Evaluation of Motorcycle Brands Using Multi-attribute Decision-Making Method Under Single-Valued Neutrosophic Cubic Hypersoft Set Environment

The process of motorcycles evaluation is intricate and influenced by several factors that are uncertain, indeterminate and vague. It is difficult to estimate to what extent the choice will satisfy all requirements and change with the times. The theoretical frameworks such as hypersoft sets, interval and single-valued neutrosophic sets are useful in managing such vagueness and uncertainty. This study introduces a novel theoretical framework; the single-valued neutrosophic cubic hypersoft set (svNCHSS), to mitigate the loss of useful data. In comparison to the frameworks mentioned above, the svNCHSS is more adaptable in handling ambiguous and unpredictable circumstances because it incorporates all of their limitations as a single model. The set-theoretic operations like P-union $$(\sqcup _{P})$$ , P-intersection $$( \sqcap _{P})$$ , R-union $$( \sqcup _{R})$$ , R-intersection $$(\sqcap _{R})$$ , AND- and OR-operations are investigated for svNCHSS environment. Two potent algorithms are proposed in the context of a decision-assisted mechanism that employs AND- and OR-operations for the evaluation of motorbikes taking into account multi-argument-based factors. To evaluate the suggested algorithms’ effectiveness, a prototype case study is used for validation. The computed results are then compared. The structural comparison reveals the flexibility of svNCHSS, making its aggregation operations a useful tool for a variety of industrial applications, including risk assessment, process improvement, and decision-making.