中国直播电商经济发展的时空格局及其影响因素空间异质性

doi:10.3969/j.issn.1004-9479.2026.03.20240652

世界地理研究 ›› 2026, Vol. 35 ›› Issue (3): 107-121.DOI: 10.3969/j.issn.1004-9479.2026.03.20240652

• 城市与产业 • 上一篇

中国直播电商经济发展的时空格局及其影响因素空间异质性

张英浩¹(), 王强², 许超¹, 汪明峰³(), 王慧龙¹

^1.山东理工大学经济学院，淄博 255012
^2.西南大学乡村振兴战略研究院，重庆 400715
^3.华东师范大学中国行政区划研究中心，上海 200241

收稿日期:2024-08-08 修回日期:2025-01-06 出版日期:2026-03-15 发布日期:2026-03-30
通讯作者: 汪明峰
作者简介:张英浩（1993—），男，副教授，硕士生导师，研究方向为数字经济地理，E-mail：zhangyinghao16@mails.ucas.ac.cn。
基金资助:
国家自然科学基金青年项目(42401210);国家自然科学基金面上项目(42171207);山东省社科规划研究项目(24DJJJ19);山东省高等学校“青创团队计划”(2025RWE012)

The geographical pattern and spatial heterogeneity of the influencing factors of China's livestreaming e-commerce economy: A study based on the MGWR model

Yinghao ZHANG¹(), Qiang WANG², Chao XU¹, Mingfeng WANG³(), Huilong WANG¹

^1.School of Economics, Shandong University of Technology, Zibo 255012, China
^2.Institute for Rural Revitalization Strategy, Southwest University, Chongqing 400715, China
^3.Research Center for China Administrative Division, East China Normal University, Shanghai 200241, China

Received:2024-08-08 Revised:2025-01-06 Online:2026-03-15 Published:2026-03-30
Contact: Mingfeng WANG

摘要/Abstract

摘要：

基于抖音平台的直播电商数据，探究中国直播电商经济发展水平的空间格局与演变特征，并运用多尺度地理加权回归模型对影响中国直播电商经济发展水平的因素进行空间异质性分析。研究发现：①2020—2023年，中国直播电商经济的高值区与高值集聚区均稳定在长三角和珠三角地区，同时，中西部省会城市及其周边地区逐渐成为直播电商经济的新兴增长点，表现出与传统电商不同的新型空间格局和演化趋势。②位序-规模法则分析表明，尽管拟合曲线的齐夫指数q值有所下降，但核心城市杭州、广州在直播电商经济中的集聚效应依然显著。直播电商经济发展的空间特征表现出“既有局部持续扩散，又有核心区域持续集聚”的演变特征。③电商环境、社会经济与人口条件等因素对直播电商经济发展的影响呈现显著的空间异质性，即存在尺度效应。本研究为认识中国直播电商经济的时空特征与影响因素以及制定新型电商高质量发展策略提供了重要参考。

关键词: 数字经济, 直播电商, MGWR, 时空格局, 影响因素

Abstract:

Based on the livestreaming e-commerce data of Douyin platform, the study explored the spatial patterns and evolutionary characteristics of the development level of China's livestreaming e-commerce economy (LSECE), and analysed the spatial heterogeneity of the factors affecting the LSECE by using a multiscale geographically weighted regression model. The study found that:① From 2020 to 2023, the high value area and high value agglomeration area of China's LSECE are both stable in the Yangtze River Delta and the Pearl River Delta regions, meanwhile, the capital cities of central and western provinces and their peripheral areas gradually become the emerging growth point of LSECE, which shows a new spatial pattern and an evolutionary trend that is different from the traditional type of e-commerce. ②The analysis of the rank-order-size law shows that the agglomeration effect of core cities such as Hangzhou and Guangzhou in the LSECE is still significant, despite the decrease in the q-value of the Zipf index of the fitted curve. The spatial characteristics of the development of the LSECE as a whole show the evolutionary characteristics of both continued local proliferation and continued strengthening of core regional agglomeration. ③ The influence of the e-commerce environment, socio-economic and demographic conditions and other factors on the LSECE shows significant spatial heterogeneity, i.e. there is a scale effect. This study provides an important reference for understanding the spatio-temporal characteristics and influencing factors of China's LSECE as well as for formulating new e-commerce high-quality development strategies.

Key words: digital economy, livestreaming e-commerce, MGWR, spatio-temporal pattern, influencing factors

张英浩, 王强, 许超, 汪明峰, 王慧龙. 中国直播电商经济发展的时空格局及其影响因素空间异质性[J]. 世界地理研究, 2026, 35(3): 107-121.

Yinghao ZHANG, Qiang WANG, Chao XU, Mingfeng WANG, Huilong WANG. The geographical pattern and spatial heterogeneity of the influencing factors of China's livestreaming e-commerce economy: A study based on the MGWR model[J]. World Regional Studies, 2026, 35(3): 107-121.

图/表 6

表1 影响因素指标体系与描述性统计

Tab.1 Impact factor indicator system and descriptive statistics

准则层	指标层	缩写	均值	标准差	最小值	最大值	VIF
消费水平与经济实力支撑	社会消费品零售总额/亿元	Trsc	755.35	1 534.68	13.88	12 668.69	2.49
消费水平与经济实力支撑	二三产业增加值占地区国民经济产值比重/%	Vsti	88.50	7.78	53.05	99.91	4.43
电商环境支撑	淘宝村数量/个	Ntbv	41.16	55.23	1.00	541.00	1.68
	网商指数	Ibi	3.85	3.54	0.01	25.45	2.47
	电商企业数量/个	Nece	15.40	31.88	1.00	244.00	1.38
相关基础条件	快递点数量/万个	Ncp	0.14	0.23	0.00	1.73	3.61
相关基础条件	移动电话用户数/万户	Nmps	468.05	565.36	25.00	4 020.00	2.21
社会人口条件	平均受教育年限/年	Ays	7.83	3.83	6.10	11.96	1.43
	城镇非私营单位在岗职工平均人数/万人	Anun	44.04	75.38	3.00	687.00	1.79
	城镇化率/%	Ur	57.03	18.73	31.01	95.37	5.94
	男女性别比	Sr	48.45	11.41	49.08	56.53	6.33

图1 中国直播电商经济发展水平的空间插值注：该图基于自然资源部地图技术审查中心标准地图服务网站下载的审图号为GS（2023）2763号的标准地图制作，底图无修改；不含港澳台数据，下同。

Fig. 1 Spatial interpolation of the level of development of the LSECE in China

图2 中国直播电商发展水平的局部空间自相关

Fig. 2 Local spatial autocorrelation of the development level of the LSECE in China

图3 全国城市位序-规模示意图

Fig 3 City rank-size schematic diagram in China

表2 基于OLS、GWR和MGWR模型的回归结果

Tab 2 Regression results based on OLS and GWR and MGWR models

变量名称	OLS模型(1)		GWR模型(2)			MGWR模型(3)
变量名称	$β$	\|t\|	$β ¯$	\| $t ¯$ \|	带宽	$β ¯$	\| $t ¯$ \|	带宽
常数项	0.000	0.000	-0.105	-0.670	271	-0.051	-0.618	71
Trsc	0.027	0.450	0.036	0.549	271	0.037	0.717	260
Ntbv	0.331^***	6.895	0.110	1.502	271	0.133^***	2.918	270
Ibi	0.242^***	4.108	0.264	2.733	271	0.221^*	2.393	113
Vsti	-0.262^***	-4.323	-0.340	-1.928	271	-0.256	-2.611	128
Ncp	0.346^***	4.868	0.713^***	4.030	271	0.798^***	8.961	211
Nmps	-0.036	-0.640	0.222	0.548	271	0.001	0.010	270
Nece	0.259^***	5.905	0.092	1.317	271	0.123^***	3.077	263
Ays	-0.136^***	-3.257	-0.133	-1.854	271	-0.133^**	-2.669	222
Anun	-0.086^*	-1.720	0.113	-0.117	271	-0.008	-0.179	270
Ur	0.081^*	1.835	0.086	1.274	271	0.113^**	2.896	270
Sr	0.020	0.481	0.012	0.231	271	0.011	0.281	270
样本数量	271		271			271
R²	0.634		0.804			0.808
调整后R²	0.619		0.765			0.782
残差的Moran’s I	-0.033^*		-0.020			0.016
AICc	524.041		419.833			396.971
AICc减少值			104.208			22.862

表2 基于OLS、GWR和MGWR模型的回归结果

Tab 2 Regression results based on OLS and GWR and MGWR models

变量名称	OLS模型(1)		GWR模型(2)			MGWR模型(3)
变量名称	$β$	\|t\|	$β ¯$	\| $t ¯$ \|	带宽	$β ¯$	\| $t ¯$ \|	带宽
常数项	0.000	0.000	-0.105	-0.670	271	-0.051	-0.618	71
Trsc	0.027	0.450	0.036	0.549	271	0.037	0.717	260
Ntbv	0.331^***	6.895	0.110	1.502	271	0.133^***	2.918	270
Ibi	0.242^***	4.108	0.264	2.733	271	0.221^*	2.393	113
Vsti	-0.262^***	-4.323	-0.340	-1.928	271	-0.256	-2.611	128
Ncp	0.346^***	4.868	0.713^***	4.030	271	0.798^***	8.961	211
Nmps	-0.036	-0.640	0.222	0.548	271	0.001	0.010	270
Nece	0.259^***	5.905	0.092	1.317	271	0.123^***	3.077	263
Ays	-0.136^***	-3.257	-0.133	-1.854	271	-0.133^**	-2.669	222
Anun	-0.086^*	-1.720	0.113	-0.117	271	-0.008	-0.179	270
Ur	0.081^*	1.835	0.086	1.274	271	0.113^**	2.896	270
Sr	0.020	0.481	0.012	0.231	271	0.011	0.281	270
样本数量	271		271			271
R²	0.634		0.804			0.808
调整后R²	0.619		0.765			0.782
残差的Moran’s I	-0.033^*		-0.020			0.016
AICc	524.041		419.833			396.971
AICc减少值			104.208			22.862

图4 直播电商经济发展水平影响因素的空间分异格局

Fig.4 Patterns of spatial differentiation in factors influencing the LSECE

参考文献 37

[1]	何金廖, 汪明峰, 席广亮, 等. 数字化转型背景下中国网络信息地理研究进展与展望. 热带地理, 2023, 43(4): 567-580.
	HE J, WANG M, XI G, et al. Research progress and prospects of Chinese cybergeography against the background of the digital transition. Tropical Geography, 2023, 43(4): 567-580.
[2]	汪明峰. 空间的流变与折叠:互联网时代的城市与区域转型. 南京社会科学, 2016(10): 50-56.
	WANG M. Spatial transformation: The urban and regional development in the internet age. Social Sciences in Nanjing, 2016(10): 50-56.
[3]	KENNEY M, ZYSMAN J. The platform economy: restructuring the space of capitalist accumulation. Cambridge Journal of Regions, Economy and Society, 2020, 13(1): 55-76.
[4]	谢亚文, 李晓青, 周楷淳, 等. 城市旅游抖音关注度空间分布及影响因素——以长江中游城市群为例. 经济地理, 2023, 43(2): 220-228.
	XIE Y, LI X, ZHOU K, et al. Spatial pattern and influencing factors of urban tourism Douyin attention: A case study of the urban agglomeration in the middle reaches of the Yangtze River. Economic Geography, 2023, 43(2): 220-228.
[5]	张英浩, 汪明峰, 汪凡,等. 中国直播电商发展的空间差异与影响机理研究. 地理科学, 2022, 42(9): 1555-1565.
	ZHANG Y, WANG M, WANG F, et al. Spatial differences in the development of livestreaming e-commerce and influence in China. Scientia Geographica Sinica, 2022, 42(9): 1555-1565.
[6]	汪凡, 汪明峰. 中国农村电商配送点建设水平空间格局及其影响因素. 热带地理, 2023, 43(2): 247-257.
	WANG F, WANG M. Spatial pattern and influencing factors of rural e-commerce logistic level in China. Tropical Geography, 2023, 43(2): 247-257.
[7]	ZHANG M, QIN F, WANG G A, et al. The impact of live video streaming on online purchase intention. The Service Industries Journal, 2020, 40(9-10): 656-681.
[8]	ZOU S. Producing value out of the invaluable: A critical/cultural perspective on the live streaming industry in China. tripleC: Communication, Capitalism & Critique Open Access Journal for a Global Sustainable Information Society, 2018, 16(2): 805-819.
[9]	裴学亮, 邓辉梅. 基于淘宝直播的电子商务平台直播电商价值共创行为过程研究. 管理学报, 2020, 17(11): 1632-1641.
	PEI X, DENG H. The process of value co-creation behavior about online live shopping in e-commerce platform based on the Taobao live shopping. Chinese Journal of Management, 2020, 17(11): 1632-1641.
[10]	陈前虎, 叶雨繁, 陈静. 杭州主城区直播电商企业区位特征及影响机制 . 经济地理, 2023, 43 (5): 97-107.
	CHEN Q, YE Y, CHEN J. Characteristics and influencing mechanism of the distribution of live-streaming e-commerce companies in main districts of Hangzhou. Economic Geography, 2023, 43 (5): 97-107.
[11]	陆建城, 罗小龙, 钱俭, 等. 城市直播电商空间的演进特征、逻辑与策略研究——以杭州市为例. 城市问题, 2022, (10): 27-34.
	LU J, LUO X, QIAN J, et al. The spatial-temporal evolution characteristics, endogenous logic and guiding strategy of live streaming e-commerce space in cities:Taking Hangzhou city as an example. Urban Problems, 2022, (10): 27-34.
[12]	丁志伟, 马芳芳, 张改素. 基于抖音粉丝量的中国城市网络关注度空间差异及其影响因素. 地理研究, 2022, 41(9): 2548-2567.
	DING Z, MA F, ZHANG G. Spatial differences and influencing factors of urban network attention by Douyin fans in China. Geographical Research, 2022, 41(9): 2548-2567.
[13]	宋周莺, 虞洋, 祝巧玲, 等. 中国县域网络购物空间格局及其影响因素 . 地理研究, 2019, 38 (12): 2997-3009.
	SONG Z, YU Y, ZHU Q, et al. Spatial characteristics and influencing factors of e-shopping development in China's counties. Geographical Research, 2019, 38 (12): 2997-3009.
[14]	SONG Z. The geography of online shopping in China and its key drivers. Environment and Planning B: Urban Analytics and City Science, 2022, 49(1): 259-274.
[15]	谷国锋, 许瑛航. 中国地级市电子商务发展水平的空间格局及影响因素. 经济地理, 2019, 39(10): 123-129.
	GU G, XU Y. Influencing factors and spatial pattern of electronic commerce development level in China at the prefecture-level city. Economic Geography, 2019, 39(10): 123-129.
[16]	陈延斌, 殷冠文, 王少慧. 山东省电子商务发展水平的地域特征及影响因素. 经济地理, 2022, 42(1): 135-143.
	CHEN Y, YIN G, WANG S. Influencing factors of e-commerce development level at county scale in Shandong Province. Economic Geography, 2022, 42(1): 135-143.
[17]	丁志伟, 韩明珑, 张改素, 等. 县域尺度下中原城市群C2C淘宝店铺服务质量的空间分异及其影响因素. 经济地理, 2019, 39(5): 143-154.
	DING Z, HAN M, ZHANG G, et al. Spatial differentiation and influencing factors of the service quality of Taobao online C2C stores in central plains urban agglomeration at county level. Economic Geography, 2019, 39(5): 143-154.
[18]	彭珏, 何金廖. 电商粉丝经济的地理格局及其影响因子探析——以抖音直播带货主播为例. 地理科学进展, 2021, 40(7): 1098-1112.
	PENG J, HE J. Spatial differentiation and influencing factors of fan economy in China: Taking TikTok livestreaming commerce host as an example. Progress in Geography, 2021, 40(7): 1098-1112.
[19]	马芳芳, 丁志伟. 中原城市群直播电商主播综合实力的空间差异及影响因素分析. 河南大学学报(自然科学版), 2024, 54(5): 505-518.
	MA F, DING Z. Spatial differences and influencing factors of the comprehensive strength of live e-commerce anchors in the Central Plains Urban Agglomeration. Journal of Henan University(Natural Science), 2024, 54(5): 505-518.
[20]	CLARKE G, THOMPSON C, BIRKIN M. The emerging geography of e-commerce in British retailing. Regional Studies, Regional Science, 2015, 2(1): 371-391.
[21]	张海平, 周星星, 代文. 空间插值方法的适用性分析初探. 地理与地理信息科学, 2017, 33(6): 14-18.
	ZHANG H, ZHOU X, DAI W. A preliminary on applicability analysis of spatial interpolation method. Geography and Geo-Information Science, 2017, 33(6): 14-18.
[22]	ANSELIN L. Exploratory spatial data analysis in a geocomputational environment. New York: Wiley, 1998.
[23]	王劲峰, 廖一兰, 刘鑫. 空间数据分析教程(第二版). 北京:科学出版社, 2019.
	WANG J, LIAO Y, LIU X. Spatial Data Analysis Tutorial (2nd edition). Beijing: Science Press, 2019.
[24]	BERRY B J, GARRISON W L. Alternate explanations of urban rank–size relationships. Annals of the Association of American Geographers, 1958, 48(1): 83-90.
[25]	鄢慧丽, 王强, 熊浩, 等. 华东地区电子商务发展水平空间差异及影响因素分析. 西北师范大学学报(自然科学版), 2018, 54 (3): 97-104.
	YAN H, WANG Q, XIONG H, et al. Analysis on the influencing factors and spatial difference of e-commerce development level in east China. Journal of Northwest Normal University(Natural Science), 2018, 54 (3): 97-104.
[26]	戚伟, 刘盛和, 金浩然. 中国城市规模划分新标准的适用性研究. 地理科学进展, 2016, 35(1): 47-56.
	QI W, LIU S, JIN H. Applicability of the new standard of city-size classification in China. Progress in Geography, 2016, 35(1): 47-56.
[27]	YU H, FOTHERINGHAM A S, LI Z, et al. Inference in multiscale geographically weighted regression. Geographical Analysis, 2020, 52(1): 87-106.
[28]	FOTHERINGHAM A S, YANG W, KANG W. Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 2017,107(6): 1247-1265.
[29]	HASTIE T, TIBSHIRANI R. Generalized additive models. Statistical Science, 1986, 1(3): 297-310.
[30]	霍雪晨, 马芳芳, 丁志伟. 河南省抖音农村网红的发育水平、空间差异及其影响因素. 地域研究与开发, 2024, 43(2): 168-174.
	HUO X, MA F, DING Z. Development level, spatial differences and influencing factors of TikTok rural internet celebrities in Henan province. Areal Research and Development, 2024, 43(2): 168-174.
[31]	雷竣超, 王敏, 买欣. 电商扶贫下的流空间与知识生产:昆明乡村重构机制研究. 世界地理研究, 2023, 32(4): 156-169.
	LEI J, WANG M, MAI X. Space of flows and knowledge production under ecommerce driven poverty alleviation: A study of rural restructuring mechanism in Kunming. World Regional Studies, 2023, 32(4): 156-169.
[32]	陈晔, 贾骏骐. 数字经济下旅游目的地发展的新路径. 旅游学刊, 2022, 37(4): 6-8.
	CHEN Y, JIA J. A new path for the development of tourism destinations in the digital economy. Tourism Tribune, 2022, 37(4): 6-8.
[33]	王强, 崔军茹, 崔璨, 等. 流动人口购房意愿影响因素的空间异质性——基于MGWR模型的研究. 地理科学, 2022, 42(8): 1381-1390.
	WANG Q, CUI J, CUI C, et al. Spatial heterogeneity of floating population's home purchase intention in China: A multi-scale geographically weighted regression approach. Scientia Geographica Sinica, 2022, 42(8): 1381-1390.
[34]	LAO X, GU H. Unveiling various spatial patterns of determinants of hukou transfer intentions in China: A multiscale geographically weighted regression approach. Growth and Change, 2020, 51(4): 1860-1876.
[35]	唐华仓, 李炜, 马恒运. 我国淘宝村形成与发展的组态路径——基于TOE框架的fsQCA分析. 河北农业大学学报(社会科学版), 2023, 25(4): 96-104.
	TANG H, LI W, MA H. The configuration path of the formation and development of Taobao villages in China: A fsQCA analysis based on the TOE framework. Journal of Hebei Agricultural University(Social Sciences), 2023, 25(4): 96-104.
[36]	GRILICHES Z. Education, human capital, and growth: A personal perspective. Journal of Labor Economics, 1997, 15: S330-S344.
[37]	王志和."直播+电商"如何助力乡村振兴. 人民论坛, 2020(15): 98-99.
	WANG Z. How "live streaming+e-commerce" helps rural revitalization. Peoples Tribune, 2020(15): 98-99.

中国直播电商经济发展的时空格局及其影响因素空间异质性

The geographical pattern and spatial heterogeneity of the influencing factors of China's livestreaming e-commerce economy: A study based on the MGWR model

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