evaluating blockchain integration in intelligent logistics ecosystems: a comparative mcdm approach

Objective: supply chain management in dynamic environments requires advanced digital technologies to enhance transparency, security, and operational efficiency. blockchain technology has emerged as a promising solution for improving traceability and trust in intelligent logistics ecosystems. the objective of this study is to evaluate and compare blockchain platform alternatives using a structured multi-criteria decision-making framework in order to support technology selection in modern logistics systems.methods: this research applies a comparative multi-criteria decision-making approach integrating analytic hierarchy process (ahp), fuzzy analytic hierarchy process (fahp), ahp-topsis, and fuzzy ahp-fuzzy topsis methods. a hierarchical evaluation model was developed. expert judgments and literature-based criteria were used to determine weights and assess the relative performance of blockchain platform alternatives.results: the evaluation results demonstrate consistent rankings across both crisp and fuzzy decision models. sensitivity analysis further confirms the robustness of the ranking results under different weighting scenarios.conclusion: the findings highlight the importance of scalability, interoperability, and transparency when selecting blockchain platforms for intelligent logistics ecosystems. the proposed framework provides decision-makers with a systematic evaluation tool that can support strategic technology adoption and improve decision quality in supply chain digital transformation initiatives.