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Human behaviour versus optimising agents and the resilience of farms – Insights from agent-based participatory experiments with FarmAgriPoliS

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  • Appel, Franziska
  • Balmann, Alfons

Abstract

This paper aims to examine the extent to which human participants show higher resilience compared to computer agents in agent-based participatory experiments. We motivate and examine three types of resilient behaviour of farmers during a crisis or as response to competitive pressure: successful survival, loss-minimising farm exits, and path breaking respectively path creating growth strategies. Our experiments revealed that human decision makers recognised and exploited such resilient strategies in periods of crisis or under challenging circumstances in general better than myopic optimising agents, although they did not perform better on average. The reason can be seen in a substantial heterogeneity of human decision makers, for which we identified four categories: negligent gamblers, actors missing opportunities, solid farm managers and successful path breakers.

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  • Appel, Franziska & Balmann, Alfons, 2019. "Human behaviour versus optimising agents and the resilience of farms – Insights from agent-based participatory experiments with FarmAgriPoliS," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 40, pages 1-1.
    • Handle: RePEc:zbw:espost:206689
    DOI: 10.1016/j.ecocom.2018.08.005
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    References listed on IDEAS

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    1. Appel, Franziska & Balmann, Alfons & Dong, Changxing & Rommel, Jens, 2018. "FarmAgriPoliS: An agricultural business management game for behavioral experiments, teaching, and gaming," IAMO Discussion Papers 271455, Institute of Agricultural Development in Transition Economies (IAMO).
    2. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    3. Olivier Barreteau, 2003. "Our Companion Modelling Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(2), pages 1-1.
    4. repec:zbw:iamodp:271455 is not listed on IDEAS
    5. Balmann, Alfons & Odening, Martin & Weikard, Hans-Peter & Brandes, Wilhelm, 1996. "Path-dependence without increasing returns to scale and network externalities," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 159-172, January.
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    Cited by:

    1. Shang, Linmei & Wang, Jifeng & Schäfer, David & Heckelei, Thomas & Gall, Juergen & Appel, Franziska & Storm, Hugo, 2024. "Surrogate modelling of a detailed farm‐level model using deep learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 75(1), pages 235-260.
    2. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.
    3. Seidel, Claudia & Shang, Linmei & Britz, Wolfgang, 2023. "A critical assessment of neural networks as meta-model of a farm optimization model," Discussion Papers 338200, University of Bonn, Institute for Food and Resource Economics.
    4. Huber, Robert & Bartkowski, Bartosz & Brown, Calum & El Benni, Nadja & Feil, Jan-Henning & Grohmann, Pascal & Joormann, Ineke & Leonhardt, Heidi & Mitter, Hermine & Müller, Birgit, 2024. "Farm typologies for understanding farm systems and improving agricultural policy," Agricultural Systems, Elsevier, vol. 213(C).
    5. Marius Eisele & Christian Troost & Thomas Berger, 2021. "How Bayesian Are Farmers When Making Climate Adaptation Decisions? A Computer Laboratory Experiment for Parameterising Models of Expectation Formation," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 805-828, September.
    6. Nyberg, Ylva & Wetterlind, Johanna & Jonsson, Mattias & Öborn, Ingrid, 2020. "The role of trees and livestock in ecosystem service provision and farm priorities on smallholder farms in the Rift Valley, Kenya," Agricultural Systems, Elsevier, vol. 181(C).

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