Σύγκριση μεθόδων

	Ανάλυση Conjoint	Μεθοδολογία Επιφανειών Απόκρισης (RSM)
Πεδίο	Πειραματικός Σχεδιασμός	Πειραματικός Σχεδιασμός
Οικογένεια	Hypothesis test	Hypothesis test
Έτος προέλευσης	1978	1951
Δημιουργός	Paul E. Green & V. Srinivasan	George E. P. Box & K. B. Wilson
Τύπος	Decomposition-based utility estimation	Second-order polynomial response surface model
Θεμελιώδης πηγή	Green, P.E. & Srinivasan, V. (1978). Conjoint analysis in consumer research: Issues and outlook. Journal of Consumer Research, 5(2), 103–123.	Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45.
Εναλλακτικές ονομασίες	CBC conjoint, choice-based conjoint, adaptive conjoint analysis, full-profile conjoint	RSM, Central Composite Design, Box-Behnken Design, CCD
Συναφείς	6	7
Σύνοψη	Conjoint analysis is a preference-measurement technique that decomposes overall product evaluations into the separate utility values — called part-worths — that respondents assign to each attribute level. Formalised by Green and Srinivasan in their seminal 1978 Journal of Consumer Research paper, the method has become the dominant tool in marketing research and product design for quantifying what buyers truly trade off when they choose between options.	Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics.