Innovation, which involves technological transformation and management reorganization, brings about significant changes in modern society. In this paper, to investigate how innovations can be promoted, we propose a ga...Innovation, which involves technological transformation and management reorganization, brings about significant changes in modern society. In this paper, to investigate how innovations can be promoted, we propose a game-based model to study the co-evolutionary dynamics of human innovative behaviors. A simulation on scale-free networks is conducted, in which the innovative behavior of each node is determined and updated based on the feedback regarding its innovation, namely the diffusion of the innovation status. Numerical simulations of the model generate a series of patterns, which is consistent with people＇s daily experiences and perceptions as regards real-world innovative behaviors. Specifically, various scaling spatiotemporal properties and rich structural impacts on dynamics can be observed. This model provides a novel approach to understand the evolution of innovative behaviors and provides insight for strategy studies of innovation promotion.展开更多
基金This work was supported by the National Natural Science Foundation of China （Grant Nos. 11547254, 11275186, 91024026, 11205040 and FOM2014OF001）, Zhe- jiang Provincial Natural Science Foundation of China （No. LGF18F030007）, the Singapore Ministry of Education Research Grant （Grant No. MOE 2013-T2-2-033）, and the Programmatic grant no. A1687b0033 from the Singapore government＇s Research,Innovation and Enterprise 2020 plan （Advanced Manufacturing and Engineering domain）.
文摘Innovation, which involves technological transformation and management reorganization, brings about significant changes in modern society. In this paper, to investigate how innovations can be promoted, we propose a game-based model to study the co-evolutionary dynamics of human innovative behaviors. A simulation on scale-free networks is conducted, in which the innovative behavior of each node is determined and updated based on the feedback regarding its innovation, namely the diffusion of the innovation status. Numerical simulations of the model generate a series of patterns, which is consistent with people＇s daily experiences and perceptions as regards real-world innovative behaviors. Specifically, various scaling spatiotemporal properties and rich structural impacts on dynamics can be observed. This model provides a novel approach to understand the evolution of innovative behaviors and provides insight for strategy studies of innovation promotion.
