摘要
国家创新系统的协同水平,不仅微观上攸关高校和研究机构知识生产、知识传播、知识转移的效率,攸关企业知识吸收和创新实践的绩效；而且宏观上攸关创新驱动发展战略的实现,攸关自主创新能力的培养,攸关国际竞争力的提升。从历史发展进程分析,美国、英国、欧盟、日本、以色列等发达国家的突出优势就是在于拥有高效协同的国家创新系统。新中国成立以后,我国人才培养、科学研究和社会经济发展等各个方面取得了长足发展,但是国家创新系统存在的分’裂、分割、孤岛现象在发展过程中显得尤为突出,成为了制约我国自主创新能力和协同创新绩效提升的重要障碍,如何构建有中国特色的协同创新体系和创新政策体系,培育企业、高校、研发机构、中介机构以及政府、金融机构等为主体的创新生态系统,提高协同创新效率,成为当务之急。基于此背景,本研究围绕国家创新体系中协同创新能力建设目标,提炼了国家创新系统协同创新的影响因素,并从理论和实证上对协同创新的静态机制和动态机制展开研究,旨在探索影响我国创新系统发展的关键瓶颈和政策激励解决方案,丰富国家创新系统理论和创新政策理论。
本论文主要采用文献分析法、案例研究法、问卷研究法、统计分析法,特别是借鉴复杂系统中经典的“B-Z”反应模型,对国家创新系统协同创新进行了较为深入的研究,主要研究了如下四个方面问题：(1)国家创新系统协同创新过程中的关键维度及其影响因素；(2)国家创新系统静态协同创新机制研究；(3)国家创新系统动态协同机制研究；(4)提高协同效率的创新政策研究。
通过理论和实证研究,本论文主要得出以下几点重要结论：
(1)基于复杂系统理论视角入手,通过文献研究梳理了国家创新系统的知识、参与者、政策体系三个关键子系统,通过案例研究提出了“知识是协同创新核心要素,知识的生产、转移、吸收和利用是影响协同创新绩效的关键环节,高校与研究机构知识转移能力和企业吸收能力是直接制约产学研协同创新绩效提升的关键因素”等理论假设,并得到了实证的支持。
(2)基于问卷调查数据和实证分析,探索了协同创新的静态机制,得出如下结论：首先,企业吸收能力是制约当前国家创新系统协同创新绩效的关键瓶颈因素；第二,高校知识转移能力也是影响国家创新系统协同创新绩效的主要因素之一；第三,激励政策能有效促进企业吸收能力与高校知识转移能力提升。
(3)在静态协同创新机制研究的基础上,借鉴复杂系统理论中经典的“B-Z”三维分析模型,基于Matlab仿真分析软件探索了三种状态中激励政策强度变化下,协同创新绩效、企业吸收能力和高校与研究机构知识转移能力三者协同演进的动态机制。研究发现：首先,吸收能力与协同创新绩效存在高度相关性。当企业吸收能力较高时,知识转移效率能够有效提高,协同创新绩效可以提升5倍；第二,高校知识转移能力呈现较稳定状态；第三,激励政策对产学研协同创新具有积极作用,当企业吸收能力不足,但是激励政策较强时,产学研协同创出新绩效具有一定提升效果；当企业吸收能力较高同时激励政策较强时,协同创新绩效可得到了4.5倍的提升。
(4)基于协同创新静态机制和动态机制的研究成果,针对企业吸收能力是制约协同创新绩效瓶颈因素的研究结论,从环境激励政策、企业吸收能力激励政策和高校与研究机构激励政策三个层面设计了政策解决方案。
本论文的主要理论贡献和创新点为三个方面：(1)本文尝试从协同创新的静态机制和动态机理的角度出发,研究不同创新主体在协同创新过程中的动态交互作用机理,在此基础上有针对性地提出政策建议。研究视角和内容的不同于以往单纯从宏观或单个创新主体视角,具有一定的创新性。(1)不同于以往的静态协同创新机制的研究方法,本文借鉴复杂系统理论中经典的“B-Z”三维分析模型,基于Matlab仿真分析协同创新绩效、企业吸收能力和高校知识转移能力三者协同演进的动态机制,是复杂系统理论在创新管理领域的探索性运用,研究方法具有一定创新性。(2)基于静态协同机制的实证研究和动态协同机制的仿真研究,发现了企业吸收能力在协同创新进程中的关键作用。这一研究发现,不仅有利于企业了解吸收能力对于实施开放式创新过程中的战略性意义,而且也为激励政策的优化提供了针对性方向,研究结论或具有一定创新性。
Collaboration level of national innovation system is of great importance, from micro level, it not only related to the efficiency of knowledge production, knowledge communication and knowledge transfer of the universities and research institutions, but also related to the knowledge absorption and innovation performance of enterprises. From macro level, it not only related to the cultivation of innovation ability, but also related to the achievement of innovation-driven development strategy and improvement of the international competitiveness. From the history of developed countries, like America, Britain, the European Union, Japan, Israel et al., their advantage owes to the highly efficient collaboration of national innovation system. After the founding of new China, personnel training, scientific research and social economic development all obtained the considerable development, but the existence of segmentation, split and islanding phenomenon of national innovation system is particularly prominent, which become main obstacles that restrict our independent innovation capacity and cooperative innovation performance. In order to improve the efficiency of collaborative innovation, how to construct collaborative innovation system and innovation policy system with Chinese characteristics, cultivate innovation ecosystem including enterprise, universities, research institutions, agencies, government and financial institutions, has become an emerging and pressing matter of the moment. Based on such background, this study focuses on the goal of collaborative. innovation ability of national innovation system, summarizes the influence factors of collaborative innovation, then researches on the static mechanism and dynamic mechanism of collaborative innovation from theoretical and empirical respective, aiming to explore the key bottlenecks which influence the development of China's innovation system and suggest policy solutions, thus to rich the theory of national innovation system and innovation policy.
Using the methods of literature analysis, case study, questionnaire research, statistical analysis, especially classic "B-Z" reaction model from the complex system, this paper deeply studied the collaborative innovation of national innovation system, mainly on the following four aspects:(1) key dimension and influencing factors in the process of collaborative innovation of national innovation system;(2)static collaborative innovation mechanism of national innovation system;(3)dynamic collaborative innovation mechanism of national innovation system;(4) innovation policy of improving the cooperative efficiency.
Through theoretical and empirical research, this paper draws the following important conclusion:
(1) Based on complex system theory, this paper reviews three key subsystem of national innovation system:knowledge, participants and policy system. Through multi-case study of the "knowledge is the core element of collaborative innovation, production, transfer, absorption and utilization of knowledge is the key process that influencing the cooperative innovation performance, knowledge transfer ability of university and absorptive capacity of enterprises directly restricted the synergetic innovation performance", such theoretical hypothesis are pointed out and supported by empirical test.
(2)Using data survey and empirical research, this paper explored the static mechanisms of collaborative innovation, draws the following conclusions:first, the absorptive capacity of enterprises is the key bottleneck factor of current innovation performance of national innovation system; second, knowledge transfer capacity of university is also one of the main factors that influcing collaborative innovation performance of national innovation system; third, incentive policy can effectively promote absorptive capacity of enterprises and knowledge transfer ability of universities.
(3)Based on the static mechanism of collaborative innovation, using classic "B-Z" three dimensional analysis model and Matlab simulation analysis software to explore the dynamic collaborative mechanism of the three elements:collaborative innovation performance, absorptive capacity of enterprise and knowledge transfer ability of university. The study found:firstly, absorptive capacity of enterprise has high correlation with cooperative innovation performance. When the absorptive capacity is high, the efficiency of knowledge transfer can effectively improve the performance, collaborative innovation can increase about5times; second, knowledge transfer capacity of universities keeps stable; third, the incentive policy has positive effects on collaborative innovation, when the absorptive capacity is insufficient, but the incentive policy is strong, certain performance can be promoted; when the absorption capability of enterprise is high and incentive policy is strong, collaborative innovation performance can be increased about4.5times.
(4)Based on static and dynamic mechanism of collaborative innovation, connecting with the conclusion that absorptive capacity of enterprises is the bottleneck factors that restrict the innovation performance, this paper designed policy solutions from three aspects:environment optimition, absorptive capacity promotion of enterprise and university motivation.
The contribution and innovation of this paper is shown in the following two aspects:(1)Different from previous perspective focused on system or single main body of innovation, this paper researched the static and dynamic mechanisms of collaborative innovation, explored interaction of many main bodys in innovation system. It's a new perspective and content.(2)Different from the previous static methods in researching collaborative innovation mechanism, this paper uses classic "B-Z" three dimensional analysis model and Matlab simulation analysis, exploring the dynamic mechanism of collaborative innovation performance, absorptive capacity and knowledge transfer ability. Which is a new application of complex system theory in the field of innovation management, therefore, research methods are innovative.(3)Based on empirical research of static mechanism and simulation research of dynamic mechanism, we found that absorptive capacity of enterprises is the key role in the process of collaborative innovation. The findings of this study, not only benefits to the promotion of absorptive capacity, but also provides the direction for the optimization of incentive policy, the conclusions are innovative.
引文
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