Simultaneous preference estimation and heterogeneity control for choice-based conjoint via support vector machines
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DOI: 10.1057/s41274-016-0013-6
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- Yajima, Yasutoshi, 2005. "Linear programming approaches for multicategory support vector machines," European Journal of Operational Research, Elsevier, vol. 162(2), pages 514-531, April.
- S Irani & Y K Dwivedi & M D Williams, 2014. "Analysing factors affecting the choice of emergent human resource capital," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(6), pages 935-953, June.
- Arora, Neeraj & Huber, Joel, 2001. "Improving Parameter Estimates and Model Prediction by Aggregate Customization in Choice Experiments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(2), pages 273-283, September.
- Jeffrey D. Camm & James J. Cochran & David J. Curry & Sriram Kannan, 2006. "Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem," Management Science, INFORMS, vol. 52(3), pages 435-447, March.
- Yves F. Atchadé, 2006. "An Adaptive Version for the Metropolis Adjusted Langevin Algorithm with a Truncated Drift," Methodology and Computing in Applied Probability, Springer, vol. 8(2), pages 235-254, June.
- Dapeng Cui & David Curry, 2005. "Prediction in Marketing Using the Support Vector Machine," Marketing Science, INFORMS, vol. 24(4), pages 595-615, January.
- Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.
- Rajagopal, 2014.
"The Human Factors,"
Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249,
Palgrave Macmillan.
- Rajagopal, 2013. "The Human Factors," Palgrave Macmillan Books, in: Managing Social Media and Consumerism, chapter 9, pages 173-194, Palgrave Macmillan.
- S Tsafarakis & E Grigoroudis & N Matsatsinis, 2011. "Consumer choice behaviour and new product development: an integrated market simulation approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1253-1267, July.
- Theodoros Evgeniou & Massimiliano Pontil & Olivier Toubia, 2007. "A Convex Optimization Approach to Modeling Consumer Heterogeneity in Conjoint Estimation," Marketing Science, INFORMS, vol. 26(6), pages 805-818, 11-12.
- K B Schebesch & R Stecking, 2005. "Support vector machines for classifying and describing credit applicants: detecting typical and critical regions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1082-1088, September.
- Hensher, David & Louviere, Jordan & Swait, Joffre, 1998. "Combining sources of preference data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 197-221, November.
- Mankila, Merja, 2004. "Retaining students in retail banking through price bundling: Evidence from the Swedish market," European Journal of Operational Research, Elsevier, vol. 155(2), pages 299-316, June.
- Olivier Toubia & John Hauser & Rosanna Garcia, 2007. "Probabilistic Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis: Theory and Application," Marketing Science, INFORMS, vol. 26(5), pages 596-610, 09-10.
- Verbeke, Wouter & Dejaeger, Karel & Martens, David & Hur, Joon & Baesens, Bart, 2012. "New insights into churn prediction in the telecommunication sector: A profit driven data mining approach," European Journal of Operational Research, Elsevier, vol. 218(1), pages 211-229.
- Scholl, Armin & Manthey, Laura & Helm, Roland & Steiner, Michael, 2005. "Solving multiattribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison," European Journal of Operational Research, Elsevier, vol. 164(3), pages 760-777, August.
- Maldonado, Sebastián & Montoya, Ricardo & Weber, Richard, 2015. "Advanced conjoint analysis using feature selection via support vector machines," European Journal of Operational Research, Elsevier, vol. 241(2), pages 564-574.
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Keywords
conjoint analysis; heterogeneity control; support vector machines; OR in marketing; artificial intelligence;All these keywords.
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