The Intertemporal Evolution Model of Enterprise R&D Cooperative Network

Cooperation plays an irreplaceable role in knowledge creation and innovation. Innovation cooperation among enterprises forms a complex network of enterprise R&D. Given the intertemporal R&D network evolution and the complex influence between stock knowledge, this study constructs a discrete indefinitely intertemporal evolution model of an enterprise R&D cooperation network. The model consists of two main parts, that is, first is how technological innovation depends on the structure of enterprise R&D cooperation network and the second is how the enterprise R&D cooperation network evolves according to the level of technological innovation. This work uses calculation experiment and simulation method to study the evolution characteristics of enterprise R&D network in different initial R&D network topology structures, such as Erdos–Renyi random graph, WS small-world network, and BA scale-free network, and determine how previous history, attractiveness, and reputation for enterprise influence the steady-state characteristics of R&D network evolution. Results show that (1) when the R&D network evolution reaches a stable state, the joint distribution of stock knowledge and the number of cooperative enterprises do not affect the initial R&D network topology. However, the evolution path of the enterprise R&D network is complicated by the initial R&D network topology. (2) Among the three factors through which enterprises make decisions, if the enterprise values previous history highly, then the stock knowledge in a steady state will dissipate; if the enterprise values reputation highly, then the stock knowledge in a steady state will decrease but always above a threshold; if the enterprise values attractiveness highly, then the stock knowledge in a steady state can rise to a high level. These conclusions have important theoretical values and practical significance for the promotion of enterprise scientific and technological innovation and cooperative research.