Abstract
This study addresses the challenge of improving the performance of waste-to-value investments by identifying the most critical strategies and operational criteria under limited resources. The main problem in this field is the lack of analytical frameworks that prioritize investment opportunities by incorporating queuing theory based operational performance indicators, such as congestion and waiting related measures, into strategic decision making. Although existing studies examine waste-to-value systems, the integration of queuing theory parameters into strategic decision making remains limited, creating a significant gap in the literature. To overcome this limitation, the study proposes a novel fuzzy decision-making model based on an extensive literature review and expert evaluations. Expert importance weights are determined using a Manhattan distance-based centrality approach, criteria weights are calculated through the cognitive maps technique to reflect interdependencies, and investment alternatives are ranked using an orthogonal metric robust aggregation method, while uncertainty is handled via cipher fuzzy sets. The results reveal that waiting time is the most influential queuing theory-based performance indicator, and plastic bottle remanufacturer and cardboard box recycler are the most essential waste-to-value investment opportunities. These findings highlight the importance of strategies that reduce operational delays and prioritize recyclable packaging waste, and the proposed model offers a structured and robust framework to support effective waste-to-value investment planning.