Abstract
Polyethylene terephthalate (PET) waste poses significant environmental, social, and economic challenges due to its non-biodegradability and inefficient management practices. This study aims to address these challenges by optimizing PET waste collection methods using Multi-Criteria Decision Analysis (MCDA) approaches, including the Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). These methods provide a structured framework for evaluating alternatives based on criteria such as costs, environmental impacts, social acceptance, and operational feasibility. PET waste, often discarded improperly, contributes to ecosystem degradation, resource wastage, and economic losses, necessitating innovative and sustainable collection strategies. The primary objective of the study is to identify and prioritize the most effective PET waste collection methods. Data collection involved gathering insights from stakeholders in the bottled water industry, including manufacturers, policymakers, and environmentalists. The methodology combines expert opinions, stakeholder input, and quantitative analyses to weigh and rank decision criteria systematically. AHP was used to assign priorities to criteria and the objective weights of the criteria. The five criteria considered in this study are: initial investment cost, operational cost, transportation cost, environmental risk, employment potential, and the objective weights allocated to them by AHP analysis are 0.4952, 0.1997, 0.1565, 0.0870, and 0.0616 are, respectively. TOPSIS was used to determine alternatives' proximity to ideal solutions, and VIKOR to analyse trade-offs and propose compromise solutions. Sensitivity analyses using Entropy Weights and Equal Weights were conducted to ensure the robustness of decision outcomes. Findings indicate that the optimization of PET waste collection can reduce environmental pollution, minimize costs, and enhance social acceptance. Among the evaluated methods, those integrating economic feasibility with environmental benefits ranked highest. Results also highlight the importance of stakeholder engagement in ensuring the acceptance and implementation of collection strategies. Sensitivity analysis confirmed that slight variations in criteria weights did not significantly alter rankings, validating the reliability of the MCDA framework. These findings demonstrate that adopting data-driven decision-making approaches can contribute to sustainable waste management practices. This study provides policymakers and stakeholders with a practical framework for selecting optimal PET waste collection methods that align with environmental sustainability and economic
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efficiency. By leveraging MCDA techniques, the research offers actionable recommendations for addressing PET waste management challenges within the circular economy paradigm. The proposed strategies aim to promote resource conservation, reduce landfill dependency, and encourage community participation. This research contributes to advancing sustainable waste management practices and offers a replicable model for addressing similar challenges in other industries and regions.