Evaluating Green Marketing Practices in the Logistics Industry Under Type-2 Neutrosophic Fuzzy Environment

Abstract

The logistics industry is under increasing pressure to implement Green Marketing (GM) strategies in response to growing environmental concerns and rising stakeholder expectations. Although international organizations and governments encourage the adoption of sustainability, practical decision support tools for executing GM strategies, particularly within logistics Small and Medium-Sized Enterprises (SMEs), remain underdeveloped. This study tries to advance the literature by introducing a novel hybrid Multi-Criteria Decision-Making (MCDM) framework that uniquely integrates Delphi, CRiteria Importance Through Inter-criteria Correlation (CRITIC), and Mixed Aggregation by cOmprehensive Normalization Technique (MACONT) methods with Type-2 Neutrosophic Numbers (T2NNs). Unlike prior fuzzy MCDM studies, this integration simultaneously incorporates subjective and objective weighting, preserves ordinal consistency, and explicitly manages higher-order uncertainty. The model is applied to evaluate the GM performance of logistics SMEs in Turkey, identify key evaluation criteria, and rank firms accordingly. Among the evaluated criteria, "Land usage" and "Investment in reducing greenhouse gas emissions" emerged as the most influential, while "Omsan Logistics" is identified as the top-performing firm in GM practices. The model's reliability is then confirmed through a two-phase sensitivity analysis, demonstrating robustness across different scenarios. The findings of this work provide significant implications for logistics managers, policymakers, and researchers aiming to enhance environmental performance and make informed decisions in complex and ambiguous operational environments.