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论文编号：	14415
作者编号：	1120180928
上传时间：	2023/12/15 12:03:51
中文题目：	双重网络度同配度对企业创新绩效的影响研究
英文题目：	Research on the Influence of Degree Assortativity of Dual Network on Innovation Performance of Firm
指导老师：	林润辉
中文关键字：	合作网络度同配度；知识网络度同配度；双重网络度同配度交互；创新数量；创新质量
英文关键字：	Degree Assortativity of Cooperative Network; Degree Assortativity of Knowledge Network; Interaction Effect of Degree Assortativity of Dual Network; Innovation Quantity; Innovation Quality
中文摘要：	企业如何权衡通过提高创新效率来为其带来持续盈利还是通过实质性创新来提高创新质量，从而为其带来持久竞争力，是企业面临的关键问题。在企业创新实践中，企业的创新绩效不仅受企业内部发明人合作网络影响，还与由知识元素组成的知识网络息息相关。双重网络度同配度，即发明人合作网络中发明人如何合作、与谁合作等和知识元素与哪些知识元素组合对创新绩效会产生差异化的影响。因此，在高质量发展的新阶段，如何构建合作网络中发明人间的连接机制和优化知识网络中知识元素间的组合方面来实现创新的提质增效成为学术界和企业界关心的核心议题。现有学者仅从中心性、结构洞等个体结构属性与网络密度、集聚系数等整体网络结构属性研究了双重网络及其互动对创新绩效的影响，也研究了网络同配度的结构特征、演化等方面研究，即网络表现出来的同配度结构特征如何，如何演化等问题，但尚未对双重网络中发明人与知识元素的匹配模式，即网络度同配度，及其交互效应是如何影响企业创新绩效这一问题进行深入研究。 本研究结合知识基础观、社会网络理论和创新理论，从“量”和“质”角度拆分企业创新绩效为创新数量与创新质量，来探究双重网络度同配度对企业创新绩效的影响。首先，在明晰网络度同配度的概念、内涵、测度与拓扑结构的基础上，将企业创新绩效分为创新数量和创新质量两个维度，分析合作网络度同配度对创新绩效的影响。同时，考虑到知识网络与合作网络存在结构同型性以及对创新绩效的重要性，本文又考察了知识网络度同配度对创新绩效的影响。此外，合作网络与知识网络并不是完全独立的，而是存在网络间效应，因此，进一步地，本文从多重网络嵌入视角，检验了双重网络度同配度交互与创新绩效间的关系。基于以上目标，本研究以2011-2019年我国计算机通信及设备制造业上市公司为研究样本，对上述假设进行实证检验，基于实证结果，本文的主要发现和结论如下： 第一，典型企业A的发明人合作网络中，具有比较大的群体划分，更多情况下是明星发明人喜欢一起合作或非明星发明人一起合作，影响力不同的发明人之间合作较少；典型企业B合作网络经历了异配网络-同配网络-异配网络的转变，可能的原因在于企业为了平衡企业创新数量与创新质量，其创新战略经历了较大的调整。典型企业A的知识网络中，存在着多个度值高的知识元素，说明企业有其专注和擅长的领域，通过度值低的知识元素与度值高的知识元素进行组合，利用现有已经熟练掌握的知识元素去理解不太熟悉的知识元素，既有知识组合潜力，又可以提升创新效率，企业不断发展其核心技术领域，使其在核心技术领域保持市场竞争力；在典型企业B的知识网络中，企业倾向于将已经熟练掌握的知识元素进行组合或者将不太熟悉的知识元素进行组合去寻求可能的创新机会，更多的可能是为了提升企业创新质量。 第二，合作网络度同配度正向促进企业创新数量，负向影响创新质量。也就是说，度值高的发明人或度值低的发明人之间合作研发，更能促进企业创新数量，度值高的发明人与度值低的发明人合作研发，更有助于创新质量提升。同时，考虑到知识元素特征的重要性，本研究探究了知识复杂性与知识多样性的调节作用，研究结果表明知识复杂性弱化合作网络度同配度对创新数量的正向影响，同时，弱化合作网络度同配度对创新质量间的负向影响；知识多样性削弱合作网络度同配度对创新质量的负向影响。 第三，知识网络度同配度降低了企业创新数量，增强了企业创新质量，也就是说，度值高的知识元素与度值低的知识元素组合可以帮助企业提升创新数量，度值高的知识元素或度值低的知识元素组合更能提升企业创新质量。此外，本研究还探索了外部研发合作的调节效应，结果发现产学研合作减弱知识网络度同配度对创新数量的负向影响，同时，增强知识网络度同配度对创新质量的正向影响；企-企合作降低知识网络度同配度对创新质量的正向影响。 第四，知识网络度同配度削弱合作网络度同配度对创新数量的正向关系，也就是说，在度值高的发明人与度值低的发明人进行合作研发时，度值高的知识元素与度值低的知识元素组合对提升创新数量起到的积极作用要强于当度值高的发明人或度值低的发明人相互合作，并且度值高的知识元素或度值低的知识元素相互组合时对创新数量的影响。同时，知识网络最大凝聚子群规模增强合作网络度同配度对创新数量的正向影响；知识网络标准化熵削弱合作网络度同配度对创新数量的正向影响，同时，增强合作网络度同配度对创新质量的负向影响。 本文的研究创新点主要包括以下四个方面。第一，本文聚焦于企业层面，考虑了发明人合作网络/知识网络中发明人/知识元素间的连接机制，解构了双重网络度同配度的拓扑结构，并探寻其随时间变化规律。第二，从合作网络结构属性出发，探究了合作网络度同配度影响创新绩效的知识情境条件，完善了社会网络理论。第三，区分知识网络度同配度与合作网络度同配度之间的差异，并探究其与创新绩效间的关系，为知识网络相关结构特征研究提供了新的素材，对于知识与创新绩效间关系提供了新的理论阐释。第四，从多重网络嵌入视角揭示双重网络度同配度与创新绩效的关系，是对从单一网络研究其之间关系的升华。 本文在理论上，第一，理清了双重网络度同配度的概念、内涵与测度，拓展了网络度同配度拓扑结构分析，对深入了解网络度同配度的拓扑结构特征提供了理论参考，同时为后续网络度同配性的实证与案例研究提供理论基础。第二，在验证现有研究对合作网络度同配度与创新数量和创新质量判断的基础上，考虑了知识复杂性和知识多样性的情境因素，进一步扩展了现有研究成果。第三，发现了知识网络度同配度对创新数量与创新质量的异质性影响，并强调了外部研发合作的重要性，深化了社会网络理论中知识网络与创新绩效关系的研究。第四，本文研究从多重网络嵌入视角剖析了双重网络度同配度交互对创新绩效影响，本研究结论丰富了基于多重网络嵌入视角来分析创新绩效提升的机制研究，为探索网络间效应提供新的理论支撑。同时，在实践上，本文在优化合作网络与知识网络决策，通过双重网络度同配度提升创新绩效，加强内部知识管理，外部合作模式选择，制定基于双重网络度同配度互动协同的创新策略，促进国家高质量发展等方面均有实践借鉴意义。
英文摘要：	How to balance between improving innovation efficiency to bring sustainable profits and improving innovation quality through substantive innovation is a key issue for enterprises. In the practice of enterprise innovation, the innovation performance of enterprises is not only affected by the cooperative network of inventors, but also closely related to the knowledge network composed of knowledge elements. Degree assortativity of dual network have differentiated effects on innovation performance. Therefore, in the new stage of high-quality development, how to construct the connection mechanism between inventors in the cooperation network and optimize the combination of knowledge elements in the knowledge network to improve quality and efficiency of innovation has become the core issue concerned by the academic and business circles. Existing scholars have studied the influence of dual networks and their interaction on innovation performance by individual structural attributes such as centrality, structural hole and overall structural attributes such as network density and clustering coefficient. The structural characteristics and evolution of network assortativity have also been studied, but how degree assortativity of dual networks and its interaction effect affect the innovation performance of enterprises has not been thoroughly studied. This study combines knowledge base view, social network theory and innovation theory, and divides enterprise innovation performance into innovation quantity and innovation quality from the perspective of “quantity” and “quality”, so as to explore the influence of degree assortativity of dual network on enterprise innovation performance. First of all, on the basis of explaining the concept, connotation, measurement and topological structure of degree assortativity of network, this dissertation divides enterprise innovation performance into innovation quantity and innovation quality, and analyzes the influence of degree assortativity of cooperative network on innovation performance. At the same time, considering homogeneity of knowledge network and cooperation network and its importance to innovation performance, we also examines the influence of degree assortativity of knowledge network on innovation performance. In addition, previous scholars have also proved that cooperation network and knowledge network are not completely independent, but there are inter-network effects. Therefore, from the perspective of multiple network embeddedness, the dissertation tests the relationship between the interaction of degree assortativity of dual networks and innovation performance. Based on the above objectives, this study takes Chinese listed companies in the computer communication and equipment manufacturing industry from 2011 to 2019 as research samples to test the above hypothesis. Based on the empirical results, the main findings and conclusions of this dissertation are as follows: First, in the inventor cooperation network of typical enterprise A, there is a large group division. In most cases, star inventors like to cooperate with each other or non-star inventors cooperate with each other, and there is less cooperation between inventors with different influences. The cooperation network of typical enterprise B has experienced the transformation from assortative mixing to disassortative mixing to assortative mixing. The possible reason is that the innovation strategy of the enterprise has undergone great adjustment in order to balance the quantity and quality of innovation. In the knowledge network of typical enterprise A, there are multiple knowledge elements with high degree value, indicating that the enterprise is focused on and good at specific fields. Combining knowledge elements with low degree value and knowledge elements with high degree value, using the knowledge elements already mastered to understand knowledge elements less familiar, which not only has the potential of knowledge combination, but also can improve innovation efficiency. The enterprise continuously develops its core technology field, so that it can maintain market competitiveness in the core technology field. In the knowledge network of typical enterprise B, the enterprise tends to combine the knowledge elements it has mastered or the knowledge elements it is not familiar with to seek for possible innovation opportunities, which more likely to improve the quality of innovation. Second, the dissertation finds that degree assortativity of cooperative network can positively promote quantity of innovation and negatively affect quality of innovation. That is to say, R&D cooperation between inventors with high degree or inventors with low degree can better promote innovation quantity of enterprises, while R&D cooperation between inventors with high degree and inventors with low degree is more conducive to improvement of innovation quality. At the same time, considering the importance of knowledge element characteristics, this study explores the moderating effect of knowledge complexity and knowledge diversity. The results show that knowledge complexity weakens positive effect of degree assortativity of cooperative network on innovation quantity, and weakens negative effect of degree assortativity of cooperative network on innovation quality. Knowledge diversity weakens negative influence of degree assortativity of cooperative network on innovation quality. Third, the research results show that degree assortativity of knowledge network reduces innovation quantity of enterprises and enhances innovation quality of enterprises. In other words, the combination of knowledge elements with high degree and low degree can help enterprises improve the innovation quantity. The combination of knowledge elements with high degree value or low degree value can improve quality of enterprise innovation. In addition, this study also explores moderating effect of external R&D cooperation. The results show that academic collaboration weakens negative effect of degree assortativity of knowledge network on innovation quantity, while strengthens positive effect of degree assortativity of knowledge network on innovation quality. Industry collaboration reduces positive influence of degree assortativity of knowledge network on innovation quality. Fourth, the results of this study show that positive relationship between degree assortativity of cooperative network and innovation quantity is weakened by the degree assortativity of knowledge network. That is to say, when inventors with high degree and inventors with a low degree cooperate in R&D, combination of knowledge elements with high degree and knowledge elements with low degree plays a stronger positive role in improving quantity of innovation than cooperation between inventors with high degree or inventors with low degree, and combination of knowledge elements with high degree or low degree. At the same time, considering the importance of clustering of knowledge network, this dissertation introduces giant and standardized entropy from cooperative network to knowledge network, and interaction effect of degree assortativity of cooperative network and giant and standardized entropy of knowledge network is further discussed. It is found that giant of knowledge network enhances the positive influence of degree assortativity of cooperative network on quantity of innovation. Knowledge network standardized entropy weakens positive effect of degree assortativity of cooperative network on innovation quantity, and strengthens negative effect of degree assortativity of cooperative network on innovation quality. The innovation points of this dissertation mainly include the following four aspects. First, this dissertation considers the connection mechanism between inventors/knowledge elements in inventor cooperation network/knowledge network, deconstructs the topology structure of degree assortativity of dual network. Second, starting from structural attributes of cooperative network, the dissertation explores situational conditions of influence of degree assortativity of cooperative network on innovation performance, and enrich social network theory. Third, this dissertation distinguishes difference between degree assortativity of cooperative network and knowledge network, and explores relationship between degree assortativity of knowledge network and innovation performance, providing new materials for study of related structural characteristics of knowledge network, and providing a new theoretical interpretation of relationship between knowledge and innovation performance. Fourth, from perspective of multiple network embeddedness, relationship between degree assortativity of dual network and innovation performance is revealed, which is an extension of the research on the relationship between single network and innovation performance. The theoretical contribution of this dissertation is as follows. First, it expands the topological structure analysis of degree assortativity of network, provides theoretical reference for in-depth understanding of topological structure characteristics of degree assortativity of network, and provides theoretical basis for subsequent empirical and case studies of degree assortativity of network. Second, on the basis of verifying the existing research’s judgment on degree assortativity of cooperative network and quantity and quality of innovation, we further extend existing research results by considering situational factors of knowledge complexity and knowledge diversity. Third, we study influence of degree assortativity of knowledge network on innovation quantity and quality, emphasize importance of external R&D cooperation, and deepen research on relationship between knowledge network and innovation performance in social network theory. Fourth, from perspective of multiple network embedding, this dissertation analyzes influence of interaction effect of degree assortativity of dual network on innovation performance. The conclusion of this study enriches the research on mechanism of analyzing innovation performance improvement based on multiple network embedding, and provides new theoretical support for exploring inter-network effect. At the same time, in practice, this dissertation has practical significance in optimizing decision-making of cooperation network and knowledge network, improving innovation performance through degree assortativity of dual network, strengthening internal knowledge management, choosing modes of external cooperation, developing interactive and collaborative innovation strategies based on degree assortativity of dual network, and promoting high-quality national development.
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