<trans-title>A Study on the Influencing Factors and Driving Forces of Spatial Differentiation of Retail Formats in Guangzhou</trans-title>

Kangmin WU; Yang WANG; Yuyao YE; Hongou ZHANG

doi:10.12082/dqxxkx.2020.190353

Journal of Geo-information Science, Volume. 22, Issue 6, 1228(2020)

A Study on the Influencing Factors and Driving Forces of Spatial Differentiation of Retail Formats in Guangzhou

Kangmin WU^1,1,2,2,3,3, Yang WANG^2,2, Yuyao YE^2,2、*, and Hongou ZHANG^2,2

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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Figures & Tables(9)

Fig. 1. Guangzhou and core circle layer, inner circle layer, outer circle layer division

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Fig. 2. The general framework for quantitative identification of influencing factors of retail business distribution

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Fig. 3. Influencing mechanism of spatial agglomeration of retail

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Fig. 4. Retail formats and its distribution in Guangzhou in 2014

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Fig. 5. Evaluation of influence Factors of Guangzhou Retail Format

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Table 1. Indicators for influencing factors of spatial differentiation of retail formats

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Table 1. Indicators for influencing factors of spatial differentiation of retail formats

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 2. Regression results of influencing factors on the overall spatial agglomeration and differentiation of retail outlets

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Table 2. Regression results of influencing factors on the overall spatial agglomeration and differentiation of retail outlets

OLS					SLM				SEM
	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^***	1.4166	102.2690	0.0000	12.4940^***	0.3013	41.4610	0.0000	29.3667^***	0.5876	49.9783	0.0000
人口密度	657.4760^***	17.9660	36.5956	0.0000	38.4481^***	3.3612	11.4386	0.0000	69.5201^***	5.5458	12.5357	0.0000
商务条件	5.5349^***	0.0356	155.5820	0.0000	0.3354^***	0.0082	40.7818	0.0000	4.3798^***	0.0380	115.2720	0.0000
公共交通便利性	5.1620^***	0.2582	19.9944	0.0000	0.2228^***	0.0482	4.6233	0.0000	1.8038^***	0.1225	14.7215	0.0000
业态丰度	-38.1272^***	0.7069	-53.9336	0.0000	-3.8552^***	0.1363	-28.2919	0.0000	7.3926^***	0.2717	27.2078	0.0000
租金条件	-2.8278^***	0.4429	-6.3848	0.0000	-0.1055	0.0824	-1.2802	0.2005	0.3857^**	0.1632	2.3638	0.0181
R-squared: 0.5155 似然估计:-286 235; AIC: 572 482					R-squared: 0.9832 似然估计:-213 619; AIC: 427 252				R-squared: 0.9903 似然估计:-202 927; AIC: 405865

Table 3. Identification of influencing factors of spatial agglomeration and differentiation of retail industry in different circles

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Table 3. Identification of influencing factors of spatial agglomeration and differentiation of retail industry in different circles

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^***	2.4841	42.9930	0.0000	42.6064^***	1.2464	34.1839	0.0000	19.3990^***	0.5358	36.2056	0.0000
人口密度	28.1051^***	7.5107	3.7420	0.0002	59.0739^***	10.8797	5.4298	0.0000	129.6830^***	12.7430	10.1767	0.0000
商务条件	2.8623^***	0.0613	46.6851	0.0000	5.6570^***	0.0847	66.8221	0.0000	3.4267^***	0.0751	45.6056	0.0000
公共交通便利性	-0.0587	0.2147	-0.2732	0.7847	0.7091^***	0.2087	3.3971	0.0007	0.8652^***	0.1832	4.7223	0.0000
业态丰度	2.2551^***	0.5978	3.7726	0.0002	8.2634^***	0.4151	19.9054	0.0000	7.7564^***	0.3042	25.4949	0.0000
租金条件	-2.3389^***	0.2440	-9.5844	0.0000	0.2213	0.3276	0.6756	0.4993	-0.1765	0.2628	-0.6715	0.5019
LAMBDA	0.9849^***	0.0006	1647.3400	0.0000	0.9768^***	0.0006	1651.7700	0.0000	0.9618^***	0.0010	993.3640	0.0000
R-squared：0.9897; AIC：133 755					R-squared：0.9835; AIC：182 900				R-squared： 0.9829; AIC：82 114

Table 4. Identification of influencing factors of agglomeration differentiation in different retail formats

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Table 4. Identification of influencing factors of agglomeration differentiation in different retail formats

	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^***	0.2959	5.2744	0.0000	2.4298^***	0.1607	15.1206	0.0000	8.1382^***	0.1967	41.3738	0.0000
人口密度	55.6831^***	3.0559	18.2216	0.0000	11.0070^***	1.8800	5.8548	0.0000	6.9395^*	3.8914	1.7833	0.0745
商务条件	0.7780^***	0.0100	77.8535	0.0000	0.0137^***	0.0048	2.8385	0.0045	0.0159	0.0108	1.4705	0.1414
公共交通便利性	1.0040^***	0.0554	18.1375	0.0000	-0.0003	0.0281	-0.0091	0.9927	-0.0795	0.0522	-1.5222	0.1280
业态丰度	2.6217^***	0.1440	18.2006	0.0000	1.0691^***	0.0875	12.2247	0.0000	1.6330^***	0.1233	13.2476	0.0000
租金条件	0.1598^*	0.0824	1.9384	0.0526	-0.1993^***	0.0463	-4.3016	0.0000	-0.8529^***	0.0878	-9.7107	0.0000
LAMBDA	0.7867^***	0.0047	165.9330	0.0000	0.5383^***	0.0237	22.7231	0.0000	0.7342^***	0.0071	102.8850	0.0000
	R-squared:0.9303; AICs: 38 557				R-squared: 0.3597; AICs: 6059				R-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^***	0.7209	52.1630	0.0000	-2.0150^***	0.4382	-4.5980	0.0000
人口密度	16.9848^***	3.3555	5.0618	0.0000	51.7967^***	3.8062	13.6084	0.0000
商务条件	0.0280^***	0.0072	3.9022	0.0001	0.5583^***	0.0113	49.5961	0.0000
公共交通便利性	5.9755^***	0.1776	33.6397	0.0000	0.8755^***	0.0725	12.0809	0.0000
业态丰度	0.5161^***	0.1643	3.1422	0.0017	2.2431^***	0.2212	10.1418	0.0000
租金条件	0.2104^**	0.0858	2.4520	0.0142	0.6456^***	0.1081	5.9716	0.0000
LAMBDA	0.9784	0.0004	2474.7900	0.0000	0.8171	0.0050	162.7250	0.0000
R-squared: 0.9861; AICs: 279 199				R-squared: 0.9272; AICs: 25 531

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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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Paper Information

Received: Jul. 4, 2019

Accepted: --

Published Online: Nov. 12, 2020

The Author Email: Yuyao YE (yeyuyao@gdas.ac.cn)

DOI:10.12082/dqxxkx.2020.190353

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