Air transportation is a unique and increasingly important perspective in studying spatial structure of urban system This paper illustrates the framework of urban system by analyzing structural features of air transportation network based on the data of the amount of airport passenger transportation and the number of weekly flights (1)Since open to the outside world, the nodes in China's air transportation network increased quickly accompanied with the expansion of air transportation network scale which presents positive correlation with the scale rank of urban system (2) On the whole, dispersion dominates the evolution of airport's spatial structure But in the variant periods and zones, the newly built airports and the increase of transportation capacity of the existing airports exert different influences on the expansion of air transportation network (3) Network linkage intensity differs in various provinces But the eastern coastal zone is still the core region of domestic and international airline linkage in which the international hub function of Beijing Tianjin Hebei and Jiangsu Shanghai is distinctive while Guangdong mainly acts as home hub (4) The capital city of a province is still of vital essence to this province's outward connection, but more and more developed cities of some provinces have partly substituted the capital cities (5) The spatial distribution of intensity and tightness of air network linkage separate from each other, which manifest that the spatial network structure of China's urban system is still in the process of dynamic evolution (6) The factors such as the change of airline structure, the airline linkage with foreign countries and the cooperation and competition of domestic airport cities will all influence urban system structure in future

中国高速铁路网“四纵四横”客运专线规划至2015 年建成,将覆盖所有省会及90%的50 万以上人口城市,高速铁路可达性因此成为近年可达性研究的热点。本文在总结前人研究方法的基础上,运用加权平均旅行时间研究高铁时代中国省际可达性及空间格局。研究结果表明:① 采用传统客运最短旅行时间(含中转及停留)数据得到的省际可达性呈中心—外围模式,以郑州—武汉为中心,其他省份按“距离衰减规律”成为圈层式阶梯状空间格局;② 高速铁路建设带来省际联系时间缩短、可达性最优区域大幅增加等“高铁效应”,空间结构仍以武汉—郑州为中心呈现中心—外围模式;③ 高铁运营使省际可达性均衡化,可达性变化幅度在空间上呈中间凹四周高的“碗形”特点,位于客运铁路网络中心附近的省份变化幅度较小,外围地区如云南、福建等省可达性变化幅度较大。

National High-Speed Rail Grid (4+4) Passenger Dedicated Lines (PDL) Railway Planning, covering all provincial capital cities and more than 90% cities with populations of more than 500,000, will be up and running in 2015. Accessibility by high speed railway network has become a hot topic in the accessibility research field. In this paper, based on review of the methods used by other researchers, the shortest time distance matrix between provincial capital cities was chosen to analyze inter-provincial accessibility by conventional railway network and by high-speed railway network, and weighted average travel time was used to analyze inter-provincial accessibility and spatial pattern in the high-speed railway time. Results are shown as fellows: (1) Inter-provincial accessibility by conventional railway network obtained with shortest time distance (including transfer and short-stay) has a "center-periphery" spatial pattern, with Zhengzhou-Wuhan as the center and other provinces as peripheries. The accessibility decreases from center to peripheries in circular gradients. The dominant factors affecting the accessibility are network pattern, node location and train organization, as Beijing has higher accessibility with radial rail network. (2) Inter-provincial accessibility by high-speed railway network also has a "center-periphery" pattern, whileWuhan is more convenient than Zhengzhou. Passenger Dedicated Lines have shortened inter- provincial travel time and doubled the 2% areas of best accessibility (from 5.3×10⁴ km² to 10.8×10⁴ km²), showing the effects of high-speed railway network. The average travel distance of each capital city is 60,000 kilometers by both conventional network and high-speed railway network, but the latter only costs half of total travel time as the former, while the area of the best accessibility is 108,000 square kilometers. (3) High-speed railway network will equalize inter-province accessibility, as standard deviation of accessibility coefficient is less than conventional railway network. Remote regions such as Yunnan and Fujian had the biggest improvement in accessibility while the center provinces had littles change.

为探究高铁通车对中国城市创业投资网络的影响,论文以2001—2017年间投资于中国大陆的41692件跨城市创业投资事件为样本,研究高铁通车对城市创业投资网络集聚力、辐射力和联系中介力的影响,并进一步探讨其作用机制。渐进双重差分模型(渐进DID模型)分析表明,高铁通车可以提高城市可达性,降低创业投资活动主体的综合交易成本,促进创新创业要素资源跨区流动,对创业投资网络集聚力、辐射力和联系中介力产生正向影响。中心城市的创业投资网络受高铁通车带来的正向影响更强。同时,高铁通车对创业投资网络最优作用范围依投资中心呈环形分布,投资中心辐射半径100~200 km的地区,创业投资网络集聚力、辐射力和联系中介力受高铁通车正向影响要明显强于100 km以内和200 km以外地区。此外,风险性低、回报稳定和市场化程度更高的扩张期和成熟期阶段的创业投资网络集聚力、辐射力和联系中介力受高铁通车影响较种子期和初创期阶段更为显著。

Based on the 41692 venture capital investment events in China's mainland from 2001 to 2017, the impact of high-speed railway on the agglomeration, radiation, and intermediary powers of Chinese venture capital network was studied by using the social network analysis model, as well as the heterogeneity of the effect of different city types, radiation radius of the central cities, and four investment stages, in order to research the impact of high-speed railway on Chinese urban venture capital network. The analysis of the time-varying Difference-in-Differences (DID) model shows that high-speed railway can improve the accessibility of cities, reduce the transaction cost of venture capital activities, promote the cross-regional flow of innovation resources, and enhance the abundance of urban innovation elements, thus having a positive impact on the venture capital network development. High-speed railways have a significant promoting effect on the city network of venture capital in both non-central cities and central cities, and the positive effect is stronger in central cities. The impact of high-speed railway on venture capital network is different under different distance scales: the influence is significantly weaker in areas within a radius of 100 km and beyond 200 km than that between 100 km and 200 km. The impact of high-speed railway on the agglomeration power, radiation power, and intermediary power of venture capital network in the expansion and maturity stages (with lower risk, stable return, and higher marketization degree) is clearly more significant than in the seed stage and initial stage.

基于2009—2017年湖南省13个地级市面板数据，运用耦合协调度测度湖南区域经济协同发展水平，采用社会网络分析（SNA）分析高铁网络演化特征，结合利用空间杜宾模型（SDM）检验湖南省高铁网络发展对区域经济协同发展的影响机理，结果表明：① 高铁时代湖南省区域经济空间关联性升高，协同发展水平稳步上升；② 湖南省高铁网络的逐渐优化对本地协同发展水平产生显著的正向直接效应，但对其他地区却存在负向的间接溢出效应；③ 高铁网络对区域间产业、市场、交通和创新等功能结构协同产生双重影响，形成了对区域经济协同发展的“双刃剑”特征，即高铁网络对本地的市场、产业、交通和创新等功能结构协同既存在显著正向促进作用，也存在负向溢出的马太效应，在促进网络中心度较高的城市发展的同时，也可能阻碍相对弱势的边缘城市发展。

Significant changes have taken place in the regional development pattern in the era of high-speed rail. Based on the panel data of 13 prefecture-level cities in Hunan Province from 2009 to 2017, this paper uses the coupling coordination degree to measure the level of regional economic synergy, social network analysis (SNA) to analyze the evolution characteristics of the high-speed rail network, and Spatial Dubin Model (SDM) to test the influence mechanism of the development of Hunan's high-speed rail network to regional economic synergy. The results show: 1) In the era of high-speed rail, the spatial correlation of regional development increases in Hunan province, and the level of regional economic synergy rises steadily; 2) The gradual optimization of the high-speed rail network has a significantly direct positive effect on its own regional economic synergy, but an indirect negative spillover effect on other regions; 3) A “double-edged sword” feature of regional economic synergistic development has been produced due to the dual influences that the high-speed rail networks put on the structural coordination among interregional functions such as industry, market, transportation and innovation. In other words, we can say the high-speed rail networks has both positive and negative effects on those interregional functions which can also be explained by the Matthew effect. With the development of cities with high network centrality, the relatively disadvantaged ones on the edge may get the opposite result.

基于2015年专利交易数据,融合数据挖掘、社会网络、空间分析等方法,从节点、关联、模块及影响因素4个方面揭示中国城际技术转移的空间格局及其影响因素：① 技术转移整体强度偏低,空间极化严重,长三角、珠三角、京津冀城市群成为技术转移的活跃地带。② 北京、深圳、上海、广州是全国技术转移网络的“集线器”,发挥城际技术流的集散枢纽和中转桥梁作用,中西部大部分城市处于网络边缘,整个网络发育典型的核心—边缘式和枢纽—网络式结构。③ 技术关联的空间层级和马太效应凸显,形成以北京、上海、广深为顶点的“三角形”技术关联骨架结构,技术流集聚在东部地带经济发达的城市之间和具有高技术能级的城市之间,中西部技术结网不足,呈现碎片化。④ 技术转移网络形成明显的四类板块（子群）,具明显自反性和溢出效应,其空间聚类既有“近水楼台先得月”式块状集聚,也有“舍近求远”式点状“飞地”镶嵌。⑤ 城际技术流呈现等级扩散、接触扩散、跳跃扩散等多种空间扩散模式,其流向表现出经济指向性和行政等级指向性特征。⑥ 城市经济发展水平、对外开放程度、政策支持等主体属性和地理、技术、社会、产业邻近性的城市主体关系均会影响其技术转移强度。

On the basis of patent transaction data in 2015, spatial pattern of interurban technology transfer network in China was portrayed by integrating big data mining, social network, and GIS, from the perspectives of nodal strength and centrality, linkage intensity, and modular divisions. Then, its key influencing factors were identified as well using the Negative Binominal Regression Analysis. Some findings were ontained as follows. First of all, the intensity of interurban technology transfers in China is not well distributed with obvious polarization. Those cities with higher-level technology transfers are concentrated in the three urban clusters, namely, the Yangtze River Delta, the Pearl River Delta and Beijing-Tianjin-Hebei urban agglomeration. Secondly, a typical core-periphery structure with hub-and-spoke organization is evidently observed, which consists of several hubs and the majority of cities with far lower technology transfers. Beijing, Shenzhen, Shanghai and Guangzhou are acting as the pivot of the technology transfer network and playing a critical role in aggregating and dispersing technology flows. Thirdly, technology linkage intensities of urban pairs appear to be significantly uneven with hierarchies, centralizing in the three edges from Beijing to Shanghai, from Shanghai to Guangzhou and Shenzhen, and from Beijing to Guangzhou and Shenzhen, which shapes a triangle pattern. Fourthly, the technology transfer network is divided into four communities or plates, with prominent reflexivity and spillover effects, which is resulted from geographical proximity and technological complementary. Last but not least, spatial flows of technology are co-organized by a variety of spatial diffusion modes such as hierarchical diffusion, contact diffusion and leapfrog diffusion, owing to economic and administrative powers. They are greatly influenced by urban economic scale, foreign linkage, policy making, as well as multiple proximity factors related to geographical, technological, social and industrial proximities.

21 世纪是知识经济时代,为了提高中国的科技创新能力以促进经济快速发展,各区域进行了大量科技创新资源的建设投入。但科技投入只有真正转化为创新能力、产出创新成果,才能促进经济的发展。本文分别从国立、地方、企业三方面综合评价了各省的科技创新资源,分析其空间分布格局,并结合经济发展水平,分析了区域科技创新资源与经济发展水平之间的相关性。研究表明,中国各省科技创新资源与经济发展水平总体上呈正相关趋势,但具体到各省份,随着科技创新资源的增加,其经济发展水平却有升有降。为充分发挥区域科技创新资源的作用,提高科研成果产出,区域科技创新资源与经济发展水平的配置关系仍需优化调整。探索中国科技创新资源与经济发展水平间的驱动与响应机制,建立科学合理的决策模型,实现国家用于宏观调控的国立科技创新资源、各地区自主决策的地方科技创新资源、市场驱动的企业科技创新资源三者有机结合、高效配置,以更大程度地实现科技产出,促进经济发展,对于转型期的中国,实现由依靠传统资源要素进入到依靠科技资源支撑和推动社会经济发展的新阶段,具有重要意义。

The 21st century is an era of knowledge. In China, to increase the innovation capacity and accelerate the economic development, every province is now injecting a great deal of investment in scientific & technological resources (STR). But only when STR produces outputs can it increase the economic progress. Classifying the regional STR into three groups: national, regional, and enterprise scales, we quantify regional STR, and analyze its spatial distribution. Based on the evaluation of regional economic development, we study the relationship between regional economy and STR. As a whole, the STR has a positive correlation with the economy level. It is not the same in different provinces. So it remains to be solved on how to deploy scientific & technological resources according to economy level and how to make full use of investment to boost economy. There is a need for further research on the driving mechanism between STR and economy to make relevant policies.

以341个地级层面区域作为空间观测单元,以专利申请受理数作为衡量指标,对中国1997~2009年期间地级区域创新产出的时空特征进行了ESDA分析。结果表明：中国地级区域创新产出的地域性特征显著,首先表现为全局上的地理集聚和地带间的巨大差异;但不同于省级空间尺度下地带内部区域创新显著的极化特征,地级空间尺度区域创新却呈现多样化的局部空间依赖模式。整体上,创新产出在地级空间尺度上自然形成2个显著的空间集群,即东部沿海的H-H集群和西部内陆的L-L集群。东部H-H集群在考察期内由东北和华北地区逐渐向山东半岛、长三角和珠三角地区转移,西部L-L集群的空间发展则相对稳定;H-L型集群和L-H型集群主要分布在中部地区和东中西邻接地区,创新的空间过渡特征明显。最后在实证分析的基础上,提出了政策建议和未来研究的方向。

With the development of the new economic geography, spatial structure study of regional innovation becomes more and more important. Using the methods of exploratory spatial data analysis（ESDA）and spatial analysis software Geoda, the article analyzes the spatial distribution of innovation outputs in China, measured by the number of patent applications examined, throughout 341 prefecture-level cities from 1997 to 2009 of China. A significantly high level of spatial concentration and regional difference of innovation outputs among Chinese cities has been captured by the exploratory spatial data analysis, and the concentration level has increased steadily over the past years. Different from the significant polarization characteristics of innovation within the provincial spatial scale regions, prefecture level regional innovation showing a diversity local spatial dependent model. On the whole, the output of innovation in the prefecture level spatial scales naturally formed two distinct spatial clusters, named the eastern H-H cluster and the western L-L cluster. The eastern H-H cluster gradually transferred to the Shandong Peninsula, the Huanghe River Delta and the Zhujiang River Delta from the northeast and North China in the study period, while the western L-L cluster spatial development maintains relatively stable. The H-L clusters and L-H clusters are mainly distributed in the middle and join area, which shows an obvious characteristic of transition. This study can provide a scientific basis for the spatial correlation of innovation outputs among prefecture-level cities, and reflects the knowledge spillover and its spatial limitations of regional innovation which make a significant contribution to the evolution of Spatial-temporal pattern of innovation in China. Finally, on the basis of empirical analysis, policy suggestions and future research direction are proposed.

从全国—本地视角,以东北三省为研究区,基于2005-2015年的专利权转移数据,融合社会网络、GIS空间分析和计量方法,定量刻画东北三省技术转移网络的空间演化规律。结果显示：① 全国视角下东北三省城际技术转移网络呈现“核心—边缘”等级层次性结构,形成了专利技术由东北辐散向全国沿海辐合的空间格局。② 本地视角下东北三省技术转移网络呈现出向心收缩结网态势,“哈长沈大”四大核心城市在本地网络中扮演“技术守门者”角色。技术转移表现出“强全国化,弱本地化”特征。③ 东北三省城际技术流动既存在路径依赖,也不断涌现路径创造。全国视角下,技术转移以东北三省核心城市为流源,基本流向以北京、上海和深圳分别为枢纽的京津冀、长三角和珠三角城市群。本地城际技术转移以哈尔滨、长春、沈阳、大连为集散中心,集中于省内转移,呈现等级、接触和跳跃式混合扩散空间模式。④ 地理距离接近度、产业结构相似度、经济水平差异度、创新能力相似度、技术吸收能力、外商直接投资对东北三省城际技术转移存在一定影响。

Interurban technology transfer becomes an essential channel for regions or cities to obtain external knowledge. Based on patent transaction data among cities during 2005-2015, this study investigates the interurban technology transfer network of Northeast China, aiming to explore spatial evolution of technology transfer network in this region from national to local perspectives based on social network analysis (SNA). A negative binomial regression analysis further reveals the factors of interurban technology transfer network. The results of the study are as follows: (1) From the national perspective, the interurban technology transfer network of Northeast China presents a core-periphery structure. The spatial pattern of "divergence in the northeast region" and "convergence in the coastal areas" has been formed. (2) From the local perspective, the technology transfer network of Northeast China shows a centripetal contraction situation, and its four hubs, namely, Harbin, Changchun, Shenyang and Dalian, play the role of technology gatekeeper. The interurban technology transfer flows present the characteristic of strengthening nationalization and weakening localization, which are more likely to emerge between the Northeast-Southeast China rather than among the Northeast China. (3) Both path-dependence and path-creation exist in the spatial dynamics of intercity technology flows in Northeast China. From the national perspective, technology flows from Northeast China to the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta urban agglomerations with Beijing, Shanghai and Shenzhen as the core respectively, while the local intercity technology transfer in Northeast China presents a mixed diffusing mode including hierarchical, contagious and jump diffusions. In addition, the local network mainly focuses on intra-provincial technology flows which centered on Haibin, Changchun, Shenyang and Dalian. (4) Some drivers, such as geographical proximity, the similarity of industrial structure, economic differences, the similarity of innovation capability, technology absorptive capacity, foreign direct investment, are evidenced to play a significant or determining role in interurban technology transfer of Northeast China.

交通运输联系是区域空间级联系统与城市体系结构研究的重要视角之一,而不同交通运输方式表达的级联体系结构亦存在一定的差异。为综合研究交通运输体系刻画的空间级联系统及克服单一交通方式的局限性,基于长途汽车、高铁和航班时刻表数据,比较分析了多元交通网络的空间级联体系结构及其表达的城市网络组织体系,并进一步揭示了地理空间的约束作用。研究发现：① 每种交通运输方式适合在一定的空间尺度和行政范围内刻画和表达城市网络体系结构与城市联系,公路客运受省域行政范围约束,高铁联系具有廊道影响效应,航空运输体现全国和区域尺度较高层次的社会经济联系。② 从旅客直达视角分析,长途汽车与高铁的城际运输市场重叠最大,近年来长途汽车的运输市场受高铁影响明显。③ 地理空间是影响陆路交通运输和组织的重要约束因子,距离衰减效应明显;结合设施空间、行政空间和管理体制的作用,长途汽车和高铁运输在空间上形成分异的社区结构;航空运输由于具有超空间连接特性,既不遵循距离衰减规律,社区结构也并不明显。

Transportation connection has always been one of the important perspectives of studying spatial cascading systems and urban systems. Based on the timetable data in 2018 of inter-city coach, high-speed train and aviation, this paper builds networks of the three modes of transportation in China. Through the methods of the city-pair connectivity and community detection, this paper compares the spatial structure and linkage systems of multi-traffic flow network and reveals the geospatial constraints. The research results show that: (1) Different modes of transportation are suitable for portraying urban systems on different spatial and administrative scales. Inter-city coaches are constrained by the provincial administrative boundaries. High-speed train network shows the effect of corridors especially along the main trunks. The aviation network reflects the spatial relationship at the national scale. (2) From the perspective of the direct accessibility, there is a large spatial overlap between inter-city coaches and high-speed trains, and the market of inter-city coaches is obviously squeezed in recent years. For air transport, its frequency advantage mainly concentrates on the city-pairs with a long distance. The competition and complementarity of the three modes of transportation have a great impact on the urban system and are useful for the understanding of the spatial cascading system. (3) Geographical space, infrastructure space and administrative space constraint and management system are important factors affecting the transportation networks. Inter-city coach network and high-speed train network are obviously affected by distance attenuation effects, and they present significant community structures in the two networks, but their communities have different spatial characteristics. However, air transport does not follow the constraint of distance attenuation, and there is not an obvious community structure in the network. Factors related to the passenger transport market, such as social and economic links and tourism resources, play the important roles in the aviation network structure.

基于中国287个地级以上城市的专利、论文数据测度中国城市创新能力,揭示2001~2014年中国创新格局的时空演变特征,并分析城市创新能力的影响因素。研究表明：① 中国创新格局刻有明显的经济地带性差异的烙印,呈“东–中–西”逐渐衰减的态势,且随着时间推移,东部的压倒性地位进一步强化。② 基尼系数呈现先增后降的倒U型变化趋势,反映了整体由极化增长向优化均衡发展的空间过程。东部地区基尼系数维持相对稳定;创新能力较弱的中西部地区,城市间的创新能力差异却在不断缩小。③ 高水平和较高水平的创新城市分布具有很强的经济依赖性,广泛分布于发达城市,而中等水平以上的城市呈集聚分布态势,表现出明显的“集群化”特征,与中国主要城市群的分布高度吻合。④ Moran’s I值均为正,并呈不断上升之势,反映了城市间显著的空间相关性。高高集聚区主要分布于京津冀、长三角和珠三角地区,而中部和西部省会城市作为区域性的创新极,对周围城市的创新带动效应并不明显,辐射作用有限。⑤ 经济基础、人力资本、教育水平、FDI规模、制度因素、基础设施6方面因素不同程度地影响城市创新能力的形成。其中经济基础和人力资本因素影响较大,教育水平和制度因素次之,而FDI规模和基础设施水平对区域的创新能力影响相对较小,但仍表现为正向影响。

Based on patent and dissertation database of China’s 287 cities, the evaluation system of urban innovation capability was established in the perspective of innovation output, which is concerning the temporal-spatial evolution of innovation in China during 2001-2014. Then the article constructed the spatial econometric model to analyze influencing factors. The results are as follows: from 2001 to 2014, there are great differences of regional innovation output in China, and the output weakened from east to west, which showed an obvious trend of strengthen of western. The Gini Index of regional innovation capability in China raised at first, then decreased, which indicated that the innovation spatial patterns has evolved from polarized development to balanced development. The Gini Index of eastern where innovation output mainly concentrated in showed little change, in contract, the Gini Index of western showed declined. High level innovation hotspots widely distributed in developed cities, and the cities in the innovation secondary level are distributed in the form of agglomeration. Spatial dependence characteristic of city innovation level was significant, and further strengthen over time. H-H cluster areas are mainly distributed in Beijing-Tianjin-Hebei, the Yangtze River Delta and the Pearl River Delta, and the central and western provincial capital cities as regional innovation, didn’t have obvious driven effect to neighboring city and had limited radiation effect. Economic base, human capital, education level, FDI scale, institutional factors and infrastructure could promote the development of regional innovation. Especially, economic base and human capital were the most important factors, followed by education level and institutional factors.

区域空间联系是不同客体之间基于空间法则下的相互作用现象,航空联系是诸多空间联系的一种。依据中国国内航班运营信息数据,运用基于O-D联系网络的GIS空间分析法,通过在大尺度数据空间内刻画每一条运营航线,深入解析全国通航中心城市间（不含港澳台）航空联系的网络结构,并与按重力模型计算的空间联系进行对比,分运距区段绘制中国城市空间相互作用联系与航空联系网络结构图谱,深入揭示航空联系的空间相互作用本质。进而分析东、中、西部及东北4区域间航空联系的网络结构差异,揭示中国航空联系的网络结构及区域结构特征。研究发现,城市航空联系网络与人口、经济之间的空间相互作用高度吻合,大城市集聚特征显著,空间分布较不平衡。依据进出港航班数量,可将通航中心城市划分为全国性、区域性、省域及地方性中心4个等级,其中北京、上海、广州为全国性中心。城市航空联系主要集中在600~2 000 km空间距离范围内,总体上服从空间距离衰减规律。全国航空客流的区域分布极不平衡,东部航空运输地位极其突出,西部相对较强,中部与东北相对较弱。

Regional spatial links is based on the interactivity phenomenon between different objects space, the aviation links is one kinds of space relationship. According to the national domestic flights information data(data of Hongkong, Macau and Tiwan excluding), using GIS spatial analysis method base on O-D network, by means of carve every aviation links within the large dimension data space, this article analyses the network structures of the aviation links between national center cities which open to air traffic, compares with special links in the abstract, and display airline network structure and its spatial atlases by different transport distance in China. Research shows, aviation network distribution highly coincide with population and economic space in China, large city agglomeration characteristics is significantly, the whole spatial distribution is not balanced. Based on the flights data, central cities can be divided into 4 grades as national, regional, provincial and local center, including Beijing, Shanghai, and Guangzhou as the national center. The study also found, national airlines mainly concentrated in the 600-2 000 km space distance range, and the aviation links network with the spatial links shows strong correlation during this range, indicates China’s domestic flights suitable travel during this spatial distance range, aviation links on the whole subject to spatial distance attenuating tendency. The regional distribution of the air passenger flows is extremely out-off-balance, the eastern air transport status is extremely prominent, the west is relatively strong, the central and northeast relatively weak. Air passenger flows interflows mainly concentrate on the eastern coastal to western, central and northeast regional, and extremely less between western, central and northeast regional.

揭示高铁对中国航空客运市场影响的空间分异特征,对于针对性协调2种交通方式的发展具有重要参考价值。运用标准差椭圆和交通综合效用分析方法,对中国中心城市高铁、航空客运市场实际发展现状及空间竞合分异特征进行分析。结果发现：① 高铁、航空客运市场均形成以武汉为重心点的空间发展格局;与高铁客运市场相比,航空客运市场区域发展更加均衡;与东西部中心城市相比,中部中心城市旅客出行选乘高铁的概率更高。② 人均时间价值与高铁优势距呈反比,优势距的不同使各中心城市高铁、航空客运市场范围存在明显的空间分异特征;基于交通出行综合效用视角,中国大多数中心城市间的交往,航空出行依旧是最好的选择。③ 高铁对航空客运市场的影响存在明显的空间分异特征。中部大部分中心城市受影响最大,是协调高铁、航空发展的关键区域;西部地区受交通区位条件及高铁发展滞后的影响,中心城市间交往时飞机仍是旅客主要的出行方式,在航空主导优势区依旧存在一定的市场空白。

The spatial differentiation characteristics of the impact of high-speed rail on China's air passenger market is of important reference value for the coordinated development of the two modes of transportation. Using the standard deviation ellipse and traffic comprehensive utility analysis methods, this study analyzed the development status and spatial competition of the high-speed rail and air passenger transport market. The results show that: 1) The high-speed rail and aviation passenger markets have all formed a spatial pattern with Wuhan as the center. Compared with the high-speed rail, the development of the air passenger market area is more balanced; compared with the central cities of the eastern and western regions, the probability of passengers traveling with high-speed rail in the central cities of central China is higher. 2) The per capita time value is inversely proportional to the superiority distance of high-speed rail. The difference in superiority distance makes the high-speed rail and aviation passenger markets in central cities clearly different spatially. Based on the comprehensive utility perspective of traffic, for travels between most central cities in China, air travel is still the best choice. 3) The impact of high-speed rail on the air passenger transport market shows clear spatial differentiation. Most of the central cities in central China are the most affected, which is a key area for coordinating the development of high-speed railways and aviation. In the western region, due to the location conditions of transportation and the lagging development of high-speed rail, air transportation is dominant, and there is still a market gap in the aviation-dominated areas.

通过建立创新能力指标体系和计算模型,并采用相关分析、回归分析、变异系数等方法,从不同空间层级剖析了东北三省的创新能力发展格局及其对经济发展的带动作用,并根据研究结果提出了相关政策建议。研究发现：① 从创新能力分析,吉林、辽宁的创新能力增长较快而黑龙江相对较慢,省际差异呈扩大态势;地级市之间的创新能力相差悬殊,呈现明显的省会城市及门户城市集聚效应,但市级差异呈缩小态势。② 从创新贡献率分析,辽宁的科技创新转化能力及其对经济发展的带动相对较强,而吉林、黑龙江相对较弱;地级市差异较大,沈阳、大连、长春、大庆的创新贡献率比较突出,而锦州、吉林、盘锦、铁岭上升较快。③ 大部分地级市的创新发展对经济带动模式为“低创新能力-弱经济带动”和“高创新能力-强经济带动”,说明各地级市的创新发展及其对经济带动的两极分化较严重。

In the globalization and information era, with the development of knowledge economy, regional innovation capacity is increasingly becoming the determinant of competitive advantage. Especially for Northeastern Old Industrial Base, the innovation of science and technology has become the key support for improving comprehensive regional strength, and the strong lead for changing the mode of regional industrial structure and production. It is against such a background that this article takes a close examination on the spatio-temporal evolution of innovation capacity and its economic contribution in Northeast China. Based on literature review, principal components analysis and fuzzy analytic hierarchy process, we establish innovation capacityindex(ICI), in order to provide a more comprehensive explanation of innovation development trends. We also try to gauge and justify the economic impacts of innovation development, by regression analysis and modeling economic contribution of innovation(ECI). The findings of this article are salutary. In general, in 2003-2014, Northeast China has achieved a great development in regional innovation capacity, and has improved the economic contribution of innovation. But its rank in China has declined, as the development of ICI in Western China and Central China are much faster. Firstly, the development of ICI in Jilin and Liaoning Province are much faster than Heilongjiang, while provincial gap is becoming bigger. At local scale, there are significant regional differences in ICI, while regional digital gap is becoming smaller. Secondly, the spatial distribution of ICI has obviously positive correlation with local GDP development. At provincial scale, innovation in Liaoning Province has strongly promoted economic development, while Jilin and Heilongjiang Province are much weakly. At local scale, the difference of ECI among cities is also very remarkable, while Shenyang, Dalian, Changchun and Daqing share much higher ECI. Thirdly, the development model of most cities are ‘low ICI-low ECI’ and ‘high ICI-high ECI’, which illustrate that there are critical spatial difference between cities’innovation capacity and its economic contribution.