Fuzzified Likert Scales in Group Multiple-Criteria Evaluation

Stoklasa, Jan; Talášek, Tomáš; Luukka, Pasi

doi:10.1007/978-3-319-60207-3_11

Cited by 11 publications

(13 citation statements)

References 22 publications

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“…With a decreasing ability to measure the values of the criterion, the need for qualitative approach to its assessment increases. Linguistic scales (Zadeh 1975), Likert-type scales (Likert 1932;Stoklasa, Talášek, Kubátová and Seitlová 2017) or semantic-differential-type scales (Osgood 1964;Osgood, Suci and Tannenbaum 1957) anchored with linguistic values are used. Unfortunately the use of linguistic values introduces another "degree of freedom" in the evaluation process.…”

Section: Introductionmentioning

confidence: 99%

“…The uncertainty inherent in the use of linguistic labels and linguistic variables has to be reflected appropriately (see e.g. Stoklasa 2014;Stoklasa, Talášek and Musilová 2014;Talašová, Stoklasa and Holeček 2014) and in many cases this is done by the use of fuzzy modelling (Fiss 2011;Stoklasa, Talašová and Holeček 2011;Stoklasa, Talášek et al 2014;Stoklasa, Talášek and Luukka 2018;Talašová et al 2014), interval-valued modelling (Stoklasa, Talášek and Stoklasová 2016;Stoklasa, Talášek and Stoklasová 2017;Stoklasa, Talášek and Stoklasová 2018) or by finding alternative lossless representations of the set of evaluations instead of their direct aggregation (Stoklasa, Talášek, Kubátová et al 2017).…”

Section: Introductionmentioning

confidence: 99%

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Reflecting Emotional Aspects and Uncertainty in Multi-expert Evaluation: One Step Closer to a Soft Design-Alternative Evaluation Methodology

Stoklasa

Talášek

Stoklasová³

2018

Advances in Systematic Creativity

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Modelling to generate alternatives (MGA)an approach to optimization aiming on providing not one, but more feasible solutions as different from each other as possible, all with the values of the objective function close to the optimal value (see e.g. Brill, Chang and Hopkins 1982 or Yeomans 2011).Kansei engineeringit is a consumer-oriented approach to product design based on the reflection of less tangible aspects such as feelings concerning the product in the design process. The aim is to inspire specific feelings by the features of the design alternative (see Nagamachi 1995;Jindo, Hirasago and Nagamachi 1995;or Kobayashi and Kinumura 2017).Kansei adjectives -Kansei words in the form of adjectives, i.e. words describing customers' or consumers' needs, feelings and perceptions concerning the product (see e.g. Jiao, Zhang and Helander (2006) for a Kansei mining system).Kansei taggroup or cluster of Kansei adjective corresponding to the same concept or basic emotion (Xu and Wunsch (2009) provide an example of a clustering algorithm suitable for the creation of Kanseiadjectives clusters, i.e. Kansei tags).Likert scalea psychometric measurement instrument popularized by Likert (see e.g. Likert ( 1932)) frequently used in questionnaires. Likert scales are discrete scales with linguistic labels on the agreedisagree or similar continuums, which are supposed to be symmetrical with respect to the middle point (either present in the scale itself, or theoretical; e.g. strongly agree, agree, undecided, disagree, strongly disagree) of the scale. Usually the equidistance of the scale-values is assumed.Semantic differentiala method proposed by Osgood, Suci and Tannenbaum (1957) for the measurement of attitudes. The method utilizes discrete bipolar-adjective scales to get input information and uses factor analysis to define the semantic space and represents the attitude towards a concept (or its connotative meaning) as a point in this n-dimensional semantic space.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reflecting Emotional Aspects and Uncertainty in Multi-expert Evaluation: One Step Closer to a Soft Design-Alternative Evaluation Methodology

Stoklasa

Talášek

Stoklasová³

2018

Advances in Systematic Creativity

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“…This step potentially introduces several methodological issues (see e.g. [9][10][11][12][13] for a more detailed discussion of some of them).…”

Section: B Different Configurations Of the Likert Scales Used In The ...mentioning

confidence: 99%

“…In this research we are focusing on the reasonability of performing calculations with the numerical values of the scales [11] that is connected with the (non)equidistance of the used numerical meanings of the linguistic values of the scale [9] and the differences in the perception of the relative distances between the linguistic values as compared to the perceived distances of their numerical meanings. We also reflect the potential ambiguity of the linguistic terms and their different interpretation by different individuals that might result in a different numerical value being the appropriate meaning of the linguistic term for different individuals [10].…”

Section: B Different Configurations Of the Likert Scales Used In The ...mentioning

confidence: 99%

“…Obviously, when the goal of simplicity of obtaining input data is set, there are drawbacks to be expected in the process of the analysis of the data. In this case we will discuss the effect of the calibration of the numerical values of discrete Likert scales with linguistic labels [8,9] and also the possibility of getting more insights or more real-life representation of the preferences, attitudes or values using the tools of fuzzy set theory [10]. We are well aware that some election surveys and popular voter "calculators" providing fast and popular "compatibility" suggestions to voters use a similar approach, but these are frequently using just a binary scale and do not offer any customizability.…”

Section: Introductionmentioning

confidence: 99%

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The voter's guide to the galaxy—a multiple-criteria fuzzy decision-support tool for voters and a fresh take on election survey methods

Panzeri¹,

Stoklasová²,

Stoklasa³

2022

Annals of Computer Science and Information Systems

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This paper suggests a multiple-criteria decisionsupport tool for voters, that compares the attitudes of the voters with the declared attitudes of the political parties in several sets of relevant issues. The model intends to identify parties that seem to provide the best fit with the voter attitude-wise. The data input methodology uses discrete 5-point Likert-type scales. We investigate the effect of the inclusion of weights of different sets of issues, of the numerical anchors of the values of the Likert-type scales and also of the potential presence of extremity/leniency effect on the suggestion of the "most compatible" political party suggestion. We also propose a simple fuzzyrule based evaluation tool to identify serious incompatibilities or desired compatibilities in the attitudes of the voter and the party to the relevant issues. This tool introduces (un)acceptability thresholds for the differences in attitudes between the parties and the respondents and provides lists of parties to vote for or to avoid voting for accompanied by the strengths of these suggestions. The tool is shown to have several desirable features including lower sensitivity to small differences in the attitudes, respondents' ability to express their preferences and also preventing the compensation of unacceptable differences in some categories of important issues by high compatibility in the other categories.

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Likert Scale-Based Evaluations with Flexible Fuzzy Numbers

Dombi

Jónás

2020

Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods With Applications

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Fuzzified Likert Scales in Group Multiple-Criteria Evaluation

Cited by 11 publications

References 22 publications

Reflecting Emotional Aspects and Uncertainty in Multi-expert Evaluation: One Step Closer to a Soft Design-Alternative Evaluation Methodology

Reflecting Emotional Aspects and Uncertainty in Multi-expert Evaluation: One Step Closer to a Soft Design-Alternative Evaluation Methodology

The voter's guide to the galaxy—a multiple-criteria fuzzy decision-support tool for voters and a fresh take on election survey methods

Likert Scale-Based Evaluations with Flexible Fuzzy Numbers

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