An Research On Innovation Network Evolution:Based On CAS Theory

In the era of open innovation(OI),the success of firm innovation does not only depend on a firm's own knowledge base and R&D abilities but also on the innovation network it embedded in,which is able to provide the firm the complementary knowledge and innovation resources.Being critical to firms' survival and growth,innovation network also plays an important role in regional and industrial economic development,which is the symbol of national competitive advantage and innovation capacity.However,the vast majority of innovation networks around the world are not well developed:most of them are in slow or unsound growth,and some even decay.Consequently,there remain several practical questions,i.e.,"how can an innovation network keep continuous and sound development?',"How can a firm grow fast by the use of innovation network?","How can a firm govern an innovation network to accomplish the enhancement of regional and industrial competitive advantage?",etc,which need to be answered badly.Against the background mentioned above,this paper aims to study "how an innovation network evolves under the driving force of firm open innovation behavior".Along the logic of“problem proposing? problem analyzing? problem solving",the paper,in the view of the theory of complex adaptive system(CAS)and by the approach of document analysis,case study and agent based modeling and simulation(ABMS),try to answer the three questions,i.e.,(1)what are the characteristics of firm open innovation across the whole behavioral process?,(2)how does the whole network evolves under the driving force of collective open innovation behavior?,and(3)how does an egocentric network in the whole network evolves under the driving force of individual open innovation behavior?,step by step.And the three main findings of the paper are:The first finding is regarding firm open innovation behavior.Focusing on the particular kind of inbound open innovation behavior-external knowledge search,the paper consider that there are three main action step in the behavioral process,i.e.,search boundary demarcation,partner selection and alliance engagement.The behavior in different action-step shows different characteristics and is influenced by different factors.In detail,search boundary demarcation is influenced by firm search breadth and knowledge complementarity,manifested in the forms of local search and distant search.Partner selection is dominated by network orientation which contains position and relationship orientation.When controlled by the position orientation,firms tend to cooperate with the ones who are close to them both geographically and cognitively,or who are in information superiority.When controlled by the relationship orientation,firms tend to cooperate with friends and acquaintance.Alliance engagement is influenced by firm search depth and absorptive capacity,and under the two forces of which inter-firm relationships show different strength.The second finding is regarding how a whole network evolves under the driving force of collective open innovation behavior.It reveals that collective openness has a significant effect on whole network evolution,and the effectiveness is moderated by the industrial innovation disruptiveness which echoes the stage in the industry life cycle(ILC).In detail,in the aspect of network structure,collective breadth is in an "inverted U shaped" relationship with a whole network's cohesion,clustering,reachability and centralization,respectively.While collective depth is in a negative relationship with the four attributes,respectively.Moreover,the disruptiveness exerts an "inverted U shaped" influence respectively on the four attributes.In the aspect of network performance,generally speaking,either collective breadth or depth is in an "inverted U shaped" relationship with the average innovation performance of a whole network,respectively.In contrast,either collective breadth or depth is negatively relative with the performance variance of a whole network.Furthermore,the disruptiveness significantly moderates the relationships between collective openness and the average innovation performance.It prolongs both the positive effects of collective breadth and depth to some extent.The third finding is regarding how an egocentric network evolves under the driving force of individual open innovation behavior.It reveals that individual openness has a significant effect on egocentric network evolution,and the effectiveness is moderated by the industrial innovation disruptiveness which echoes the ILC stage.In detail,in the aspect of network structure,individual breadth mainly influences the scale of an egocentric network,while the individual depth mainly influences the strength of an egocentric network.Both the influences are positive and with the increasing disruptiveness they will be magnified until reaching to the relative stable status respectively.In the aspect of network performance,individual breadth mainly influences the possibility of extremely high performance of an egocentric network,while individual depth mainly influences the mean performance.Both the influences are positive and with the increasing disruptiveness they will be magnified until reaching to the relative stable status respectively.