IDEAS home Printed from https://ideas.repec.org/h/spr/spbrcp/978-3-642-29151-7_4.html
   My bibliography  Save this book chapter

Applicability of Random Regret Minimization-Models, and Their Strong and Weak Points

In: Random Regret-based Discrete Choice Modeling

Author

Listed:
  • Caspar G. Chorus

    (Delft University of Technology)

Abstract

This chapter starts (Sect. 4.1) with discussing the applicability of the RRM-model in other than the quite straightforward choice context presented in Chap. 3. More specifically, it is explained how RRM can be applied to model non-generic attributes, constants, non-continuous attributes, and interactions with socio-demographic variables. Subsequently, Sects. 4.2 and 4.3 present strong, respectively weak points of the RRM-model.

Suggested Citation

  • Caspar G. Chorus, 2012. "Applicability of Random Regret Minimization-Models, and Their Strong and Weak Points," SpringerBriefs in Business, in: Random Regret-based Discrete Choice Modeling, edition 127, chapter 0, pages 35-41, Springer.
    • Handle: RePEc:spr:spbrcp:978-3-642-29151-7_4
    DOI: 10.1007/978-3-642-29151-7_4
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Haghani, Milad & Sarvi, Majid, 2019. "Laboratory experimentation and simulation of discrete direction choices: Investigating hypothetical bias, decision-rule effect and external validity based on aggregate prediction measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 134-157.

    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:spr:spbrcp:978-3-642-29151-7_4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.