Modeling random and non-random decision uncertainty in ratings data: a fuzzy beta model

• Published in: Advances in statistical analysis : AStA : a journal of the German Statistical Society Vol. 106; no. 1; pp. 145 - 173
• Main Authors: Calcagnì, Antonio, Lombardi, Luigi
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2022; Springer Nature B.V
• Subjects: Algorithms; Applied statistics; Decision making; Econometrics; Economics; Finance; Insurance; Management; Mathematics and Statistics; Modelling; Original Paper; Probability Theory and Stochastic Processes; Ratings; Ratings & rankings; Statistics; Statistics for Business; Uncertainty; Fuzzy ratings data; Decision uncertainty; Customer satisfaction; Fuzzy data analysis; 62P25; 62-07; Risk-taking behaviors; Beta fuzzy numbers; Beta linear model; 62J12

Modeling human ratings data subject to raters’ decision uncertainty is an attractive problem in applied statistics. In view of the complex interplay between emotion and decision making in rating processes, final raters’ choices seldom reflect the true underlying raters’ responses. Rather, they are i...