IDEAS home Printed from https://ideas.repec.org/p/ags/eaae14/182925.html
   My bibliography  Save this paper

Bayesian Belief Network approach in assessment of agricultural landscapes competitiveness

Author

Listed:
  • Malak-Rawlikowska, Agata
  • Kobus, Pawel

Abstract

The study focuses on the relations between landscape structure and composition, functions and benefits, and its contribution to the regional competitiveness. The Bayesian Belief Network method has occurred to be useful for the analysis of the problem, however, the proper determination of the relationship between the variables in the model, requires a large number of observations based on the assessments of experts. It was found that all considered landscape elements (fields, forests, shelterbelts, and water reservoirs) have a positive influence on regional competitiveness and the potential of agricultural land. The strongest, positive impact on the competitiveness of the region have agricultural fields and pastures.

Suggested Citation

  • Malak-Rawlikowska, Agata & Kobus, Pawel, 2014. "Bayesian Belief Network approach in assessment of agricultural landscapes competitiveness," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182925, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae14:182925
    DOI: 10.22004/ag.econ.182925
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/182925/files/EAAE2014_Malak-Rawlikowska_and_Kobus.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.182925?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
    ---><---

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    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:ags:eaae14:182925. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    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.