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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Frustration occurs when people are obstructed or prevented from achieving a desired goal or fulfilling a perceived need. For example, when someone's input is ignored in a discussion, it can lead to feelings of frustration. Conflict, however, arises from opposing interests, goals, or actions. Conflicts can take various forms based on the nature of these opposing desires or goals.
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Hesitant and uncertain linguistics based executive decision making using risk and regret aversion: Methods,

Taniya Seth1, Pranab K Muhuri1

  • 1Department of Computer Science, South Asian University, Maidan Garhi, Rajpur Road, New Delhi-110068, India.

Methodsx
|April 25, 2024
PubMed
Summary
This summary is machine-generated.

Global crises like pandemics challenge high-stake companies. This study introduces the THREAD model, using regret theory and fuzzy logic, to aid optimal decision-making under uncertainty and hesitancy for business resilience.

Keywords:
COVID-19Hesitant fuzzy linguistic term setsInterval type-2 fuzzy setsLinguistic decision makingLinguistic uncertaintyMulti-criteria decision makingRegret theoryTHREAD stading for Type-2 fuzzy sets, Hesitancy and Regret thEory bAsed linguistic Decision making

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Area of Science:

  • Decision Sciences
  • Operations Management
  • Fuzzy Logic Applications

Background:

  • Global events, exemplified by the COVID-19 pandemic, significantly disrupt high-stake company operations.
  • Maintaining market relevance and achieving internal goals amidst crises necessitates robust decision-making frameworks.
  • Existing models may not adequately address the inherent hesitancy and risk associated with unprecedented disruptions.

Purpose of the Study:

  • To introduce a novel linguistic decision-making model for high-stake companies facing operational disruptions.
  • To incorporate human cognition, risk, and regret into a structured decision-making process.
  • To address inherent hesitancy in decision-making using advanced fuzzy set techniques.

Main Methods:

  • Development of the THREAD (Theory of Regret-based Hesitant-fuzzy linguistic decision-making) model.
  • Utilizes regret theory principles to inform optimal choices.
  • Employs interval type-2 fuzzy sets (IT2 FS) and hesitant fuzzy linguistic term sets for handling uncertainty and vagueness.

Main Results:

  • The THREAD model provides a computational framework for decision-making under conditions of uncertainty and hesitancy.
  • Demonstrates the integration of regret theory with fuzzy linguistic techniques for practical application.
  • Offers a method to compute optimal decisions considering potential risks and regrets.

Conclusions:

  • The THREAD model offers a valuable tool for high-stake companies to navigate complex decision-making during global crises.
  • Effective decision-making in disruptive environments requires accounting for cognitive factors like regret and hesitancy.
  • Fuzzy linguistic methodologies, specifically IT2 FS and hesitant fuzzy sets, are effective for modeling such complex decision problems.