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Fuel Panics: insights from spatial agent-based simulation

Author

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  • Eben Upton

    (Judge Business School, University of Cambridge Cambridge)

  • William J. Nuttall

    (Department of Design, Development, Environment and Materials, The Open University,Milton Keynes,)

Abstract

The United Kingdom has twice suffered major disruption as a result of fuel panics first in September 2000 coincident with a wave of fuel protests and more recently in March 2012 following politcal warnings of possible future supply chain disruption. In each case the disruption and economic consequences were serious. Fuel distribution is an example of a supply chain. Approaches to supply-chain planning based on linear programming are poorly suited to modelling non-equilibrium effects, while coarse-grained system dynamics models often fail to capture local phenomena which contribute to the evolution of global demand. In this Paper, we demonstrate that agent-based techniques offer a powerful framework for cosimulation of supply chains and consumers under conditions of transient demand. In the case of fuel panic crisis, we show that even a highly abstract model can reproduce a range of transient phenomena seen in the real world, and present a set of practical recommendations for policymakers faced with panic-buying.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Eben Upton & William J. Nuttall, 2013. "Fuel Panics: insights from spatial agent-based simulation," Working Papers EPRG 1305, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg1305
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    References listed on IDEAS

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    More about this item

    Keywords

    Fuel Panics; Agent Based Simulation; Supply Chain;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • H30 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - General
    • J48 - Labor and Demographic Economics - - Particular Labor Markets - - - Particular Labor Markets; Public Policy
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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