IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-540-47064-9_13.html

Exploring Pedestrian Shopping Decision Processes — an Application of Gene Expression Programming

In: Pedestrian and Evacuation Dynamics 2005

Author

Listed:
  • W. Zhu

    (Eindhoven University of Technology, Urban Planning Group, Vertigo 08.16)

  • H. Timmermans

    (Eindhoven University of Technology, Urban Planning Group)

Abstract

Random utility theory and discrete choice models have been widely used to explore mechanisms underlying pedestrian shopping behavior. However, these models tend to be mis-specified due to unrealistic assumption of utility maximising behavior. The bounded rationality theory may be more suitable for building models representing real shopping decision process, but existing statistical models are not able to extract information hidden in the decision process proposed by the theory. We therefore developed GEPAT, a computer program using Gene Expression Programming to solve this problem with its two most significant features. The first feature is that it has an extendable multigene-section chromosome structure which allows several inter-related target functions to be estimated simultaneously. The second feature is that it uses processors, representing mental operators, as building blocks to implement simple information processing and facilitate constructing and testing complex schemes of the problem by linking the processors properly. The overall workflow of GEPAT, its advantages, disadvantages and potentials are discussed.

Suggested Citation

  • W. Zhu & H. Timmermans, 2007. "Exploring Pedestrian Shopping Decision Processes — an Application of Gene Expression Programming," Springer Books, in: Nathalie Waldau & Peter Gattermann & Hermann Knoflacher & Michael Schreckenberg (ed.), Pedestrian and Evacuation Dynamics 2005, pages 145-154, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-47064-9_13
    DOI: 10.1007/978-3-540-47064-9_13
    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
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-3-540-47064-9_13. 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.