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Dynamics of human innovative behaviors

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  • Lin, Ying-Ting
  • Han, Xiao-Pu
  • Wang, Bing-Hong

Abstract

How to promote the innovative activities is an important problem for modern society. In this paper, combining the evolutionary games with information spreading, we propose a lattice model to investigate dynamics of human innovative behaviors based on benefit-driven assumption. Simulations show several properties in agreement with peoples’ daily cognition on innovative behaviors, such as slow diffusion of innovative behaviors, gathering of innovative strategy on “innovative centers”, and quasi-localized dynamics. Furthermore, our model also emerges rich non-Poisson properties in the temporal–spatial patterns of the innovative status, including the scaling law in the interval time of innovation releases and the bimodal distributions on the spreading range of innovations, which would be universal in human innovative behaviors. Our model provides a basic framework on the study of the issues relevant to the evolution of human innovative behaviors and the promotion measurement of innovative activities.

Suggested Citation

  • Lin, Ying-Ting & Han, Xiao-Pu & Wang, Bing-Hong, 2014. "Dynamics of human innovative behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 74-81.
    • Handle: RePEc:eee:phsmap:v:394:y:2014:i:c:p:74-81
    DOI: 10.1016/j.physa.2013.09.039
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    References listed on IDEAS

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    Cited by:

    1. Luo, Gui-Xun & Liu, Yun & Zeng, Qing-An & Diao, Su-Meng & Xiong, Fei, 2014. "A dynamic evolution model of human opinion as affected by advertising," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 254-262.
    2. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.

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