Toward sustainable maritime logistics with electric reach stackers: A spherical fuzzy decision-making framework

The electrification of cargo-handling equipment has become increasingly important for reducing the environmental impacts of port operations. However, selecting an appropriate electric reach stacker is a complex procurement decision involving multiple operational, environmental, and technical criteria, often evaluated using incomplete and heterogeneous performance data. This study develops an integrated spherical fuzzy Multi-Criteria Decision-Making (MCDM) framework to support this decision. The proposed framework combines Spherical Fuzzy Delphi (SF-Delphi), K-means clustering, and the Spherical Fuzzy Mixed Aggregation by COmprehensive Normalization Technique (SF-MACONT), which incorporates multiple normalization procedures. Methodologically, the study introduces a spherical fuzzy score function that explicitly accounts for hesitation when processing expert assessments. It also integrates criteria refinement, uncertainty modeling, alternative ranking, and robustness evaluation within an integrated decision-making framework. The applicability of the proposed approach is demonstrated through a real-world case study at a Mediterranean port in Türkiye. Drawing on manufacturer performance reports and expert evaluations, five electric reach stackers are assessed against 11 criteria. The results identify energy efficiency, carbon footprint, and compliance with emission standards as the most influential criteria, while Kalmar emerges as the preferred alternative. Sensitivity analysis, rank-reversal testing, and comparisons with state-of-the-art spherical fuzzy MCDM methods confirm that the resulting recommendation remains stable across the scenarios examined.