大数据环境下的网络协同创新平台及其应用研究

大数据环境下,对网络信息资源进行深度开发与利用,有利于挖掘信息资源价值,并协同创新主体完成知识、技术创新。本文通过阐述网络协同创新对信息资源开发利用的需求,结合大数据分析技术,展现网络信息资源的协同创新作用。最后,结合大数据的背景构建网络协同创新平台以及描绘协同创新平台3种应用路径,来展现网络协同创新平台的作用和应用前景。     

祁连山草地植被NDVI变化及其对气温降水的旬响应特征

本文利用SPOT VGT-NDVI数据和旬气温、降水数据,分析了祁连山草地植被NDVI时空变化趋势及其 对气温、降水的旬响应特征。结果表明：①1999年-2007年祁连山草地植被NDVI呈缓慢增加趋势。典型草原和平 原草地植被年均NDVI和生长季NDVI增加速率高于高寒草甸草地和沙漠草地。祁连山草地植被NDVI增加和减少 的面积分别为6 9776km²和1 5928km²,植被NDVI增加的区域分布在冷龙岭、拉脊山、大通山、达坂山、青海南山、走 廊南山、托来山、托来南山等地区,减少的区域分布在乌鞘岭、大通河、石羊河、黑河、北大河、疏勒河等河流河谷以 及青海湖周边地区;②祁连山草地植被NDVI年内月和旬变化曲线均呈单峰型;③祁连山地区气温变化对草地植被 NDVI的影响强于降水,气温、降水与草地植被NDVI的最大相关性滞后期都为2旬左右。春季和秋季NDVI对气温 和降水响应的滞后期较短,而夏季响应滞后期较长;④气温是影响典型草原生长的主要因素,夏季降水是影响植被 生长期内植被生长的重要因子。温度是高寒草甸草地生长的限制因子,而降水量则是沙漠草地、平原草地的生长 限制因子。     

祁连山区日照时数的空间差异、突变与多尺度分析

基于祁连山区8个气象站点1958年-2006年逐月日照时数资料,利用线性趋势线、ArcGIS中的Inverse Distance Weighted插值、Mann-Kendall突变检验和Morlet小波分析等方法,对祁连山区日照时数的时空变化特征、突变特点和变化周期进行分析。结果表明:近50a来,祁连山区年平均日照时数呈增加趋势,冬季日照时数呈减少趋势,春、夏、秋季呈增加趋势,且以春季增幅最大;日照时数增幅大小具有显著的中西段大、东南段小的地域差异;增加突变显著,突变时间存在空间差异性。日照时数的周期(p≤0.1)具有多尺度、多层次和多分辨的特性结构,且表现出由中段21a中尺度周期向西、向东逐渐变为4～7a短周期的地域特征。     

中国在国际创新成果保护网络中的地位及其演化分析

本文以世界知识产权组织(WIPO)所公布的国家间专利申请数据构建国际创新成果保护网络,并基于社会网络分析方法分析了该网络的结构特征、演化格局以及中国在网络中的地位。研究结果表明:国际创新成果保护网络表现为明显的小世界特征和"核心-边缘"结构,中国在国际创新成果保护网络中的地位和控制力在逐渐增强,但点入度、中介中心度和PageRank中心度仍落后于美、德、日、英等发达国家,仅点出度排名相对较高,反映出我国整体创新能力仍相对不足,在全球创新成果保护网络中的话语权和影响力也仍需进一步提高。     

高寒地区生态贫困评价及影响因素分析——以色林错地区为例

生态贫困研究对于理解生态环境恶劣地区生态环境与贫困作用机制、支撑巩固减贫成果的政策制定具有重要意义,然而对高寒地区的生态贫困评价和影响因素探索较少.本文以藏北深度贫困区色林错地区为例,构建生态贫困评价体系,将BP神经网络模型和DEMATEL方法相结合,对该地区生态贫困水平及其影响因素进行分析.研究表明:①色林错地区各乡...     

浙江省秋季降水特征及其对太平洋海温的响应

利用1960-2008年浙江省秋季降水资料计算了秋季区域降水指数,基于NCEP/NCAR全球多个再分析资料、SST资料,采用相关分析、趋势分析、Mann-Kendall突变检验等统计方法分析了浙江省秋季降水的长期气候特征、水汽输送通道、秋季降水对SST的响应以及和500 hPa高度场的遥相关。结果表明:近49年来浙江秋季降水呈现显著的下降趋势,1990年前后发生突变;太平洋、南海以及孟加拉湾地区是浙江秋季降水的水汽来源;影响浙江省秋季降水的SST关键区域是中太平洋海盆西南部海区,关键期是当年的6～8月,该区域SST突变前后,秋季500 hPa高度场变化显著;青藏高压、东亚大槽、西太平洋副高和印缅槽是影响浙江省秋季降水的主要天气系统。     

The evolving relations between government agencies of innovation policymaking in emerging economies: A policy network approach and its application to the Chinese case

Literature on innovation policy reveals little of how relations between government agencies as policymakers evolve. Taking the policy network approach, this paper investigates three mechanisms underlining the evolution of inter-government agency relations in emerging economies – policy agenda, power concentration and heterogeneity dependence, and applies them to the analysis of the evolution of innovation policymaking in China. Operationally, the paper proposes a social network analysis (SNA)-based method to quantitatively study China’s innovation policy network, which consists of 463 innovation policy documents formulated by its central government ministries between 1980 and 2011. The findings show that the formal policy network for innovation has been not only sustained through the intervention of policy agendas but also self-organized because of policy network’s nature of power concentration and heterogeneity dependence. The presence of such mixed mechanisms in China’s innovation policy network’s evolution differs from the findings from industrialized countries where self-organization plays a central role. This work advances our theoretical understanding of the evolution of innovation policy network and has implications for innovation policymaking in emerging economies.     

科研人员省际流动网络分析及演化过程研究

   本文基于“科学家在线”平台数据,运用复杂网络分析方法,按照年份分别构建2010—2017年间全国34个省份之间科研人员流动网络模型,测度并分析8年间科研人员流动的复杂性网络整体特征和随时间变化的趋势。研究发现：（1）8年间科研人员流动呈现整体较为明显的“无标度”特性,即北京、上海、江苏等经济科技发达地区不仅流入科研人员的规模较大,流出科研人员的规模也不小,但是全国大部分省份流动科研人员规模较为有限;（2）除了小部分省份之外其余省份的人员流入流出相对较为均衡,一些经济科技发达省份在一定程度上也是全国或本区域科研人员流动的中心节点;（3）从发展态势来看,8年间全国省级科技人员流动态势相对平稳,但是省份之间科研人员流动规模差距越来越明显,经济科技发达省份与其他省份科研人员流动的规模相比差距越来越大;（4）最为突出的变化是流动人员规模显著增加,人员流动更加便利。     

The evolution of government sponsored collaboration network and its impact on innovation: A bibliometric analysis in the Chinese solar PV sector

This study explores the dynamics of a government sponsored collaboration network concerning the development of solar photovoltaics (PV) technologies in China, and investigates the effect of network evolution on the subsequent innovation performance of network actors. Network structure characteristics and attribute proximity variables are jointly examined through a bibliometric methodology based on scientific publication and patent data. In addressing the evolution of the government sponsored collaboration network, this study has identified that actors are more likely to engage in collaboration with prior partners, partners of direct & indirect partners, and partners with similar attributes. These collaboration patterns, in turn, negatively impact direct ties and network efficiency, and increase the attribute proximity of an actor’s network. On the other hand, the estimation results indicate that direct ties have an inverted U-shaped effect on innovation performance, while indirect ties are found to be positively related to innovation performance. As expected, a positive effect of network efficiency is found on innovation performance. The results of attribute proximity variables suggest geographical proximity is negatively related to innovation performance. Taken together, the collaboration patterns in the government sponsored network might have a negative impact on innovation performance of network actors. The empirical findings extend the network literature that collaboration network matters differently in different research contexts, and it is no longer appropriate to simply assume that collaboration is purely a good thing. As such, special attention should be paid to the network structure and composition in further policy design.