Analyzing the Service Quality Evaluation of Railway Cold Chain Logistics Based on Probabilistic Linguistic Group Decision-Making

The evaluation of railway cold chain logistics service quality is essential for ensuring the safe, efficient, and reliable transport of temperature-sensitive goods, such as food and pharmaceuticals. It identifies strengths and weaknesses in logistics processes, enabling continuous improvement and optimal resource allocation. As the evaluation of railway cold chain logistics involves multiple-attribute group decision-making (MAGDM), this study employs the TODIM and PROMETHEE approaches to propose a robust framework. To effectively manage fuzzy information during the quality evaluation process, probabilistic linguistic term sets (PLTSs) are utilized. The study manages the probabilistic linguistic TODIM-PROMETHEE (PL-TODIM-PROMETHEE) approach, which is specifically designed to address MAGDM problems within the PLTSs framework. To determine weight values in this context, the MEREC approach is applied. Finally, a numerical example evaluating the service quality of railway cold chain logistics is provided to validate the effectiveness of the PL-TODIM-PROMETHEE approach.