IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v32y2005i6p821-834.html

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. repec:ags:agsaem:288652 is not listed on IDEAS
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Shahadha, Saadi Sattar & Wendroth, Ole & Zhu, Junfeng & Walton, Jason, 2019. "Can measured soil hydraulic properties simulate field water dynamics and crop production?," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    9. Giovanni Dosi & Marcelo C. Pereira & Maria Enrica Virgillito, 2017. "The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(2), pages 187-210.
    10. Ruiyao Ying & Li Zhou & Wuyang Hu & Dan Pan, 2017. "Agricultural technical education and agrochemical use by rice farmers in China," Agribusiness, John Wiley & Sons, Ltd., vol. 33(4), pages 522-536, September.
    11. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    12. Jason Wood & James Nolan, 2021. "Plant location decisions in the ethanol industry: a dynamic and spatial analysis," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 103-132, June.
    13. Elodie Letort & Pierre Dupraz & Laurent Piet, 2017. "The impact of environmental regulations on the farmland market and farm structures: An agent-based model applied to the Brittany region of France," Working Papers SMART 17-01, INRAE UMR SMART.
    14. Nicholas R. Magliocca, 2020. "Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus," Land, MDPI, vol. 9(12), pages 1-25, December.
    15. Filippini, Massimo & Hirl, Bettina & Masiero, Giuliano, 2018. "Habits and rational behaviour in residential electricity demand," Resource and Energy Economics, Elsevier, vol. 52(C), pages 137-152.
    16. Andersen, Lykke E. & Groom, Ben & Killick, Evan & Ledezma, Juan Carlos & Palmer, Charles & Weinhold, Diana, 2017. "Modelling Land Use, Deforestation, and Policy: A Hybrid Optimisation-Heterogeneous Agent Model with Application to the Bolivian Amazon," Ecological Economics, Elsevier, vol. 135(C), pages 76-90.
    17. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
    18. Balmann, A. & Happe, K. & Kellermann, K. & Kleingarn, A., 2001. "Agricultural policy switchings – an agent-based approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 37.
    19. Duersch, Peter & Oechssler, Jörg & Schipper, Burkhard C., 2012. "Unbeatable imitation," Games and Economic Behavior, Elsevier, vol. 76(1), pages 88-96.
    20. Berger, Thomas, 2015. "Adaptation of farm-households to increasing climate variability in Ethiopia: Bioeconomic modeling of innovation diffusion and policy interventions," 2015 Conference, August 9-14, 2015, Milan, Italy 229062, International Association of Agricultural Economists.

    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.