A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data
Environment, social, and governance (ESG) considerations have become a necessity for businesses. A company’s environmental and community initiatives have been found to greatly influence customer perception. This is even more critical for industries that are difficult to decarbonize like the aviation...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIDIC Servizi S.r.l.
2023-12-01
|
| Series: | Chemical Engineering Transactions |
| Online Access: | https://www.cetjournal.it/index.php/cet/article/view/14062 |
| _version_ | 1797389645947863040 |
|---|---|
| author | Josiah Kurt B. Aviso Jonna C. Baquillas Kathleen B. Aviso Tsai-Chi Kuo Hsiao-Min Chen Raymond R. Tan |
| author_facet | Josiah Kurt B. Aviso Jonna C. Baquillas Kathleen B. Aviso Tsai-Chi Kuo Hsiao-Min Chen Raymond R. Tan |
| author_sort | Josiah Kurt B. Aviso |
| collection | DOAJ |
| description | Environment, social, and governance (ESG) considerations have become a necessity for businesses. A company’s environmental and community initiatives have been found to greatly influence customer perception. This is even more critical for industries that are difficult to decarbonize like the aviation industry. There has been little investigation on the role of ESG strategies on company financial performance which can dictate the sustainability of initiative implementation. This work uses ESG performance indicators to develop a rule-based model for predicting company financial performance as measured by return on assets (ROA). Results suggest that the most critical attributes of the ESG framework are Innovation, Workforce, Human Rights, Product Responsibility, Shareholders, and the aggregate ESG score. The best–performing model correctly predicts 15 out of 28 of the validation data (53.57 %). A rule of interest is that which states IF (Human Rights = Average) THEN (ROA = Average). It had the highest coverage for both training and validation data with a certainty of 61 %, and a prediction accuracy of 71.4 %, highlighting the importance of Human Rights on firm value. |
| first_indexed | 2024-03-08T22:59:59Z |
| format | Article |
| id | doaj.art-de4e5ea25ef148f399bed674d725810f |
| institution | Directory Open Access Journal |
| issn | 2283-9216 |
| language | English |
| last_indexed | 2024-03-08T22:59:59Z |
| publishDate | 2023-12-01 |
| publisher | AIDIC Servizi S.r.l. |
| record_format | Article |
| series | Chemical Engineering Transactions |
| spelling | doaj.art-de4e5ea25ef148f399bed674d725810f2023-12-15T23:51:34ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162023-12-0110610.3303/CET23106002A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance DataJosiah Kurt B. AvisoJonna C. BaquillasKathleen B. AvisoTsai-Chi KuoHsiao-Min ChenRaymond R. TanEnvironment, social, and governance (ESG) considerations have become a necessity for businesses. A company’s environmental and community initiatives have been found to greatly influence customer perception. This is even more critical for industries that are difficult to decarbonize like the aviation industry. There has been little investigation on the role of ESG strategies on company financial performance which can dictate the sustainability of initiative implementation. This work uses ESG performance indicators to develop a rule-based model for predicting company financial performance as measured by return on assets (ROA). Results suggest that the most critical attributes of the ESG framework are Innovation, Workforce, Human Rights, Product Responsibility, Shareholders, and the aggregate ESG score. The best–performing model correctly predicts 15 out of 28 of the validation data (53.57 %). A rule of interest is that which states IF (Human Rights = Average) THEN (ROA = Average). It had the highest coverage for both training and validation data with a certainty of 61 %, and a prediction accuracy of 71.4 %, highlighting the importance of Human Rights on firm value.https://www.cetjournal.it/index.php/cet/article/view/14062 |
| spellingShingle | Josiah Kurt B. Aviso Jonna C. Baquillas Kathleen B. Aviso Tsai-Chi Kuo Hsiao-Min Chen Raymond R. Tan A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data Chemical Engineering Transactions |
| title | A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data |
| title_full | A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data |
| title_fullStr | A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data |
| title_full_unstemmed | A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data |
| title_short | A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data |
| title_sort | rule based model for predicting airline financial performance from environmental social and governance data |
| url | https://www.cetjournal.it/index.php/cet/article/view/14062 |
| work_keys_str_mv | AT josiahkurtbaviso arulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT jonnacbaquillas arulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT kathleenbaviso arulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT tsaichikuo arulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT hsiaominchen arulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT raymondrtan arulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT josiahkurtbaviso rulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT jonnacbaquillas rulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT kathleenbaviso rulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT tsaichikuo rulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT hsiaominchen rulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata AT raymondrtan rulebasedmodelforpredictingairlinefinancialperformancefromenvironmentalsocialandgovernancedata |