摘要
随着知识经济的兴起，知识作为关键资源在经济发展过程中的作用显得尤为重要。作为技术创新的基础，知识创新是人类科学技术进步的动力之源，不断驱动一个国家或区域经济向前发展。鉴于知识、知识创新在经济发展中的重要作用，以及建设创新型国家发展战略目标的需要，近年来中国的各个区域也在不断地根据自身发展基础积极开展区域知识创新活动，培育和建设自己的区域知识创新体系。
目前，中国的区域创新活动还存在着分工不明确、创新体系结构雷同、区域之间为争夺创新资源恶性竞争等问题。解决这些问题需要在更大范围内配置创新资源，并加强区域之间的创新互动与联系。无论区域采用知识创新的竞争模式还是协同模式，都必须面对创新过程中的知识溢出。一方面，区域之间的知识溢出可以使落后地区以较低的成本和较快的速度吸收利用发达地区溢出的知识，提升其知识创新能力和水平，进而缩小地区间的差距，实现落后地区的赶超；另一方面，知识溢出也会导致落后地区的“搭便车”行为，挫伤发达地区知识创新的积极性，使之减少知识创新的投入，限制了其自主创新能力的提升。要合理利用知识溢出对区域知识创新的积极效应，就必须明确知识溢出影响区域知识创新的机理。
论文在系统梳理知识溢出和区域知识创新相关文献的基础上，明确了如下三个方面的问题：
第一，知识溢出为什么会对区域知识创新活动产生影响？
第二，知识溢出是如何影响区域知识创新活动的？即知识溢出通过什么样的方式和渠道对区域知识创新活动产生影响？
第三，如何破解知识溢出障碍，如何提高知识溢出吸收能力，通过哪些途径提高区域知识创新水平？
基于上述问题，论文开展了如下几个方面的研究：
第一，构建知识溢出影响区域知识创新机理的理论模型。
第二，明确知识溢出对区域知识创新模式选择的影响。区域创新模式的选择受到知识溢出的影响。针对区域创新竞争和区域协同创新两种典型的区域创新模式，在考虑知识吸收能力的基础上，分析知识溢出对两种创新模式下的创新利润和创新投入的影响。鉴于区域协同知识创新已经成为一种高效的创新模式，论文进一步分析在区域协同创新模式下，知识外溢对协同创新共同努力、创新知识投入和创新利润的影响。
第三，探析知识溢出对区域知识创新网络形成的影响。区域知识创新网络是知识创新活动开展和创新知识扩散的重要平台，通过分析知识溢出对区域知识创新网络形成的影响，可以明确知识溢出究竟是如何影响区域创新活动和创新绩效。论文分别分析了知识溢出对区域知识创新网络规模、网络联系强度、网络分布和网络聚类程度的影响。并运用仿真技术，模拟知识溢出对知识创新网络结构的影响。
第四，知识溢出影响区域知识创新的实证研究。首先对知识创新的投入和产出进行界定，并以1998-2009年间中国30个省级行政区域的知识创新活动作为研究样本，分析了省域知识创新产出与投入要素的空间梯度分布，运用探索性空间数据分析和空间计量经济方法对中国省域知识创新的空间分布特征进行全局和局部空间自相性分析，从而在整体上刻画出省域知识创新的集聚情况。在此基础上，构建基于空间面板数据模型的知识创新函数，分析知识溢出对中国省域知识创新绩效的影响。并进一步测度中国省域知识溢出的吸收情况。
第五，从破解知识溢出障碍、构建学习型区域知识创新网络和实施跨区域知识协同创新三个方面提出提升区域知识创新水平的对策建议。
通过理论和实证研究，得出如下几个方面的结论：
第一，在不同的创新模式下，知识溢出对不同创新主体创新利润的影响方向和程度是不同的。对于领导者区域而言，无论是创新竞争还是协同创新，知识创新收益都会随着知识溢出的增加而增加。只有当知识溢出系数非常高时，协同创新的收益才会高于创新竞争。对于追随者区域而言，创新竞争的利润随着知识溢出的增加而增加，而协同创新的利润随着知识溢出的增加而减少。当知识溢出系数比较小时，协同创新的利润大于创新竞争。在区分知识内溢和知识外溢的协同创新模式下，无论是领导者区域还是追随者区域，创新利润与知识外溢系数呈正相关关系。
第二，在不同的创新模式下，知识溢出对不同创新主体创新投入的影响方向和程度也是不同的。在创新竞争模式下，领导者区域的均衡研发投入随着知识溢出系数的提高而增加，追随者区域的均衡研发投入随着知识溢出系数的提高而减少，而且领导者区域的均衡研发投入要高于追随者区域。在协同创新模式下，创新联盟的均衡研发投入随着知识溢出系数的提高而增加。在协同创新模式下，协同创新主体共同合作努力以及因付出努力而产生的成本与知识外溢呈正相关关系；在协同创新过程中，领导者的知识投入与追随者的知识外溢呈正相关关系而与自身的知识外溢呈负相关关系，追随者的知识投入与领导者的知识外溢呈正相关关系而与自身的知识外溢呈负相关关系。
第三，知识溢出对区域创新网络结构具有显著影响。随着知识溢出水平的提高，经过演化，网络的幂律截尾特征会更加显著，网络中各结点的度不断增加，网络关系强度迅速提高。说明知识溢出有利于加强网络成员彼此之间的联系，对网络的结构产生显著的影响。
第四，知识溢出对中国省域知识创新活动具有显著影响。并且中国省域知识溢出吸收呈现出“中部隆起”的特点，存在显著的空间集聚现象。
在已有研究成果的基础上，论文从以下几个方面进行了创新：
第一，构建了区域知识创新的博弈分析模型，分析知识溢出对区域创新竞争和区域协同创新模式下的创新利润和创新投入的影响。并通过数值模拟得出了更加细致的研究结论。
第二，运用社会网络分析理论与仿真模拟方法，分析知识溢出对创新网络结构的影响，分别研究了知识溢出对创新网络的无标度属性、网络结点的度、网络关系强度的影响。
第三，运用探索性数据分析方法分析了中国省域知识创新活动的空间分布特征，并运用基于面板数据的空间计量经济模型分析了知识溢出对中国省域知识创新活动的影响以及中国省域知识溢出的吸收情况。
第四，提出了基于知识溢出的区域知识创新水平提升对策。
With the development of knowledge economics, knowledge as a key resource isplaying a decisive role in economic development. Knowledge innovation which isthe premise and foundation of technology innovation is the power to promote theevolution of science and technology and the development of national and regionaleconomy. In recent years, in view of knowledge and knowledge innovation playingimportant roles in the economic development and the requirements of thedevelopment strategy to build an innovation-oriented country, regions of China carryout regional knowledge innovation activities based on their own development andrequirements, and build their own regional innovation system.
At present, there are problems existing in regional innovation activities, such asunreasonable regional division of innovation, similar regional innovation system,malignant competition for the possession of innovation resources and so on. Solvingthese problems need to strengthen regional interaction and collaboration and allocateinnovation resources in a larger scope. But, no matter choosing regional innovationcompetition or collaboration, knowledge spillover is a vital important problem thatwe must face. Regional knowledge spillovers may let the backwards regions quicklyabsorb knowledge spillovers in low cost in order to improve innovation capabilityand innovation level, narrow regional gap and catch up with the developed regions.But knowledge spillovers may also lead to “free-rider” behavior of backward regions,dampen the enthusiasm of knowledge innovation in developed regions, and limit theability of the independent innovation. If want to reasonably use of the positiveimpact of knowledge spillover on regional knowledge innovation, it must make clearthe mechanism of the impact of knowledge spillover on regional knowledgeinnovation.
Based on systematic study on literature about knowledge spillover and regionalknowledge innovation, it brings out the following three questions need to beanswered:
The first question is why knowledge spillover influencing regional knowledgeinnovation activities. The second question is how knowledge spillover influencingregional knowledge innovation activities. That is to say, knowledge spilloversinfluence regional knowledge innovation activities by what means and channels inthe process of knowledge diffusion. The third question is how to break barriers ofknowledge spillover, how to improve knowledge spillover absorption ability, andhow to raise the level of regional knowledge innovation.
Based on questions mentioned above, it conducts the following research:
Firstly, it creates a general theoretical model of the mechanism of knowledgespillover influencing regional knowledge innovation.
Secondly, it analyses the impact of knowledge spillovers on regionalknowledge innovation mode choosing. For two typical regional innovation modeswhich are regional competitive innovation and regional collaborative innovation,which one on earth should be chosen affected by knowledge spillover.Incorporating absorption ability, it conducts research on the impacts of knowledgespillover on innovation profit and input in these two innovation modes from viewpoint of theory and model. In view of the regional collaborative knowledgeinnovation becoming a kind of more efficient innovation mode, it conducts furtherresearch on the impacts of outgoing spillover and incoming spillover on innovationprofit and input in the regional collaborative innovation mode.
Thirdly, using social network analysis theory and simulation method, it analysesimpacts of knowledge spillover on regional knowledge innovation network structure.Regional knowledge innovation network is an important platform for carrying outknowledge innovation activities and influencing knowledge diffusion. From theimpacts of knowledge spillover on regional knowledge innovation network structure,it is easy to find how knowledge spillover influencing regional knowledgeinnovation by influencing knowledge diffusion. After analysis on composition of regional knowledge innovation network, it analyses impacts of knowledge spilloveron network structure such as network scale, network connection strength, degreedistribution and network clustering degree theoretically. And then using thesimulation technology, it simulates impacts of knowledge spillover on the knowledgeinnovation network structure.
Fourthly, it explores an empirical research on the impacts of knowledgespillover on regional knowledge innovation. After defining the input and output ofknowledge innovation, choosing30provincial knowledge innovation regions duringthe period of1998to2009as research sample, it analyses spatial distribution ofprovincial knowledge inputs and outputs, and using exploratory spatial data analysisit conducts globle and local spatial correlation analysis in order to describe thegeneral agglomeration characteristics. And then it uses spatial panel data modelestablishes knowledge production function to analyze impacts of knowledgespillover on provincial knowledge innovation activities, and then it evaluatesknowledge spillovers absorption of provincial regions of China.
At last, it puts forward suggestions on improving regional innovation fromaspects of breaking barriers of knowledge spillovers, constructing learning regionalknowledge innovation network, implementing cross-regional knowledgecollaborative innovation.
Through theoretical and empirical research, it draws conclusions as follows:
Firstly, in different innovation mode, the impact direct and degree of knowledgespillover on the profits of different innovation bodies are different. For leaderregions, no matter in competitive innovation mode or in collaborative innovationmode, profits of innovation increase with the increase of knowledge spillovers. Onlywhen knowledge spillover coefficient is very high, collaborative innovation profitswill be higher than the competitive innovation. For follower regions, competitiveinnovation profits increase with the increase of the knowledge spillovers, butcollaborative innovation profits decrease with the increase of the knowledgespillovers. Only when knowledge spillover coefficient is very small, collaborativeinnovation profits will be higher than the competitive innovation. For collaborative innovation, no matter for leader region or follower region, innovation profits arepositive related with outgoing spillovers.
Secondly, in different innovation mode the impact direction and degree ofknowledge spillover on innovation input are different. In the competitive innovationmode, the equilibrium innovation input of the leader region increases with theincrease of knowledge spillover coefficient; the equilibrium innovation input of thefollower region decreases with the increase of knowledge spillover coefficient, andthe equilibrium input of the leader region is higher than the follower region. In thecollaborative innovation mode, equilibrium innovation input of the alliance increaseswith the increase of knowledge spillover coefficient. In collaborative innovationmode, cooperation effort and cost resulting from it are positively correlated withoutgoing knowledge spillover.In the collaborative innovation process, knowledgeinput of the leader region is positively correlated with knowledge spillover of thefollower region and negatively correlated with knowledge spillover of itself;knowledge input of the follower region is positively correlated with knowledgespillover of the leader region and negatively correlated with knowledge spillover ofitself.
Thirdly, knowledge spillover has significant impact on the structure of regionalknowledge innovation network. Through network evolution simulation it finds withthe increase of knowledge, the charactistic of stretched exponential distribution ismuch more significant, the degree of each network node is increasing and the networkstrength is rapidly increasing. That means knowledge spillover is conductive tostrengthen connections of of network members.
Fourthly, knowledge spillover has significant impact on provincial knowledgeinnovation of China and provincial knowledge absorptions show protruding in themiddle region of China and the phenomenon of spatial aggregation is in evidence
Compared with previous studies, it is innovative in the following several aspects:
Firstly, it builds a game analysis model and makes analysis on the impacts ofknowledge spillovers on profit and innovation input both in competitive innovationmode and collaborative innovation mode. And make more detailed research conclusions by numerical simulation.
Secondly, using social network analysis theory and simulation method, it makesanalysis on impacts of knowledge spillovers on scale-free attribute of innovationnetwork, the network node degree and the network relation intensity.
Thirdly, by exploratory spatial data analysis it explores special distributions ofprovincial knowledge innovation activities, based on spatial panel data model it teststhe impacts of knowledge spillovers on provincial knowledge innovation activitiesand it evaluates provincial knowledge spillover absorption of China.
At last, it puts forwards suggestions on improving regional knowledgeinnovation based on knowledge spillover.
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