Fuzzified Likert scales in group multiple-criteria evaluation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F18%3A73581261" target="_blank" >RIV/61989592:15210/18:73581261 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-60207-3_11" target="_blank" >http://dx.doi.org/10.1007/978-3-319-60207-3_11</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-60207-3_11" target="_blank" >10.1007/978-3-319-60207-3_11</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fuzzified Likert scales in group multiple-criteria evaluation

Popis výsledku v původním jazyce

Likert scales have been in use since 1930s as tool for attitude expression in many fields of social science. Recently there have even been several attempts for the fuzzification of this instrument. In this chapter we explore the possibility of their use in multiple-criteria multi-expert evaluation.We focus on discrete fuzzy Likert scales, that are a generalization of the standard Likert scales. We propose a methodology that deals with the non-uniformity of the distribution of linguistic labels along the underlying ordinal evaluation scale and also with possible response bias.We also consider the analogy of Likert scales (crisp and fuzzy) on continuous universes. Likert-type evaluations of an alternative with respect to various criteria are represented using histograms. Histograms are also used to aggregate the Likert- type evaluations. A transformation of the multi-expert multiple-criteria evaluation represented by a histogram into a 3-bin histogram to control for the response bias is performed and an ideal-evaluation 3-bin histogram is defined. We propose a distance measure to assess the closeness of the overall evaluation to the ideal and suggest the use of the proposed methodology in multiple-criteria multi-expert evaluation.

Název v anglickém jazyce

Fuzzified Likert scales in group multiple-criteria evaluation

Popis výsledku anglicky

Likert scales have been in use since 1930s as tool for attitude expression in many fields of social science. Recently there have even been several attempts for the fuzzification of this instrument. In this chapter we explore the possibility of their use in multiple-criteria multi-expert evaluation.We focus on discrete fuzzy Likert scales, that are a generalization of the standard Likert scales. We propose a methodology that deals with the non-uniformity of the distribution of linguistic labels along the underlying ordinal evaluation scale and also with possible response bias.We also consider the analogy of Likert scales (crisp and fuzzy) on continuous universes. Likert-type evaluations of an alternative with respect to various criteria are represented using histograms. Histograms are also used to aggregate the Likert- type evaluations. A transformation of the multi-expert multiple-criteria evaluation represented by a histogram into a 3-bin histogram to control for the response bias is performed and an ideal-evaluation 3-bin histogram is defined. We propose a distance measure to assess the closeness of the overall evaluation to the ideal and suggest the use of the proposed methodology in multiple-criteria multi-expert evaluation.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Soft Computing Applications for Group Decision-making and Consensus Modeling

ISBN

978-3-319-60206-6

Počet stran výsledku

21

Strana od-do

165-185

Počet stran knihy

488

Název nakladatele

Springer International Publishing AG

Místo vydání

Cham

Kód UT WoS kapitoly

—