Applications of Network Science and Systems Thinking

  • Igor Linkov
  • Benjamin D. Trump
Part of the Risk, Systems and Decisions book series (RSD)


As our last collection of cases, Chap.  9 includes brief demonstrations of how network science may be utilized to explore elements of a system’s resilience. Through the modeling of systems as a series of interconnected nodes and linkages, network science provides a more quantitative assessment that many stakeholders in transportation systems, cybersecurity, or epidemiology would require to assist with decision-making. As with Chap.  8, each case includes a brief introduction of the case and the potential role for resilience, and includes a notation of how a network science approach might be constructed for cases ranging from transportation systems to epidemiological modeling.


  1. Allen, W. B., Liu, D., & Singer, S. (1993). Accesibility measures of US metropolitan areas. Transportation Research Part B: Methodological, 27(6), 439–449.CrossRefGoogle Scholar
  2. Beverly, K. (2010). Efficient use of highway capacity. College Station, TX: Texas Transportation Institute. FHWA-HOP-10-023.Google Scholar
  3. Chang, S. E., & Nojima, N. (2001). Measuring post-disaster transportation system performance: The 1995 Kobe earthquake in comparative perspective. Transportation Research Part A: Policy and Practice, 35(6), 475–494.Google Scholar
  4. Çolak, S., Lima, A., & González, M. C. (2016). Understanding congested travel in urban areas. Nature Communications, 7, 10793.CrossRefGoogle Scholar
  5. D’Este, G. M., Zito, R., & Taylor, M. A. (1999). Using GPS to measure traffic system performance. Computer-Aided Civil and Infrastructure Engineering, 14(4), 255–265.CrossRefGoogle Scholar
  6. Ganin, A. A., et al. (2016). Operational resilience: Concepts, design and analysis. Scientific Reports, 6, 19540.CrossRefGoogle Scholar
  7. Ganin, A. A., Kitsak, M., Marchese, D., Keisler, J. M., Seager, T., & Linkov, I. (2017). Resilience and efficiency in transportation networks. Science Advances, 3(12), e1701079.CrossRefGoogle Scholar
  8. Hoogendoorn, R., van Arem, B., & Hoogendoorn, S. (2014). Automated driving, traffic flow efficiency, and human factors: Literature review. Transportation Research Record: Journal of the Transportation Research Board, 2422, 113–120.CrossRefGoogle Scholar
  9. Kargl, F., Maier, J., & Weber, M. (2001, April). Protecting web servers from distributed denial of service attacks. In Proceedings of the 10th international conference on World Wide Web (pp. 514–524). ACM.Google Scholar
  10. Lambert, J. H., Karvetski, C. W., Spencer, D. K., Sotirin, B. J., Liberi, D. M., Zaghloul, H. H., & Linkov, I. (2011). Prioritizing infrastructure investments in Afghanistan with multiagency stakeholders and deep uncertainty of emergent conditions. Journal of Infrastructure Systems, 18(2), 155–166.CrossRefGoogle Scholar
  11. Massaro, E., Ganin, A., Perra, N., Linkov, I., & Vespignani, A. (2018). Resilience management during large-scale epidemic outbreaks. Scientific Reports, 8(1), 1859.CrossRefGoogle Scholar
  12. Sami, J., Pascal, F., & Younes, B. (2013). Public road transport efficiency: A stochastic frontier analysis. Journal of Transportation Systems Engineering and Information Technology, 13(5), 64–71.CrossRefGoogle Scholar
  13. Samuelsson, A., & Tilanus, B. (1997). A framework efficiency model for goods transportation, with an application to regional less-than-truckload distribution. Transport Logistics, 1(2), 139–151.CrossRefGoogle Scholar
  14. Schrank, D., Eisele, B., Lomax, T., & Bak, J. (2015). 2015 urban mobility scorecard. College Station, TX: Texas A&M Transportation Institute and INRIX.Google Scholar
  15. Sterbenz, J. P., Çetinkaya, E. K., Hameed, M. A., Jabbar, A., Qian, S., & Rohrer, J. P. (2013). Evaluation of network resilience, survivability, and disruption tolerance: Analysis, topology generation, simulation, and experimentation. Telecommunication Systems, 52(2), 705–736.Google Scholar
  16. Turnbull, K., Technical Activities Division, Transportation Research Board, & National Academies of Sciences, Engineering, and Medicine. (2016). Transportation resilience: Adaptation to climate change. Washington, DC: Transportation Research Board.CrossRefGoogle Scholar
  17. Yamashita, T., Izumi, K., & Kurumatani, K. (2004). Car navigation with route information sharing for improvement of traffic efficiency. In Proceedings of the 7th International IEEE Conference on Intelligent Transportation Systems, Washington, DC (pp. 465–470).Google Scholar
  18. Yan, G., Zhou, T., Hu, B., Fu, Z. Q., & Wang, B. H. (2006). Efficient routing on complex networks. Physical Review E, 73(4), 046108.CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Igor Linkov
    • 1
  • Benjamin D. Trump
    • 1
  1. 1.US Army Corps of EngineersConcordUSA

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