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Issue title: Special Section: Intelligent Data Aggregation Inspired Paradigm and Approaches in IoT Applications
Guest editors: Xiaohui Yuan and Mohamed Elhoseny
Article type: Research Article
Authors: Jingjing, Zhanga | Jiaxin, Wangb | Ta, Liuc; * | Dongping, Hanc
Affiliations: [a] Department of Human Resource Management, School of Management, Putian University, Putian, China | [b] Department of Hotel and Tourism Management, Jinjiang Huaqiao Vocational School, Jinjiang, China | [c] School of Management, Harbin Institute of Technology, P.R. China
Correspondence: [*] Corresponding author. Liu Ta, School of Management, Harbin Institute of Technology, 150001, P.R. China. E-mail: liangliangliang196@163.com.
Abstract: As the theme of sustainable development in the 21st century, environmental management creates value through the combination of ecological and economic elements and forms the enterprise Eco-efficiency. Enterprise Eco-efficiency can not only measure the performance of the company’s environmental management, but also guide the implementation of enterprise environmental management strategy and the realization of business objectives. There is a mutual causal relationship between environmental management and enterprise Eco-efficiency. Based on the analysis of the forming mechanism of enterprise Eco-efficiency within the environmental management system, it is found that whether the place influencing factors or vicissitude influencing factors, their impacts on the enterprise Eco-efficiency measurement value may be uncertain and ambiguous. In this paper, the similarity model of intuitionistic fuzzy set is established to conduct the intuitionistic fuzzy identification of the enterprise Eco-efficiency influencing factors, and a large-scale oil refining and chemical company is used as an example for application testing to determine measurement effectiveness.
Keywords: Enterprise Eco-efficiency, environmental management, place influencing factor, vicissitude influencing factor, intuitionistic fuzzy identification
DOI: 10.3233/JIFS-179076
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 185-192, 2019
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