Abstract
Soon after the introduction of conjoint analysis into marketing by Green and Rao (1972), Srinivasan and Shocker (1973a, 1973b) introduced a conjoint analysis estimation method, Linmap, based on linear programming. Linmap has been applied successfully in many situations and has proven to be a viable alternative to statistical estimation (Jain, et. al. 1979, Wittink and Cattin 1981). Recent modification to deal with “strict pairs” has improved the estimation accuracy with the result that, on occasion, the modified Linmap predicts holdout data better than statistical estimation based on hierarchical Bayes methods (Srinivasan 1998, Hauser, et. al. 2006).
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Toubia, O., Evgeniou, T., Hauser, J. (2007). Optimization-Based and Machine-Learning Methods for Conjoint Analysis: Estimation and Question Design. In: Gustafsson, A., Herrmann, A., Huber, F. (eds) Conjoint Measurement. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71404-0_12
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