Research On The Evolution Of Biopharmaceutical Industry Innovation Network In Shandong Province Based On Cooperative Patents

As a typical representative of strategic emerging industries,the biopharmaceutical industry has been highly valued by the state in recent years.The biopharmaceutical industry is knowledge-intensive and capital-intensive,and innovation has higher risks and uncertainties than other industries.Collaborative innovation can enable organizations to achieve complementary resources,risk sharing,and benefit sharing,thus reducing tension and improving innovation efficiency.With the increase in the breadth and depth of cooperation,one-to-one cooperation gradually develops into an innovation network with multi-subject interaction.The biopharmaceutical industry can rely on the network effect of innovation network to promote the transformation of scientific and technological achievements,industrial specialization,etc.In order to deeply understand the evolution mechanism of the biomedical industry innovation network and grasp the operation trend,this paper takes the biomedical industry in Shandong Province as the research object and constructs the temporal and spatial network models of the innovation network with innovation subjects and cities as node scales,respectively.Firstly,the temporal network model is analyzed by using the social network analysis method,including overall index analysis,small-world and scale-free characteristics analysis,network centrality analysis,and network motif analysis,and the temporal evolution regularity of the biomedical industry innovation network in Shandong Province is derived.The scale of the biomedical industry innovation network in Shandong Province has experienced a phase explosion and then maintained stable growth.Secondly,the structure undergoes an evolutionary process from fragmentation to aggregation and re-diversification.In addition,the network structure presents increasingly complex characteristics and,in the second and third stages of development,offers prominent small-world features and scale-free characteristics,i.e.,the network has many irregular connections and uneven distribution of node degrees.The Matthew effect of the network is increasing,with a few core organizations holding most of the relationships in the network and a large number of edge organizations prioritizing cooperation with them,eventually leading to an extreme "polarization" pattern.In addition,the spatial evolutionary dynamics of the innovation network of the Shandong biomedical industry were quantitatively estimated by using the network statistical model time-exponential random graph model(TERGM)from three dimensions of network self-organization effects,actor attributes,and exogenous situational variables.The results are also tested for robustness and goodness-of-fit,and the following conclusions are drawn.First,the formation of the spatial network structure of the innovation network is the result of the combined effect of endogenous structural factors and exogenous factors.Second,the influence of endogenous factors means that cities in the network are more inclined to connect with other cities in multiple ways to reduce dependence on individual connections.In addition,the innovation capabilities of cities in the network and their congruence effects significantly influence the evolution of the spatial structure of the innovation network of the biomedical industry in Shandong province.Finally,geographical and cultural proximity are also important drivers influencing the spatial evolution of the network.The results of this study provide rich experience and empirical evidence for further optimizing the innovation network structure,rational allocation of innovation resources,promoting collaborative innovation,and enhancing the overall innovation competitiveness of the biopharmaceutical industry in Shandong Province.