An Evolution Analysis of Collaborative Innovation Network considering Government Subsidies and Supervision

Abstract

Collaborative innovation networks have the basic attributes of complex networks. The interaction of innovation network members has promoted the development of collaborative innovation networks. Using the game-based theory in the B-A scale-free network context, this paper builds an evolutionary game model of network members and explores the emergence mechanism from collaborative innovation behavior to the macroevolution of networks. The results show that revenue distribution, compensation of the betrayer, government subsidies, and supervision have positively contributed to the continued stability of collaborative innovation networks. However, the effect mechanisms are dissimilar for networks of different scales. In small networks, the rationality of the revenue distribution among members that have similar strengths should receive more attention, and the government should implement medium-intensity supervision measures. In large networks, however, compensation of the betrayer should be attached greater importance to, and financial support from the government can promote stable evolution more effectively.Collaborative innovation networks are the main topic in this paper. After reviewing some recent research, we found that the main fields of related work focused on the characteristics of the collaborative networks members (micro), the evolution processes of the networks (macro), and the networks' collaborative performance. We report some of our findings below.In terms of the works on members of in collaborative innovation networks, social network analysis is the main method to study the characteristics of network nodes and the relationships between them. Landart et al. found that innovation networks that are well managed can providemany benefits to enterprises [9]. Dhanaraj studied the activity and openness of network nodes and found that the core members of innovation networks can coordinate overall network actions to achieve the effects of collaborative innovation [10]. Tsai pointed out that if enterprises occupy the center of the networks, they can generate more innovations. Tseng analyzed centrality and density of firms in the innovation networks, and found that the higher centrality and higher density, the stronger innovation capability [11].The research on the evolution of innovative networks mainly focuses on network topology and its influencing factors. Woo found that the connection mechanism has a great impact on network evolution using social network analysis to study the dynamic evolution of high-tech innovation networks [12]. Fleming analyzed the impacts of core firms on the evolution of innovation networks and thought that core innovation network members are important factors that drive the network to centralize [13]. Lazzeretti investigated the impact of neighborhood on innovation network dynamics [14]. Liang explored the evolution of collaboration network within government sponsored and found that network structure and composition should be involved into the specific policies [15].In terms of collabora...

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