Abstract
The transition to sustainable agricultural supply chains requires adopting innovative, eco-friendly logistics solutions that balance cost-effectiveness, operational performance, and ecological responsibility. In this study, a comprehensive decision-making framework was developed to evaluate and prioritize green logistics alternatives in sustainable agricultural product supply chains. Seven alternatives, such as multimodal transportation, electric vehicle-based distribution, renewable energy-supported cold chain systems, and reverse logistics, were examined in line with twelve realistic criteria covering cost, environmental, technological, and operational dimensions. Triangular Fuzzy Numbers (TFNs) have been used to address uncertainty and imprecision in expert opinions. The LOPCOW method was applied to objectively determine the relative importance of the criteria, followed by the RAM method to rank the logistic alternatives according to their integrated performance. The board, comprised of four experts from diverse academic and professional backgrounds, contributed to the evaluations to ensure credibility and inclusiveness. The findings indicate that low-emission, technology-integrated solutions are key to sustainability in agricultural logistics. This research contributes to the literature by applying TFN-based LOPCOW and RAM integration in a unique context. It provides policymakers, logistics providers, and supply chain stakeholders with valuable insights for developing greener, more resilient agricultural systems.
| Keywords: | Sustainable Agriculture Agricultural Supply Chains Green Logistics Multi-Criteria Decision Making LOPCOW RAM Triangle Fuzzy Numbers Logistics Alternatives Sustainability Assessment |