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Modelling Fresh Strawberry Supply “From-Farm-to-Fork” as a Complex Adaptive Network

Author

Listed:
  • Engelseth, Per
  • Karlsen, Anniken
  • Verwaart, Tim

Abstract

The purpose of this study is to model and thereby enable simulation of the complete business entity of fresh food supply. A case narrative of fresh strawberry supply provides basis for this modelling. Lamming et al. (2000) point to the importance of discerning industry-specific product features (or particularities) regarding managing supply networks when discussing elements in “an initial classification of a supply network” while Fisher (1997) and Christopher et al. (2006, 2009) point to the lack of adopting SCM models to variations in products and market types as an important source of SCM failure. In this study we have chosen to move along a research path towards developing an adapted approach to model end-to-end fresh food supply influenced by a combination of SCM, system dynamics and complex adaptive network thinking.

Suggested Citation

  • Engelseth, Per & Karlsen, Anniken & Verwaart, Tim, 2011. "Modelling Fresh Strawberry Supply “From-Farm-to-Fork” as a Complex Adaptive Network," 2011 International European Forum, February 14-18, 2011, Innsbruck-Igls, Austria 122012, International European Forum on System Dynamics and Innovation in Food Networks.
  • Handle: RePEc:ags:iefi11:122012
    DOI: 10.22004/ag.econ.122012
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    References listed on IDEAS

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    1. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.
    2. Sylvie Huet & Guillaume Deffuant, 2008. "Differential Equation Models Derived from an Individual-Based Model Can Help to Understand Emergent Effects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-10.
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