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The 5-Item Likert Scale and Percentage Scale Correspondence with Implications for the Use of Models with (Fuzzy) Linguistic Variables

Author

Listed:
  • Jiří Mazurek

    (Silesian University in Opava)

  • Cristina Pérez Rico

    (EPN - Escuela Politécnica Nacional)

  • Carlos Fernández García

    (UDLA - Universidad de Las Américas [Ecuador])

  • Jean-Pierre Magnot

    (LAREMA - Laboratoire Angevin de Recherche en Mathématiques - UA - Université d'Angers - CNRS - Centre National de la Recherche Scientifique)

  • Tristan Magnot

    (AMU IMPGT - Institut de management public et de gouvernance territoriale - AMU - Aix Marseille Université)

Abstract

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.

Suggested Citation

  • Jiří Mazurek & Cristina Pérez Rico & Carlos Fernández García & Jean-Pierre Magnot & Tristan Magnot, 2021. "The 5-Item Likert Scale and Percentage Scale Correspondence with Implications for the Use of Models with (Fuzzy) Linguistic Variables," Post-Print hal-03194889, HAL.
    • Handle: RePEc:hal:journl:hal-03194889
    DOI: 10.46661/revmetodoscuanteconempresa.4010
    Note: View the original document on HAL open archive server: https://hal.science/hal-03194889
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    Cited by:

    1. Carmen Lozano & Cesaire Chiatchoua, 2022. "Conditions Influencing Salary of the Automotive Industry in Mexico City—A Linguistic Fuzzy-Set Approach," Sustainability, MDPI, vol. 14(11), pages 1-22, May.

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