2002
DOI: 10.1016/s0148-2963(00)00127-2
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The ability of ratings and choice conjoint to predict market shares: a Monte Carlo simulation

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Cited by 35 publications
(15 citation statements)
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“…By means of a choice-based conjoint analysis, a variety of stimuli was presented -each comprising different nutritive values within the traffic light signposting scheme. A conjoint method was chosen to assess the relative impact of single product attributes as this has proved to be an adequate tool for preference and utility measurement (42,43) . Choice-based conjoint analyses are advantageous compared with classical rating-based approaches as choice tasks are more comparable to reallife buying decisions, thus leading to a higher external validity (44) .…”
Section: Methodsmentioning
confidence: 99%
“…By means of a choice-based conjoint analysis, a variety of stimuli was presented -each comprising different nutritive values within the traffic light signposting scheme. A conjoint method was chosen to assess the relative impact of single product attributes as this has proved to be an adequate tool for preference and utility measurement (42,43) . Choice-based conjoint analyses are advantageous compared with classical rating-based approaches as choice tasks are more comparable to reallife buying decisions, thus leading to a higher external validity (44) .…”
Section: Methodsmentioning
confidence: 99%
“…The first reference to this method was made in Luce and Tukey (1964), followed by Wilkie and Pessemier (1973), who talked about using multi-attribute models to analyze and understand consumer preferences (Varela and Braña, 1996;Picón et al, 2006;Ramírez, 2008). Additionally, researchers' interest in this methodology has been growing in recent years, both in academia and business (Chakraborty et al, 2002;Chen et al, 2010;Feltrinelli and Molteni, 2004;Gates et al, 2000;Hatzinger and Mazanec, 2007;Keen et al, 2002;Klenosky et al, 2001;Montes et al, 2008;Picón et al, 2006;Ramirez, 2008;Sethuraman et al, 2005;Vag, 2007). Multi-attribute models explain the manner in which consumers form their preferences.…”
Section: Conjoint Analysismentioning
confidence: 99%
“…This makes the choice experiment more realistic. It gives a better predicted accuracy, especially in market simulations [11,12]. Hence, CBC is the conjoint technique applied in this experiment.…”
Section: Choice-based Conjoint Theorymentioning
confidence: 99%