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Issue title: Cross-domain Applications of Fuzzy Logic and Machine Learning
Guest editors: Ekaterina Isaeva and Álvaro Rocha
Article type: Research Article
Authors: Junshu, Dua | Shaofeng, Pengb; * | Jisheng, Pengc
Affiliations: [a] School of Modern Service Industry, Changzhou College of Information Technology, Changzhou, China | [b] School of Public Administration and Institute of Social Governance and Social Policies, Hunan Normal University, Changsha, China | [c] Business School, Nanjing University, Nanjing, China
Correspondence: [*] Corresponding author. Peng Shaofeng, School of Public Administration and Institute of Social Governance and Social Policies, Hunan Normal University, 36 Lushan Road, 410081, Changsha, China. Tel.: +86 188 7472 8607; Fax: +86 0519 8633 8170; E-mail: [email protected].
Abstract: While high-tech enterprises have achieved high returns through technological innovation, they also face high risks. This study builds a technology innovation risk evaluation system for high-tech enterprises from eight dimensions: technology risk, capital risk, patent risk, talent risk, management risk, policy risk, industrial risk, and market risk. Based on the subjective and fuzzy characteristics of the evaluation indicators, a risk evaluation model for technological innovation based on fuzzy evaluation was established, and an empirical study was conducted with a technological innovation project of a petrochemical company in Shanghai. The research results show that the high-tech enterprises’ technology innovation risk evaluation model constructed in this study has high accuracy for the quantification of technological innovation risk, and the technology innovation risk evaluation model is highly practical, which provides a reasonable basis for risk management decisions in the process of a high-tech company technology innovation.
Keywords: Fuzzy evaluation, technology innovation, risk evaluation, high-tech enterprises
DOI: 10.3233/JIFS-179758
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 6, pp. 6805-6814, 2020
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