The integration of machine learning and decision support system in sustainability performance management
This study developed a framework of a machine learning embedded decision support system that supports company sustainability performance management activities through the assessment of sustainability reports and generation of sustainability scores. The sustainability report assessment function hopes...
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| Format: | Final Year Project / Dissertation / Thesis |
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2024
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| Online Access: | http://eprints.utar.edu.my/7015/ http://eprints.utar.edu.my/7015/1/Ng_Jia_Ying_2006527.pdf |
| _version_ | 1848886826448715776 |
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| author | Ng, Jia Ying |
| author_facet | Ng, Jia Ying |
| author_sort | Ng, Jia Ying |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | This study developed a framework of a machine learning embedded decision support system that supports company sustainability performance management activities through the assessment of sustainability reports and generation of sustainability scores. The sustainability report assessment function hopes to assist companies in compliance with sustainability reporting standards to improve stakeholder engagement and enhance financing prospects. A rule-based system complemented by Natural Language Processing (NLP) technology is adopted for the system. The role of sustainability scores is to provide a direct indicator of the company sustainability performance. The machine learning model, Random Forest Regressor, is deployed to evaluate the performance of the machine learning model in generating sustainability scores under a supervised learning style. The data used in the development of the machine learning model is extracted from company sustainability reports available online. The results of model testing deliver promising results with the performance of the model improving with sample size. However, the model failed to deliver consistently accurate predictions, mainly due to the small data size and the imbalance distribution of data in the database. Lastly, recommendations for the challenges of machine learning integration with sustainability performance management are suggested for the improvement in the data collection and processing during database preparation. |
| first_indexed | 2025-11-15T19:44:40Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-7015 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:44:40Z |
| publishDate | 2024 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-70152025-02-14T06:52:50Z The integration of machine learning and decision support system in sustainability performance management Ng, Jia Ying HD28 Management. Industrial Management TD Environmental technology. Sanitary engineering This study developed a framework of a machine learning embedded decision support system that supports company sustainability performance management activities through the assessment of sustainability reports and generation of sustainability scores. The sustainability report assessment function hopes to assist companies in compliance with sustainability reporting standards to improve stakeholder engagement and enhance financing prospects. A rule-based system complemented by Natural Language Processing (NLP) technology is adopted for the system. The role of sustainability scores is to provide a direct indicator of the company sustainability performance. The machine learning model, Random Forest Regressor, is deployed to evaluate the performance of the machine learning model in generating sustainability scores under a supervised learning style. The data used in the development of the machine learning model is extracted from company sustainability reports available online. The results of model testing deliver promising results with the performance of the model improving with sample size. However, the model failed to deliver consistently accurate predictions, mainly due to the small data size and the imbalance distribution of data in the database. Lastly, recommendations for the challenges of machine learning integration with sustainability performance management are suggested for the improvement in the data collection and processing during database preparation. 2024-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/7015/1/Ng_Jia_Ying_2006527.pdf Ng, Jia Ying (2024) The integration of machine learning and decision support system in sustainability performance management. Final Year Project, UTAR. http://eprints.utar.edu.my/7015/ |
| spellingShingle | HD28 Management. Industrial Management TD Environmental technology. Sanitary engineering Ng, Jia Ying The integration of machine learning and decision support system in sustainability performance management |
| title | The integration of machine learning and decision support system in sustainability performance management
|
| title_full | The integration of machine learning and decision support system in sustainability performance management
|
| title_fullStr | The integration of machine learning and decision support system in sustainability performance management
|
| title_full_unstemmed | The integration of machine learning and decision support system in sustainability performance management
|
| title_short | The integration of machine learning and decision support system in sustainability performance management
|
| title_sort | integration of machine learning and decision support system in sustainability performance management |
| topic | HD28 Management. Industrial Management TD Environmental technology. Sanitary engineering |
| url | http://eprints.utar.edu.my/7015/ http://eprints.utar.edu.my/7015/1/Ng_Jia_Ying_2006527.pdf |