Response bias in decision making: an application of intuitionistic fuzzy targeting decision uncertainties
by Arnab Kundu; Tripti Bej; Samirranjan Adhikari
International Journal of Fuzzy Computation and Modelling (IJFCM), Vol. 4, No. 1, 2022

Abstract: The human cognitive structure is very uncertain and ever-elusive to arrest. The purpose of this study was to formulate a mathematical model to evade response bias latent in the quantification process in any decision-making by applying intuitionistic fuzzy logic, potent in arresting uncertainties. Following this research aim, a sample problem was adopted from the school setting regarding the election of a class monitor based on an opinion survey among five teachers on a Likert scale. The numerical decision values were converted to intuitionistic fuzzy. Findings revealed a palpable difference between Likert values and their Fuzzified corresponding values wherefrom the authors empirically deduced that fuzzified result is more precise over the quantified Likert values considering respondents' biases, uncertainties, inter-rater agreements, or disagreements. Finally, the researchers proposed the intuitionistic fuzzy score function evolved in this study, needs to be investigated with a larger sample size to draw more authentication.

Online publication date: Mon, 25-Jul-2022

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