Evolution of Knowledge Space Adaptability in the Famous Grand Demonstration Zone: A Study Based on the Stimulus-Response Model

  • Duan Qi
  • Kang JianEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1060)


In order to clarify the environmental change-oriented knowledge space adaptability evolution of the famous brand demonstration zone, the stimulus-response multilayered structure model is built and the agent approach is adopted for a simulation experiment. Experimental results suggest that the adaptability of knowledge space evolution results in the demonstration zone is decided by the structure and status of the original knowledge space, external environment, selection of the rule set, knowledge flow, etc. Meanwhile, the activity degree of knowledge gene and the “stimulus” intensity of environmental changes are positively correlated.


Stimulus-response Famous brand demonstration zone Knowledge space Adaptability evolution 



This research was financially supported by China Central Public-interest Scientific Institution Basal Research Fund (Grant No.: 552018Y-5930).


  1. 1.
    Anonymous. Fuji xerox: knowledge management ideas to be copied. Strateg Dir. 2005:21(3):16–8.Google Scholar
  2. 2.
    Microsoft P.l B. Information World Review. Oxford. 2000;155:25.Google Scholar
  3. 3.
    Holland JH. Hidden order: how adaptation builds complexity. New York: Basic Books; 1995.Google Scholar
  4. 4.
    Sherif K, Xing B. Adaptive processes foe knowledge creation in complex systems: the case of a global IT consulting firm. Inf Manag. 2006;43(3):530–40.CrossRefGoogle Scholar
  5. 5.
    Popoveniuc B. Self-reflexivit knowledge. Procedia—Soc Behav Sci. 2014;163:213.CrossRefGoogle Scholar
  6. 6.
    Valverde-Albacete FJ, Gonzalea-Calabozo JM, Penas A, et al. Supporting scientific knowledge discovery with extended, generalized formal concept analysis. Expert Syst Appl. 2016;22:196–216.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.China National Institute of StandardizationBeijingChina

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