Study Based On The Relationship Between Corporate Network Capacity And Innovation Performance Of The Resource Based View

For the globalization, high uncertainty of market and rapidly changing technology environment, individual firms find it increasingly difficult to master the lasted knowledge and meet the requirements of technologies for development and operation. For firms, building innovation network is becoming an important way to acquire information and knowledge, and to improve the efficiency of innovation as well. So the topic of innovation network has become the focus of many scholars' attention. However, the researches of innovation network are mostly from the theory of social network, and the point of these researches is mainly focus on the configuration of the network rather than from the perspective of single firm. This has resulted in that we can not analyze the effect of behaviors and strategy of single firm on its benefit from the innovation network and how the firm attain and maintain the competitive advantage. In this dissertation, through resource based view of the firm being introduced to the field of innovation network, and a theory of RBV in the context of network being proposed in this study, the process and the way of capturing competitive advantage by single firm based on the innovation network is revealed.Based on the theory of RBV and existing literatures, the mechnasim of generation, classification and characters of network resource are analyzed firstly in this study. Then the signification of network rents is emphasized by illuminating that network rents are measure of network resources in the view of economics. Thus, the dissertation extends the RBV to the context of interfirm network. Based on this extended RBV, the concept of network capability and its connotation are defined. And this dissertation point out that network capability plays a role in the process of operating network resources to actualize their potential value for competitive advantage. It is the network capability that enables the network rents which embed in network resource and decides the proportion of the additional benefit which the firm gets from network. And this theory reveals the reason why firms obtain different benefits in the same innovation network. Secondly, through exploratory factor analysis and confirmatory factor analysis, this dissertation comes up with a method to measure network capability. By usinge the method of multiple regression, the approachs for the firms to improve their network capability are also analized. Thirdly, through the exploratory case study and normative analysis, a conceptual model that reveals the effect of the network capability on innovation is bulit. At last, structural equation is used to revise the model and analyze the effect of different network capabilities on firms' innovation levels in different types of innovation networks. So far, the mechanism of single firm to achieve the competitive advantage in more microcosmic level is revealed.The conclusions of this dissertation are: (1) the network configuration, which comprises network structure, network relationship and network position, will impact significantly networked firm's knowledge acquirement and its innovation performance; (2) the network resource comes from the learning effect, the spillover effect, synergy effect and complementarily effect between the firms in the network. The network resource can be classified as three types: network structure resource, network relationship resource and network position resource, which all have the characters of share, value, scarcity, difficult to imitation and difficult to substitute; (3) all of the three types network resources can provide network rents, these rents are shared but not equally by the members of network. The proportion of rents that firms get depends on their network capability. This reveals the essential relationships between network resource, network rents and network capability: First of all, network rents come from the network resources. Furthermore, network rent is the representative of the competitive advantage and the value of the network resource. Second, network resource is the foundation of the network capability, the function of network capability is activated in the process of using network resource by firm. It enables the network resource to be a potential value resource of the competitive advantage. At last, network capability activates the network rents in the network resource, and make sure that the firm get the additional benefit; (4) the network capability can be classified as: network visioning capability, network constructing capability, network operating capability and network constructing capability. Some factors, such as maturity of IT, openness of culture, management system involved, experience of participation in network, have a positive effect on the network capability of the firm; (5) the impact of network capability on innovation performance is realized through knowledge transfer between network partners, namely, knowledge transfer is the mediator; and (6) the type of innovation network, exporation network or exploitation network, has moderator effect on the relationship of network capability and knowledge transfer, and network capability and innovation performance as well. In the exploration network, network constructing capability has more effect on the performance of the knowledge transfer and innovation. In the exploitation network, network operating capability has more effect on the performance of the knowledge transfer and innovation.By building the RBV in the context of network, this dissertation point out that the competitive advantage can also come from the interfirm network, and try to make some innovation in the following points: (1) to break through the traditional perspective which fucoses on the whole innovation network. From the view of single firm in the innovation network, the approach of acq-uiring and maintaining competitive advantage of the firm through some heterogeneity resource in the innovation network is put forward. It provides a new perspective to the study of innovation network, and extends the research of this field; (2) based on the theoretical analysis, RBV is extended to the context of interfirm network. Meanwhile, the concepts of network resource, network capability and network rents are clarified, and the essential relationships between them are revealed; (3) the role of network capability in the process of the firm in acquiring competitive advantage is analyzed. The classification of the network capability and its measure are also completed; (4) some important factors which have influence on the level of network capability are proposed exploringly, and some advices for the firm in the innovation network to improve their performance of organizational learning and innovation are given; (5) combining with the RBV, social network theory, the knowledge transfer theory and technological innovation theory, the way that network capability influences the innovation performance is finally revealed.The dissertation is divided to six sub-researchs. In the first sub-research, the theory of RBV in the context of network is built, which mainly includes the definition of network resource, the source of network rents and its distribution, the concept of network capability, and competitive advantage of the networked firm. In the second sub-research, based on the theoretical analysis and statistical analysis, network capability is classified, and the meaning of network capability is clarified. A measurement method and scale of network capability is also put forward in this sub-research. In the third sub-research, based on the literature review and the normative analysis, some influential factors that would effect on the different network capability in organizations are identified. In the fourth sub-research, through multi-case analysis, the mechanism through which that network capability influence the innovation performance is found. In the fifth sub-research, firstly, a conceptual model that network capability influences the innovation performance is proposed; then, this model is validated by using the methods of multiple regression and structural equation model. The moderator effect of the type of network and the mediator effect of knowledge transfer are the key points in this sub-research. At last, the shortcomings and the future direction of this dissertation are described.