An integrated CRITIC and EDAS model using linguistic T spherical fuzzy Hamacher aggregation operators and its application to group decision making

Abstract

Green technologies are defined as the utilization of advanced scientific and technological methodologies to fabricate products that minimize environmental impact. The assessment of green technology alternatives necessitates a comprehensive analysis incorporating a multitude of criteria, many of which may be conflicting. Optimal selections must encompass technical performance, economic feasibility, environmental sustainability, and societal implications. Additionally, the data gaps and vague information typical when dealing with emerging technologies make traditional techniques unproductive. This work thus proposes a dynamic multi-criteria group decision making (MCGDM) model by integrating the Criteria Importance Through Intercriteria Correlation (CRITIC) method with the Evaluation based on Distance from Average Solution (EDAS) technique under the linguistic T-spherical fuzzy (LT-SF) environment. Initially, we define some Hamacher operations for LT-SF numbers (LT-SFNs) and then use them to develop some Hamacher aggregation operators (HAOs) synthesizing expert assessments. Meanwhile, some prominent features of these newly developed operators are also discussed. Next, we introduce a novel LT-SF-CRITIC-EDAS model, where LT-SF-CRITIC determines criteria weights, and LT-SF-EDAS evaluates the ranking of available alternatives. To illustrate the designed model’s applicability, we apply it to a real-world scenario of selecting the most appropriate green technology from available options. Finally, a sensitivity analysis and comparative evaluation against existing methods demonstrate our proposed approach’s superior feasibility and reliability. This research contributes to advancing decision making methodologies for assessing green technologies under complex and uncertain conditions.