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References (13)
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- Publisher
- INFORMS
- Copyright
- Copyright © INFORMS
- Subject
- Research Article
- ISSN
- 0025-1909
- eISSN
- 1526-5501
- DOI
- 10.1287/mnsc.33.12.1523
- Publisher site
- See Article on Publisher Site
Abstract
A dynamic-programming heuristic is described to find approximate solutions to the problem of identifying a new, multi-attribute product profile associated with the highest share-of-choices in a competitive market. The input data consist of idiosyncratic multi-attribute preference functions estimated using conjoint or hybrid-conjoint analysis. An individual is assumed to choose a new product profile if he/she associates a higher utility with it than with a status-quo alternative. Importance weights are assigned to individuals to account for differences in their purchase and/or usage rates and the performance of a new product profile is evaluated after taking into account its cannibalization of a seller's existing brands. In a simulation with real-sized problems, the proposed heuristic strictly dominates an alternative lagrangian-relaxation heuristic in terms of both computational time and approximation of the optimal solution. Across 192 simulated problems, the dynamic-programming heuristic identifies product profiles whose share-of-choices, on average, are 98.2% of the share-of-choices of the optimal product profile, suggesting that it closely approximates the optimal solution.
Journal
Management Science – INFORMS
Published: Dec 1, 1987
Keywords: Keywords : marketing ; product design ; conjoint analysis ; heuristics