中国电子竞技产业地理集聚特征及影响因素

doi:10.13249/j.cnki.sgs.2021.06.008

地理科学 ›› 2021, Vol. 41 ›› Issue (6): 989-997.doi: 10.13249/j.cnki.sgs.2021.06.008

中国电子竞技产业地理集聚特征及影响因素

马宏智¹(), 钟业喜¹^,^*(), 张艺迪²

1.江西师范大学地理与环境学院，江西南昌 330022
2.天津城建大学建筑学院，天津 300384

收稿日期:2020-02-16 修回日期:2020-04-18 出版日期:2021-06-10 发布日期:2021-08-13
通讯作者: 钟业喜 E-mail:mahongzhi18@163.com;zhongyexi@jxnu.edu.cn
作者简介:马宏智（1992-），男，河北张家口人，博士研究生，主要从事产业集聚、大湖/大河流域人地关系演变研究。E-mail： mahongzhi18@163.com
基金资助:
国家自然科学基金(41561025);国家自然科学基金(41961043);江西省高校人文社会科学研究项目(JC20206);江西师范大学研究生创新基金

The Characteristics and Influencing Factors of Geographical Agglomeration of E-sports Industry in China

Ma Hongzhi¹(), Zhong Yexi¹^,^*(), Zhang Yidi²

1. School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
2. School of Architecture, Tianjin Chengjian University, Tianjin 300384, China

Received:2020-02-16 Revised:2020-04-18 Online:2021-06-10 Published:2021-08-13
Contact: Zhong Yexi E-mail:mahongzhi18@163.com;zhongyexi@jxnu.edu.cn
Supported by:
National Natural Science Foundation of China(41561025);National Natural Science Foundation of China(41961043);Humanities and Social Science Research Projects in Colleges and Universities in Jiangxi Province(JC20206);Graduate Innovation Foundation of Jiangxi Normal University

摘要/Abstract

摘要：

基于2003—2016年电子竞技企业数据，运用赫芬达尔-赫希曼指数、空间自相关分析和空间面板计量经济学模型的方法，对中国电子竞技产业地理集聚特征及其影响因素进行定量分析。研究表明：① 中国电竞产业发展经历从“非法”到“合法化”的曲折历程，阶段性特征明显，可分为“波动发展-蓄力扩散-集中爆发”3个阶段。② 电竞产业发展存在空间依赖性，产业集聚空间存在2级集聚中心，集聚模式经历了从“双核”到“单核”的结构演变。随着时间的推移，电竞产业向中南、华南地区集聚的趋势愈加明显，粤港澳大湾区的集聚程度最高。③ 实证研究表明经济水平、产业结构、人力资源、政府政策、创新环境、经济外向度、用户规模是影响电竞产业集聚的主要因素。

关键词: 电竞产业, 地理集聚, 电子竞技企业

Abstract:

Based on the data of e-sports enterprises from 2003 to 2016, using the Herfindahl-Hirschman index, spatial autocorrelation analysis and spatial panel econometric model, the geographic agglomeration characteristics of China’s e-sports industry and its influencing factors are quantitatively analyzed. The research fidnding shows: 1) The development of China’s e-sports industry is advancing through twists and turns, and has significant stage characteristics. Since the entry of e-sports games into China in 1998, it has a history of more than two decades. It has experienced many iconic events such as germination, officialization, twists and turns, recovery, and rebirth. It has finally been recognized by the public and the official. After being officially listed in China’s sports events in 2003, it experienced three stages of “volatility development-power accumulation diffusion-concentrated outburst”, which was characterized by difficult exploration, legal and correct name, and entering life. 2) The development of China’s e-sports industry is spatially dependent, and the evolution of industrial agglomeration has undergone various structural models. The spatial distribution state of the e-sports industry presents a spatial dependence from random to agglomeration, and its evolutionary model is constantly changing, showing an overall two-level agglomeration center and undergoing a structural evolution from “dual-core” to “single-core”. The focus of development has generally moved to the Guangdong-Hong Kong-Macao Greater Bay Area. 3) Analysis of driving factors shows that factors such as economic level, industrial structure, human resources, government policies, innovation environment, economic extroversion, and user scale all affect the geographic agglomeration of the e-sports industry. Among them, the influence of industrial structure, human resources and economic level on the agglomeration of e-sports industry is particularly significant. The high economic development level, excellent completion structure and good human resources are more conducive to the development and agglomeration of e-sports industry.

Key words: e-sports industry, geographical agglomeration, e-sports enterprisement

中图分类号:

G898

马宏智, 钟业喜, 张艺迪. 中国电子竞技产业地理集聚特征及影响因素[J]. 地理科学, 2021, 41(6): 989-997.

Ma Hongzhi, Zhong Yexi, Zhang Yidi. The Characteristics and Influencing Factors of Geographical Agglomeration of E-sports Industry in China[J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(6): 989-997.

图/表 5

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图1

图2

表2

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影响因素	解释变量	单位	符号
经济水平	人均GDP	元	f1
产业结构	第三产业生产总值占比	%	f2
人力资源	信息传输、计算机服务和软件业就业人数	万人	f3
政府政策	教育与科研经费支出占财政支出比重	%	f4
创新环境	互联网宽带接入用户数	万户	f5
经济外向度	实际利用外资	万美元	f6
用户规模	普通高等学校在校生人数	人	f7

年份	省级尺度			模式	地级市尺度			模式
年份	Moran’s I	Z	P	模式	Moran’s I	Z	P	模式
注：R表示随机模式，C表示集聚模式；粗体说明通过显著性检验。
2003	-0.041748	-0.079994	0.936242	R	-0.007231	-0.468603	0.639354	R
2004	-0.041450	-0.083525	0.933434	R	-0.003888	-0.049604	0.960438	R
2005	-0.025646	0.080667	0.935707	R	-0.003867	-0.046342	0.963038	R
2006	0.017567	0.579609	0.562178	R	0.003607	0.820758	0.411784	R
2007	-0.070033	-0.399036	0.689867	R	-0.004643	-0.135903	0.891898	R
2008	0.054192	0.860126	0.406468	R	-0.004276	-0.090517	0.927877	R
2009	-0.029400	0.037199	0.970326	R	-0.002616	0.188659	0.850360	R
2010	0.101943	1.509127	0.131266	R	0.001009	0.893879	0.371386	R
2011	0.084225	1.201760	0.229457	R	-0.000732	0.553187	0.580135	R
2012	0.117983	1.960069	0.049988	C	0.003518	1.426633	0.153686	R
2013	0.076659	1.714688	0.086403	C	0.002135	1.247538	0.212200	R
2014	0.067891	1.814853	0.069457	C	0.004833	1.834460	0.066586	C
2015	0.077815	2.310340	0.020869	C	0.006919	2.288562	0.022105	C
2016	0.073548	2.065746	0.038852	C	0.006073	2.169150	0.030071	C

固定效应模型	模型1	模型2	模型3	模型4	模型5	模型6	模型7
注：* 、、*分别代表在1%，5%，10%水平上显著；括号内数值为稳健型标准误差；空白项为未加入变量；未含港澳台数据。
f1	0.547***	0.481***	0.302***	0.308***	0.260***	0.275***	0.269***
f1	（-37.12）	（-35.97）	（-22.24）	（-22.25）	（-14.75）	（-15.56）	（-15.16）
f2		1.424***	0.801***	0.805***	0.781***	0.765***	0.773***
f2		（-31.28)	（-17.23)	（-17.30)	（-16.73)	（-16.44)	（-16.64)
f3			0.371***	0.368***	0.326***	0.351***	0.364***
f3			（-29.28）	（-28.89）	（-20.26）	（-21.35）	（-21.82）
f4				0.0847**	0.0448	0.0553	0.0524
f4				（-2.18）	（-1.12）	（-1.39）	（-1.32）
f5					0.0678***	0.0941***	0.1090***
f5					（-4.36）	（-5.89）	（-6.68）
f6						-0.0338***	-0.0278***
f6						（-6.58）	（-5.24）
f7							-0.0264***
f7							（-4.28）
常数项	-5.007***	-9.445***	-4.988***	-5.313***	-4.895***	-4.765***	-4.543***
常数项	（-33.65）	（-48.49）	（-21.38）	（-19.20）	（-16.75）	（-16.35）	（-15.38）
Wald chi²	1378.13	2691.34	4120.74	4130.33	4168.79	4256.89	4294.58
Prob>chi²	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
N	4032	4032	4032	4032	4032	4032	4032

中国电子竞技产业地理集聚特征及影响因素

The Characteristics and Influencing Factors of Geographical Agglomeration of E-sports Industry in China

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