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Understanding the Impact of Farmer Autonomy on Transportation Collaboration Using Agent-Based Modeling

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Proceedings of the 2018 Conference of the Computational Social Science Society of the Americas (CSSSA 2018)

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Abstract

Food from small-scale farms has seen a recent resurgence in demand as consumers have become increasingly aware of the benefits of buying from regional food supply chains (RFSCs). However, these farmers still face pressure to reduce their costs and remain financially solvent. One potential solution for farmers is to use collaborative transportation methods to reduce costs. However, shared transportation means a reduction in the autonomy of the farmers, something they highly prize. To investigate this trade-off, an agent-based model (ABM) of farmers forming coalitions was created. This ABM includes cooperative game theory concepts to enable the farmers (agents) to form coalitions strategically. As expected, the model finds that the farmers do not form coalitions when their preference for autonomy is high, or the impact of distance between farmers is too great. These results represent a proof-of-concept for using agent-based modeling to investigate this problem.

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Author information

Authors and Affiliations

  1. Old Dominion University, Norfolk, VA, USA

    Andrew J. Collins

  2. University of Texas at Arlington, Arlington, TX, USA

    Caroline C. Krejci

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  1. Andrew J. Collins
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  2. Caroline C. Krejci
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Correspondence to Andrew J. Collins .

Editor information

Editors and Affiliations

  1. Department of Software and Information Systems, University of North Carolina at Charlotte, Charlotte, NC, USA

    Ted Carmichael

  2. Department of International Studies, Claremont Graduate University, Claremont, CA, USA

    Zining Yang

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Collins, A.J., Krejci, C.C. (2020). Understanding the Impact of Farmer Autonomy on Transportation Collaboration Using Agent-Based Modeling. In: Carmichael, T., Yang, Z. (eds) Proceedings of the 2018 Conference of the Computational Social Science Society of the Americas. CSSSA 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-35902-7_13

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