Dynamics of human innovative behaviors

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

Physica A: Statistical Mechanics and its Applications, 2014, vol. 394, issue C, 74-81

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.

Keywords: Innovative behaviors; Evolution of strategies; Non-Poisson properties in temporal–spatial patterns; Quasi-localized effects; Innovation spreading (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:394:y:2014:i:c:p:74-81

DOI: 10.1016/j.physa.2013.09.039

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