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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: Zhao, Yiqia | Qin, Yuanjiana | Zhao, Xianfengb; * | Shi, Leileic
Affiliations: [a] School of Management, Wuhan University of Technology, Wuhan, China | [b] School of Business, Hebei GEO University, Shijiazhuang, China | [c] State Grid Hebei Electric Power Company Xingtai Power Supply Branch, Xingtai, China
Correspondence: [*] Corresponding author. Xianfeng Zhao, School of Business, Hebei GEO University, Shijiazhuang, China. E-mail: [email protected].
Abstract: This study conducts data analysis on hypocritical and non-hypocritical enterprises to explore the influence of altruistic motivation perception on corporate social responsibility (CSR) implementation, CSR communication, and corporate hypocrisy. To analyze the data of hypocritical and non-hypocritical companies, a fuzzy set qualitative comparative analysis is applied. In hypocrisy enterprises, high neutral altruism and low positive altruism are sufficient conditions for high CSR communication. Low negative altruism is a necessary condition for CSR implementation, and low positive altruism and high neutral altruism are sufficient conditions for CSR implementation. And low positive altruism and low CSR implementation behavior are sufficient conditions for corporate hypocrisy, while high neutral altruism is sufficient conditions for corporate hypocrisy. In non-hypocritical enterprises, high neutral altruism and high negative altruism are sufficient conditions for high CSR communication. And high CSR implementation needs high positive altruism and CSR communication interaction. And High positive altruism and low CSR communication are sufficient conditions for corporate non-hypocrisy.
Keywords: Altruistic motivation perception, corporate hypocrisy, qualitative comparative analysis of fuzzy sets
DOI: 10.3233/JIFS-179757
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 6, pp. 6795-6803, 2020
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