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Top1. Introduction
With the economic globalization, “Closed innovation” has been out of date compared to “open innovation”, more and more enterprises have implemented the “open innovation”. The “open innovation” refers that the enterprises carry out innovation by using the internal and external sources at the same time. Under “open innovation” mode, the innovation process of the enterprise is nonlinear and open, the innovation main body of the enterprise no longer relies on its own strength, and interacts effectively with external sources of innovation, and then enterprise efficiency can be maximized. In the internet age the open innovation requires the innovation subject be good at network management, and can coordinate the cross organizational, cross cultural knowledge transfer and flow. Knowledge sharing, and innovative behavior have been no longer restricted to communication between internal employees, the virtual community based on social media has become the new platform that publishes the innovative ideas. The enterprise can establish the open innovation community to connect the external users and enterprises, and the users are encouraged to express the ideas and opinions in community (Lee et al., 2018).
The increase of the knowledge transfer speed, the acceleration of human capital flow and more and more wide of venture capital range require enterprises to accelerate the development and promotion of new technology and new products and actively search, identify, and obtain all the resources inside and outside the enterprises (Pirkkalainen et al., 2018; Martinez-Torres & Olmedilla, 2016; Hannigan, 2018), and seek innovative cooperation Initiatively, and achieve technological innovation through sharing resources and complementary advantages. Therefore, it is necessary to carry out operation mechanism and system analysis for open innovation community network, and analyze the cause and effect relationship of each node in community, and integration mechanism of innovation resources (Cui et al., 2018; Jason et al., 2018; Angela et al., 2018). The system dynamics is an important method for studying complex problem, absorbs the essence of cybernetics and information theory (Sam & Petros, 2017; Mila, 2017), and integrates the computer technology into the system modeling and simulation based on system, explores the problems existing in the system by analyzing the mechanism of information feedback (Jan et al., 2017; Mari, 2017; Birgit et al., 2018), and solve the system problem based on structure method, function method and historical method, therefore the system dynamics can deal with the system problems with complex, nonlinear and delay phenomena.
The system dynamics has been applied in natural and society fields (Wondowossen et al., 2018; Khanmohammadi et al., 2018; Albert et al., 2018), which belongs to a cross disciplinary discipline. The system dynamics can effectively cope with the complex problem, and correctly evaluate the nonlinear problem (Michael et al., 2017; Zhang et al., 2018; Juan et al., 2017). A dynamic simulation model is established based on the observed information of the system, and the future behavior of the system is described by computer experiments (Mohammed et al., 2018; Alberto et al., 2018). Therefore, it is feasible to apply the system dynamics to this research.