Author(s)

Peng Wang ¹

Affiliation(s)

¹ School of Economics and Management, Dalian University, No.10, Xuefu Avenue, Economic & Technical Development Zone, Dalian, Liaoning, The People's Republic of China (PRC)

Corresponding Author

Peng Wang

ABSTRACT

Based on the theory of self-organization, the paper comprehensively analyses the self-organizing features, self-organizing conditions, and self-organizing forms of the innovation cluster and constructs the entropy change model by analysing the changes in the entropy flow of the innovation cluster. Furthermore, it discusses the dynamics mechanisms and synergistic mechanisms of innovation cluster Self-organizing evolutionary. Through the above research, this paper summarizes the self or ganizing evolution mechanism of innovation clusters, reveals the self-organization regular pattern of the formation and development of innovation clusters, and holds that the innovation cluster has experienced the changing process of “Micro fluctuation-Macro fluctuation-Far from equilibrium” under the influence of positive and negative entropy flow changes and positive feedback mechanisms. It conducts self-adjustment through three dimensions of synergistic mechanism which consist of competition, technology innovation and environmental support synergistic mechanism and nonlinear dynamic mechanism, which promote the innovation cluster to an orderly direction, and then realize optimize and upgrade with experiencing iterations.

KEYWORDS

Innovation cluster; Formation mechanism; Evolution path; Self-organization; Synergy mechanism

CITE THIS PAPER

Peng Wang. Research on the Formation Mechanism of Innovation Clusters Based on Self-Organization Theory. Social Security and Administration Management (2020) Vol. 1: 1-4. DOI: http://dx.doi.org/10.23977/socsam.2020.010101.

REFERENCES

[1] Jia, X. H. (2015) The dynamic impact of industrial cluster life cycle on regional innovation capacity, Economic Research, 1, 807-829.
[2] Jia, X. H. (2016) Research on Cooperative Innovation Behavior of Industrial Cluster Based on Subject Adaptability, Discrete Dynamics in Nature and Society, 3, 169-179.
[3] Christiane, G. (2017) The transfer of corruptive routines from old industrial regions to innovation clusters: a blind spot in innovation studies. Triple helix (Heidelberg), 2, 103-116.

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