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A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem

Author

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  • Xinfang (Jocelyn) Wang

    (Department of Finance and Quantitative Analysis, Georgia Southern University, Statesboro, Georgia 30460)

  • Jeffrey D. Camm

    (Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221)

  • David J. Curry

    (Department of Marketing, University of Cincinnati, Cincinnati, Ohio 45221)

Abstract

We develop a branch-and-price algorithm for constructing an optimal product line using partworth estimates from choice-based conjoint analysis. The algorithm determines the specific attribute levels for each multiattribute product in a set of products to maximize the resulting product line's share of choice, i.e., the number of respondents for whom at least one new product's utility exceeds the respondent's reservation utility. Computational results using large commercial and simulated data sets demonstrate that the algorithm can identify provably optimal, robust solutions to realistically sized problems.

Suggested Citation

  • Xinfang (Jocelyn) Wang & Jeffrey D. Camm & David J. Curry, 2009. "A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem," Management Science, INFORMS, vol. 55(10), pages 1718-1728, October.
    • Handle: RePEc:inm:ormnsc:v:55:y:2009:i:10:p:1718-1728
    DOI: 10.1287/mnsc.1090.1058
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    References listed on IDEAS

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    2. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    3. Hongmin Li & Scott Webster & Gwangjae Yu, 2020. "Product Design Under Multinomial Logit Choices: Optimization of Quality and Prices in an Evolving Product Line," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 1011-1025, September.
    4. Cornelia Schön, 2010. "On the Optimal Product Line Selection Problem with Price Discrimination," Management Science, INFORMS, vol. 56(5), pages 896-902, May.
    5. Wang, Xinfang (Jocelyn) & Curry, David J., 2012. "A robust approach to the share-of-choice product design problem," Omega, Elsevier, vol. 40(6), pages 818-826.
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    7. Tan Wang & Genaro Gutierrez, 2022. "Robust Product Line Design by Protecting the Downside While Minding the Upside," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 194-217, January.
    8. Francesco Moresino, 2021. "A Robust Share-of-Choice Model," Mathematics, MDPI, vol. 9(3), pages 1-10, February.
    9. Hein, Maren & Goeken, Nils & Kurz, Peter & Steiner, Winfried J., 2022. "Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data," European Journal of Operational Research, Elsevier, vol. 297(2), pages 630-651.
    10. Zhiqiao Wu & C.K. Kwong & C.K.M. Lee & Jiafu Tang, 2016. "Joint decision of product configuration and remanufacturing for product family design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(15), pages 4689-4702, August.
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    12. Meng, Qiang & Wang, Shuaian & Lee, Chung-Yee, 2015. "A tailored branch-and-price approach for a joint tramp ship routing and bunkering problem," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 1-19.

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