J 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.