IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v32y2005i6p821-834.html
   My bibliography  Save this article

Modeling Enrollment in the Conservation Reserve Program by Using Agents within Spatial Decision Support Systems: An Example from Southern Illinois

Author

Listed:
  • Raja Sengupta

    (Department of Geography, McGill University, 805 Sherbrooke Street W, Montreal, Quebec H3A 2K6, Canada)

  • Christopher Lant

    (Department of Geography (MailCode 4514), Southern Illinois University, Carbondale, IL 62901-4514, USA)

  • Steven Kraft
  • Jeffrey Beaulieu
  • William Peterson
  • Timothy Loftus

    (Water Quality Laboratory, Heidelberg College, 310 E. Market Street, Tiffin, OH 44883-2462, USA)

Abstract

Existing models of agricultural decisionmaking based on economic optimization often fall short of capturing the complex dynamics of land-use choices at both individual parcel and watershed-level scales. The complexity arises from an interplay of several factors, as explained by Herbert Simon's model of bounded rationality, the theory of diffusion of innovations through spatial contagion, the role of personal environmental values and local culture, and simple historical momentum. This complexity can be captured using ‘artificial life agents’ that model land-use choice for individual parcels by considering characteristics and personal beliefs of the owner or operator, physical traits of the land, and information obtained via social networks. Agents are therefore able to consider holistically a large number of factors affecting land-use choice. The creation of agent-based models of human behavior described herein is based upon empirical data on the acceptance of Conservation Reserve Program for the Cache River watershed of southern Illinois (USA). These models are interfaced with a geographic information system to produce a spatial decision support system capable of anticipating the effects of policies that affect land-use decisionmaking on a real landscape and their economic performance.

Suggested Citation

  • Raja Sengupta & Christopher Lant & Steven Kraft & Jeffrey Beaulieu & William Peterson & Timothy Loftus, 2005. "Modeling Enrollment in the Conservation Reserve Program by Using Agents within Spatial Decision Support Systems: An Example from Southern Illinois," Environment and Planning B, , vol. 32(6), pages 821-834, December.
    • Handle: RePEc:sae:envirb:v:32:y:2005:i:6:p:821-834
    DOI: 10.1068/b31193
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/b31193
    Download Restriction: no
    File URL: https://libkey.io/10.1068/b31193?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
    ---><---

    References listed on IDEAS

    as
    1. Anderson, Jock R. & Dillon, John L. & Hardaker, Brian, 1977. "Agricultural Decision Analysis," Monographs: Applied Economics, AgEcon Search, number 288652, November.
    2. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    3. Cain, J. D. & Jinapala, K. & Makin, I. W. & Somaratna, P. G. & Ariyaratna, B. R. & Perera, L. R., 2003. "Participatory decision support for agricultural management. A case study from Sri Lanka," Agricultural Systems, Elsevier, vol. 76(2), pages 457-482, May.
    4. Gerd Gigerenzer & Reinhard Selten (ed.), 2002. "Bounded Rationality: The Adaptive Toolbox," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571641, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Kremmydas, Dimitris & Athanasiadis, Ioannis N. & Rozakis, Stelios, 2018. "A review of Agent Based Modeling for agricultural policy evaluation," Agricultural Systems, Elsevier, vol. 164(C), pages 95-106.
    2. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    3. Chen, Xiaodong & Lupi, Frank & An, Li & Sheely, Ryan & Viña, Andrés & Liu, Jianguo, 2012. "Agent-based modeling of the effects of social norms on enrollment in payments for ecosystem services," Ecological Modelling, Elsevier, vol. 229(C), pages 16-24.

    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. Anderson, Kim B. & Mapp, Harry P., Jr., 1996. "Risk Management Programs In Extension," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 21(1), pages 1-8, July.
    2. Doppler, Werner & Salman, Amer Z. & Al-Karablieh, Emad K. & Wolff, Heinz-Peter, 2002. "The impact of water price strategies on the allocation of irrigation water: the case of the Jordan Valley," Agricultural Water Management, Elsevier, vol. 55(3), pages 171-182, June.
    3. Sugu M.M. Zuhair & Daniel B. Taylor & Randall A. Kramer, 1992. "Choice of utility function form: its effect on classification of risk preferences and the prediction of farmer decisions," Agricultural Economics, International Association of Agricultural Economists, vol. 6(4), pages 333-344, April.
    4. Young, Douglas & Lin, William & Pope, Rulon & Robison, Lindon & Selley, Roger, 1979. "Risk Preferences Of Agricultual Producers:Their Measurement And Use," Risk Management in Agriculture: Behavioral, Managerial, and Policy Issues, January 25-26, 1979, San Francisco, California 271459, Regional Research Projects > W-149: An Economic Evaluation of Managing Market Risks in Agriculture.
    5. Serrao, Amilcar & Coelho, Luis, 2004. "Cumulative Prospect Theory: A Study Of The Farmers' Decision Behavior In The Alentejo Dryland Region Of Portugal," 2004 Annual meeting, August 1-4, Denver, CO 20245, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Sheahan, Megan & Black, Roy & Jayne, T.S., 2013. "Are Kenyan farmers under-utilizing fertilizer? Implications for input intensification strategies and research," Food Policy, Elsevier, vol. 41(C), pages 39-52.
    7. Rich, Karl M. & Ross, R. Brent & Baker, A. Derek & Negassa, Asfaw, 2011. "Quantifying value chain analysis in the context of livestock systems in developing countries," Food Policy, Elsevier, vol. 36(2), pages 214-222, April.
    8. David J. Pannell, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, International Association of Agricultural Economists, vol. 5(4), pages 361-383, August.
    9. Randall Jones & Oscar Cacho & Jack Sinden, 2006. "The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 245-256, November.
    10. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    11. Aspasia Tsaoussi & Eleni Zervogianni, 2010. "Judges as satisficers: a law and economics perspective on judicial liability," European Journal of Law and Economics, Springer, vol. 29(3), pages 333-357, June.
    12. Rasmussen, Svend, 2003. "Criteria for optimal production under uncertainty. The state-contingent approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 47(4), pages 1-30.
    13. Gomez-Limon, Jose A. & Riesgo, Laura, 2004. "Irrigation water pricing: differential impacts on irrigated farms," Agricultural Economics, Blackwell, vol. 31(1), pages 47-66, July.
    14. Nicolas Marciales Parra, 2013. "A mathematical model for consumers based on aspiration adaptation theory and bounded rationality," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 5(1), pages 136-143, June.
    15. Shonkwiler, J. Scott & Emerson, Robert D., 1981. "The Market for Winter Tomatoes: A Rational Expectations Interpretation," 1981 Annual Meeting, July 26-29, Clemson, South Carolina 279305, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Claudia Dislich & Elisabeth Hettig & Jan Salecker & Johannes Heinonen & Jann Lay & Katrin M Meyer & Kerstin Wiegand & Suria Tarigan, 2018. "Land-use change in oil palm dominated tropical landscapes—An agent-based model to explore ecological and socio-economic trade-offs," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-20, January.
    17. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    18. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
    19. Musser, Wesley N. & Tew, Bernard V., 1984. "Use Of Biophysical Simulation In Production Economics," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 16(1), pages 1-10, July.
    20. Meyer-Aurich, Andreas & Karatay, Yusuf Nadi, 2019. "Effects of uncertainty and farmers' risk aversion on optimal N fertilizer supply in wheat production in Germany," Agricultural Systems, Elsevier, vol. 173(C), pages 130-139.

    More about this item

    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:sae:envirb:v:32:y:2005:i:6:p:821-834. 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: SAGE Publications (email available below). General contact details of provider: .

    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.