Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee
<p class="03Abstract" style="margin: 0cm 0cm 0pt;"><span lang="EN-GB"><span style="font-family: Calibri; font-size: x-small;">D'Elia and Piccolo (2005) have recently proposed a mixture distribution, named CUB, for ordinal data. The use o...
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| Format: | Article |
| Language: | English |
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CentMa
2010-01-01
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| Series: | International Journal on Food System Dynamics |
| Subjects: | |
| Online Access: | http://centmapress.ilb.uni-bonn.de/ojs/index.php/fsd/article/view/13 |
| _version_ | 1828494617354436608 |
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| author | Gianni Cicia Marcella Corduas Teresa Del Giudice Domenico Piccolo |
| author_facet | Gianni Cicia Marcella Corduas Teresa Del Giudice Domenico Piccolo |
| author_sort | Gianni Cicia |
| collection | DOAJ |
| description | <p class="03Abstract" style="margin: 0cm 0cm 0pt;"><span lang="EN-GB"><span style="font-family: Calibri; font-size: x-small;">D'Elia and Piccolo (2005) have recently proposed a mixture distribution, named CUB, for ordinal data. The use of such a mixture distribution for modelling ratings is justified by the following consideration: the judgment that a subject expresses is the result of two components, uncertainty and selectiveness. The possibility of relating the parameters of CUB models to covariates makes the formulation interesting for practical applications</span></span></p><span style="font-family: "Times New Roman","serif"; font-size: 12pt; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: IT; mso-fareast-language: IT; mso-bidi-language: AR-SA;" lang="IT">In this case study, a sample of 224 fair-trade coffee consumers were interviewed at stores. With this data-set, CUB model split consumers, according to their preferences, in two different segments: one showing high price elasticity, and one with a low price elasticity. As regards the potential of the CUB model, it showed a considerable integration capacity with stochastic utility models, namely latent class models. Indeed, by using the segmentation factors emerging from the CUB as covariates of segmentation in a latent class model and setting the number of classes equal to those emerging from the CUB, it was possible to estimate a model which not only validated the findings of the CUB but also allowed estimation of the WTP for the fair trade characteristic in the different groups.</span> |
| first_indexed | 2024-12-11T11:59:14Z |
| format | Article |
| id | doaj.art-f905818fb6c54020b825f7fba450bd42 |
| institution | Directory Open Access Journal |
| issn | 1869-6945 |
| language | English |
| last_indexed | 2024-12-11T11:59:14Z |
| publishDate | 2010-01-01 |
| publisher | CentMa |
| record_format | Article |
| series | International Journal on Food System Dynamics |
| spelling | doaj.art-f905818fb6c54020b825f7fba450bd422022-12-22T01:08:08ZengCentMaInternational Journal on Food System Dynamics1869-69452010-01-011182938Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade CoffeeGianni CiciaMarcella CorduasTeresa Del GiudiceDomenico Piccolo<p class="03Abstract" style="margin: 0cm 0cm 0pt;"><span lang="EN-GB"><span style="font-family: Calibri; font-size: x-small;">D'Elia and Piccolo (2005) have recently proposed a mixture distribution, named CUB, for ordinal data. The use of such a mixture distribution for modelling ratings is justified by the following consideration: the judgment that a subject expresses is the result of two components, uncertainty and selectiveness. The possibility of relating the parameters of CUB models to covariates makes the formulation interesting for practical applications</span></span></p><span style="font-family: "Times New Roman","serif"; font-size: 12pt; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: IT; mso-fareast-language: IT; mso-bidi-language: AR-SA;" lang="IT">In this case study, a sample of 224 fair-trade coffee consumers were interviewed at stores. With this data-set, CUB model split consumers, according to their preferences, in two different segments: one showing high price elasticity, and one with a low price elasticity. As regards the potential of the CUB model, it showed a considerable integration capacity with stochastic utility models, namely latent class models. Indeed, by using the segmentation factors emerging from the CUB as covariates of segmentation in a latent class model and setting the number of classes equal to those emerging from the CUB, it was possible to estimate a model which not only validated the findings of the CUB but also allowed estimation of the WTP for the fair trade characteristic in the different groups.</span>http://centmapress.ilb.uni-bonn.de/ojs/index.php/fsd/article/view/13CUB modelfair trade coffeelatent class choice model |
| spellingShingle | Gianni Cicia Marcella Corduas Teresa Del Giudice Domenico Piccolo Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee International Journal on Food System Dynamics CUB model fair trade coffee latent class choice model |
| title | Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee |
| title_full | Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee |
| title_fullStr | Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee |
| title_full_unstemmed | Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee |
| title_short | Valuing Consumer Preferences with the CUB Model: A CaseStudy of Fair Trade Coffee |
| title_sort | valuing consumer preferences with the cub model a casestudy of fair trade coffee |
| topic | CUB model fair trade coffee latent class choice model |
| url | http://centmapress.ilb.uni-bonn.de/ojs/index.php/fsd/article/view/13 |
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