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A choice model for mixed decision variables

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  • Lee, Sanghak
  • Kim, Hyowon
  • Kim, Jaehwan
  • Allenby, Greg M.

Abstract

Consumers increasingly face decisions among discrete and continuous choice alternatives. Deciding what to wear, watch, read and drive often includes alternatives that allow access for a period of time, as opposed to outright ownership of a good. Consumers may also want both, where access provides a wider variety of offerings than possible with ownership, and ownership provides greater assurance of availability. We propose a mixed discrete/continuous utility model for assessing the economic relationship between mixed decision variables. In application to two studies involving on-line music and videos, we find that commonly used models of choice mischaracterize the economic relationship between access and ownership. We explore the degree to which profit maximizing prices are dependent on correctly assessing whether access through subscription services are substitutes or complements to product ownership.

Suggested Citation

  • Lee, Sanghak & Kim, Hyowon & Kim, Jaehwan & Allenby, Greg M., 2018. "A choice model for mixed decision variables," Journal of choice modelling, Elsevier, vol. 28(C), pages 82-96.
    • Handle: RePEc:eee:eejocm:v:28:y:2018:i:c:p:82-96
    DOI: 10.1016/j.jocm.2018.05.003
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    References listed on IDEAS

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    1. Knox, George & Eliashberg, Jehoshua, 2009. "The consumer's rent vs. buy decision in the rentailer," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 125-135.
    2. Sanghak Lee & Greg M. Allenby, 2014. "Modeling Indivisible Demand," Marketing Science, INFORMS, vol. 33(3), pages 364-381, May.
    3. Anita Rao, 2015. "Online Content Pricing: Purchase and Rental Markets," Marketing Science, INFORMS, vol. 34(3), pages 430-451, May.
    4. Sanghak Lee & Jaehwan Kim & Greg M. Allenby, 2013. "A Direct Utility Model for Asymmetric Complements," Marketing Science, INFORMS, vol. 32(3), pages 454-470, May.
    5. Takuya Satomura & Jaehwan Kim & Greg M. Allenby, 2011. "Multiple-Constraint Choice Models with Corner and Interior Solutions," Marketing Science, INFORMS, vol. 30(3), pages 481-490, 05-06.
    6. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    7. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    8. P. K. Kannan & Barbara Kline Pope & Sanjay Jain, 2009. "—Pricing Digital Content Product Lines: A Model and Application for the National Academies Press," Marketing Science, INFORMS, vol. 28(4), pages 620-636, 07-08.
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