中国区域创新的时空动态分析

doi:10.11821/dlxb201412004

Abstract

Abstract:

Through an integration of exploratory spatial data analysis (ESDA) and confirmatory spatial data analysis (CSDA), this study examines the space-time dynamics of regional innovation at the provincial scale in China from 2000 to 2011. The results show that: firstly, since the implementation of national innovation strategy, the annual growth ratio of innovation outputs of the provinces in China has experienced a drastic process of acceleration, which suggests the overall improvement of regional innovation capabilities. However, an overwhelming status in growth rate still belongs to eastern region, leading to the rise of the coastal-interior division and the divergence among regions, and regional innovation in China may fall into the “Matthew Effect” that the strong will become stronger and the weak will be constantly weaker. Secondly, regional innovation outputs and inputs in China experience an increasing change of spatial clustering over time. Various types of hot spots are identified over time, revealing that innovation hot spots overlay well with other variables. Finally, the selected explanatory variables, such as GDP, RDE, RDP and PCH, have significant direct impacts on provincial innovation in China. There exist obvious spatial spillover effects in provincial innovation activities, and the geographic region of which has crossed the provincial border. The spatial dependence of innovation activities gives rise to the feedback among the provinces, and the acknowledge spillover of adjacent province have material influence on a specific province.

Key words: regional innovation, exploratory spatial data analysis, confirmatory spatial data analysis, hot spot, spatial panel Dubin mode, acknowledge spillover, China

Yeqing CHENG, Zheye WANG, Jing MA. Analyzing the space-time dynamics of innovation in China[J].Acta Geographica Sinica, 2014, 69(12): 1779-1789.

Figures/Tables 11

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省/区域	代码	专利申请数 (项)			年均增长率 (%)
省/区域	代码	2000	2006	2011	2000-2006	2006-2011
沿海 (东部) 地区		91613	349258	1124594	24.99	33.96
辽宁	LN	7151	17052	37102	15.58	21.45
河北	HeB	3848	7220	17595	11.06	24.94
北京	BJ	10344	26555	77955	17.02	30.90
天津	TJ	2789	13299	38489	29.74	30.43
山东	SD	10019	38284	109599	25.04	30.08
江苏	JS	8211	53267	348381	36.57	59.92
上海	SH	11337	36042	80215	21.26	22.14
浙江	ZJ	10316	52980	177066	31.35	35.21
福建	FJ	4211	10351	32325	16.17	32.93
广东	GD	21123	90886	196272	27.53	21.22
海南	HaN	502	538	1489	1.16	28.98
广西	GX	1762	2784	8106	7.92	30.63
中部地区		23080	60096	212569	17.29	37.14
黑龙江	HLJ	3106	6535	23432	13.20	37.61
吉林	JL	2501	4578	8196	10.60	15.67
内蒙古	NMG	1138	1946	3841	9.35	18.53
山西	SX	1475	2824	12769	11.43	45.82
河南	HeN	3823	11538	34076	20.21	31.09
湖北	HuB	3486	14576	42510	26.93	30.68
安徽	AH	1877	4679	48556	16.44	79.48
湖南	HuN	4117	10249	29516	16.42	30.27
江西	JX	1557	3171	9673	12.59	32.16
西部地区		13481	35857	141598	17.71	40.97
重庆	CQ	1780	6471	32039	24.00	49.17
四川	SC	4496	13109	49734	19.52	39.56
贵州	GZ	986	2674	8351	18.09	32.94
云南	YN	1710	3085	7150	10.33	23.39
西藏	XZ	28	89	263	21.26	31.11
陕西	SSX	2080	5717	32227	18.35	54.09
甘肃	GS	798	1460	5287	10.59	37.95
青海	QH	174	325	732	10.97	22.51
宁夏	NX	341	671	1079	11.94	12.61
新疆	XJ	1088	1187	4736	12.92	20.37

变量	1999 (2000)	2005 (2006)	2010 (2011)
PAT	0.1112**	0.2077**	0.3247***
PCH	0.2591**	0.1392**	0.1570**
GDP	0.3062***	0.4011***	0.5099***
RDP	0.0824*	0.1386**	0.2028**
RDE	-0.0381	0.0647	0.1067**

变量	弹性系数	t-统计量	概率
RDP	0.197554***	2.968552	0.002992
RDE	0.073244	1.061109	0.288640
PCH	0.186669***	3.029316	0.002451
GDP	1.390521***	8.467188	0.000001
W*RDP	0.109720	0.718619	0.472376
W*RDE	0.498953***	3.723155	0.000197
W*PCH	0.137290	0.982938	0.325638
W*GDP	-0.570832**	-2.228075	0.025876
W*PAT	0.193968***	2.911511	0.003597

变量	直接效应	t-统计量	间接效应	t-统计量
RDP	0.2047***	3.0237	0.1766	1.0078
RDE	0.0964*	1.4214	0.6146***	3.7809
PCH	0.1972***	3.0709	0.2115	1.2431
GDP	1.3711***	8.4905	-0.3523	-1.3039

Analyzing the space-time dynamics of innovation in China

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