| The production network of different dimensions between economic subjects have been established via input-output relations,which has enabled the China’s manufacturing industry to form a complete domestic value chain at home and fully merge into the global value chain,continuously enhance its value-added capacity.In this process,technology,research,development and other innovative elements have become more equal and advanced with the product flow and allocation,formed innovation networks at different levels,including provincial,industrial and international networks.The fundamental focus of developing China’s advanced manufacturing industry is to improve its R&D capability,the innovation network intuitively presents R&D activities and production activities in the form of network,which is becoming an important tool to understand the R&D model of China’s manufacturing industry.The innovation network stems from the production network and combined with the R&D expenditures of economic subjects,reflecting the driving effect of demand on R&D in the production process.This paper first combs the existing research system of production network from three aspects:the construction of production network,the decomposition and measurement of production network,and the estimate application of production network,forming the characterization method and analysis paradigm of innovation network.The construction and decomposition of the production network closely combines the demand side and the supply side,effectively distinguishes the product flow path.There is also a progressive relationship between the decomposition,measurement and estimate application of the production network,which not only realizes the detailed description of network characteristics,but also can effectively discuss the interaction relationship and mechanism between variables when it is included in the ecnometric model.This research system reflects the complete logical chain of network analysis,establishes the decomposition and research framework of China’s manufacturing R&D model.The R&D system of China’s manufacturing industry includes regional R&D,industrial R&D and national R&D.First,this paper takes the manufacturing industry in various provinces of China as the innovation network nodes,constructs the provincial manufacturing innovation spatial correlation network based on the input-output table of the departments of China’s provinces(cities,autonomous regions)in 2007,2010,2012 and the R&D expenditure data of each province,analyzes the network characteristics and decomposes the R&D driving model.The network visualization and characteristic analysis results show that,the spatial layout of China’s provincial innovation network has changed from ’east-west’ difference to ’south-north’ difference,and finally formed the network characteristics of ’center-edge’,shaping a wide range of innovation linkages between regional manufacturing industries.While the degree centrality and closeness centrality of manufacturing in China’s provinces have increased significantly,the betweenness centrality has continued to decrease,reflecting the characteristics of provincial manufacturing innovation spatial correlation network have changed from ’single province-led’ to’multi-provincial-coordinated development’.The result of block division shows that the change of innovation block of provincial manufacturing industry follows the development path of ’net spillover block→middleman block→main beneficiary block’.The northwest and southwest regions,where the manufacturing industry is relatively slow to develop,have less technological links between their internal manufacturing industries,and have been locked in the middleman block for a long time,making it difficult to realize the position transition.Decomposing the R&D driving model of manufacturing industry in each province on the basis of the characteristics of product flow and product use,I find that the R&D model of manufacturing industry in developed regions such as East China,Central and South China is ’final demand-driven’,the self-sufficiency of final products is obvious.The R&D model of manufacturing industry in other regions is ’intermediate demand-driven’.The cross-provincial flow of intermediate products involves a wider geographical range and more technical elements,which leads to a stronger R&D driving force.For regions with a high level of manufacturing development,investment demand has a stronger driving effect on R&D expenditures compared with consumer demand.The key to optimize the R&D model from the domestic perspective is to improve the innovation output efficiency of R&D expenditures.This paper further takes the manufacturing industry segment as the innovation network node,extends the scope of demand from domestic to domestic and foreign and decomposes the R&D driving model of China’s manufacturing industry based on the world input-output table from 2000 to 2014 and the R&D expenditure data of China’s manufacturing industries.The decomposition results show that the R&D expenditures driven by intermediate demand in capital-intensive manufacturing industry has occupied a leading position and the proportion has continued to rise,mainly integrating intermediate trade into the middle and low end of the global value chain.The R&D expenditures of technology-intensive manufacturing industry are driven by both domestic final demand and intermediate demand,the proportion of foreign final demand-driven part is the lowest,industrialized technical advantages have not yet been formed.In this paper,’production—R&D—innovation’ is included in the same analysis framework,with demand-driven R&D as the explanatory variable,the characteristics of the production network of various industries in China’s manufacturing industry as the adjusting variable,I use fixed effect model to estimate the correlation.The regression results show that all types of R&D have a significant positive impact on innovation,and the final demand is the main driving force to drive R&D expenditures to achieve innovation output.The characteristics of the production network have a significant intermediary effect,the degree centrality enhances the promotion of demand-driven R&D on innovation output,while the upstreamness inhibits the exertion of the innovation contribution of intermediate demand-driven R&D expenditures.The R&D model of China’s manufacturing industry is reflected in the complex network structure between provinces and the efficient conversion from industrial R&D to innovation outputs in China,and in the international perspective,it is deeply integrated into the world innovation network by participating in the global value chain.Then,based on the world input-output table from 2000 to 2014 and the R&D expenditure data of various countries,this paper constructs the world innovation network with China’s manufacturing industry,China’s non-manufacturing industry and other economies as nodes,studies the integration path and correlation characteristics of China’s manufacturing industry from the perspective of nodes,paths and linkages.The study found that China’s manufacturing industry,as a knowledge exporter and technology beneficiary,has significantly improved its central position in the world innovation network,but it also has weak control over technological linkages,forming a typical feature of high degree centrality,high closeness centrality and low betweenness centrality.Examining the integration path of China’s manufacturing industry in the world’s innovation network,I find the R&D expenditures due to domestic demands of China’s manufacturing industry have been growing with a high speed.The United States,Japan and other developed countries lead to most of China’s manufacturing industry’s R&D expenditures source from foreign demands,while the BRICS countries trigger the fastest growth of them.This paper also calculates the forward and backward technological linkages based on the direction of product flow when China’s manufacturing industry participates in global value chain activities.The changes of the forward and backward technical linkage indexes of China’s manufacturing industry are characterized by rising and stability.Among them,the forward technical linkage has always been greater than the backward technical linkage,China’s manufacturing industry has a more significantly supply status in the global innovation network.This paper provides the industrial upgrading path of China’s manufacturing industry from the perspective of R&D.The leading contributions are as follows:First,accurately portray the internal structure of China’s manufacturing innovation network and its position in the world’s innovation network from domestic and international perspectives,achieve the organic combination of input-output analysis and social network analysis.At the same time,understanding the functions and roles changing characteristics of China’s manufacturing industry in the innovation network helps to expound the advantages and disadvantages of the existing development and R&D model.Second,it makes a comprehensive understanding of the R&D driving model of China’s manufacturing industry from the perspective of the province,industry and country.According to the characteristics of product flow and product use,I have carried out multi-dimensional decomposition of the R&D expenditures of China’s manufacturing industry in various provinces,segments and the whole manufacturing industry in China,comprehensively compared the absolute differences in the level of R&D expenditures of innovation subjects and the driving effect of production activities on R&D.Matching the supply side with the demand side is beneficial to improving the specificity of R&D expenditure.Third,this paper puts’production—R&D—innovation’ under the same framework to understand the impact mechanism of demand-driven R&D expenditures on innovation output,builds a regulatory effect model to test the direct impact of R&D types and the indirect impact of production network characteristics on innovation,which can form a manufacturing R&D model oriented to meet market demand,and thus maximize the efficiency of innovation output of R&D expenditures. |
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