IDEAS home Printed from https://ideas.repec.org/p/ags/gewi12/133052.html

Viele Köche Verderben Den Brei – Agentenbasierte Simulationen Zum Föderalismusdurcheinander Während Der Ehec-Krise

Author

Listed:
  • Saggau, Volker

Abstract

Das Jahr 2011 hatte zahlreiche einschneidende globale Ereignisse vorzuweisen. Die Medienberichterstattung, zumal im Zeitalter allgegenwärtiger, dezentraler und mobiler Medien, war erfüllt von bedrohlichen Nachrichten. Angefangen beim Dioxinskandal ging die Berichterstattung über den Arabischen Frühling und Fukushima hin zur EHEC-Krise. Lebensmittelskandale geschehen in wiederkehrenden Abständen und gelangen in die Medien zumeist mit verunsichernden Berichterstattungen. Dieser Beitrag beschäftigt sich mit der EHEC-Krise und wendet ein agentenbasiertes Modell zur Analyse unterschiedlicher Informationsszenarien an. Hierbei wird insbesondere auf die Problematik der Zuständigkeiten und Kompetenzen bei einer Lebensmittelkrise im föderalen System der Bundesrepublik Deutschland eingegangen. Die Simulationen zeigen auf, dass die Bündelung von Informationen über unsichere Lebensmittel durch eine zentrale Instanz, die sachlich aufklärt, negative Effekte auf die Wohlfahrt reduzieren kann. Auch wenn das Modell eine starke Vereinfachung der Realität aufweist, so lassen sich doch zentrale Prozesse gut abbilden und die Ergebnisse geben einige Hinweise auf die Ausgestaltung von effizienten Risikokommunikationsstrategien.

Suggested Citation

  • Saggau, Volker, 2012. "Viele Köche Verderben Den Brei – Agentenbasierte Simulationen Zum Föderalismusdurcheinander Während Der Ehec-Krise," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 133052, German Association of Agricultural Economists (GEWISOLA).
    • Handle: RePEc:ags:gewi12:133052
    DOI: 10.22004/ag.econ.133052
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/133052/files/Saggau_GEWISOLA_2012.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.133052?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. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    2. Tesfatsion, Leigh, 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," ISU General Staff Papers 200201010800001251, Iowa State University, Department of Economics.
    3. Arthur, W. Brian & Lane, David A., 1993. "Information contagion," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 81-104, June.
    4. Wentholt, M.T.A. & Rowe, G. & König, A. & Marvin, H.J.P. & Frewer, L.J., 2009. "The views of key stakeholders on an evolving food risk governance framework: Results from a Delphi study," Food Policy, Elsevier, vol. 34(6), pages 539-548, December.
    5. Orlean, Andre, 1995. "Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 28(2), pages 257-274, October.
    6. Brandes, Wilhelm, 1978. "Zur Konzentration der Agrarproduktion in der Bundesrepublik Deutschland aus betriebswirtschaftlicher Sicht," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 27(01).
    7. Balmann, Alfons, 1997. "Farm-Based Modelling of Regional Structural Change: A Cellular Automata Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 24(1), pages 85-108.
    8. John H. Miller & Scott E. Page, 2007. "Social Science in Between, from Complex Adaptive Systems: An Introduction to Computational Models of Social Life," Introductory Chapters, in: Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press.
    9. Berger, Thomas, 2004. "Agentenbasierte Modellierung von Landnutzungsdynamiken und Politikoptionen," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 53(02), pages 1-11.
    10. Bocker, Andreas & Hanf, Claus-Hennig, 2000. "Confidence lost and -- partially -- regained: consumer response to food scares," Journal of Economic Behavior & Organization, Elsevier, vol. 43(4), pages 471-485, December.
    11. McCarthy, Mary & Brennan, Mary, 2009. "Food risk communication: Some of the problems and issues faced by communicators on the Island of Ireland (IOI)," Food Policy, Elsevier, vol. 34(6), pages 549-556, December.
    Full references (including those not matched with items on IDEAS)

    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. Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad, 2004. "The agricultural policy simulator (AgriPoliS): an agent-based model to study structural change in agriculture (Version 1.0)," IAMO Discussion Papers 71, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    2. Ostermeyer, Arlette & Balmann, Alfons, "undated". "Perception of dairy farming from different views - results of a stakeholder discussion in the region Altmark, Germany," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114578, European Association of Agricultural Economists.
    3. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    4. Zengqing Wu & Run Peng & Xu Han & Shuyuan Zheng & Yixin Zhang & Chuan Xiao, 2023. "Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations," Papers 2311.06330, arXiv.org, revised Dec 2023.
    5. Cope, S. & Frewer, L.J. & Houghton, J. & Rowe, G. & Fischer, A.R.H. & de Jonge, J., 2010. "Consumer perceptions of best practice in food risk communication and management: Implications for risk analysis policy," Food Policy, Elsevier, vol. 35(4), pages 349-357, August.
    6. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.
    7. Balmann, Alfons & Happe, Kathrin, 2001. "Agentenbasierte Politik- und Sektoranalyse - Perspektiven und Herausforderungen," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 50(08), pages 1-12.
    8. Devaney, Laura, 2016. "Good governance? Perceptions of accountability, transparency and effectiveness in Irish food risk governance," Food Policy, Elsevier, vol. 62(C), pages 1-10.
    9. Andrew J Collins & Sheida Etemadidavan, 2022. "Humans and the core partition: An agent-based modeling experiment," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-23, September.
    10. JeongWook Son, 2022. "Complexity and Dynamics in Construction Project Organizations," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    11. Block, C. & Collins, J. & Ketter, W. & Weinhardt, C., 2009. "A Multi-Agent Energy Trading Competition," ERIM Report Series Research in Management ERS-2009-054-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Santiago J. Gangotena, 2017. "Dynamic coordinating non-equilibrium," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 30(1), pages 51-82, March.
    13. Bhuiyan, Shamsuzzaman, 2005. "Policy Options for Dryland Salinity Management: An Agent-Based Model for Catchment Level Analysis," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137795, Australian Agricultural and Resource Economics Society.
    14. Weisbuch, Gerard, 2000. "Environment and institutions: a complex dynamical systems approach," Ecological Economics, Elsevier, vol. 35(3), pages 381-391, December.
    15. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2016. "Agent-based modelling and simulation of smart electricity grids and markets – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 205-215.
    16. Fré Dé & Ric Deroian, 2001. "Morphogenesis Of Social Networks And Coexistence Of Technologies," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 10(6), pages 427-448.
    17. Denis Phan, 2004. "From Agent-Based Computational Economics towards Cognitive Economics," Post-Print halshs-03916500, HAL.
    18. Bier, Vicki & Gutfraind, Alexander, 2019. "Risk analysis beyond vulnerability and resilience – characterizing the defensibility of critical systems," European Journal of Operational Research, Elsevier, vol. 276(2), pages 626-636.
    19. Citera, Emanuele & Sau, Lino, 2019. "Complexity, Conventions and Instability: the role of monetary policy," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201924, University of Turin.
    20. Oliver Hinz & Jochen Eckert, 2010. "The Impact of Search and Recommendation Systems on Sales in Electronic Commerce," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(2), pages 67-77, April.

    More about this item

    Keywords

    ;
    ;
    ;

    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:gewi12:133052. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/gewisea.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.