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: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| 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 |
| Summary: | 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. |
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