.00007.7564***0.304225.49490.0000
    租金条件-2.3389***0.2440-9.58440.00000.22130.32760.67560.4993-0.17650.2628-0.67150.5019
    LAMBDA0.9849***0.00061647.34000.00000.9768***0.00061651.77000.00000.9618***0.0010993.36400.0000
    R-squared:0.9897; AIC:133 755R-squared:0.9835; AIC:182 900R-squared: 0.9829; AIC:82 114
    Table 3. Identification of influencing factors of spatial agglomeration and differentiation of retail industry in different circles
    便利店超市购物商场
    系数标准差t统计值p系数标准差t统计值p系数标准差t统计值p
    常数项1.5604***0.29595.27440.00002.4298***0.160715.12060.00008.1382***0.196741.37380.0000
    人口密度55.6831***3.055918.22160.000011.0070***1.88005.85480.00006.9395*3.89141.78330.0745
    商务条件0.7780***0.010077.85350.00000.0137***0.00482.83850.00450.01590.01081.47050.1414
    公共交通便利性1.0040***0.055418.13750.0000-0.00030.0281-0.00910.9927-0.07950.0522-1.52220.1280
    业态丰度2.6217***0.144018.20060.00001.0691***0.087512.22470.00001.6330***0.123313.24760.0000
    租金条件0.1598*0.08241.93840.0526-0.1993***0.0463-4.30160.0000-0.8529***0.0878-9.71070.0000
    LAMBDA0.7867***0.0047165.93300.00000.5383***0.023722.72310.00000.7342***0.0071102.88500.0000
    R-squared:0.9303; AICs: 38 557R-squared: 0.3597; AICs: 6059R-squared: 0.6936; AICs:22 347
    专业店食杂店
    系数标准差t统计值p系数标准差t统计值p
    常数项37.6027***0.720952.16300.0000-2.0150***0.4382-4.59800.0000
    人口密度16.9848***3.35555.06180.000051.7967***3.806213.60840.0000
    商务条件0.0280***0.00723.90220.00010.5583***0.011349.59610.0000
    公共交通便利性5.9755***0.177633.63970.00000.8755***0.072512.08090.0000
    业态丰度0.5161***0.16433.14220.00172.2431***0.221210.14180.0000
    租金条件0.2104**0.08582.45200.01420.6456***0.10815.97160.0000
    LAMBDA0.97840.00042474.79000.00000.81710.0050162.72500.0000
    R-squared: 0.9861; AICs: 279 199R-squared: 0.9272; AICs: 25 531
    Table 4. Identification of influencing factors of agglomeration differentiation in different retail formats
    Kangmin WU, Yang WANG, Yuyao YE, Hongou ZHANG. A Study on the Influencing Factors and Driving Forces of Spatial Differentiation of Retail Formats in Guangzhou[J]. Journal of Geo-information Science, 2020, 22(6): 1228
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