Selection of Investment Policy Using a Novel Three-Way Group Decision Model under Intuitionistic Hesitant Fuzzy Sets

In today’s fast-paced and dynamic business environment, investment decision making is becoming increasingly complex due to the inherent uncertainty ambiguity of financial data. Traditional decision-making models that rely on crisp precise data are no longer sufficient address these challenges. Fuzzy logic-based can handle uncertain imprecise have become popular in recent years. However, they still face limitations when dealing with complex, multi-criteria problems. To overcome limitations, this paper, we propose a novel three-way group model incorporates decision-theoretic rough sets intuitionistic hesitant fuzzy provide more robust accurate approach for selecting an policy. The set theory used reduce information redundancy inconsistency process. allow makers express their degrees hesitancy decision, which not possible traditional sets. combine opinions, introduce aggregation operators under (IHFSs), including IHF Aczel-Alsina average (IHFAAA) operator, weighted (IHFAAWA?) ordered (IHFAAOWA?) hybrid (IHFAAHA?) operator. These desirable properties such as idempotency, boundedness, monotonicity, essential reliable A mathematical presented case study evaluate effectiveness proposed results show effective provides policy recommendations compared existing methods. This research help investors analysts better decisions achieving goals.