<trans-title>The impact of local knowledge base on the formation of innovation clusters in emerging industries: The case study of China's fuel cell industry</trans-title>

三大方面	具体指标	指标变量	单位	权重
创新集群规模	创新主体数量	$NIS$	个	1/4
创新集群内部联系	专利合作数量	$NPC$	条	1/4
	专利引证数量	$NPQ$	条	1/4
创新集群专业化程度	区位熵	$LQ$	-	1/4

Table 2. Selection of indicators for the impact of local knowledge base of fuel cell industry on innovation cluster in China

View table

View in Article

Table 2. Selection of indicators for the impact of local knowledge base of fuel cell industry on innovation cluster in China

指标	表征含义	指标变量（变量类型）	单位
创新集群指数	创新集群的形成程度	$ICI$ （被解释变量）	-
本地解析型知识库	解析型知识库	$Analytic$ （解释变量）	篇
本地合成型知识库	合成型知识库	$Synthetic$ （解释变量）	条
本地符号型知识库	符号型知识库	$Symbolic$ （解释变量）	条
职工平均工资	用工成本	$AWSW$ （解释变量）	元
科技支出占公共财政支出比例	城市创新投入	$Ti$ （解释变量）	%
外资企业工业总产值占比	外资占比	$FIE$ （解释变量）	%
固定资产投资	资金	$FAI$ （解释变量）	万元

Table 3. Change of annual average innovation cluster index from 2000 to 2016 (Top 20)

View table

View in Article

Table 3. Change of annual average innovation cluster index from 2000 to 2016 (Top 20)

排名	城市	2000—2016年	2000—2005年	2006—2010年	2011—2016年
1	北京	0.9854	0.4763	0.9100	1.5574
2	上海	0.7968	0.3861	0.8228	1.1857
3	大连	0.4122	0.1330	0.4983	0.6195
4	武汉	0.2358	0.0850	0.1954	0.4203
5	深圳	0.2247	0.0852	0.3827	0.2325
6	苏州	0.2199	0.0194	0.1279	0.4970
7	广州	0.2141	0.0974	0.1849	0.3550
8	南京	0.2047	0.0822	0.1667	0.3588
9	天津	0.1766	0.1303	0.1690	0.2292
10	杭州	0.1655	0.0589	0.1464	0.2878
11	成都	0.1611	0.0456	0.1319	0.3009
12	哈尔滨	0.1205	0.0474	0.1338	0.1825
13	长春	0.1156	0.1012	0.0659	0.1714
14	合肥	0.1116	0.1008	0.1151	0.1194
15	青岛	0.1082	0.0347	0.0895	0.1973
16	沈阳	0.1025	0.0577	0.1009	0.1486
17	西安	0.1022	0.0366	0.0967	0.1724
18	长沙	0.1011	0.0280	0.1259	0.1534
19	重庆	0.0953	0.0494	0.1162	0.1238
20	马鞍山	0.0927	0.1189	0.1011	0.0594

Table 4. Fisher panel unit root test results

View table

View in Article

Table 4. Fisher panel unit root test results

	P	Z	L*	Pm
$LnICI$	0.0000	0.0000	0.0000	0.0000
$LnAnalytic$	0.0000	0.0000	0.0000	0.0000
$LnSynthetic$	0.0000	0.0000	0.0000	0.0000
$LnSymbolic$	0.0000	0.0000	0.0000	0.0000
$LnAWSW$	0.0000	0.0003	0.0000	0.0000
$LnTi$	0.0000	0.0000	0.0000	0.0000
$LnFIE$	0.0000	0.0000	0.0000	0.0000
$LnFAI$	0.0000	0.0000	0.0000	0.0000

Table 5. 2-step system GMM regression results of the impact of local knowledge base on innovation cluster of fuel cell industry

View table

View in Article

Table 5. 2-step system GMM regression results of the impact of local knowledge base on innovation cluster of fuel cell industry

变量	$LnICI$
变量	模型1	模型2	模型3
$LnICI$ L.l	0.3631***	0.2350***	0.2926***
	(0.0007)	(0.0005)	(0.0003)
$LnAnalytic$	0.0569***
	(0.0001)
$LnSynthetic$		0.0572***
		(0.5120e-04)
$LnSymbolic$			0.0712***
			(0.0001)
$LnAWSW$	-0.0032***	-0.0086***	-0.0053***
	(0.8410e-04)	(0.6100e-04)	(0.4500e-04)
$LnTi$	0.0006***	0.0005***	0.0014***
	(0.2720e-04)	(0.1200e-04)	(0.1860e-04)
$LnFIE$	0.0023***	0.0042***	0.0023***
	(0.7000e-04)	(0.5740e-04)	(0.3520e-04)
$LnFAI$	0.0003***	0.0005***	0.0023***
	(0.4120e-04)	(0.3970e-04)	(0.3300e-04)
常数项	-0.0032***	0.0195***	0.0029***
	(0.0001)	(0.0002)	(0.0001)
样本数	4365	4365	4365
城市数量	291	291	291

Table 6. Sargan test results for each model
View table
View in Article
Table 6. Sargan test results for each model
模型 sargan检验
模型1 Prob > chi2 = 0.2829
模型2 Prob > chi2 = 0.3081
模型3 Prob > chi2 = 0.2758

Table 7. Abond test results for each model
View table
View in Article
Table 7. Abond test results for each model
模型 Order z Prob > z
模型6-1 1 -4.5685 0.0000
2 1.8006 0.1718
3 -0.1800 0.8572
模型6-2 1 -4.1063 0.0000
2 1.4816 0.1684
3 0.3682 0.7127
模型6-3 1 -4.2401 0.0000
2 1.6201 0.1452
3 -1.0813 0.2796

Table 8. Robustness test based on 2-step panel difference GMM and panel OLS

View table

View in Article

Table 8. Robustness test based on 2-step panel difference GMM and panel OLS

变量	$LnICI$
	二步面板差分GMM方法			面板OLS回归
	模型1	模型2	模型3	模型1	模型2	模型3
$LnICI$ L.l	0.5070***	0.1620***	0.3930***
	(0.0007)	(0.0002)	(0.0004)
$LnAnalytic$	0.0217***			0.0525***
	(0.9270e-04)			(0.0017)
$LnSynthetic$		0.0640***			0.0675***
		(0.4940e-04)			(0.0009)
$LnSymbolic$			0.0422***			0.0746***
			(0.4670e-04)			(0.0015)
$LnAWSW$	-0.0045***	-0.0038***	-0.0008***	-0.0005***	-0.0002*	-0.6220e-04**
	(0.0001)	(0.5600e-04)	(0.4170e-04)	(0.0001)	(0.0001)	(0.0000)
$LnTi$	0.0014***	0.0007***	0.0013***	0.0048***	0.0006	0.0031***
	(0.2120e-04)	(0.1780e-04)	(0.1660e-04)	(0.0009)	(0.0007)	(0.0009)
$LnFIE$	0.0004***	0.0027***	0.0024***	0.0004***	0.0002**	0.1130e-04**
	(0.0001)	(0.7450e-04)	(0.7260e-04)	(0.0002)	(0.0001)	(0.0000)
$LnFAI$	0.0041***	0.0013***	0.0015***	0.0014***	0.0005*	0.0024***
	(0.7660e-04)	(0.3720e-04)	(0.2790e-04)	(0.0004)	(0.0003)	(0.0004)
常数项	0.0047***	0.0129***	0.0046***	-0.0158***	0.0040**	-0.0095***
	(0.0010)	(0.0006)	(0.0008)	(0.0024)	(0.0018)	(0.0022)
样本数	4365	4365	4365	4365	4365	4365
城市数量	291	291	291	291	291	291

Tools

Get Citation

Copy Citation Text

Zefeng MI, Can ZHOU, Yongmin SHANG, Shuang MA, Gang ZENG. The impact of local knowledge base on the formation of innovation clusters in emerging industries: The case study of China's fuel cell industry[J]. Geographical Research, 2020, 39(7): 1478

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Received: Jul. 15, 2019

Accepted: --

Published Online: Apr. 23, 2021

The Author Email: ZHOU Can (zc070260046@126.com)

DOI:10.11821/dlyj020190595

Topics

Resource Economy

Research Articles

Table 1. The index system of innovation cluster evaluation

Table 1. The index system of innovation cluster evaluation

Table 2. Selection of indicators for the impact of local knowledge base of fuel cell industry on innovation cluster in China

Table 2. Selection of indicators for the impact of local knowledge base of fuel cell industry on innovation cluster in China

Table 3. Change of annual average innovation cluster index from 2000 to 2016 (Top 20)

Table 3. Change of annual average innovation cluster index from 2000 to 2016 (Top 20)

Table 4. Fisher panel unit root test results

Table 4. Fisher panel unit root test results

Table 5. 2-step system GMM regression results of the impact of local knowledge base on innovation cluster of fuel cell industry

Table 5. 2-step system GMM regression results of the impact of local knowledge base on innovation cluster of fuel cell industry

Table 6. Sargan test results for each model

Table 6. Sargan test results for each model

Table 7. Abond test results for each model

Table 7. Abond test results for each model

Table 8. Robustness test based on 2-step panel difference GMM and panel OLS

Table 8. Robustness test based on 2-step panel difference GMM and panel OLS