참고문헌
- Journal of Marketing Research v.20 An empirical comparison of predictive validity for self-explicated, Huber-hybrid, traditional conjoint, and hybrid conjoint models Akaah, I. P.;Korgaonkar, P. K. https://doi.org/10.2307/3151685
- Mathematical Programming v.5 On L₁ and Chebyshev estimation Appa, G.;Smith, C. https://doi.org/10.1007/BF01580112
- Industrial Marketing Management v.24 Using conjoint analysis in industrial marketing Auty, S. https://doi.org/10.1016/0019-8501(94)00078-B
- ACM Transactions on Mathematical Software v.1 Algorithm 495 : Solution of an over-determined system of linear equations in the Chebyshev norm Barrodale, I.;Phillips, C. https://doi.org/10.1145/355644.355651
- Journal of Marketing Research v.32 Psychometric methods in marketing research: Part Ⅰ, conjoint analysis Carroll, J. D.;Green P. E. https://doi.org/10.2307/3152174
- Journal of Marketing Research v.45 A general approach to product design optimization via conjoint analysis Green, P. E.;Carroll, D.;Goldberg, S. M. https://doi.org/10.2307/1251539
- Journal of Marketing Research v.26 Cross-validation assessment of alternatives to individual-level conjoint analysis : A case study Green P. E.;Helsen, K. https://doi.org/10.2307/3172906
- Journal of Marketing Research v.8 Conjoint measurement for quantifying judgemental data Green P. E.;Rao, V. R. https://doi.org/10.2307/3149575
- Journal of Consumer Research v.5 Conjoint analysis in consumer research : issues and outlook Green P. E.;Srinivasan, V. https://doi.org/10.1086/208721
- Journal of Marketing v.54 Conjoint analysis in marketing : new developments with implications for research and practice Green P. E.;Srinivasan, V. https://doi.org/10.2307/1251756
- Multivariate data analysis Hair, J. F.;Anderson, R. E.;Tatham, R. L.;Black, W. C.
- Journal of Marketing Reasearch v.25 A least squares procedure for benefit segmentation with conjoint experiments Kamakura, W. A. https://doi.org/10.2307/3172647
- Journal of the Royal Statistical Society (B) v.27 Analysis of factorial experiments by estimating monotone transformations of the data Kruskal, J. B.
- Journal of Marketing Research v.23 An approach to the measurement of consumer preferences using limited information Malhotra, N. K. https://doi.org/10.2307/3151774
- Journal of the American Statistical Association v.97 A unified approach to conjoint analysis models Marshall, P.;Bradlow, E. T. https://doi.org/10.1198/016214502388618410
- Technical Report Sample size issues for conjoint analysis studies Orme, B.
- Naval Research Logistics v.35 An assumption-free convergence analysis for a perturbation of the scaling algorithm for linear programs, with application to the L₁-estimation problem Sherali, H. D.;Skarpness, B. O.;Kim, B. Y. https://doi.org/10.1002/1520-6750(198808)35:4<473::AID-NAV3220350403>3.0.CO;2-C
- Commun. Statist. -Simula. Computa. v.13 An algorithm for discrete Chebychev curve fitting for the simple model using a dual linear programming approach Sklar, M. G.;Armstrong, R. D.
- Journal of Marketing v.53 Commercial use of conjoint analysis: an update Wittink, D. R.;Cattin, P. https://doi.org/10.2307/1251345
- International Journal of Research in Marketing v.11 Commercial use of conjoint analysis in europe: results and critical reflections Wittink, D. R.;Vriens, M.;Burhenne, W. https://doi.org/10.1016/0167-8116(94)90033-7
피인용 문헌
- Consumer preference for edible insect-containing cookies determined by conjoint analysis: An exploratory study of Korean consumers vol.47, pp.2, 2017, https://doi.org/10.1111/1748-5967.12203