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The use of violence in cargo theft – a supply chain disruption case

Author

Listed:
  • Daniel Ekwall

    (University of Borås
    Hanken School of Economics)

  • Björn Lantz

    (Chalmers University of Technology)

Abstract

This paper examines patterns of reported cargo thefts involving violence in the Europe, Middle East, and Africa region with regard to the value of stolen goods, incident frequency, transport chain location, and incident category. The research method is deductive and is based on analyses of secondary data obtained from the Incident Information Service by the Transported Asset Protection Association. The results are discussed within a frame of reference based on supply chain risk management and supply chain disruption literature. We found that perpetrators who use violence seem to cause greater losses per theft than those who use other types of modus operandi. Further, the most common type of violent cargo theft occurs on Mondays in January when cargo vehicles are robbed on the road and consumer electronics are stolen. In terms of supply chain disruption, violent cargo thefts can be seen as externally-caused disruptions, which can indirectly cause major problems for the supply chain.

Suggested Citation

  • Daniel Ekwall & Björn Lantz, 2018. "The use of violence in cargo theft – a supply chain disruption case," Journal of Transportation Security, Springer, vol. 11(1), pages 3-21, June.
    • Handle: RePEc:spr:jtrsec:v:11:y:2018:i:1:d:10.1007_s12198-018-0186-0
    DOI: 10.1007/s12198-018-0186-0
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    References listed on IDEAS

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    1. David L Levy, 1995. "International Sourcing and Supply Chain Stability," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 26(2), pages 343-360, June.
    2. Gorr, Wilpen & Olligschlaeger, Andreas & Thompson, Yvonne, 2003. "Short-term forecasting of crime," International Journal of Forecasting, Elsevier, vol. 19(4), pages 579-594.
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    Cited by:

    1. Daniel Ekwall & Björn Lantz, 2022. "Seasonality of incident types in transport crime – Analysis of TAPA statistics," Journal of Transportation Security, Springer, vol. 15(3), pages 193-222, December.
    2. Liang, Xinrui & Fan, Shiqi & Lucy, John & Yang, Zaili, 2022. "Risk analysis of cargo theft from freight supply chains using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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