Research On Firm Complex Netwrok Relationship:From The Perspective Of Industry Chain

To enhance the stability and competitiveness of the industrial chain supply chain and improve the ability of enterprise of supply chain management has become an important stragic to enhance the independent controllable ability of the industrial chain supply chain in our country.However,the global spread of COVID-19 epidemic and the local “rise” of “anti-globalization” have further increased the operational risk of Chinese industrial chain supply chain.As the industrial chain supply chain is a networked organization,the impact of an enterprise or a link will quickly spread to the whole system.Therefore,to enhance the resilience of Chinese industrial chain supply chain,increase the flexibility of supply chain of core enterprise,reduce the dependence of “sticking neck” nodes,based on the framework of complex network,this dissertation clarifies the dependence structure,key nodes and action mechanism of enterprises among the industrial chain supply chain,and then discusses the impact of network structure characteristics on enterprise operation management and financial management,optimizing the enterprise management strategy has important theoretical significance and application value.Based on the above analysis,this dissertation chooses the research topic of“Research on Firm Complex Netwrok Relationship: From the Perspective of Industry Chain”,adopts the multi-disciplinary knowledge such as management,economics,finance and complex network,and adopts a research paradigm that combination of theoretical hypothesis,model development and empirical testing,based on the research idea of “depicting network structure-clarifying network relationship-exploring financial performance”.First of all,a dependency network based on financial returns is constructed to describe the dependence structure of enterprises in 5G industry.Next,a dependency network based on financial risk spillover is constructed to describe the dependence structure among enterprises in new energy vehicles industry.Finally,a dependency network scheme based on joint investment behavior is constructed to explore the dependence structure among enterprises in the electronic manufacturing industry and its impact on the financial performance of enterprises.The specific work and main innovations of this dissertation are as follows:Firstly,the complex network relationship of enterprises in the industrial chain based on returns dependence is studied,and an industrial chain network model based on Copula is proposed,which realizes the effective description of the dependence relationship between enterprises in the case of 5G industrial chain.Inspired by the resource dependence theory,the financial returns dependence of enterprises in the industrial chain is very important for enterprise financial management and operation management.However,how to effectively describe the interdependence mechanism between enterprises needs to solve the two problems of financial return correlation measurement and complex relationship construction at the same time.Therefore,based on the complex network framework,this dissertation first measures the financial returns dependence among enterprises through Copula as the link matrix,and then takes a single enterprise as a node,uses the TMFG algorithm to construct the dependence network in the industrial chain,and measures the different network structure characteristics for each enterprise.At the end of this paper,the network construction method based on return dependence is applied to the 5G industrial chain,the results show that the dependence characteristics of different firms are heterogeneous,most of firms are highly related to the members of the whole industry chain,a few firms are weakly connected,and the firms with strong ties are usually in the midstream of the industry chain.In addition,as for the upstream,midstream and downstream firms,the downstream firms usually have closer dependence and stronger influence.Secondly,the complex network relationship of enterprises in the industrial chain based on risk dependence is studied,and an industrial chain network model based on Co Va R is proposed,which realizes the effective description of the dependence relationship between enterprises in the case of new energy vehicles industrial chain.In the information correlation generated by the financial market,in addition to the selected financial return correlation,there is also a typical information correlation behavior-the spillover effect of financial risk.Therefore,the construction of financial dependence network based on the perspective of financial risk spillover effect is one of the effective ways to clarify the complex network relationship of enterprises in the industrial chain.Considering the basic impact of macro-economy on industrial operation,this dissertation first combines Co Va R with TMFG algorithm to propose the tail dependence network of enterprises in the industrial chain based on risk spillover effect.Finally,this dissertation applies the network construction method based on risk spillover effect to the new energy vehicle industry chain,analyzes the topological structure of the acquired dependent network,and finds out the structural characteristics of each enterprise in the whole industry chain and its different levels.The empirical results show that the degree of dependence and influence of different firms are various in the whole industry chain.In particular,upstream firms have a higher degree of dependence at all levels.Thirdly,the complex network relationship of enterprises in the industrial chain based on joint investment behavior is studied,and an industrial chain network model based on joint investment behavior is proposed,which realizes the effective description of the complex network relationship between enterprises in the case of electronic manufacturing industry chain,it is found that the characteristics of network structure can effectively improve the financial performance of enterprises.This dissertation takes the joint investment relationship between the electronic communication manufacturing industry and the financial service industry as the research object,constructs the financial supply chain network through the TMFG algorithm,and discusses how the network structure characteristics(network centralities and network power)affect the firms' financial performance.The results show that network centralities(eigenvector centrality,closeness centrality and betweenness centrality)and network power(degree and clustering coefficient)improve the firms' financial performance(ROA,ROE and Tobin's Q).However,the strength of nodes from the network power stream has a negative effect on Tobin's Q,which shows that when the partnership of a firm has a strong influence,it can weaken the bargaining power of the firms in the industry chain,to reduce its flexibility in choosing partners and its long-term financial performance.Therefore,the theoretical significance of this dissertation lies in that according to the networked organization characteristics of the industrial chain and supply chain,based on the link behaviors of financial returns dependence,financial risk infectivity and joint investment relevance respectively,this dissertation establishes a set of complex network models and based on the perspective of industrial chain,thus enriches the existing research methods of industrial chain supply chain management.It also enriches the existing research tools of complex network relationship for enterprise.In practice,this dissertation chooses the common scenarios of industrial chain which is closely related to Chinese manufacturing industry,such as 5G industry,new energy automobile industry,and electronic manufacturing industry.It is committed to accurately depict the complex relationship of enterprises,enhance the stability and competitiveness of the industrial chain,and optimize the strategy of enterprise operation and management from the perspective of industrial chain,to help regulators,business managers and investors to master the industrial operation mechanism,reduce corporate financial risks,and improve the capability of investment decision-making.