Fuzzy Cognitive Research on Factors Influencing Technological Innovation – From Path Dependence Perspective
Author(s) -
Jing Hu,
Zhang Yong,
Yilin Wang
Publication year - 2016
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2016.p0543
Subject(s) - fuzzy cognitive map , computer science , perspective (graphical) , fuzzy logic , knowledge management , path (computing) , artificial intelligence , cognition , industrial engineering , fuzzy control system , neuro fuzzy , neuroscience , engineering , biology , programming language
This paper aims to establish a framework for evaluating technological innovation and to emphasize the important influence of path dependence on technological innovation. The fuzzy cognitive map (FCM) method is used to identify causal relationships among factors that influence technological innovation, and a FCM structural diagram for evaluating enterprise technological innovation is described. Meanwhile, a fuzzy feedback system for the evaluation of technological innovation, integrated with a nonlinear Hebbian learning algorithm, is established; dependence on expert opinions may be avoided through learning and practice using the cognitive map. Finally, using a computer software platform, a dynamic simulation of any complex index system can be realized. From this simulation, stable conditions can provide path references by which an enterprise engaging in technological innovation can improve the integrative efficiency and the overall effect of any realistic technological innovation activity.
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