Detailed Information on Publication Record
2021
The 5-Item Likert Scale and Percentage Scale Correspondence with Implications for the Use of Models with (Fuzzy) Linguistic Variables
MAZUREK, Jiří, Cristina PEREZ RICO, Carlos GARCIA FERNANDEZ, Jean-Pierre MAGNOT, Tristan MAGNOT et. al.Basic information
Original name
The 5-Item Likert Scale and Percentage Scale Correspondence with Implications for the Use of Models with (Fuzzy) Linguistic Variables
Authors
MAZUREK, Jiří (203 Czech Republic, guarantor, belonging to the institution), Cristina PEREZ RICO (724 Spain), Carlos GARCIA FERNANDEZ (724 Spain), Jean-Pierre MAGNOT (250 France) and Tristan MAGNOT (250 France)
Edition
REVISTA DE MÉTODOS CUANTITATIVOS PARA LA ECONOMÍA Y LA EMPRESA, 2021, 1886-516X
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
50202 Applied Economics, Econometrics
Country of publisher
Spain
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
RIV identification code
RIV/47813059:19520/21:A0000243
Organization unit
School of Business Administration in Karvina
Keywords in English
decision-making; evaluation; fuzzy linguistic variables; international study; Likert scale
Tags
Reviewed
Změněno: 12/4/2022 09:38, Miroslava Snopková
Abstract
V originále
The aim of this paper is to examine how people perceive correspondence between the 5-item Likert scale and the percentage scale (the LS-PS correspondence thereinafter). Are all five items of the Likert scale equidistant? Do people use the same scale when evaluating different objects? Are men and women different? Are people from different countries / cultures different? The method of the study was a questionnaire with 661 participating respondents altogether from the Czech Republic, Ecuador, and France. The results indicate that the 5-item Likert scale is neither equidistant, nor symmetrical. Furthermore, there are (highly) statistically significant differences in the LS-PS correspondence with respect to location, age, or gender of respondents. The results can be used as an input for more precise decision-making modeling associated with (fuzzy) linguistic variables.