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Technical Note: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis

Author

Listed:
  • Kyle D. Chen

    (Computer Science Department, IBM Almaden Research Center, San Jose, California 95120-6099)

  • Warren H. Hausman

    (Department of Industrial Engineering and Engineering Management, Stanford University, Stanford, California 94305-4024)

Abstract

Selecting and pricing product lines is an essential activity in many businesses. In recent years, quantitative approaches for such tasks have been gaining in popularity. One often-employed method is to use data from traditional rankings/ratings-based conjoint analysis and attack the product line selection problem with enumeration or heuristics. In this note, we employ a relatively new methodology known as choice-based conjoint analysis (to model customer preferences) and investigate its mathematical properties when used to model the product line selection problem. Despite some inherent limitations resulting from its aggregated formulation, we show that this more parsimonious conjoint approach has some special mathematical properties that lead to an efficient optimal algorithm to tackle the product line/price selection problem. As a result, problems of realistic size can be solved efficiently using standard, commercially available mathematical programming codes.

Suggested Citation

  • Kyle D. Chen & Warren H. Hausman, 2000. "Technical Note: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis," Management Science, INFORMS, vol. 46(2), pages 327-332, February.
    • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:2:p:327-332
    DOI: 10.1287/mnsc.46.2.327.11931
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    References listed on IDEAS

    as
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