IDEAS home Printed from https://ideas.repec.org/a/now/fntmkt/1700000008.html
   My bibliography  Save this article

Choice Models in Marketing: Economic Assumptions, Challenges and Trends

Author

Listed:
  • Chandukala, Sandeep R.
  • Kim, Jaehwan
  • Otter, Thomas
  • Rossi, Peter E.
  • Allenby, Greg M.

Abstract

Direct utility models of consumer choice are reviewed and developed for understanding consumer preferences. We begin with a review of statistical models of choice, posing a series of modeling challenges that are resolved by considering economic foundations based on constrained utility maximization. Direct utility models differ from other choice models by directly modeling the consumer utility function used to derive the likelihood of the data through Kuhn-Tucker conditions. Recent advances in Bayesian estimation make the estimation of these models computationally feasible, offering advantages in model interpretation over models based on indirect utility, and descriptive models that tend to be highly parameterized. Future trends are discussed in terms of the antecedents and enhancements of utility function specification.

Suggested Citation

  • Chandukala, Sandeep R. & Kim, Jaehwan & Otter, Thomas & Rossi, Peter E. & Allenby, Greg M., 2008. "Choice Models in Marketing: Economic Assumptions, Challenges and Trends," Foundations and Trends(R) in Marketing, now publishers, vol. 2(2), pages 97-184, September.
    • Handle: RePEc:now:fntmkt:1700000008
    DOI: 10.1561/1700000008
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1561/1700000008
    Download Restriction: no
    File URL: https://libkey.io/10.1561/1700000008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kabbashi M. Suliman, 2013. "Factors Affecting the Choice of Households’ Primary Cooking Fuel in Sudan," Working Papers 760, Economic Research Forum, revised Jun 2013.
    2. Allenby, Greg M., 2017. "Structural forecasts for marketing data," International Journal of Forecasting, Elsevier, vol. 33(2), pages 433-441.
    3. Nino Hardt & Alex Varbanov & Greg M. Allenby, 2016. "Monetizing Ratings Data for Product Research," Marketing Science, INFORMS, vol. 35(5), pages 713-726, September.
    4. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.
    5. Shuyu Zhou & Yeming (Yale) Gong & René de Koster, 2016. "Designing self-storage warehouses with customer choice," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3080-3104, May.
    6. Ali Aouad & Danny Segev, 2021. "Display Optimization for Vertically Differentiated Locations Under Multinomial Logit Preferences," Management Science, INFORMS, vol. 67(6), pages 3519-3550, June.
    7. Srikanth Jagabathula & Gustavo Vulcano, 2018. "A Partial-Order-Based Model to Estimate Individual Preferences Using Panel Data," Management Science, INFORMS, vol. 64(4), pages 1609-1628, April.
    8. Fasih Ahmed & Muhammad Nawaz & Aisha Jadoon, 2022. "Topic Modeling of the Pakistani Economy in English Newspapers via Latent Dirichlet Allocation (LDA)," SAGE Open, , vol. 12(1), pages 21582440221, March.
    9. Oliver Meixner & Felix Katt, 2020. "Assessing the Impact of COVID-19 on Consumer Food Safety Perceptions—A Choice-Based Willingness to Pay Study," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    10. Bernhard Baumgartner & Daniel Guhl & Thomas Kneib & Winfried J. Steiner, 2018. "Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 837-873, October.
    11. Inderst, Roman & Obradovits, Martin, 2019. "Competitive Strategies when Consumers are Relative Thinkers: Implications for Pricing, Promotions, and Product Choice," EconStor Preprints 253658, ZBW - Leibniz Information Centre for Economics.
    12. Schlereth, Christian & Skiera, Bernd & Schulz, Fabian, 2018. "Why do consumers prefer static instead of dynamic pricing plans? An empirical study for a better understanding of the low preferences for time-variant pricing plans," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1165-1179.
    13. Sanghak Lee & Greg M. Allenby, 2014. "Modeling Indivisible Demand," Marketing Science, INFORMS, vol. 33(3), pages 364-381, May.
    14. Lim, Jooyoung & Hahn, Minhi, 2020. "Regulatory focus and decision rules: Are prevention-focused consumers regret minimizers?," Journal of Business Research, Elsevier, vol. 120(C), pages 343-350.
    15. Marcel Fritz & Christian Schlereth & Stefan Figge, 2011. "Empirical Evaluation of Fair Use Flat Rate Strategies for Mobile Internet," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 3(5), pages 269-277, October.
    16. Hui Li, 2019. "Intertemporal Price Discrimination with Complementary Products: E-Books and E-Readers," Management Science, INFORMS, vol. 67(6), pages 2665-2694, June.
    17. Vivek F. Farias & Srikanth Jagabathula & Devavrat Shah, 2013. "A Nonparametric Approach to Modeling Choice with Limited Data," Management Science, INFORMS, vol. 59(2), pages 305-322, December.
    18. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:now:fntmkt:1700000008. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lucy Wiseman (email available below). General contact details of provider: http://www.nowpublishers.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.