Abstract
Four cases are studied in this assessment of how the harsh 2010 winter weather affected rail freight operations in Norway, Sweden, Switzerland and Poland and also of the reactive behaviour rail managers mobilised to reduce the adverse outcomes. The results are utilised in a fifth case assessing the proportion of freight train delays in Finland during 2008–2010 by modelling the odds for freight train delays as a function of changes in met-states on the Finnish network and weather-induced infrastructure damage. The results show that rail operators were totally unprepared to deal with the powerful and cascading effects of three harsh weather elements—long spells of low temperatures, heavy snowfalls and strong winds—which affected them concurrently and shut down large swathes of European rail infrastructure and train operations. Rail traffic disruptions spread to downstream and upstream segments of logistics channels, causing shippers and logistics operators to move freight away from rail to road transfer. As a result, railways lost market share for high-value container cargo, revenues and long-term business prospects for international freight movement. Analyses of measures employed to mitigate the immediate damage show that managers improvised their ways of handling crises rather than drew on a priori contingency, i.e. fight-back programmes and crisis management skills. Modelling the co-variation between extreme weather and freight train delays in Finland during 2008–2010 revealed that 60 % of late arrivals were related to winter weather. Furthermore, the combined effect of temperatures below −7 °C and 10–20 cm changes in snow depth coverage from 1 month to the next explained 62 % of the variation in log odds for freight train delays. Also, it has been shown that changes in the number of days with 10–20 cm snow depth coverage explained 66 % of the variation in late train arrivals, contributing to 626 min or 10.5 additional hours’ delay. Changes in the number of days with snowfalls over 5 mm accounted for 77 % variation in late train arrivals, implying that each additional day with this snowfall could contribute to 19.5 h’ delay. Finally, the combination of increased mean number of days with 5 mm snowfall and temperature below −20 °C explained 79 % of the variation in late arrivals, contributing to 193 min or 3.25 h’ delay. All results were significant (p = 0.00).
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Notes
As Qiang et al. (2009) have shown in numerical modelling of changes in supply chain risk level invoked by transport disruptions, this statement indicates that manufacturers, retailers and transport carriers within a given supply network place zero weights on disruption risks (page 108).
Although a disruption in transportation will certainly delay the arrival of goods at destination, a distinction is made here between a transportation disruption and a transportation delay which fall into two different risk categories. Because of larger element of surprise and lower preparedness level, Wilson (2007) maintained that risk drivers for a delay are much smaller than those of disruptions, which may last longer and hit several supply segments simultaneously. This distinction was also useful for determining the conditions of supply network robustness and strategies for dealing with disruptions caused by natural hazards.
Operations of freight trains by Dutch company’ on Swiss and Swedish networks were possible due to the First Infrastructure Package, and particularly directive 2001/14/EC, which defined rules for allocation of infrastructure capacity on the third countries’ networks, levying of infrastructure usage charges and safety certification for private rail undertakings.
None of the interviewees mentioned a possibility of receiving help from an inter-rail aid arrangement where several operators deposit equipment and spare parts for use in emergency situations. This differs evidently from a relatively common practice in the US where railways create aid banks from which spare parts, components and other not-so-often used types of equipment could be leased for swift dealing with emergencies and/or other urgent needs.
BDO Seidman, LLP is the US professional service firm providing assurance, tax, financial advisory and accounting services to a wide range of publicly traded and privately held companies. The company’s international arm, BDO International Limited, serves multinational clients through a global network of 1,138 offices in 115 countries.
The number of days with a stable snow depth cover could also indicate that measurement was simply undertaken at the end of the winter season and not the actual depth of snow changing between the different time periods.
Given that our case studies assessed the impacts of extreme harsh winter weather only, the impacts of extremely high summer temperatures and/or seasonal flooding were excluded from model analyses. This decision was supported by a finding that values of time lost (a product of valuations assigned to on-time arrivals and a proportion of train cargo arriving late) were highest during the late autumn and winter seasons, although delays occurred all year long.
References
Adegoke O, Gopalakrishnan M (2009) Managing disruptions in supply chains: a case study of a retail supply chain. Int J Prod Econ 118:168–174
Agresti A, Natarajan R (2001) Modelling clustered ordered categorical data: a survey. Int Stat Rev 69(3):345–371
BDO Study (2011) Disclosure and management of climate impacts. Virtual Strategy Magazine, October 5 (http://www.virtual-strategy.com)
Bundschuh M, Klabjan D, Thurston DL (2003) Modelling of robust and reliable supply chains. Organization Online e-print. htt://www.optimization-online.org. Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL
Closs D, McGarrel E (2004) Enhancing security through the supply chain. IBM Center for the Business of Government. Special Report Series
Delmonaco G, Margottini C, Spizzichino D (2006) ARMONIA methodology for mulit-risk assessment and the harmonization of different natural risk maps. Deliverable 3.11., ARMONIA
Fishhoff B, Lichtenstein S, Slovik P, Derby S, Keeney R (1981) Acceptable risk. Cambridge University Press, New York
Gunipero LC, Eltantawy RA (2004) Securing the upstream supply chain: a risk management approach. Int J Phys Distrib Logist Manag 9(34):698–713
Hendricks KB, Singhal VR (2005) An empirical analysis of the effect of supply chain disruptions on long-term stock price performance and risk of the firm. Prod Oper Manag 14:35–52
Holmgren AJ (2007) A framework for vulnerability assessment in electric power systems. In: Murray A, Grubesic T (eds) Critical infrastructure: reliability and vulnerability. Springer, New York
Hosmer DW, Lemeshow S (1989) Applied logistic regression. Wiley, New York
Kappes MS, Keiler M, von Elverfeldt K, Glade T (2012) Challenges of analyzing multi-hazard risk: a review. Nat Hazards. doi:10.1007/s11069-012-0294-2
Kleindorfer PR, Saad GH (2005) Managing disruption risks in supply chains. Prod Oper Manag 14(1):53–68
Kunreuther H (1976) Limited knowledge and insurance protection. Public Policy 24:227–261
Lai KH, Ngai EWT, Cheng TCE (2002) Measures for evaluating supply chain performance in transport logistics. Matekon 13:35–49
Long SJ (1997) Regression models for categorical and limited dependent variables. Sage Publications, London
March J, Shapira Z (1987) Managerial perspectives on risk and risk taking. Manage Sci 33:1404–1418
National Cooperative Freight Research Program (2011) Performance measures for freight transportation, transportation research board, report 10
Qiang Q, Nagurnet A, Dong J (2009) Modelling of supply chain risk under disruption with performance measurement and robustness analysis. In: Wu T, Blackhurst J (eds) Managing supply chain risk and vulnerability. Springer, New York
Repenning N, Sterman J (2001) Nobody ever gets credit for fixing problems that never happened. Calif Manage Rev 43:64–88
Rice B, Caniato F (2003) Supply chain response to terrorism: creating resilient and secure supply chains. Supply chain response to terrorism project interim report. MIT Center for Transportation and Logistics. MIT, Massachusetts
Sheffi Y (2001) Supply chain management under the threat of international terrorism. Int J Logist Manag 12(2):1–11
Sheffi Y (2005) The resilient enterprise. Overcoming vulnerability for competitive advantage. MIT Press, Cambridge
Snyder M, Swann WB (1978) Hypothesis-testing processes in social interactions. J Pers Soc Psychol 36(11):1202–1212
Supply Chain Digest (2011) Managing risk in a multi-tier supply chain. Demand Video cast, June 30th at http://www.sctvchannel.com/webinars/videocast3.php?cid
Svensson G (2002) A typology of vulnerability scenarios towards suppliers and customers in supply chains based upon perceived time and relationships dependencies. Int J Phys Distrib Logist Manag 32(3):168–187
Tang CS (2006) Perspectives on supply chain risk management. Int J Prod Econ 103:451–488
Wilson MC (2007) The impact of transportation disruptions on supply chain performance. Transp Res E 43:295–320
Yin RK (1994) Case study research: design and methods. Sage Publications, Thousand Oaks
Zsidisin G, Elram L, Carter J, Cavinato J (2004) An analysis of risk assessment techniques. Int J Phys Distrib Logist Manag 34(5):397–413
Acknowledgments
Our gratitude goes to Dr Pekka Leviakängas from VTT, Finland, who scientifically coordinated the EU-co-funded EWENT project (Extreme Weather Impacts on European Networks on Transport), which provided funding and opportunity to perform studies reported in this article. We also recognise and acknowledge professional help of Marko Nokkala and Anna-Maija Hietajärvi from VTT as regards facilitation of data provision by VR Group Ltd, the Finnish Transport Agency and the Finnish Meteorological Institute. We thank the Research Council of Norway for funding the Infra-Risk project from which our work also benefitted. Finally, we thank an anonymous reviewer who helped us to clarify important issues related to the modes how the European rail freight rail system functions.
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Ludvigsen, J., Klæboe, R. Extreme weather impacts on freight railways in Europe. Nat Hazards 70, 767–787 (2014). https://doi.org/10.1007/s11069-013-0851-3
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DOI: https://doi.org/10.1007/s11069-013-0851-3