中国旅游产业科技创新能力的时空动态和驱动因素分析

doi:10.3724/SP.J.1047.2017.00613

摘要/Abstract

摘要：

从科技创新的基础、投入、产出和潜力4方面构建了旅游产业科技创新能力结构模型和综合评价指标体系,利用熵值法、线性加权法以及ArcGIS空间分析工具分析评价了2004、2008、2014年中国旅游产业科技创新能力的总体水平、时空动态演化及驱动因素。结果表明：① 2004-2014年,中国旅游产业科技创新能力总体上呈不断提高态势,但空间分布极不均衡,存在明显的地区差异,在趋势上基本表现出东西方向递增,南北方向倒“U”型分布态势;② 中国旅游产业科技创新能力在地理空间上存在着显著而稳定的集聚特征和一定的极化特征,毗邻的区域在旅游科技创新方面存在一定的空间外溢效应;③ 中国旅游产业科技创新能力热点区主要分布在北京、天津和少数东部沿海省份和中部省份,冷点区主要集中在中西部内陆地区的省份;④ 空间残差回归和地理加权回归研究表明,旅游产业基础、空间外溢效应、政策制度因素是驱动中国旅游产业科技创新能力时空变化3个核心因素。

关键词: 旅游产业, 科技创新能力, 时空动态, 驱动因素, 中国

Abstract:

Science and technology innovation is not only the core driving force of the development of the tourism industry but also an important part of tourism innovation system. It affects the quality and speed of economic development of the tourism. Science and technology innovation can improve the tourism industrial structure and change the development mode of the tourism industry. This paper builds the structural model and evaluation index system of scientific and technological innovation ability of tourism industry from four respects including base, input, output and potential. Then, we analyzed and evaluated the overall level, space-time dynamics and influencing factors of scientific and technological innovation ability of China in 2004, 2008 and 2014. The results are as follows: from 2004 to 2014, the overall level of scientific and technological innovation ability of China had been growing. But there were obvious regional differences. All the three time sections presented the distributional pattern, namely East-West direction increasing and South-North direction having the inverted“U-shaped”pattern. The spatial autocorrelation analysis showed that there were significant and stable agglomeration features and some polarization features in the scientific and technological innovation ability of China. The type of spatial correlation mainly appeared to “HH” type and “LL” type. Specifically, they were the eastern coastal areas HH cluster and the western inland areas LL cluster. Simultaneously, its spatial structure presented characteristic of lock-in and road dependence. The spatial hot spots of scientific and technological innovation ability of China mainly concentrated in Beijing, Tianjin and a few eastern coastal provinces. And in 2014, Henan, Anhui, Fujian and Guangdong became the spatial hot spots. The spatial cold spots were mainly concentrated in the Midwest hinterland. There were spatial spillover effect of scientific and technological innovation activity among adjacent areas. The spatial error regression model and the geographically weighted regression analyses indicated that the tourism industry base, spatial spillover effect and policy system were three core driving forces of the change of time and space pattern of the scientific and technological innovation ability in China.

Key words: tourism industry, scientific and technological innovation ability, space-time dynamics, driving factors, China

王毅, 陈娱, 陆玉麒, 丁正山, 车冰清. 中国旅游产业科技创新能力的时空动态和驱动因素分析[J]. 地球信息科学学报, 2017, 19(5): 613-624.DOI:10.3724/SP.J.1047.2017.00613

WANG Yi,CHEN Yu,LU Yuqi,DING Zhengshan,CHE Bingqing. Analysis of the Space-time Dynamics and Influencing Factors of Scientific and Technological Innovation Ability of Tourism Industry in China[J]. Journal of Geo-information Science, 2017, 19(5): 613-624.DOI:10.3724/SP.J.1047.2017.00613

图/表 11

图1

表1

表2

图2

图3

表3

图4

图5

表4

2004年和2014年的全局回归分析结果

OLS模型
		2004年				2014年
变量	系数	标准差	T/Z值	P值	系数	标准差	T/Z值	P值
X₁	0.0061	0.0141	0.4052	0.6715	0.0485	0.0078	5.1841	0.0000
X₂	0.1029	0.0241	4.3099	0.0002	0.1193	0.0259	4.5196	0.0001
X₃	-0.0008	0.0131	-0.0578	0.9528	0.0061	0.0204	0.2756	0.7863
X₄	0.0204	0.0069	3.0419	0.0049	0.0057	0.0139	0.4125	0.6826
X₅	0.0963	0.1151	0.8312	0.4128	0.0961	0.0396	2.4185	0.0231
X₆	0.1223	0.0635	1.9377	0.0612	0.1235	0.0344	1.9463	0.2839
常数项	0.0071	0.0018	4.1595	0.0003	0.0089	0.0035	2.3895	0.0238
2004年——Adjusted R²：0.9491,F统计：105.851,似然估计：141.545,AIC：-265.186
2014年——Adjusted R²：0.9589,F统计：133.458,似然估计：121.102,AIC：-222.125
空间滞后模型（SLM）
X₁	0.0099	0.0124	0.7731	0.4238	0.0458	0.0073	5.968	0.0000
X₂	0.1031	0.0212	4.9745	0.0000	0.1201	0.0265	5.3624	0.0000
X₃	-0.0013	0.0118	-0.1065	0.9101	0.0069	0.0179	0.4052	0.7425
X₄	0.0179	0.0062	3.2016	0.0011	0.0055	0.0169	0.4689	0.6501
X₅	0.0921	0.0979	0.9039	0.3645	0.0954	0.0396	2.9256	0.0078
X₆	0.1240	0.0556	2.2615	0.0241	0.1295	0.0678	2.5351	0.2416
常数项	0.0083	0.0020	4.4328	0.0000	0.0102	0.0052	2.3697	0.0223
2004年——Adjusted R²：0.962,Rho：-0.067,似然估计：141.994,AIC：-266.787,SC：-254.576
2014年——Adjusted R²：0.969,Rho：-0.015,似然估计：121.522,AIC：-224.804,SC：-212.593
空间残差模型（SEM）
X₁	0.0102	0.0114	-0.1061	0.9115	0.0435	0.0069	5.5896	0.0000
X₂	0.0869	0.0180	4.9654	0.0000	0.1191	0.0225	5.5238	0.0000
X₃	0.0001	0.0114	0.0018	0.9948	0.0002	0.0176	0.0025	0.9854
X₄	0.0175	0.0049	3.2812	0.0011	0.0081	0.0131	0.6214	0.5470
X₅	0.1251	0.1012	1.2378	0.2135	0.0997	0.0362	3.2107	0.0051
X₆	0.1339	0.0478	2.7394	0.0072	0.0994	0.0329	1.2589	0.2529
常数项	0.0086	0.0014	6.7597	0.0000	0.0096	0.0056	2.7415	0.0081
2004年——Adjusted R²：0.964,Lambda：-0.495,似然估计：143.625,AIC：-269.428,SC：-258.744 2014年——Adjusted R²：0.971,Lambda：0.218,似然估计：123.253,AIC：-227.288,SC：-216.603

表4

表5

图6

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系统层	子系统层（权重）	指标层（单位）	权重
U旅游产业科技创新能力综合测度体系	U₁旅游产业科技创新基础（0.3974）	U₁₁人均GDP/（元/人）	0.0384
		U₁₂第三产业增加值占GDP的比重/%	0.0182
		U₁₃旅游总收入/万元	0.0403
		U₁₄旅游企业数^*/家	0.1047
		U₁₅互联网用户数/万户	0.0419
	U₂旅游产业科技创新投入（0.2749）	U₂₁旅游高等院校在校学生数/人	0.0425
		U₂₂旅游业R&D经费占地区生产总值比重^*/%	0.1088
		U₂₃人均旅游业固定资产投资额^*/元/人	0.0423
		U₂₄从事旅游科技活动人员的数量^*/人	0.1387
		U₂₅旅游业从业人员数/人	0.0397
	U₃旅游产业科技创新产出（0.1946）	U₃₁旅游类国家自然科学基金^*/万元	0.0089
		U₃₂旅游业发明专利授权的数量^*/项	0.1021
		U₃₃技术市场成交额/亿元	0.0689
		U₃₄旅游业全员劳动生产率^*/（万元/人）	0.0756
		U₃₅旅游企业效率绩效^*/%	0.0256
	U₄旅游产业科技创新潜力（0.1331）	U₄₁含有旅游专业的旅游院校数量/所	0.0241
		U₄₂科研机构数量/家	0.0458
		U₄₃研发机构研发经费来自企业的比重/%	0.0091
		U₄₄规上企业中有R&D机构企业的比重/%	0.0046
		U₄₅国际旅游收入年增长率/%	0.0198

年份	中国旅游产业科技创新能力综合水平
年份	最大值	最小值	总和	平均值	标准差
2004年	0.1033	0.0081	0.8059	0.0262	0.0186
2008年	0.1332	0.0091	1.2297	0.0403	0.0241
2014年	0.1998	0.0389	3.1865	0.0879	0.0406

	2004年	2008年	2014年
Moran’s I	-0.0128	0.1112	0.1649
E(I)	-0.0312	-0.0312	-0.0312
Z(I)	0.2391	1.7662	1.9171
G(d)	0.0078	0.0211	0.0234
E(d)	0.0532	0.0532	0.0532
Z(d)	0.9451	2.4262	2.5094

地理加权回归模型
		2004年			2014年
变量	平均值	最大值	最小值	中位值	平均值	最大值	最小值	中位值
X₁	0.0053	0.0079	0.0035	0.0049	0.0439	0.0498	0.0365	0.0438
X₂	0.1034	0.1171	0.0832	0.1061	0.1256	0.1395	0.0978	0.1288
X₃	-0.0015	-0.0011	-0.0027	-0.0017	0.0041	0.0131	-0.0020	0.0031
X₄	0.0201	0.0258	0.0131	0.0211	0.0058	0.0069	0.0025	0.0039
X₅	0.1146	0.1905	0.0725	0.1132	0.1231	0.1215	0.0756	0.1071
X₆	0.1155	0.1487	0.0798	0.1129	0.1162	0.1529	0.0834	0.1191
常数项	0.0069	0.0086	0.0059	0.0070	0.0091	0.0113	0.0067	0.0078
2004年——Bandwidth：2430158,Residual Square：0.0005,Effective Numb：9.8591,Sigma：0.0042,AICc：-276.5284,Adjusted R：0.9669
2014年——Bandwidth：3036262,Residual Square：0.0014,Effective Numb：9.169,Sigma：0.0084,AICc：-235.7589,Adjusted R：0.9786