Descriptive analysis of responses to items in questionnaires. Why not using a fuzzy rating scale?

被引:37
作者
Asuncion Lubiano, Maria [1 ]
de la Rosa de Saa, Sara [1 ,2 ]
Montenegro, Manuel [1 ]
Sinova, Beatriz [1 ]
Angeles Gil, Maria [1 ]
机构
[1] Univ Oviedo, Fac Ciencias, Dept Estadist IO & DM, E-33071 Oviedo, Spain
[2] Vienna Univ Technol, Inst Stochast & Wirtschaftsmath, Wiedner Hauptstr 8-10-E105, A-1040 Vienna, Austria
关键词
Descriptive summary measures; Fuzzy data; Fuzzy linguistic data; Fuzzy rating scale; Questionnaire; TRAPEZOIDAL APPROXIMATIONS; STATISTICAL-ANALYSIS; LINGUISTIC APPROACH; RECOMMENDER SYSTEM; DECISION-MAKING; SERVICE QUALITY; NUMBERS; MODEL; METHODOLOGY; INFORMATION;
D O I
10.1016/j.ins.2016.04.029
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In evaluating aspects like quality perception, satisfaction or attitude which are intrinsically imprecise, the fuzzy rating scale has been introduced as a psychometric tool that allows evaluators to give flexible and quite accurate, albeit non numerical, ratings. The fuzzy rating scale integrates the skills associated with the visual analogue scale, because of the total freedom in assessing ratings, with the ability of fuzzy linguistic variables to capture the natural imprecision in evaluating such aspects. Thanks to a recent methodology, the descriptive analysis of the responses to a fuzzy rating scale-based questionnaire can be now carried out. This paper aims to illustrate such an analysis through a real-life example, as well as to show that statistical conclusions can often be rather different from the conclusions one could get from either Likert scale based responses or their fuzzy linguistic encoding. This difference encourages the use of the fuzzy rating scale when statistical conclusions are important, similarly to the use of exact real-valued data instead of grouping them. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:131 / 148
页数:18
相关论文
共 68 条
[1]   The evaluation of hospital service quality by fuzzy MCDM [J].
Akdag, Herman ;
Kalayci, Turgay ;
Karagoz, Suat ;
Zulfikar, Haluk ;
Giz, Deniz .
APPLIED SOFT COMPUTING, 2014, 23 :239-248
[2]   Analyzing data from a fuzzy rating scale-based questionnaire. A case study [J].
Angeles Gil, Maria ;
Asuncion Lubiano, Maria ;
de la Rosa de Saa, Sara ;
Sinova, Beatriz .
PSICOTHEMA, 2015, 27 (02) :182-191
[3]  
[Anonymous], 2008, Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, DOI DOI 10.1027/1614-2241.4.2.73
[4]   Hypothesis testing for means in connection with fuzzy rating scale-based data: algorithms and applications [J].
Asuncion Lubiano, Maria ;
Montenegro, Manuel ;
Sinova, Beatriz ;
de la Rosa de Saa, Sara ;
Angeles Gil, Maria .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2016, 251 (03) :918-929
[5]   Empirical Sensitivity Analysis on the Influence of the Shape of Fuzzy Data on the Estimation of Some Statistical Measures [J].
Asuncion Lubiano, Maria ;
de la Rosa de Saa, Sara ;
Sinova, Beatriz ;
Angeles Gil, Maria .
STRENGTHENING LINKS BETWEEN DATA ANALYSIS AND SOFT COMPUTING, 2015, 315 :123-131
[6]   Trapezoidal approximation and aggregation [J].
Ban, Adrian ;
Coroianu, Lucian ;
Grzegorzewski, Przemyslaw .
FUZZY SETS AND SYSTEMS, 2011, 177 (01) :45-59
[7]   Expression of uncertainty in fuzzy scales based measurements [J].
Benoit, Eric .
MEASUREMENT, 2013, 46 (09) :3778-3782
[8]   The role of fuzzy scales in measurement theory [J].
Benoit, Eric ;
Foulloy, Laurent .
MEASUREMENT, 2013, 46 (08) :2921-2926
[9]  
Bertoluzza C., 1995, MATHWARE SOFT COMPUT, V2, P71
[10]  
Blagoveschensky Y. N., 2012, FUZZY LOGIC ALGORITH, P3