@article{ART003084080},
author={Do Hyeok Yoo and SuJin Bak},
title={Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={5},
pages={155-164},
doi={10.9708/jksci.2024.29.05.155}
TY - JOUR
AU - Do Hyeok Yoo
AU - SuJin Bak
TI - Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 5
PB - The Korean Society Of Computer And Information
SP - 155
EP - 164
SN - 1598-849X
AB - This study proposes an unsupervised learning-based clustering model to estimate the ESG ratings of domestic public institutions. To achieve this, the optimal number of clusters was determined by comparing spectral clustering and k-means clustering. These results are guaranteed by calculating the Davies-Bouldin Index (DBI), a model performance index. The DBI values were 0.734 for spectral clustering and 1.715 for k-means clustering, indicating lower values showed better performance. Thus, the superiority of spectral clustering was confirmed. Furthermore, T-test and ANOVA were used to reveal statistically significant differences between ESG non-financial data, and correlation coefficients were used to confirm the relationships between ESG indicators. Based on these results, this study suggests the possibility of estimating the ESG performance ranking of each public institution without existing ESG ratings. This is achieved by calculating the optimal number of clusters, and then determining the sum of averages of the ESG data within each cluster. Therefore, the proposed model can be employed to evaluate the ESG ratings of various domestic public institutions, and it is expected to be useful in domestic sustainable management practice and performance management.
KW - ESG evaluation;Korean Public Institutions;Statistical Analysis;Unsupervised Learning
DO - 10.9708/jksci.2024.29.05.155
ER -
Do Hyeok Yoo and SuJin Bak. (2024). Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation. Journal of The Korea Society of Computer and Information, 29(5), 155-164.
Do Hyeok Yoo and SuJin Bak. 2024, "Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation", Journal of The Korea Society of Computer and Information, vol.29, no.5 pp.155-164. Available from: doi:10.9708/jksci.2024.29.05.155
Do Hyeok Yoo, SuJin Bak "Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation" Journal of The Korea Society of Computer and Information 29.5 pp.155-164 (2024) : 155.
Do Hyeok Yoo, SuJin Bak. Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation. 2024; 29(5), 155-164. Available from: doi:10.9708/jksci.2024.29.05.155
Do Hyeok Yoo and SuJin Bak. "Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation" Journal of The Korea Society of Computer and Information 29, no.5 (2024) : 155-164.doi: 10.9708/jksci.2024.29.05.155
Do Hyeok Yoo; SuJin Bak. Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation. Journal of The Korea Society of Computer and Information, 29(5), 155-164. doi: 10.9708/jksci.2024.29.05.155
Do Hyeok Yoo; SuJin Bak. Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation. Journal of The Korea Society of Computer and Information. 2024; 29(5) 155-164. doi: 10.9708/jksci.2024.29.05.155
Do Hyeok Yoo, SuJin Bak. Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation. 2024; 29(5), 155-164. Available from: doi:10.9708/jksci.2024.29.05.155
Do Hyeok Yoo and SuJin Bak. "Development of an unsupervised learning-based ESG evaluation process for Korean public institutions without label annotation" Journal of The Korea Society of Computer and Information 29, no.5 (2024) : 155-164.doi: 10.9708/jksci.2024.29.05.155
