Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry

The unclear and vague information, subjective assessments, and the languages spoken with diversity in these domains are some of the linguistic features that complicate the decision-making process in the construction industry. Language-specific terminology, context-specific terms, and terms requiring a common translation all provide challenges. Furthermore, it is challenging to compile linguistic information from several sources with a cohesive framework due to interpretation variability. To address these challenges, in this article, we propose a novel theory term as linguistic q-rung orthopair fuzzy hypersoft set (Lq-ROFHS). To aggregate the various information, we defined some new weighted averaging and geometric operators by using Einstein t-norm operations. The fundamental properties of all these stated operators are derived in detail. To illustrate the method, a multi-criteria group decision making algorithm is proposed by using the stated operators and apply them to the case study related to the selection of the best construction company. To demonstrate the efficiency of the proposed algorithm, a comparative analysis between the proposed and the several existing studies is done by comparing the order of preference. The proposed approach is a significant advancement that will enable decision-makers to navigate the complexities of their choice with greater assurance and precision using a single tool.