Author
Listed:
- Yung-Fa Yang
(Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10670, Taiwan)
- Haon-Yao Chen
(Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10670, Taiwan)
- Yun-Hsiang Chen
(Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10670, Taiwan)
- Shih-Ping Ho
(Department of Civil Engineering, National Taiwan University, Taipei 10670, Taiwan)
- Chuan-San Wang
(Department of Accounting, National Taiwan University, Taipei 10670, Taiwan)
- Cheng-Fang Lin
(Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10670, Taiwan)
Abstract
Environmental, Social, and Governance (ESG) reports have become essential tools for enterprises to showcase their commitment to sustainable development and social responsibility. However, discrepancies persist regarding the criteria, assessments, and ratings disclosed in these reports. Moreover, there is a need for more objective methods to determine the weight distribution of indicator items. This study introduces a novel approach utilizing semantic variables in fuzzy theory and a multiple logic fuzzy inference system to develop an ESG environmental management performance assessment model. Therefore, this paper aims to develop a novel approach utilizing semantic variables and a multiple logic fuzzy inference system to quantitatively evaluate the sustainable performance of an environmental management plan. This research also aims to ensure fair and objective assessment outcomes, providing valuable guidance for enterprises in implementing performance management strategies. Key aspects investigated include the impact of membership functions, the extended utilization of semantic variables and logical rules, a comparative analysis of traditional weight assessments, and the limitations of applying fuzzy theory. Through comprehensive discussions and calculations, it is evident that fuzzy theory offers considerable flexibility in application. By tailoring fuzzy rules and selecting appropriate membership functions, diverse application scenarios can be accommodated. The Fuzzy systems evaluation and scoring EMP model generates EMP evaluation scores ranging from 1.76 to 8.29 for Gaussian membership, 1.80 to 8.19 for Triangular membership-A, 1.92 to 8.00 for Triangular membership-B, and 1.81 to 8.19 for Quadrilateral trapezoidal membership, based on simulated rating scenarios using the semantic variables of completeness and feasibility. This approach successfully incorporates distribution logic from subjective membership degrees to evaluate EMP scores. The findings demonstrate that fuzzy theory enables the consideration of multiple factors and facilitates the provision of objective-level membership, underscoring its potential in addressing complex evaluation challenges. This study illuminates the versatility of the fuzzy system theory, with its applications poised to extend across various domains.
Suggested Citation
Yung-Fa Yang & Haon-Yao Chen & Yun-Hsiang Chen & Shih-Ping Ho & Chuan-San Wang & Cheng-Fang Lin, 2024.
"Refining Environmental Sustainability Governance Reports through Fuzzy Systems Evaluation and Scoring,"
Sustainability, MDPI, vol. 16(16), pages 1-19, August.
Handle:
RePEc:gam:jsusta:v:16:y:2024:i:16:p:7227-:d:1461806
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:7227-:d:1461806. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.