IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2606.15593.html

Discrete Choice and Competitive Reactions: End-to-End Simulation with the R Package cash

Author

Listed:
  • Jan H. R. Dressler
  • Peter Kurz
  • Winfried J. Steiner

Abstract

Although discrete choice (choice-based conjoint) analysis has become a widely used technique for the elicitation of consumer preferences and hence a foundation for product design, to the best of our knowledge, there exists neither free and open-source nor commercial software that covers the game-theoretic simulation of competitive reactions among firms based on discrete choice models to improve decision making beyond traditional product (line) optimization. The R package cash (conjoint + Nash) does not only provide functions to fill this gap but comprises an entire simulation pipeline including the upstream processes of discrete choice analysis itself. cash ranges from preference generation, choice design, error and response simulation, through Bayesian model estimation and evaluation, to Nash equilibrium computation. Doing so, it partly draws from established R packages concerned with discrete choice analysis. While the structure of cash generally aims towards end-to-end simulation as well as simulation of competitive dynamics based on real data, all its key elements mentioned above may be of use independently of each other.

Suggested Citation

  • Jan H. R. Dressler & Peter Kurz & Winfried J. Steiner, 2026. "Discrete Choice and Competitive Reactions: End-to-End Simulation with the R Package cash," Papers 2606.15593, arXiv.org.
    • Handle: RePEc:arx:papers:2606.15593
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2606.15593
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maren Hein & Peter Kurz & Winfried J. Steiner, 2020. "Analyzing the capabilities of the HB logit model for choice-based conjoint analysis: a simulation study," Journal of Business Economics, Springer, vol. 90(1), pages 1-36, February.
    2. Joan L. Walker & Yanqiao Wang & Mikkel Thorhauge & Moshe Ben-Akiva, 2018. "D-efficient or deficient? A robustness analysis of stated choice experimental designs," Theory and Decision, Springer, vol. 84(2), pages 215-238, March.
    3. Vithala R. Rao, 2014. "Applied Conjoint Analysis," Springer Books, Springer, edition 127, number 978-3-540-87753-0, January.
    4. Richard Norman & Benjamin M. Craig & Paul Hansen & Marcel F. Jonker & John Rose & Deborah J. Street & Brendan Mulhern, 2019. "Issues in the Design of Discrete Choice Experiments," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(3), pages 281-285, June.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, August.
    6. Hensher, David A. & Stopher, Peter R. & Louviere, Jordan J., 2001. "An exploratory analysis of the effect of numbers of choice sets in designed choice experiments: an airline choice application," Journal of Air Transport Management, Elsevier, vol. 7(6), pages 373-379.
    7. 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.
    8. Rinus Haaijer & Michel Wedel, 2007. "Conjoint Choice Experiments: General Characteristics and Alternative Model Specifications," Springer Books, in: Anders Gustafsson & Andreas Herrmann & Frank Huber (ed.), Conjoint Measurement, edition 0, chapter 11, pages 199-229, Springer.
    9. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jan H. R. Dressler & Peter Kurz & Winfried J. Steiner, 2025. "Computing Nash equilibria for product design based on hierarchical Bayesian mixed logit models," Papers 2512.22864, arXiv.org.
    2. Amirnequiee, Shobeir & Naoum-Sawaya, Joe & Pun, Hubert, 2026. "Robust framework for the joint learning of consumer preferences and market segmentation," Omega, Elsevier, vol. 138(C).
    3. 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.
    4. Carsten Herbes & Johannes Dahlin & Peter Kurz, 2020. "Consumer Willingness To Pay for Proenvironmental Attributes of Biogas Digestate-Based Potting Soil," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    5. Sriwastava, Ambuj & Reichert, Peter, 2023. "Reducing sample size requirements by extending discrete choice experiments to indifference elicitation," Journal of choice modelling, Elsevier, vol. 48(C).
    6. Yegoryan, Narine & Guhl, Daniel & Klapper, Daniel, 2018. "Inferring Attribute Non-Attendance Using Eye Tracking in Choice-Based Conjoint Analysis," Rationality and Competition Discussion Paper Series 111, CRC TRR 190 Rationality and Competition.
    7. Raux, Charles & Chevalier, Amandine & Bougna, Emmanuel & Hilton, Denis, 2021. "Mobility choices and climate change: Assessing the effects of social norms, emissions information and economic incentives," Research in Transportation Economics, Elsevier, vol. 90(C).
    8. Byambadorj, Nyamdavaa & Best, Rohan & Mandakh, Undram & Sinha, Kompal, 2025. "Parental beverage choices to inform policy on sugar-sweetened beverages: a discrete choice experiment," Social Science & Medicine, Elsevier, vol. 383(C).
    9. Hein, Maren & Kurz, Peter & Steiner, Winfried J., 2019. "On the effect of HB covariance matrix prior settings: A simulation study," Journal of choice modelling, Elsevier, vol. 31(C), pages 51-72.
    10. Maren Hein & Peter Kurz & Winfried J. Steiner, 2020. "Analyzing the capabilities of the HB logit model for choice-based conjoint analysis: a simulation study," Journal of Business Economics, Springer, vol. 90(1), pages 1-36, February.
    11. Wen, Chieh-Hua & Huang, Chia-Jung & Fu, Chiang, 2020. "Incorporating continuous representation of preferences for flight departure times into stated itinerary choice modeling," Transport Policy, Elsevier, vol. 98(C), pages 10-20.
    12. Sant'Anna, Ana Claudia & Bergtold, Jason & Shanoyan, Aleksan & Caldas, Marcellus & Granco, Gabriel, 2021. "Deal or No Deal? Analysis of Bioenergy Feedstock Contract Choice with Multiple Opt-out Options and Contract Attribute Substitutability," 2021 Conference, August 17-31, 2021, Virtual 315289, International Association of Agricultural Economists.
    13. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    14. Qian, Lixian & Grisolía, Jose M. & Soopramanien, Didier, 2019. "The impact of service and government-policy attributes on consumer preferences for electric vehicles in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 70-84.
    15. Roy Brouwer & Solomon Tarfasa, 2020. "Testing hypothetical bias in a framed field experiment," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(3), pages 343-357, September.
    16. Hyunjoo Lee & Misuk Lee & Sesil Lim, 2018. "Do Consumers Care about the Energy Efficiency of Buildings? Understanding Residential Choice Based on Energy Performance Certificates," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    17. Esther W. Bekker-Grob & Bas Donkers & Jorien Veldwijk & Marcel F. Jonker & Sylvia Buis & Jan Huisman & Patrick Bindels, 2021. "What Factors Influence Non-Participation Most in Colorectal Cancer Screening? A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(2), pages 269-281, March.
    18. Cho, Woohyun & Windle, Robert J. & Dresner, Martin E., 2017. "The impact of operational exposure and value-of-time on customer choice: Evidence from the airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 455-471.
    19. Forbes-Brown, Shelicia & Mcheels, Eric & Hobbs, Jill, 2015. "Signalling Origin: Consumer Willngness to Pay for Dairy Products with the "100% Canadian Milk" Label," 2015 Conference, August 9-14, 2015, Milan, Italy 211636, International Association of Agricultural Economists.
    20. Tamaki Kitagawa & Kenichi Kashiwagi & Hiroko Isoda, 2020. "Effect of Religious and Cultural Information of Olive Oil on Consumer Behavior: Evidence from Japan," Sustainability, MDPI, vol. 12(3), pages 1-17, January.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2606.15593. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    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.