基于知识型服务机构嵌入视角的产业集群升级机制研究
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摘要
当前,经济、技术等全球化热潮风起云涌,全球化正深刻地改变着世界经济的版图,催生和加快了中国经济的崛起。对于外向型经济较为突出的浙江省而言,从家庭作坊、合伙企业起步,形成了具有比较优势的产业集群和专业化产业区,以“一乡一品、一县一业”为特征的块状特色经济已成为浙江经济的一大亮点。然而,经历20多年的发展壮大,浙江省的大多数产业集群,仍然徘徊在全球价值链的低端,技术附加值不高、生产技术较为落后、品牌价值不高成为制约集群发展的主要问题。目前的迫切任务是加速推进产业集群从“代工者”到“合作者”再到“竞争者”动态提升,最终实现集群升级。
本文在回顾、梳理集群升级相关文献的基础上,将集群升级研究归纳为“外源化”和“地域化”两大研究视角。考虑到集群升级的外部动力首先是通过影响和改变集群内部状态,激发内部动力,最终导致集群升级的,从而确立“地域化”研究视角作为本文研究的主要出发点。其次,通过借鉴集群发展的集群演化理论、集群竞争力理论以及现有的外部价值链升级理论,揭示了集群地域化升级的两大动力要素和一表征要素,分别为网络结构、知识行为与知识结构。结合集群实践以及知识型服务机构的相关理论研究,本文分析认为知识型服务机构这一集群重要节点对产业集群升级三要素都有直接影响,从而确立了以基于知识型服务机构嵌入视角的产业集群升级机制为本文研究的主要命题。
通过构筑“知识型服务机构嵌入——网络结构——集群升级”的概念模型,本文分别对两阶段模型即“知识型服务机构嵌入——网络结构”、“网络结构——知识行为——集群升级”进行深入理论分析,揭示了知识型服务机构嵌入对产业集群升级的作用机制。在此基础上,对来自浙江省19个不同集群797家企业与企业、企业与知识型服务机构间2年、3年甚至是4年间相互关系的考察,本文分别结合整体网络演进分析以及集群层面的统计分析研究,从实证角度验证了知识型服务机构嵌入通过影响网络结构,进而网络结构通过影响集群知识行为,最终影响集群升级的作用机制,并据此为集群升级实践提出了相应的政策建议。
基于以上研究论证工作,本文主要得出以下主要结论:(1)从地域化视角出发对产业集群升级进行研究是剖析集群升级内生动力的根本途径,集群升级的外部动力需要通过激发内部动力导致集群升级;(2)集群升级的本质是集群内部知识结构的强化、更新和重构,知识结构的衰退、更新表征了集群工艺流程和产品升级,而知识结构的跃迁、稳固表征了集群功能升级;(3)产业集群地域化升级的关键路径之一是知识型服务机构在集群网络中的有效嵌入,知识型服务机构嵌入通过改变集群网络结构进而影响集群知识行为和知识结构,最终推动集群升级;(4)知识型服务机构嵌入可以运用“关系与结构”分析方法进行全面的刻画,社会网分析方法可以用来对此进行较好的分析;(5)知识型服务机构嵌入对网络结构的影响主要通过知识桥梁功能实现,不同类型知识桥梁对网络结构影响的侧重点也各不相同;(6)知识型服务机构嵌入集群的程度受到其与集群原有技术更新速度和知识势差两方面因素的影响,因而在设计知识型服务机构引进和培育机制时需要考虑到集群现有特征;(7)作为本研究的前提,服务于产业集群的知识型服务机构归纳为16种,分为两大类,进一步细分为四小类。
与产业集群升级领域已有的研究成果相比,本研究的创新和发展主要体现在以下几个方面:
(1)对集群升级的现有研究大多滞留在借助外部价值链分析工具的反复案例实证研究上,而忽视了集群升级本身的内涵、动力因素等基本问题的界定。尤其是现有研究更多局限于外部拉动的集群升级而缺乏从集群内部探究升级机制的研究。本文在综述得到集群升级三大关键要素的基础上,界定了产业集群的内涵、类型,进而通过三要素与集群升级类型的深入剖析,揭示了集群升级内在机理,为理解和研究集群升级机理提供了一个研究框架
(2)知识型服务机构作为集群网络中一类特殊的结点,对于集群升级有着难以估量的重要意义,遗憾的是,迄今为止这方面还缺乏专门的、比较深入的研究。在集群升级研究框架内,本文通过构建二阶段模型,从知识型服务机构视角深入分析了产业集群升级机制。其中,第一阶段模型重点考察知识型服务机构如何嵌入以及嵌入对网络结构的影响问题,第二阶段模型则侧重分析网络结构、知识行为这两大关键动力要素与集群升级的关系。
(3)现有集群研究往往以群内企业代替整体集群研究,对于集群升级研究则多以静态理论分析和状态性的案例描述为主。本研究通过引入近七年的整体网演进的案例分析,从集群整体网络以及动态演进层面,用三个结构变量直观刻画出了集群整体网络结构随知识型服务机构嵌入的变化过程,并通过考察这些具体结构变量的变化情况,结合第二阶段的实证研究,描绘出了知识型服务机构嵌入影响网络结构,进而通过知识行为影响产业集群升级的作用机理。
Nowadays, the globalization of economy and technology is actively and profoundly changing the territory of world economy, while boosting the growth of China's economy. As an export-oriented economy, Zhejiang Province, starting with family workshops and partnerships, has formed industrial clusters and specialized industrial regions with comparative advantages. Agglomerative economy has become a prominent characteristic of Zhejiang economy. However, after 20 years of development, most industrial clusters in Zhejiang province are still wandering at the bottom of global value chain. It becomes a constraint restricting the development of industrial clusters that the products are of low added value for lagging in technology and brand. The most exigent task confronted by the industrial clusters is to realize the upgrading from the role of "foundry" to that of "collaborator", and then to "competitor".
After a review of related work, this dissertation categorizes the upgrading research of industrial clusters into two major viewpoints, i.e. "GVC" and "localization" viewpoints. Regarding that the external impetus of upgrading firstly influences and changes the internal state of clusters to activate internal momentum and ultimately results in cluster upgrading, we establish the "localized" viewpoint. Secondly, by referring to the theory of cluster evolution, theory of cluster competitive advantage and upgrading theory of external value chain, we discover the two major impetuses and one representative factor for cluster localized upgrading, i.e. network structure, knowledge behavior and knowledge structure. Incorporating the cluster practice and the related theoretical achievements on Knowledge-intensive Services(KIBS), we analyze and consider that KIBS plays an essential role during the process of cluster upgrading, therefore establish KIBS embedding viewpoint towards industrial cluster upgrading.
By constructing the concept model of "Embedding of KIBS—Network Structure—Cluster Upgrading", this dissertation explores the two-phase model, i.e. one from Embedding of KIBS to Network Structure and the other from Network Structure to Cluster Upgrading respectively, and then reveals the impacting mechanism of KIBS embedding towards upgrading of industrial clusters. We investigated 797 enterprises within 19 different industrial clusters on the relationships between enterprise and enterprise, enterprise and KIBS during 2 years, 3 years and even 4 years. This dissertation combines the evolving analysis of overall network and the statistical analysis on the level of industrial clusters, verifies the impact of KIBS' embedding towards the network structure, then subsequently towards the knowledge behavior of clusters and finally towards the upgrading of industrial clusters, based on which we make policy proposals.
This dissertation makes the following conclusions based on the theoretical analysis and empirical study above. (1) It is an intrinsic approach to analyzing the internal motives of industrial cluster upgrading from a viewpoint of localization. The external motives of cluster upgrading achieve results by activating the internal motives. (2) The nature of cluster upgrading is the intensification, updating and reconstruction of internal knowledge structure within the clusters. The degradation and renewal of knowledge structure represent the process and product upgrading of clusters, while the transition and stabilization of knowledge structure represent the functional upgrading of clusters. (3) One of the essential paths to cluster upgrading is effective embedding of KIBS into cluster networks. The embedding of KIBS influences the knowledge behaviors and knowledge structures by changing the networking structure of clusters and consequently promotes the upgrading. (4) The embedding of KIBS can be depicted by analysis methods of relation and structure, which can be modeled by social networking analysis (SNA). (5) The impact of KIBS embedding on network structure is mainly realized through the function of Knowledge Bridge. Different types of knowledge bridges have different points of focus towards impact on network structure. (6) The embedding degree of KIBS is affected by the gap of knowledge potential and technical upgrading velocity between KIBS and member firms. Therefore in the design of cluster upgrading mechanism, the internal characteristics of the industrial cluster need to be taken into account. (7) The KIBS serving industrial clusters has 16 classes, which can be divided into two major categories and further divided into four subdivisions.
Compared with existing research results in the domain of cluster upgrading, the novelties of this dissertation are as follows.
(1) Existing research on cluster upgrading was mostly stuck to the repetitive case studies by the analysis tools of GVC, but neglects the definition of connotation and motive factors of upgrading within the clusters. Especially, the existing studies are lack of exploration into internal upgrading mechanism within clusters. On a basis of defining the connotation and categorization of cluster upgrading, we reveal the internal upgrading mechanism of clusters and provide a novel viewpoint for understanding and studying cluster upgrading mechanisms, by illustrating three key upgrading factors and one impacting mechanism of upgrading types.
(2) As a group of special nodes within cluster networks, KIBS has a significant impact on cluster upgrading. However, there is still a lack of such specialized and profound research on this topic. By constructing a two-phase model, we analyze the mechanism of cluster upgrading from a viewpoint of KIBS. The model of first phase puts an emphasis on the inspection how KIBS is embedded and the impact which the embedding of KIBS makes on the network structure. In the second phase our model mainly focuses on the analysis of the relationship between the decisive motive factors, i.e. network structure and knowledge behavior, and the upgrading of clusters.
(3) The literature mainly focuses on theoretical analysis and case descriptions, while we depict the evolving process of network structure with the embedding of KIBS with three structural variables based on an empirical study of overall network evolution during a period of seven years. By inspecting the transformation of these structural variables, and integrating the real case study of the second phase, we describe the mechanism by which the embedding of KIBS influences the network structure and subsequently influences the upgrading of industrial clusters through knowledge behaviors.
本文在回顾、梳理集群升级相关文献的基础上,将集群升级研究归纳为“外源化”和“地域化”两大研究视角。考虑到集群升级的外部动力首先是通过影响和改变集群内部状态,激发内部动力,最终导致集群升级的,从而确立“地域化”研究视角作为本文研究的主要出发点。其次,通过借鉴集群发展的集群演化理论、集群竞争力理论以及现有的外部价值链升级理论,揭示了集群地域化升级的两大动力要素和一表征要素,分别为网络结构、知识行为与知识结构。结合集群实践以及知识型服务机构的相关理论研究,本文分析认为知识型服务机构这一集群重要节点对产业集群升级三要素都有直接影响,从而确立了以基于知识型服务机构嵌入视角的产业集群升级机制为本文研究的主要命题。
通过构筑“知识型服务机构嵌入——网络结构——集群升级”的概念模型,本文分别对两阶段模型即“知识型服务机构嵌入——网络结构”、“网络结构——知识行为——集群升级”进行深入理论分析,揭示了知识型服务机构嵌入对产业集群升级的作用机制。在此基础上,对来自浙江省19个不同集群797家企业与企业、企业与知识型服务机构间2年、3年甚至是4年间相互关系的考察,本文分别结合整体网络演进分析以及集群层面的统计分析研究,从实证角度验证了知识型服务机构嵌入通过影响网络结构,进而网络结构通过影响集群知识行为,最终影响集群升级的作用机制,并据此为集群升级实践提出了相应的政策建议。
基于以上研究论证工作,本文主要得出以下主要结论:(1)从地域化视角出发对产业集群升级进行研究是剖析集群升级内生动力的根本途径,集群升级的外部动力需要通过激发内部动力导致集群升级;(2)集群升级的本质是集群内部知识结构的强化、更新和重构,知识结构的衰退、更新表征了集群工艺流程和产品升级,而知识结构的跃迁、稳固表征了集群功能升级;(3)产业集群地域化升级的关键路径之一是知识型服务机构在集群网络中的有效嵌入,知识型服务机构嵌入通过改变集群网络结构进而影响集群知识行为和知识结构,最终推动集群升级;(4)知识型服务机构嵌入可以运用“关系与结构”分析方法进行全面的刻画,社会网分析方法可以用来对此进行较好的分析;(5)知识型服务机构嵌入对网络结构的影响主要通过知识桥梁功能实现,不同类型知识桥梁对网络结构影响的侧重点也各不相同;(6)知识型服务机构嵌入集群的程度受到其与集群原有技术更新速度和知识势差两方面因素的影响,因而在设计知识型服务机构引进和培育机制时需要考虑到集群现有特征;(7)作为本研究的前提,服务于产业集群的知识型服务机构归纳为16种,分为两大类,进一步细分为四小类。
与产业集群升级领域已有的研究成果相比,本研究的创新和发展主要体现在以下几个方面:
(1)对集群升级的现有研究大多滞留在借助外部价值链分析工具的反复案例实证研究上,而忽视了集群升级本身的内涵、动力因素等基本问题的界定。尤其是现有研究更多局限于外部拉动的集群升级而缺乏从集群内部探究升级机制的研究。本文在综述得到集群升级三大关键要素的基础上,界定了产业集群的内涵、类型,进而通过三要素与集群升级类型的深入剖析,揭示了集群升级内在机理,为理解和研究集群升级机理提供了一个研究框架
(2)知识型服务机构作为集群网络中一类特殊的结点,对于集群升级有着难以估量的重要意义,遗憾的是,迄今为止这方面还缺乏专门的、比较深入的研究。在集群升级研究框架内,本文通过构建二阶段模型,从知识型服务机构视角深入分析了产业集群升级机制。其中,第一阶段模型重点考察知识型服务机构如何嵌入以及嵌入对网络结构的影响问题,第二阶段模型则侧重分析网络结构、知识行为这两大关键动力要素与集群升级的关系。
(3)现有集群研究往往以群内企业代替整体集群研究,对于集群升级研究则多以静态理论分析和状态性的案例描述为主。本研究通过引入近七年的整体网演进的案例分析,从集群整体网络以及动态演进层面,用三个结构变量直观刻画出了集群整体网络结构随知识型服务机构嵌入的变化过程,并通过考察这些具体结构变量的变化情况,结合第二阶段的实证研究,描绘出了知识型服务机构嵌入影响网络结构,进而通过知识行为影响产业集群升级的作用机理。
Nowadays, the globalization of economy and technology is actively and profoundly changing the territory of world economy, while boosting the growth of China's economy. As an export-oriented economy, Zhejiang Province, starting with family workshops and partnerships, has formed industrial clusters and specialized industrial regions with comparative advantages. Agglomerative economy has become a prominent characteristic of Zhejiang economy. However, after 20 years of development, most industrial clusters in Zhejiang province are still wandering at the bottom of global value chain. It becomes a constraint restricting the development of industrial clusters that the products are of low added value for lagging in technology and brand. The most exigent task confronted by the industrial clusters is to realize the upgrading from the role of "foundry" to that of "collaborator", and then to "competitor".
After a review of related work, this dissertation categorizes the upgrading research of industrial clusters into two major viewpoints, i.e. "GVC" and "localization" viewpoints. Regarding that the external impetus of upgrading firstly influences and changes the internal state of clusters to activate internal momentum and ultimately results in cluster upgrading, we establish the "localized" viewpoint. Secondly, by referring to the theory of cluster evolution, theory of cluster competitive advantage and upgrading theory of external value chain, we discover the two major impetuses and one representative factor for cluster localized upgrading, i.e. network structure, knowledge behavior and knowledge structure. Incorporating the cluster practice and the related theoretical achievements on Knowledge-intensive Services(KIBS), we analyze and consider that KIBS plays an essential role during the process of cluster upgrading, therefore establish KIBS embedding viewpoint towards industrial cluster upgrading.
By constructing the concept model of "Embedding of KIBS—Network Structure—Cluster Upgrading", this dissertation explores the two-phase model, i.e. one from Embedding of KIBS to Network Structure and the other from Network Structure to Cluster Upgrading respectively, and then reveals the impacting mechanism of KIBS embedding towards upgrading of industrial clusters. We investigated 797 enterprises within 19 different industrial clusters on the relationships between enterprise and enterprise, enterprise and KIBS during 2 years, 3 years and even 4 years. This dissertation combines the evolving analysis of overall network and the statistical analysis on the level of industrial clusters, verifies the impact of KIBS' embedding towards the network structure, then subsequently towards the knowledge behavior of clusters and finally towards the upgrading of industrial clusters, based on which we make policy proposals.
This dissertation makes the following conclusions based on the theoretical analysis and empirical study above. (1) It is an intrinsic approach to analyzing the internal motives of industrial cluster upgrading from a viewpoint of localization. The external motives of cluster upgrading achieve results by activating the internal motives. (2) The nature of cluster upgrading is the intensification, updating and reconstruction of internal knowledge structure within the clusters. The degradation and renewal of knowledge structure represent the process and product upgrading of clusters, while the transition and stabilization of knowledge structure represent the functional upgrading of clusters. (3) One of the essential paths to cluster upgrading is effective embedding of KIBS into cluster networks. The embedding of KIBS influences the knowledge behaviors and knowledge structures by changing the networking structure of clusters and consequently promotes the upgrading. (4) The embedding of KIBS can be depicted by analysis methods of relation and structure, which can be modeled by social networking analysis (SNA). (5) The impact of KIBS embedding on network structure is mainly realized through the function of Knowledge Bridge. Different types of knowledge bridges have different points of focus towards impact on network structure. (6) The embedding degree of KIBS is affected by the gap of knowledge potential and technical upgrading velocity between KIBS and member firms. Therefore in the design of cluster upgrading mechanism, the internal characteristics of the industrial cluster need to be taken into account. (7) The KIBS serving industrial clusters has 16 classes, which can be divided into two major categories and further divided into four subdivisions.
Compared with existing research results in the domain of cluster upgrading, the novelties of this dissertation are as follows.
(1) Existing research on cluster upgrading was mostly stuck to the repetitive case studies by the analysis tools of GVC, but neglects the definition of connotation and motive factors of upgrading within the clusters. Especially, the existing studies are lack of exploration into internal upgrading mechanism within clusters. On a basis of defining the connotation and categorization of cluster upgrading, we reveal the internal upgrading mechanism of clusters and provide a novel viewpoint for understanding and studying cluster upgrading mechanisms, by illustrating three key upgrading factors and one impacting mechanism of upgrading types.
(2) As a group of special nodes within cluster networks, KIBS has a significant impact on cluster upgrading. However, there is still a lack of such specialized and profound research on this topic. By constructing a two-phase model, we analyze the mechanism of cluster upgrading from a viewpoint of KIBS. The model of first phase puts an emphasis on the inspection how KIBS is embedded and the impact which the embedding of KIBS makes on the network structure. In the second phase our model mainly focuses on the analysis of the relationship between the decisive motive factors, i.e. network structure and knowledge behavior, and the upgrading of clusters.
(3) The literature mainly focuses on theoretical analysis and case descriptions, while we depict the evolving process of network structure with the embedding of KIBS with three structural variables based on an empirical study of overall network evolution during a period of seven years. By inspecting the transformation of these structural variables, and integrating the real case study of the second phase, we describe the mechanism by which the embedding of KIBS influences the network structure and subsequently influences the upgrading of industrial clusters through knowledge behaviors.
引文
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