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Degree of satisfaction-difference (DOSD) method for measuring consumer acceptance: Comparative and absolute measures of satisfaction based on signal detection theory
- Degree of satisfaction-difference (DOSD) method for measuring consumer acceptance: Comparative and absolute measures of satisfaction based on signal detection theory
- Kim M.-A.; van Hout D.; Lee H.-S.
- Ewha Authors
- SCOPUS Author ID
- Issue Date
- Journal Title
- Food Quality and Preference
- Food Quality and Preference vol. 68, pp. 167 - 172
- Absolute measure; Acceptance test; Consumer evaluation; Degree of satisfaction-difference; d’; Rating; Signal detection theory
- Elsevier Ltd
- SCI; SCIE; SCOPUS
- Document Type
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- Recently, we have proposed the degree of satisfaction-difference (DOSD) method to measure changes in consumer product acceptance (Kim, van Hout, Dessirier, et al., 2018). The DOSD method utilizes A-Not A with reminder format to improve the stability and validity of the consumer evaluation by reminding consumers of the evaluative criteria with the reference sampling and by controlling the sequence effects on each sampling of the blind test product. Using the data obtained from DOSD method, in this paper, a way to compute a measure of the absolute degree of satisfaction for a product based on signal detection theory (SDT), referred to as d’SAT (d-prime satisfaction), is suggested. This new measure is compared to the comparative distance measure of d’ the degree of satisfaction difference of a product from the reference product, which has been already described in the previous study. The absolute satisfaction degree is a value indicating each product's degree of consumer satisfaction as in the hedonic score. However, the degree of satisfaction measure presented herein is superior to the hedonic score because it enables easy interpretation of whether a group of consumers are satisfied or not with a product. In practical situations, the two measures of the degree of satisfaction difference from the reference and the degree of satisfaction, which are computed using the data from DOSD method, can be used complementarily in order to reveal information about consumer perception and evaluation. © 2018 Elsevier Ltd
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