Type 2 fuzzy set analysis in management surveys

Numerical data from human sources is often used in management studies. MBAs' attitudes and perceptions about the commitment to their school were collected. In an earlier paper, the utility allowing respondents to draw fuzzy membership functions over the set of questionnaire answers was explored...

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Main Authors: Auephanwiriyakul S., Adrian A., Keller J.M.
Format: Conference or Workshop Item
Language:English
Published: 2014
Online Access:http://www.scopus.com/inward/record.url?eid=2-s2.0-0036456255&partnerID=40&md5=0bd3ffb07bd83c2fb534fae1565a2f34
http://cmuir.cmu.ac.th/handle/6653943832/1307
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Institution: Chiang Mai University
Language: English
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spelling th-cmuir.6653943832-13072014-08-29T09:29:07Z Type 2 fuzzy set analysis in management surveys Auephanwiriyakul S. Adrian A. Keller J.M. Numerical data from human sources is often used in management studies. MBAs' attitudes and perceptions about the commitment to their school were collected. In an earlier paper, the utility allowing respondents to draw fuzzy membership functions over the set of questionnaire answers was explored. This response format produced good qualitative information. In this paper, we look at a quantitative analysis of these linguistic responses. In particular, we develop a linguistic nearest prototype and computational efficient linguistic Hard C-Means for vectors of fuzzy sets and apply these algorithms to such "linguistic vectors" derived from a set of forty-nine subjects answering questions about students' commitment to their university. 2014-08-29T09:29:07Z 2014-08-29T09:29:07Z 2002 Conference Paper 10987584 60408 PIFSF http://www.scopus.com/inward/record.url?eid=2-s2.0-0036456255&partnerID=40&md5=0bd3ffb07bd83c2fb534fae1565a2f34 http://cmuir.cmu.ac.th/handle/6653943832/1307 English
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
language English
description Numerical data from human sources is often used in management studies. MBAs' attitudes and perceptions about the commitment to their school were collected. In an earlier paper, the utility allowing respondents to draw fuzzy membership functions over the set of questionnaire answers was explored. This response format produced good qualitative information. In this paper, we look at a quantitative analysis of these linguistic responses. In particular, we develop a linguistic nearest prototype and computational efficient linguistic Hard C-Means for vectors of fuzzy sets and apply these algorithms to such "linguistic vectors" derived from a set of forty-nine subjects answering questions about students' commitment to their university.
format Conference or Workshop Item
author Auephanwiriyakul S.
Adrian A.
Keller J.M.
spellingShingle Auephanwiriyakul S.
Adrian A.
Keller J.M.
Type 2 fuzzy set analysis in management surveys
author_facet Auephanwiriyakul S.
Adrian A.
Keller J.M.
author_sort Auephanwiriyakul S.
title Type 2 fuzzy set analysis in management surveys
title_short Type 2 fuzzy set analysis in management surveys
title_full Type 2 fuzzy set analysis in management surveys
title_fullStr Type 2 fuzzy set analysis in management surveys
title_full_unstemmed Type 2 fuzzy set analysis in management surveys
title_sort type 2 fuzzy set analysis in management surveys
publishDate 2014
url http://www.scopus.com/inward/record.url?eid=2-s2.0-0036456255&partnerID=40&md5=0bd3ffb07bd83c2fb534fae1565a2f34
http://cmuir.cmu.ac.th/handle/6653943832/1307
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