A Heuristic Approach to Product Design

Rajeev Kohli and Ramesh Krishnamurti
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Rajeev Kohli: Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
Ramesh Krishnamurti: School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada V5A1S6

Management Science, 1987, vol. 33, issue 12, 1523-1533

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.

Keywords: marketing; product design; conjoint analysis; heuristics (search for similar items in EconPapers)
Date: 1987
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