企业孵化器知识网络中的知识转移研究
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摘要
企业孵化器是为新创企业提供发展所需的一系列管理支持和资源网络,帮助和促进新创企业成长的创业服务机构。企业孵化器将政府机构、大学/研究机构、中介机构和在孵企业紧密联系起来,构成一个跨组织的知识网络。知识转移在这个网络中频繁发生,网络中知识主体向在孵企业的知识转移,可弥补在孵企业创业过程中的知识缺口,促进在孵企业成长。
本文界定了企业孵化器知识网络的内涵,构建了企业孵化器知识网络概念模型,给出了其形式化表达,并将其分为两个子网,其一是企业孵化器组织知识网络；其二是企业孵化器个体知识网络,分别定义了两个子网的结构特征参数,指出企业孵化器组织知识网络是一个以孵化器为整体中心点的具有较高中心势的网络,企业孵化器个体知识网络具有小世界网络的特征。
基于个体间非正式知识转移理论,本文构建了企业孵化器个体知识网络中的知识转移模型,利用Matlab7.3软件设计了仿真实验,考察了网络特征对知识转移的影响,结果表明：当企业孵化器个体知识网络形成小世界网络结构时,知识转移绩效最好；节点的平均度越大,知识转移绩效越好；知识转移阈值越高,知识转移绩效越好；网络中的专家比例越多,专家在知识类上分布越均衡,知识转移绩效越好；节点的吸收能力越强,知识转移绩效越好。本文同时考察了创业者在网络中形成的自我中心网的结构特征对其知识转移的影响,得出的结论是：创业者自我中心网的网络规模越大,网络密度越低,网络多样性越高,越有利于其知识转移。
基于组织影响力理论,本文将企业孵化器组织知识网络中节点在知识转移中的影响力定义为该节点在网络中的知识地位,用该节点在网络知识转移中的影响指数来测量。识别了网络中节点间的主要知识转移活动并确定了各类知识转移活动的权值,给出了节点对网络知识转移影响力的测量方法。为考察企业孵化器组织知识网络中节点对子群知识转移的影响力,将网络划分为知识调配子群,知识源子群,初创期在孵企业子群、成长期在孵企业子群和成熟期在孵企业子群等五个互不重叠的子群,给出了节点对各子群知识转移影响指数的计算方法。
本文将系统动力学方法应用于企业孵化器知识网络中知识转移动态行为的研究中。在分析企业孵化器知识网络中知识转移影响因素的基础上,建立了企业孵化器知识网络中知识转移的系统动力学模型。使用建模软件Vensim作为仿真平台,采用理论检验的方法对模型进行了有效性检验,结果表明：模型能很好地刻画实际的企业孵化器知识网络中知识转移的动态行为。本文还探索了企业孵化器知识网络中知识转移行为的调控参数,对各调控参数对知识转移行为的影响进行了仿真分析。
基于上述研究成果,本文提出了政府机构、企业孵化器、在孵企业促进企业孵化器知识网络中知识转移的对策。
Business incubator is an organization which providing a series of administrative support and resource network to new ventures in order to promote their growth. Business incubator linking government agencies, universities or research institutions, professional service organizations and incubatees forms an inter-organizational knowledge network. Knowledge transfer frequently occurs in this network. Incubatees can narrow their knowledge gap and promote their growth by transferred knowledge from other actors within the network.
This paper defines business incubator knowledge network. A conceptual model of business incubator knowledge network is put forward and the formal expression is given. The network is divided into two subnets. One is business incubator organizational knowledge network. The other is business incubator individual knowledge network. Parameters that describe structural feature of the two subnets are defined respectively. The paper argues that business incubator organizational knowledge network is a network that has high centrality with incubator as a centre node and business incubator individual knowledge network presents characteristics of small world network.
Based on informal individual knowledge transfer theory, a model of knowledge transfer within business incubator individual knowledge network is established. Adopting matlab7.3software, effects of network characteristics on network knowledge transfer are explored using simulation experiment method. The results show that knowledge transfer achieves the best performance when the network formed small world network structure. The greater average degree of nodes, the better knowledge transfer performance. The higher knowlege transfer threshold, the better knowledge transfer performance. The more proportion of experts as well as more balanced distribution of experts on knowledge type, the better knowledge transfer performance. The stronger absorptive capacity of nodes, the better knowledge transfer performance. Meanwhile, effects of entrepreneurs'ego-centric network on its knowledge transfer are also explored. The results show that greater size, low density and high diversity ego-centric network can facilitate entrepreneurs'knowledge transfer.
Based on organizational influence theory, the paper defines influence of a node on network knowledge transfer as its knowledge status in the network that can be measured by influence index of the node. The knowledge transfer activities within the network and their weights are identified. The method for measuring influences of nodes on network knowledge transfer are proposed. In order to explore the influences of nodes on subgroups, the network is divided into five non-overlapping subgroups that including knowledge coordination group, knowledge source group, start-up stage incubatee group, growing stage incubatee group and mature stage incubatee group. The method for calculating influence index of nodes on subgroups is given.
This paper studies knowledge transfer dynamic behaviors within business incubator knowledge network using system dynamic theory. Based on analysis of influence factors on knowledge transfer within business incubator knowledge network, a system dynamic model of knowledge transfer within the network is established. Using Vensim simulation software platform and adopting theory test method, the effectiveness of the model is verified. The results indicate that the model is quite well able to depict the actual knowledge transfer dynamic behavior within the business incubator knowledge network. Besides this, the paper also explores control parameters for improving knowledge transfer behaviors within the network. The influences of the control parameters on knowledge transfer behaviors within the network is simulated respectively.
Based on above results, the paper proposes strategies to promote knowledge transfer within business incubator knowledge network for government agency, business incubator and incubatee.
本文界定了企业孵化器知识网络的内涵,构建了企业孵化器知识网络概念模型,给出了其形式化表达,并将其分为两个子网,其一是企业孵化器组织知识网络；其二是企业孵化器个体知识网络,分别定义了两个子网的结构特征参数,指出企业孵化器组织知识网络是一个以孵化器为整体中心点的具有较高中心势的网络,企业孵化器个体知识网络具有小世界网络的特征。
基于个体间非正式知识转移理论,本文构建了企业孵化器个体知识网络中的知识转移模型,利用Matlab7.3软件设计了仿真实验,考察了网络特征对知识转移的影响,结果表明：当企业孵化器个体知识网络形成小世界网络结构时,知识转移绩效最好；节点的平均度越大,知识转移绩效越好；知识转移阈值越高,知识转移绩效越好；网络中的专家比例越多,专家在知识类上分布越均衡,知识转移绩效越好；节点的吸收能力越强,知识转移绩效越好。本文同时考察了创业者在网络中形成的自我中心网的结构特征对其知识转移的影响,得出的结论是：创业者自我中心网的网络规模越大,网络密度越低,网络多样性越高,越有利于其知识转移。
基于组织影响力理论,本文将企业孵化器组织知识网络中节点在知识转移中的影响力定义为该节点在网络中的知识地位,用该节点在网络知识转移中的影响指数来测量。识别了网络中节点间的主要知识转移活动并确定了各类知识转移活动的权值,给出了节点对网络知识转移影响力的测量方法。为考察企业孵化器组织知识网络中节点对子群知识转移的影响力,将网络划分为知识调配子群,知识源子群,初创期在孵企业子群、成长期在孵企业子群和成熟期在孵企业子群等五个互不重叠的子群,给出了节点对各子群知识转移影响指数的计算方法。
本文将系统动力学方法应用于企业孵化器知识网络中知识转移动态行为的研究中。在分析企业孵化器知识网络中知识转移影响因素的基础上,建立了企业孵化器知识网络中知识转移的系统动力学模型。使用建模软件Vensim作为仿真平台,采用理论检验的方法对模型进行了有效性检验,结果表明：模型能很好地刻画实际的企业孵化器知识网络中知识转移的动态行为。本文还探索了企业孵化器知识网络中知识转移行为的调控参数,对各调控参数对知识转移行为的影响进行了仿真分析。
基于上述研究成果,本文提出了政府机构、企业孵化器、在孵企业促进企业孵化器知识网络中知识转移的对策。
Business incubator is an organization which providing a series of administrative support and resource network to new ventures in order to promote their growth. Business incubator linking government agencies, universities or research institutions, professional service organizations and incubatees forms an inter-organizational knowledge network. Knowledge transfer frequently occurs in this network. Incubatees can narrow their knowledge gap and promote their growth by transferred knowledge from other actors within the network.
This paper defines business incubator knowledge network. A conceptual model of business incubator knowledge network is put forward and the formal expression is given. The network is divided into two subnets. One is business incubator organizational knowledge network. The other is business incubator individual knowledge network. Parameters that describe structural feature of the two subnets are defined respectively. The paper argues that business incubator organizational knowledge network is a network that has high centrality with incubator as a centre node and business incubator individual knowledge network presents characteristics of small world network.
Based on informal individual knowledge transfer theory, a model of knowledge transfer within business incubator individual knowledge network is established. Adopting matlab7.3software, effects of network characteristics on network knowledge transfer are explored using simulation experiment method. The results show that knowledge transfer achieves the best performance when the network formed small world network structure. The greater average degree of nodes, the better knowledge transfer performance. The higher knowlege transfer threshold, the better knowledge transfer performance. The more proportion of experts as well as more balanced distribution of experts on knowledge type, the better knowledge transfer performance. The stronger absorptive capacity of nodes, the better knowledge transfer performance. Meanwhile, effects of entrepreneurs'ego-centric network on its knowledge transfer are also explored. The results show that greater size, low density and high diversity ego-centric network can facilitate entrepreneurs'knowledge transfer.
Based on organizational influence theory, the paper defines influence of a node on network knowledge transfer as its knowledge status in the network that can be measured by influence index of the node. The knowledge transfer activities within the network and their weights are identified. The method for measuring influences of nodes on network knowledge transfer are proposed. In order to explore the influences of nodes on subgroups, the network is divided into five non-overlapping subgroups that including knowledge coordination group, knowledge source group, start-up stage incubatee group, growing stage incubatee group and mature stage incubatee group. The method for calculating influence index of nodes on subgroups is given.
This paper studies knowledge transfer dynamic behaviors within business incubator knowledge network using system dynamic theory. Based on analysis of influence factors on knowledge transfer within business incubator knowledge network, a system dynamic model of knowledge transfer within the network is established. Using Vensim simulation software platform and adopting theory test method, the effectiveness of the model is verified. The results indicate that the model is quite well able to depict the actual knowledge transfer dynamic behavior within the business incubator knowledge network. Besides this, the paper also explores control parameters for improving knowledge transfer behaviors within the network. The influences of the control parameters on knowledge transfer behaviors within the network is simulated respectively.
Based on above results, the paper proposes strategies to promote knowledge transfer within business incubator knowledge network for government agency, business incubator and incubatee.
引文
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