Abstract

Human Response to a question with multiple alternatives can be imprecise or fuzzy for various reasons. Part of this fuzziness can be attributed to the lack of sincerity and clarity in the thought process of the respondent. A formal measure of this aspect of fuzziness is formulated in this work on the basis of consistency of the respondent's response to the same question repeated in multiple scales. Discarding haphazard and insincere respondents can improve the quality of data resulting in more efficient survey analysis. This may be achieved in the framework of statistical testing of hypothesis using the probability distribution of the proposed fuzziness measure. Similarly, an attribute can be fuzzy, and it may generate inconsistent response from many respondents. The application of the proposed methodology extends to identifying such fuzzy or unclear attributes. The paper also proposes an algorithm for screening inconsistent respondents and fuzzy attributes simultaneously.

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