中国城市日企的同业与同源效应——以京、沪、广、深为例

doi:10.18306/dlkxjz.2020.11.006

Abstract

Abstract:

The distribution of Japanese foreign direct investment (FDI) companies in China is extremely uneven and these companies are highly concentrated in the Beijing, Shanghai, and Guangzhou-Shenzhen regions. Traditional FDI research has always focused on how urban attributes and conditions affect the location choice of companies. But the role of spatial agglomeration should be equally concerned. Existing research on agglomeration has shortcomings, such as homogenizing FDI and lack of detailed classification of industries, which lead to significant differences in the results of the studies. Whether companies will follow the investment location choice of other companies with the same source country has not received enough attention. At the same time, there is insufficient attention to the similarities and differences of typical urban agglomerations. To address these issues, based on the research of agglomeration and by focusing on typical cities where Japanese companies are concentrated, this study compared and analyzed the same industry agglomeration effect and the same source agglomeration effect. Using the FDI enterprise data of Japan in Beijing, Shanghai, and Guangzhou-Shenzhen in 1984 to 2017 and the multivariate logistic regression analysis method, with Guangzhou-Shenzhen as the reference region, we established the same industry agglomeration effect model and the same source agglomeration effect model, which includes seven equations each. Enterprise heterogeneity control variables such as industry and value chain links, entry mode, and entry time were added to the model to compare and analyze similarities and differences between Beijing, Shanghai, and Guangzhou-Shenzhen. The results show that the similarities and differences of the same industrial agglomeration effect and the agglomeration effects of the same source are obvious for Japanese companies in typical cities in China. Specifically: 1) Shanghai's same industrial agglomeration and cross-industry agglomeration are the most significant, and the results are stable. Guangzhou-Shenzhen's same industrial agglomeration is slightly stronger than Beijing, but the results are less robust. 2) The results of Shanghai's same source agglomeration are stable and significant and the agglomeration effect of enterprises is strong. The difference between Beijing and Guangzhou-Shenzhen is small. 3) The introduction of enterprise attribute variables has effectively improved the explanatory power of the model. The entry time of Japanese companies in Shanghai is earlier, and the overall size of enterprises across the country is not much different. The entry mode of Japanese enterprises in Shanghai is mainly sole proprietorship. In Beijing and Guangzhou-Shenzhen these companies are mainly joint ventures, but the increasing trend of sole proprietorship is obvious. The proportion of companies in the service industry is relatively high in Beijing, and the number of manufacturing companies is the largest in Guangzhou-Shenzhen. The Japanese companies in Guangzhou-Shenzhen and Shanghai focus on manufacturing or import and export trade in the industrial chain, and the number of companies specializing in business services and research and development is the highest in Beijing.

Key words: foreign direct investment (FDI), agglomeration, the same industry effect, the same source effect, company heterogeneity

LIU Yuxiao, WANG Maojun. The same industry effect and the same source effect of Japanese companies in China: Take Beijing, Shanghai, Guangzhou and Shenzhen as examples[J].PROGRESS IN GEOGRAPHY, 2020, 39(11): 1845-1859.

Figures/Tables 14

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References 26

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变量名称	指标	衡量指标	单位或说明
同业效应	同业集聚	投资前城市已有同行业日企数	个
同业效应	异业集聚	投资前城市已有其他行业日企数	个
同源效应	同源集聚	已有同源子公司数量	个
同源效应	异源集聚	已有不同源子公司数量	个
异质性因素	进入时间	日企子公司首次进驻时间	年
	企业规模	子公司的从业人员规模	人
	进入模式	进入城市的所有权形式	独资=1,合资=0
	产业链环节	企业所处价值链环节	生产制造=0,商务服务=1,进出口贸易=2, 研发设计=3,销售营销=4
	行业类别	企业所属行业	服务业=0,制造业=1

指标		方程1	方程2	方程3	方程4	方程5	方程6	方程7
N		342	342	193	342	342	342	186
伪R²	Cox和Snell	0.183	0.226	0.178	0.218	0.288	0.278	0.670
	Nagelkerke	0.209	0.257	0.203	0.248	0.328	0.316	0.761
	McFadden	0.096	0.121	0.093	0.117	0.161	0.154	0.522
似然比显著性水平		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
分类百分比校正/%		49.40	47.70	47.20	51.80	56.70	54.00	78.50

变量	方程1		方程2		方程3		方程4		方程5		方程6		方程7
变量	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海
进入时间			0.104^**(0.025)	0.002^*(0.093)									0.143(0.391)	-1.373^***(<0.001)
企业规模					<0.001(0.173)	<0.001(0.286)							<0.001(0.794)	-0.001(0.177)
合资							-1.475^**(0.001)	-1.314^**(0.002)					-1.263^*(0.051)	-1.182(0.158)
生产制造									-2.519^***(<0.001)	-1.090^**(0.010)			-1.066(0.253)	2.857 (0.145)
商务服务									0.033(1.034)	0.035(0.941)			0.031(0.968)	3.290^*(0.062)
进出口贸易									-1.162^** (0.036)	-0.472(0.310)			-0.362(0.623)	3.719^**(0.035)
研发设计									-0.182(0.777)	-1.113^*(0.098)			-0.131(0.888)	3.978^*(0.065)
服务业											2.277^*** (<0.001)	0.742^**(0.012)	2.087^**(0.006)	-0.649(0.480)
同业集聚	0.008(0.700)	0.057^**(0.001)	-0.005(0.817)	0.056^**(0.001)	-0.005(0.879)	-0.028(0.270)	0.014(0.524)	0.062^*** (<0.001)	0.003(0.907)	-0.060^**(0.001)	0.006(0.804)	0.055^**(0.010)	-0.045(0.425)	0.282^**(0.003)
异业集聚	-0.006(0.218)	0.014^**(0.001)	-0.002^**(0.022)	0.014^**(0.001)	-0.008(0.269)	0.016^**(0.006)	-0.008(0.113)	0.012^**(0.004)	-0.014^**(<0.001)	-0.014^***(<0.001)	-0.016^**(0.007)	0.010^**(0.012)	-0.046(0.233)	0.210^*** (<0.001)
百分比校正/%	19.3	75.8	19.3	77.0	29.8	74.5	14.5	72.0	45.8	67.7	48.2	64.6	60.0	93.0

指标		方程1	方程2	方程3	方程4	方程5	方程6	方程7
N		342	340	187	342	342	342	186
伪R²	Cox和Snell	0.189	0.383	0.205	0.220	0.288	0.283	0.678
	Nagelkerke	0.215	0.436	0.233	0.251	0.328	0.322	0.771
	McFadden	0.099	0.229	0.108	0.118	0.161	0.158	0.535
似然比显著性水平		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
分类百分比校正/%		47.10	66.20	47.10	51.20	56.10	54.70	78.00

变量	方程1		方程2		方程3		方程4		方程5		方程6		方程7
变量	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海
进入时间			0.185^**(0.006)	-0.487^***(<0.001)									0.093(0.579)	-1.392^** (<0.001)
企业规模					<0.001(0.204)	<0.001(0.401)							<0.001(0.996)	-0.001(0.199)
合资							-1.432^***(0.001)	-1.220^**(0.004)					-1.360^**(0.042)	-1.065(0.210)
生产制造									-2.505^***(<0.001)	-1.098 (<0.001)			-1.105(0.225)	2.978(0.130)
商务服务									0.038(0.939)	-0.180(0.175)			0.198(0.802)	3.374^*(0.054)
进出口贸易									-1.115^** (0.036)	-0.630(0.175)			0.032(0.996)	3.691^**(0.033)
研发设计									-0.135(0.832)	-0.858(0.183)			-0.234(0.800)	4.164^*(0.052)
服务业											2.298^*** (<0.001)	0.693^** (0.017)	2.140^**(0.005)	-0.531(0.564)
同源集聚	-0.014(0.168)	0.030^***(<0.001)	0.017(0.258)	0.102^*** (<0.001)	-0.031(0.003)	-0.029^**(0.003)	-0.014(0.155)	0.030^*** (<0.001)	-0.023(0.030)	-0.026^***(<0.001)	-0.026^**(0.017)	0.026^*** (<0.001)	-0.072^*(0.068)	0.237^*** (<0.001)
异源集聚	-0.002(0.769)	0.014^**(0.001)	0.032(0.022)	0.089^*** (<0.001)	-0.003(0.594)	0.013^**(0.021)	-0.003(0.623)	0.014^**(0.003)	-0.008(0.140)	-0.011^**(0.015)	-0.009^*(0.096)	0.012^**(0.012)	-0.026(0.475)	0.220^*** (<0.001)
百分比校正/%	21.7	75.2	19.3	86.3	32.6	74.4	15.7	71.4	45.8	67.7	48.2	66.5	64.4	93.0

The same industry effect and the same source effect of Japanese companies in China: Take Beijing, Shanghai, Guangzhou and Shenzhen as examples

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地区	2001年前		2002—2012年		2013年后		合计
地区	合资数量/家	比重/%	合资数量/家	比重/%	合资数量/家	比重/%	合资企业/家	比重/%
北京	70	63.63	119	60.71	20	42.55	209	59.21
上海	282	53.80	527	39.80	115	47.13	924	44.17
广深	77	81.00	178	64.96	32	69.56	267	64.34

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