## 2 Literature Review
### Type-2 Fuzzy Environments and Group Decision Making  
IVT2 FSs are accepted as an extension of traditional fuzzy sets. However, IVT2 FSs provide for a more comprehensive representation of ambiguity, vagueness, or uncertainty. This comprehensive representation is characterized by interval membership functions. IVT2 FSs effectively capture the complexities of real-world cases under imprecise information [10]. Due to this capability, IVT2 FSs could be applied as a multicriteria decision-making method to evaluate alternatives under conflicting criteria. In this context, [PERSON] and [PERSON] (2014) presents the advantages of IVT2 FSs in various applications such as engineering, healthcare, management, economics, and political science [11]. [PERSON] et al. (2020) applied IVT2F-TOPSIS to capture linguistic variables in decision-making. The proposed approach shows how IVT2 FSs can provide a more detailed modeling framework [12]. In addition, the integration of IVT2 FSs with the Analytic Hierarchy Process (AHP) to enhance decision-making models is provided for a more comprehensive evaluation of alternatives by incorporating both qualitative and quantitative criteria [13]. [PERSON] et al. (2016) show the flexibility of IVT2 FSs in fuzzy shortest-path problems [14]. Therefore, IVT2F-TOPSIS could be applied to evaluate complex alternatives in international disputes where decisions are often affected by different qualitative criteria such as legal, political, and social considerations. [PERSON] (2023) emphasizes the defuzzification process in IVT2 FSs because the defuzzification process is one of the vital processes when fuzzy evaluations transform to crisp number outcomes [15]. The transition may cause a loss of information; thus, maintaining the integrity of fuzzy evaluations is crucial. Thus, IVT2 FSs help handle this ambiguity accurately and effectively in decision-making. IVT2 FSs are defined theoretically in [PERSON] et al. (2017) [16]. They extend traditional decision-making methods by comprehensive analysis of risk and uncertainty. Furthermore, [PERSON] et al. (2015) provide a literature review of the development of fuzzy logic starting from type-1 to type-2 fuzzy sets [17]. This review work is a resource for understanding the current applications of fuzzy logic in decision-making. IVT2 FSs are applied in decision-making and preferred in various studies. [PERSON] et al. (2023) apply fuzzy logic for viability analysis of tidal turbine installations [18]. [PERSON] (2023) introduces a novel intuitionistic fuzzy method to enhance the traditional TOPSIS approach. The proposed method was applied to risk-based supplier selection problems. The results of these studies imply that the potential for similar methodologies could be applied to resolving international disputes, where multiple decision-makers and conflicting criteria appear simultaneously [19]. [PERSON] et al. (2019) worked on a hybrid decision-making model to utilize IVT2 FSs to evaluate economic development plans [20]. The proposed model used the hesitant fuzzy linguistic term sets to address MCDM challenges. Other fuzzy types such as type-1 and type-2 fuzzy systems in decision support systems are analyzed by [PERSON] et al. (2018), which imply that type-2 fuzzy systems offer enhanced capabilities for handling uncertainty and are more suitable for complex decision-making models under a fuzzy environment [21]. [PERSON] et al. (2021) applied the q-Rung Orthopair Fuzzy TOPSIS method to green supplier selection problems. They showed that q-Rung Orthopair Fuzzy outperformed classical and intuitionistic fuzzy TOPSIS methodologies. The results of this research indicate that enhanced fuzzy methodologies can yield more stable and accurate results [22]. Therefore, such extensions and improvements in fuzzy logic integration in TOPSIS help researchers apply them in international dispute resolution. Because decision-makers in international dispute resolution frequently need to translate fuzzy evaluations into actionable outcomes.