大学科技园知识管理的理论与实证研究
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摘要
知识管理、知识创新作为当今学术界、理论界的研究热点,正逐渐成为知识社会中对国民经济健康发展具有深远影响的最重要理论之一。近年来,随着我国“科教兴国”战略的全面实施,大学科技园以一种新兴的经济组织形式应运而生并且在短时间内蓬勃发展,对推动区域创新、拉动地方经济发展发挥了积极的作用。作为国家创新体系的一个重要组成部分,大学科技园是一个知识密集的基地,园区企业通过对知识的获取、积累、传播、整合以及应用,不断地完成知识创新过程。因此,大学科技园同样需要通过知识管理来营造一种良好的创新文化氛围,促进园区的知识共享和知识创新。然而,虽然知识管理理论逐步趋于成熟,但现有的研究多数把目光集中在单个企业或企业集群中,对于知识集群的大学科技园却鲜有涉及,形成了该研究领域的相对空白。
本研究独辟蹊径,从知识创新的视角对大学科技园实施知识管理进行了理论与实证分析。本研究基于文献回顾以及对大学科技园知识创新的基本理论分析构建了一个探讨大学科技园知识创新的影响因素、大学科技园的知识创新能力以及大学科技园的创新绩效三者之间影响关系的理论模型,提出了相应的研究假设。同时,根据文献研究、专家建议以及大学科技园的发展实践,开发和设计了一套测量量表,并利用SPSS和AMOS等软件工具对所构建的理论模型进行了实证分析。最后,得出了初步的研究结论并提出了相应的实践启示。研究内容和结论主要体现在以下几个方面：
(1)大学科技园知识创新的基本理论分析。本研究提出,大学科技园的知识体系由技术知识、市场知识以及管理知识构成,三者互相渗透、共同作用。大学科技园作为一种特殊的企业集群现象,其本质内涵就是“知识集群”。因而,大学科技园的知识创新活动,不仅是指各行为主体内部的个体创新,还包括集群内跨组织之间的协作创新,它的内在机理是通过社会化、外在化、组合化以及内在化等一系列动态循环过程,实现知识在隐性和显性状态下的相互转化,不断创造出新的知识。在此基础上,本研究构建了由知识资产、微观巴、宏观巴和SECI模型组成的大学科技园知识创新系统,亦即本研究理论模型的雏形。
(2)理论模型的构建与变量界定。本研究以大学科技园知识创新系统为基础,将大学科技园的微观巴、宏观巴和已有的知识资产作为前因变量来衡量大学科技园知识创新活动的影响因素,把SECI模型作为中介变量反映知识创新能力的大小,而将输出的知识资产作为结果变量来衡量大学科技园的创新绩效,构建了本研究的理论模型。在具体界定时,将影响因素划分为基础因素域、组织因素域以及支撑因素域三个维度,将知识创新能力划分为技术知识创新水平和市场知识创新水平两个维度,将创新绩效划分为孵化产出、创新产出、人才培养成效以及区域互动成效四个维度。同时,围绕理论模型,本研究提出了研究假设,认为基础因素域、组织因素域与支撑因素域分别对大学科技园的技术知识创新水平、市场知识创新水平具有显著正向影响,而技术知识创新水平、市场知识创新水平分别对大学科技园的孵化产出、创新产出以及人才培养成效、区域互动成效具有显著正向影响
(3)实证分析。本研究根据文献分析、专家建议以及大学科技园的发展实践,开发设计了一套测量量表,并通过小样本测试对测量量表的信度和效度进行了栓验,修订后得到正式问卷。同时,通过对大样本数据进行探索性因子分析、验证性因子分析,发现大样本数据的各项检验值均达到了统计要求,说明测量量表结构合理并且具有较高的信度和效度。在结构方程分析环节,所选择的八个拟合指数的统计值均符合可接受值,说明模型的拟合效果较好。最后,通过分析模型中各条路径的C.R.值和P值,对本研究所提出的关系假设进行了检验,发现除H4外,其他的关系假设都得到了支持,说明各变量之间具有显著正向影响,本研究对各变量的维度划分以及界定具有一定的合理性。进一步研究表明,基础因素域对技术知识创新水平的影响最明显,其次是组织因素域和支撑因素域；而对市场知识创新水平的影响,支撑因素域比基础因素域更显著。同时,技术知识创新水平对大学科技园创新产出的影响较孵化产出要大；而市场知识创新水平对大学科技园区域互动成效的影响比对人才培养成效的影响更明显。
(4)实践启示。根据理论分析和实证结果,本研究从大学科技园知识创新的影响因素着手,围绕三个因素域和十个具体影响因素,对应地提出了若干对策建议。希望通过对大学科技园知识创新的影响因素进行调节,进一步增强大学科技园的知识创新能力,最终达到提高大学科技园的创新绩效的目的。
本研究的主要创新点有：
首先,本研究将知识管理理论、集群理论引入我国的大学科技园管理中,开辟了大学科技园知识创新这一全新的理论研究视角,并综合运用知识管理和企业集群等相关理论,提出了“知识集群”概念,指出大学科技园企业集群现象的本质内涵就是“知识集群”。
其次,本研究对大学科技园知识创新的基本理论进行了探索性的梳理,厘清了大学科技园的知识分类和知识体系,剖析了大学科技园知识创新的内在作用机理,并构建了大学科技园知识创新系统。同时,在加拿大学者Tim Padmore和Hervey Gibson的GEM模型基础上,提出了大学科技园的GOS影响因素模型,将GEM模型“因素对”的概念改进为“因素域”,归纳了大学科技园知识创新的十个影响因素,将其分别划分到基础、组织和支撑三个因素域中。
再次,本研究从贴近发展实践出发,对大学科技园的知识创新能力及其创新绩效进行了具体的界定,并构建了一个探讨大学科技园知识创新的影响因素、知识创新能力以及创新绩效三者之间影响关系的理论模型,开发设计了一套具有良好信度和效度的测量量表。
最后,本研究通过实证分析,检验了大学科技园知识创新的影响因素、知识创新能力和创新绩效三者之间的路径影响关系,并从大学科技园知识创新的影响因素着手,提出了相应的对策建议,为大学科技园增强知识创新能力、提高创新绩效提供了理论依据。
Knowledge management and knowledge innovation has become a hot topic research point in academic and theory circles, and will be one of the most important theories in knowledge society that has a far-reaching impact on national economic development. In recent years, with the full implementation of the strategy for invigorating China through science and education, a new economic organization named University Science Park came into being, and flourished in a short period of time. They have played a positive role to promote regional innovation and stimulate local economic development. As an important part of the national innovation system, University Science Parks are the knowledge bases. The enterprises in the park complete the process of knowledge innovation constantly through knowledge acquisition, accumulation, dissemination, integration, and application. Therefore, University Science Parks also need knowledge management to create a culture of innovation and promote knowledge sharing and knowledge innovation. However, the theory of knowledge management is gradually maturing, but the existing researches mainly focus on a single enterprise or enterprise clusters, and rarely relate to University Science Parks which are knowledge cluster. So the research of knowledge management about University Science Parks is still a blank field.
The paper focused on knowledge innovation and carried out a theory and empirical research on knowledge management of University Science Parks. On the basis of literature review and a theoretical analysis on the knowledge innovation of University Science Parks, the paper built a theoretical model to dicuss the relationships among the influencing factors of knowledge innovation, the capability of knowledge innovation and the innovation performance and proposed some specific research assumptions. Meanwhile, based on literature analysis, expert's advice and the development practice of University Science Parks, the paper designed a set of measuring scales relate to all variables and conducted an empirical analysis to test the theoretical model by using the software tools, such as Spss and Amos. Finally, the paper summarized its conclusions and corresponded some countermeasures and suggestions on the mechanism of knowledge innovation of University Science Parks. The main contents and conclusions of the paper were as follows:
(1) Basic theoretical analysis on the knowledge innovation of University Science Parks. The paper proposed that the knowledge hierarchy of University Science Parks was constituted by the technical knowledge, market knowledge and management knowledge, which interpenetrated and was combined action. As a special phenomenon of enterprise cluster, the essential meaning of University Science Parks was knowledge cluster. So the activities of knowledge innovation in University Science Parks referred to not only individual innovation, but also collaborative innovation. Through a series of dynamic cycle like socialization, externalization. combination as well as the internalization, knowledge was transformed into each other under the recessive and dominant states, and new knowledge was created constantly. On this basis, the paper constructed the knowledge innovation system of University Science Parks, which was composed of knowledge assets, micro bar, macro bar and SECI model. The knowledge innovation system of University Science Parks was also a prototype of the theoretical model.
(2) Building theoretical model and variable definition. Based on the knowledge innovation system of University Science Parks, the paper constructed the theoretical model. In the model, micro bar, macro bar and the existing knowledge assets was taken as the antecedent variables to measure the influencing factors of knowledge innovation, the SECI model was taken as the mediating variables to reflect the capability of knowledge innovation and the exporting knowledge assets was taken as the outcome variables to measure innovation performance. When defining, the paper divided the influencing factors of knowledge innovation into three dimensions, like groundings domain, organizations domain as well as supportings domain; divided the capacity of knowledge innovation into two dimensions, including the level of technical knowledge innovation and the level of market knowledge innovation; divided innovation performance into four dimensions, including incubator output, innovation output, personnel training effectiveness and regional interaction effectiveness. Around the theoretical model, the paper proposed ten relational hypotheses relate to all variables, which assumed having significantly positive effect among the antecedent variable, the mediating variables and the outcome variables.
(3) Empirical analysis. Based on literature analysis, expert's advice and the development practice of University Science Parks, the paper designed a set of measuring scales relate to all variables. After examining the validity and reliability of the initial questionnaire, the paper revised the formal questionnaire. Meanwhile, the paper carried out an exploratory factor analysis and an confirmatory factor analysis by using SPSS statistical software. The analysis results showed that all test values of the large sample data reached statistical requirements, which indicated that the structure of the measuring scales was reasonable and had high reliability and validity. At the same time, the paper carried out a structural equation analysis on the knowledge innovation model of University Science Parks by using AMOS software. The analysis results showed that all statistical values of the fit indexs selected by the paper were consistent with the acceptable values and the model fit well. When analyzing the CR values and P values of each path in the model, we found that the H4hypothese couldn't be supported, while all other hypotheses were tenable. It indicated that all variables (except H4) had significantly positive effect and the method about the division of dimension and the definition of the variables was reasonable. Further research showed that the groundings domain was the most obvious impact on the level of technical knowledge innovation, followed by the organizations domain as well as the supportings domain. As to the effect on the level of market knowledge innovation, the supportings domain was higher than the groundings domain. As to the effect produced by the level of technical knowledge innovation, innovation output was higher than incubator output. As to the effect produced by the level of market knowledge innovation, regional interaction effectiveness was higher than personnel training effectiveness.
(4) Practice implications. Based on the theoretical analysis and empirical results, the paper focused on the influencing factors of knowledge innovation and made several countermeasures and suggestions on the development practice of University Science Parks.
The major innovation was listed as the followings:
Firstly, knowledge management theory and cluster theory was applied in the management of University Science Parks, which was a new theory perspective on knowledge innovation of University Science Parks. Based on the theory of knowledge management and enterprise clusters, the paper put forward a new concept named knowledge cluster and pointed out that the essence of enterprise cluster in University Science Parks was knowledge cluster.
Secondly, the paper clarified the classification of knowledge and knowledge hierarchy of University Science Parks, discussed the internal mechanism of knowledge innovation of University Science Parks and proposed the knowledge innovation system. Based on this, the paper put forward the GOS model improved from the GEM model by Tim Padmore and Hervey Gibson. Compared with the GEM model, the GOS model proposed the concept of factor domains corresponding to that of factor pairs in GEM model. The GOS model summarized ten influencing factors on knowledge innovation of University Science Parks and categorized them into groundings domain, organizations domain and supportings domain.
Thirdly, the paper specified the definition of the capability of knowledge innovation and innovation performance, closely to the actual development of University Science Parks. The paper also constructed a theoretical model to discuss the relationships among the influencing factors of knowledge innovation, capability of knowledge innovation and innovation performance. Meanwhile, the paper designed a set of measuring scales, which was proved to have good reliability and validity.
Finally, by empirical analysis, the paper succeeded in examining the path relationships among the influencing factors of knowledge innovation, capability of knowledge innovation and innovation performance of University Science Parks. At the same time, the paper focused on the influencing factors of knowledge innovation of University Science Parks and put forward several countermeasures and suggestions, which provided a theoretical basis to enhance the capacity of knowledge innovation and improve innovation performance for University Science Parks.
本研究独辟蹊径,从知识创新的视角对大学科技园实施知识管理进行了理论与实证分析。本研究基于文献回顾以及对大学科技园知识创新的基本理论分析构建了一个探讨大学科技园知识创新的影响因素、大学科技园的知识创新能力以及大学科技园的创新绩效三者之间影响关系的理论模型,提出了相应的研究假设。同时,根据文献研究、专家建议以及大学科技园的发展实践,开发和设计了一套测量量表,并利用SPSS和AMOS等软件工具对所构建的理论模型进行了实证分析。最后,得出了初步的研究结论并提出了相应的实践启示。研究内容和结论主要体现在以下几个方面：
(1)大学科技园知识创新的基本理论分析。本研究提出,大学科技园的知识体系由技术知识、市场知识以及管理知识构成,三者互相渗透、共同作用。大学科技园作为一种特殊的企业集群现象,其本质内涵就是“知识集群”。因而,大学科技园的知识创新活动,不仅是指各行为主体内部的个体创新,还包括集群内跨组织之间的协作创新,它的内在机理是通过社会化、外在化、组合化以及内在化等一系列动态循环过程,实现知识在隐性和显性状态下的相互转化,不断创造出新的知识。在此基础上,本研究构建了由知识资产、微观巴、宏观巴和SECI模型组成的大学科技园知识创新系统,亦即本研究理论模型的雏形。
(2)理论模型的构建与变量界定。本研究以大学科技园知识创新系统为基础,将大学科技园的微观巴、宏观巴和已有的知识资产作为前因变量来衡量大学科技园知识创新活动的影响因素,把SECI模型作为中介变量反映知识创新能力的大小,而将输出的知识资产作为结果变量来衡量大学科技园的创新绩效,构建了本研究的理论模型。在具体界定时,将影响因素划分为基础因素域、组织因素域以及支撑因素域三个维度,将知识创新能力划分为技术知识创新水平和市场知识创新水平两个维度,将创新绩效划分为孵化产出、创新产出、人才培养成效以及区域互动成效四个维度。同时,围绕理论模型,本研究提出了研究假设,认为基础因素域、组织因素域与支撑因素域分别对大学科技园的技术知识创新水平、市场知识创新水平具有显著正向影响,而技术知识创新水平、市场知识创新水平分别对大学科技园的孵化产出、创新产出以及人才培养成效、区域互动成效具有显著正向影响
(3)实证分析。本研究根据文献分析、专家建议以及大学科技园的发展实践,开发设计了一套测量量表,并通过小样本测试对测量量表的信度和效度进行了栓验,修订后得到正式问卷。同时,通过对大样本数据进行探索性因子分析、验证性因子分析,发现大样本数据的各项检验值均达到了统计要求,说明测量量表结构合理并且具有较高的信度和效度。在结构方程分析环节,所选择的八个拟合指数的统计值均符合可接受值,说明模型的拟合效果较好。最后,通过分析模型中各条路径的C.R.值和P值,对本研究所提出的关系假设进行了检验,发现除H4外,其他的关系假设都得到了支持,说明各变量之间具有显著正向影响,本研究对各变量的维度划分以及界定具有一定的合理性。进一步研究表明,基础因素域对技术知识创新水平的影响最明显,其次是组织因素域和支撑因素域；而对市场知识创新水平的影响,支撑因素域比基础因素域更显著。同时,技术知识创新水平对大学科技园创新产出的影响较孵化产出要大；而市场知识创新水平对大学科技园区域互动成效的影响比对人才培养成效的影响更明显。
(4)实践启示。根据理论分析和实证结果,本研究从大学科技园知识创新的影响因素着手,围绕三个因素域和十个具体影响因素,对应地提出了若干对策建议。希望通过对大学科技园知识创新的影响因素进行调节,进一步增强大学科技园的知识创新能力,最终达到提高大学科技园的创新绩效的目的。
本研究的主要创新点有：
首先,本研究将知识管理理论、集群理论引入我国的大学科技园管理中,开辟了大学科技园知识创新这一全新的理论研究视角,并综合运用知识管理和企业集群等相关理论,提出了“知识集群”概念,指出大学科技园企业集群现象的本质内涵就是“知识集群”。
其次,本研究对大学科技园知识创新的基本理论进行了探索性的梳理,厘清了大学科技园的知识分类和知识体系,剖析了大学科技园知识创新的内在作用机理,并构建了大学科技园知识创新系统。同时,在加拿大学者Tim Padmore和Hervey Gibson的GEM模型基础上,提出了大学科技园的GOS影响因素模型,将GEM模型“因素对”的概念改进为“因素域”,归纳了大学科技园知识创新的十个影响因素,将其分别划分到基础、组织和支撑三个因素域中。
再次,本研究从贴近发展实践出发,对大学科技园的知识创新能力及其创新绩效进行了具体的界定,并构建了一个探讨大学科技园知识创新的影响因素、知识创新能力以及创新绩效三者之间影响关系的理论模型,开发设计了一套具有良好信度和效度的测量量表。
最后,本研究通过实证分析,检验了大学科技园知识创新的影响因素、知识创新能力和创新绩效三者之间的路径影响关系,并从大学科技园知识创新的影响因素着手,提出了相应的对策建议,为大学科技园增强知识创新能力、提高创新绩效提供了理论依据。
Knowledge management and knowledge innovation has become a hot topic research point in academic and theory circles, and will be one of the most important theories in knowledge society that has a far-reaching impact on national economic development. In recent years, with the full implementation of the strategy for invigorating China through science and education, a new economic organization named University Science Park came into being, and flourished in a short period of time. They have played a positive role to promote regional innovation and stimulate local economic development. As an important part of the national innovation system, University Science Parks are the knowledge bases. The enterprises in the park complete the process of knowledge innovation constantly through knowledge acquisition, accumulation, dissemination, integration, and application. Therefore, University Science Parks also need knowledge management to create a culture of innovation and promote knowledge sharing and knowledge innovation. However, the theory of knowledge management is gradually maturing, but the existing researches mainly focus on a single enterprise or enterprise clusters, and rarely relate to University Science Parks which are knowledge cluster. So the research of knowledge management about University Science Parks is still a blank field.
The paper focused on knowledge innovation and carried out a theory and empirical research on knowledge management of University Science Parks. On the basis of literature review and a theoretical analysis on the knowledge innovation of University Science Parks, the paper built a theoretical model to dicuss the relationships among the influencing factors of knowledge innovation, the capability of knowledge innovation and the innovation performance and proposed some specific research assumptions. Meanwhile, based on literature analysis, expert's advice and the development practice of University Science Parks, the paper designed a set of measuring scales relate to all variables and conducted an empirical analysis to test the theoretical model by using the software tools, such as Spss and Amos. Finally, the paper summarized its conclusions and corresponded some countermeasures and suggestions on the mechanism of knowledge innovation of University Science Parks. The main contents and conclusions of the paper were as follows:
(1) Basic theoretical analysis on the knowledge innovation of University Science Parks. The paper proposed that the knowledge hierarchy of University Science Parks was constituted by the technical knowledge, market knowledge and management knowledge, which interpenetrated and was combined action. As a special phenomenon of enterprise cluster, the essential meaning of University Science Parks was knowledge cluster. So the activities of knowledge innovation in University Science Parks referred to not only individual innovation, but also collaborative innovation. Through a series of dynamic cycle like socialization, externalization. combination as well as the internalization, knowledge was transformed into each other under the recessive and dominant states, and new knowledge was created constantly. On this basis, the paper constructed the knowledge innovation system of University Science Parks, which was composed of knowledge assets, micro bar, macro bar and SECI model. The knowledge innovation system of University Science Parks was also a prototype of the theoretical model.
(2) Building theoretical model and variable definition. Based on the knowledge innovation system of University Science Parks, the paper constructed the theoretical model. In the model, micro bar, macro bar and the existing knowledge assets was taken as the antecedent variables to measure the influencing factors of knowledge innovation, the SECI model was taken as the mediating variables to reflect the capability of knowledge innovation and the exporting knowledge assets was taken as the outcome variables to measure innovation performance. When defining, the paper divided the influencing factors of knowledge innovation into three dimensions, like groundings domain, organizations domain as well as supportings domain; divided the capacity of knowledge innovation into two dimensions, including the level of technical knowledge innovation and the level of market knowledge innovation; divided innovation performance into four dimensions, including incubator output, innovation output, personnel training effectiveness and regional interaction effectiveness. Around the theoretical model, the paper proposed ten relational hypotheses relate to all variables, which assumed having significantly positive effect among the antecedent variable, the mediating variables and the outcome variables.
(3) Empirical analysis. Based on literature analysis, expert's advice and the development practice of University Science Parks, the paper designed a set of measuring scales relate to all variables. After examining the validity and reliability of the initial questionnaire, the paper revised the formal questionnaire. Meanwhile, the paper carried out an exploratory factor analysis and an confirmatory factor analysis by using SPSS statistical software. The analysis results showed that all test values of the large sample data reached statistical requirements, which indicated that the structure of the measuring scales was reasonable and had high reliability and validity. At the same time, the paper carried out a structural equation analysis on the knowledge innovation model of University Science Parks by using AMOS software. The analysis results showed that all statistical values of the fit indexs selected by the paper were consistent with the acceptable values and the model fit well. When analyzing the CR values and P values of each path in the model, we found that the H4hypothese couldn't be supported, while all other hypotheses were tenable. It indicated that all variables (except H4) had significantly positive effect and the method about the division of dimension and the definition of the variables was reasonable. Further research showed that the groundings domain was the most obvious impact on the level of technical knowledge innovation, followed by the organizations domain as well as the supportings domain. As to the effect on the level of market knowledge innovation, the supportings domain was higher than the groundings domain. As to the effect produced by the level of technical knowledge innovation, innovation output was higher than incubator output. As to the effect produced by the level of market knowledge innovation, regional interaction effectiveness was higher than personnel training effectiveness.
(4) Practice implications. Based on the theoretical analysis and empirical results, the paper focused on the influencing factors of knowledge innovation and made several countermeasures and suggestions on the development practice of University Science Parks.
The major innovation was listed as the followings:
Firstly, knowledge management theory and cluster theory was applied in the management of University Science Parks, which was a new theory perspective on knowledge innovation of University Science Parks. Based on the theory of knowledge management and enterprise clusters, the paper put forward a new concept named knowledge cluster and pointed out that the essence of enterprise cluster in University Science Parks was knowledge cluster.
Secondly, the paper clarified the classification of knowledge and knowledge hierarchy of University Science Parks, discussed the internal mechanism of knowledge innovation of University Science Parks and proposed the knowledge innovation system. Based on this, the paper put forward the GOS model improved from the GEM model by Tim Padmore and Hervey Gibson. Compared with the GEM model, the GOS model proposed the concept of factor domains corresponding to that of factor pairs in GEM model. The GOS model summarized ten influencing factors on knowledge innovation of University Science Parks and categorized them into groundings domain, organizations domain and supportings domain.
Thirdly, the paper specified the definition of the capability of knowledge innovation and innovation performance, closely to the actual development of University Science Parks. The paper also constructed a theoretical model to discuss the relationships among the influencing factors of knowledge innovation, capability of knowledge innovation and innovation performance. Meanwhile, the paper designed a set of measuring scales, which was proved to have good reliability and validity.
Finally, by empirical analysis, the paper succeeded in examining the path relationships among the influencing factors of knowledge innovation, capability of knowledge innovation and innovation performance of University Science Parks. At the same time, the paper focused on the influencing factors of knowledge innovation of University Science Parks and put forward several countermeasures and suggestions, which provided a theoretical basis to enhance the capacity of knowledge innovation and improve innovation performance for University Science Parks.
引文
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