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Review Highlights•Methodology for the newly proposed decision-making technique using IT2 FSs and HFLTSs is provided in detail, with a working illustration on executive decision making.•The model intakes hesitant-linguistic responses in executive-settings, converts them into IT2 FSs, followed by computation of utility values based on regret theory.•Comparisons with existing models reveal that the proposed methodology is more user-friendly and also provides relevant and effective ranks.AbstractPresence of globally-affecting issues, such as the recent COVID-19 pandemic is a major factor impacting the operation of services provided by high-stake companies. These factors create huge hindrances in the regular and proper operations of companies in staying relevant in market while catering to the services they provide. In such cases, in order to maintain and achieve their internal goals should any possible losses that the grave situation might incur, relevant experts within these firms must arrive at optimal decisions taking into account human cognition as well as all possibilities of risk and regrets. A suitable regret theory based linguistic decision-making model called THREAD which computes with inherent hesitancy using interval type-2 fuzzy sets (IT2 FS) and hesitant fuzzy linguistic term sets-based techniques is introduced in this paper.Graphical abstract
Seth et al. (Sun,) studied this question.
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