Green Energy Adoption under Uncertainty: An MCDM Approach

The supplier selection in green energy domain is a complex process not only because of many criteria but more because of mulltiple types of uncertainty. In this paper, an approach is presented to rank suppliers in the renewable energy domain in the face of uncertainty due to uncertain factors such as government policy, etc., and hesitancy of experts in subjective evaluations. The proposed approach is accomplished through a framework derived from the intuitionistic fuzzy set (IFS) theory. A novel aggregation operator is also proposed, which promises potential in many applications. The proposed approach is distinguished with its ability to accommodate multi-faceted uncertainty and opens avenues for many applications. The usefulness of the work is illustrated through real case study.Supplier selection in the green energy sector is a complex decision-making process, primarily due to the presence of multiple evaluation criteria and various forms of uncertainty. This paper presents a novel approach for ranking suppliers in the renewable energy domain by addressing uncertainties arising from factors such as fluctuating government policies and expert hesitancy in subjective assessments. The methodology is grounded in Intuitionistic Fuzzy Set (IFS) theory and incorporates a newly developed aggregation operator designed to effectively handle multi-dimensional uncertainty. The proposed framework demonstrates strong potential for broader applications and is validated through a real-world case study, showcasing its practical relevance and robustness in uncertain decision-making environments.