Research On Evolution Of Techno-innovation Network In High-tech Industry-Application Of Complex Networks

Complexity of innovation determines High-tech firms expanding their R&D boundaries for acquisition of external knowledge resource, thus to accumulate their knowledge stock. In order to maximum value creation and minimum transaction cost, firms would select a rational governance structure to protect this cooperative transaction. To understand the potential complementarities between individual transactions in a firm's portfolio (or a network) we further consider another theoretical perspective on firm strategy:the relational view of the firm, which emphasizes the whole portfolio of transactions as a unique resource of the firm. This paper constructs several evolutional models, for considering many original topology structures and different evolutional mechanism, to analyze the ultimate network topology structure and function.Recent years, there has some important broke through in complex theory area, especially the development of "complex networks". As the development of complex networks theory, at meanwhile, researchers expand its application areas, for example, this methodology can be used as a useful tool for studying innovation networks.In order to build network evolutional model, we must find the original topology structure. Therefore, this paper constructs a static equilibrium analytical framework according to two principles:effective principle and stable principle. As a result, "star network" and "homogeneous network" are found as the original network structure. In the real world, these two network structure exist wildly. Out of our mind, there exists a complex innovation network in some industry clusters. But these findings are all useful for constructing our evolutional models.In order to build network evolutional model, we should also conclude evolutional mechanisms. The characteristics of high-tech industry:complementary of individual firm's knowledge resource, uncertainty of network development and importance of social capital for whole network, and many other contingency factors ask for the high-tech firms to outsourcing external knowledge resource through inter-organizational learning. This makes network expand its scale, thus network appears growth mechanism; in another way, there proximities (cognitive proximity, relational proximity and geographical proximity) affect this learning process. This makes network present "preferential attachment" mechanism when firms choose their cooperative partners. In others words, firms are ease to choose these who possess higher knowledge stock, or those who have good cooperative history, or those who has good cooperative reputation as their partner.Base on this, this paper built two evolutional models separately. In this first situation, the original network structure is "star network". In the network development process, there are cooperative transactions between un-core nodes; thus the network will be a free-scale network, or few nodes possess huge verticals, we called these nodes "rich-node"; these nodes are also ease to connect with each other, they form "rich-club". In the second model, the original network structure is "homogeneous network". This network will be a free-scale network at finally.Individual firm also can gain knowledge by their self through R&D besides external knowledge resource acquisition, this also can raise his influential capacity in the innovation networks, and thus individual firm presents adaptive learning mechanism in the evolution process. Although the original network structures are different, the final outcome is the same; so here, we built a unified improved evolutional model. The outcome shows that we can conclude evolutional behaviors from knowledge flow perspective, network nodes using clustering and distant linkage to find innovative opportunities. Beside this, the network will be a small world network, also have free-scale character.The purpose of studying network topology structure is to find the impact of network structure on the knowledge diffusion on the innovation networks. According to synchronization theory, considering knowledge creation in the process of knowledge diffusion, this paper builds a knowledge diffusion network synchronization model. This model requires the networks have multi core nodes. But, this structure is fragile to "deliberate attack". For comprehensive considering of robustness and synchronization, this paper builds a synchronous preference innovation networks; This network possesses higher robustness though some core nodes deviate from this network.This paper also did empirical study on China gene engineering pharmaceutical firms, in the period 2004-2008, this network is a free-scale network. During this period, many new nodes enter into this network, but the average path length is becoming shorter. These findings can be used to give suggestions for China gene engineering pharmaceutical industry; they should build a national small world network. This network will have shorter average path length and high cluster coefficient; these are good for knowledge diffusion and knowledge creation.