Integrating multi-criteria decision-making methods for plastic waste mitigation: A systematic literature review
Mitigation of plastic waste problem has been the center of interest due to the growing and ever increasing of plastic consumption and waste. A myriad of solutions to plastic waste problem has been proposed, although the effectiveness might vary depending on factors such as location, population, and...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Penerbit Akademia Baru
2025
|
| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/45935/1/FULLTEXT.pdf https://eprints.ums.edu.my/id/eprint/45935/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Mitigation of plastic waste problem has been the center of interest due to the growing and ever increasing of plastic consumption and waste. A myriad of solutions to plastic waste problem has been proposed, although the effectiveness might vary depending on factors such as location, population, and financial support. Therefore, selecting the most viable solution is crucial to ensure the success of mitigation efforts. This paper attempts to review recent research on plastic waste mitigation using analytical and prediction-based approach. To identify the application of Multi Criteria Decision Making (MCDM) in plastic consumption and waste management, a wide range of publications published between 2019 and 2023 were examined. The findings showed that the adoption of MCDM is prevalent in the manufacturing and waste management sector, with AHP and TOPSIS being the primary MCDM methods frequently used in previous studies. The environment, economic, and society domain of the Triple Bottom Line (TBL) are commonly applied to assess sustainability of activities or process, which often concludes with the selection of best solution and alternatives of the given problem. This review underscores the potential yet underexploited role of Multi-Criteria Decision Making (MCDM) in sectors like the food industry. Adopting this method helps address concerns about plastic consumption and waste mitigation by providing objective and reliable results, which is crucial for decision makers. |
|---|