1 / 22

Guillaume Deffuant, Frédéric Amblard, Nils Ferrand (Cemagref, France)

A decision process model mixing rational anticipations and social influences : the example of agri-environmental measure adoption in Breadalbane ESA (Scotland). Guillaume Deffuant, Frédéric Amblard, Nils Ferrand (Cemagref, France) Nigel Gilbert (university of Surrey, UK)

leanne
Download Presentation

Guillaume Deffuant, Frédéric Amblard, Nils Ferrand (Cemagref, France)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A decision process model mixing rational anticipations and social influences : the example of agri-environmental measure adoption in Breadalbane ESA (Scotland) Guillaume Deffuant, Frédéric Amblard, Nils Ferrand (Cemagref, France) Nigel Gilbert (university of Surrey, UK) Gérard Weisbuch (Ecole Normal Supérieure, France)

  2. Farmer Agri-environmental measures + $$ • Pilot zones from 1986 • Generalised to all Europe in 1992

  3. + $$ • Breadalbane ESA Scotland European project • First goal : evaluate the model on the past • Then evaluate prescriptive use

  4. Breadalbane ESA • 150 farms, mainly sheep, average size : 650 ha • 39 farmers interviewed • 10 re-interviewed • 10 interviews with institutional actors • First ESA : From 1986 to 1992 • Second ESA : From 1992 to 1999

  5. End 1986 : • Press : first rough description of the measure • The measure is about landscape and biodiversity Breadalbane ESA : implementation

  6. End 1986 : • SAC : contact 10 "leader" farmers and promote the measure • More financial information Breadalbane ESA : implementation

  7. March 1987 : • Organisation of the official presentation meeting • All farmers invited • Participation 50% Breadalbane ESA : implementation

  8. The interested farmer calls SAC advisor • SAC advisor comes to the farm and makes to ecological diagnosis • The still interested farmer calls SAC advisor • The advisor comes to the farm and the farm plan is negotiated Breadalbane ESA : implementation • From April 87 to End 92:

  9. The model

  10. Motivations d a -1 +1 d a -1 +1 d a -1 +1 The decision model : variables • Uncertain anticipations of impacts (or impressions) • Income • Independence • Nature

  11. a d’ a’ d F F’ a a’ d’ Da d Dd F F’ The decision model : Interactions • Before meeting After meeting

  12. The decision model : rational evaluation • The impact on income is evaluated "rationally" with the advisor when the farm plan is established • The calculation of this impact takes into account : • the size of the farm • the level payments • the level of the associated costs

  13. Farmer not interested by the measure. • m.a < T1 • Interested, • Discussions with colleagues • T1 < m.a < T2 • Interested, • willing to begin the procedure • m.a > T2 • Ready to adopt • can if procedure completed • m.a- mr.dr >T3 The decision model : decision stages

  14. Motivations d d d -1 -1 -1 a a a +1 +1 +1 Initialisation of anticipated impacts • Uncertain anticipations (or impressions) • Income • Independence • Nature

  15. Motivation distribution for interviewed farms • Randomly affected to non interviewed farms Initialisation of the motivations

  16. Social network • link probability = exp (- D(F,F')) • Average link number : 4.8

  17. d d d • Press -1 -1 -1 +1 +1 +1 a a a d d • SAC -1 -1 +1 +1 a a Institutional messages • Income • Independence • Nature

  18. First results

  19. Messages from the press First messages from SAC Meeting Beginning of advisor visits Example of results no interest discussing visit ready non adopter adopter

  20. Average fitting the first adoption points number of adopters average data of adoption

  21. Fitting first point and last point number of adopters average data of adoption

  22. Conclusion • Progressive refinement of the model : • institutional scenarios • dynamic model • more impacts and motivations • Study for the use in a prospective purpose

More Related