Annals of Operations Research

, Volume 283, Issue 1–2, pp 961–1000 | Cite as

Defining and measuring the network flexibility of humanitarian supply chains: insights from the 2015 Nepal earthquake

  • Hossein BaharmandEmail author
  • Tina Comes
  • Matthieu Lauras
S.I.:Applications of OR in Disaster Relief Operations, Part II


The efficient and effective response to disasters critically depends on humanitarian supply chains (HSCs). HSCs need to be flexible to adapt to uncertainties in needs, infrastructure conditions, and behavior of other organizations. The concept of ‘network flexibility’ is, however, not clearly defined. The lack of an unanimous definition has led to a lack of consistent understanding and comparisons. This paper makes a threefold contribution: first, it defines the concept of network flexibility for HSC in the context of sudden onset disasters. Second, it proposes a framework to measure network flexibility in HSCs. Third, we apply our framework to the 2015 Nepal earthquake case and provide evidence-based insights regarding how humanitarian organizations can improve network flexibility in HSCs. Our analyses for Nepal case show that delivery, IT support, and fleet criteria have the most influence on flexibility. Also, the application of our framework on the downstream network of nine humanitarian organizations shows low levels of network flexibility in all but one. This finding explains why several disruptions happened in relief distributions during the Nepal response.


Humanitarian supply chain Network flexibility Measurement framework Field research 2015 Nepal earthquake 



(We are particularly grateful to guest editors and reviewers for their constructive comments.) We would like to thank all the interviewees for taking part in our research and sharing their valuable information and experiences. Last but not least, our special thanks to other research team members in Nepal field research.

Supplementary material


  1. Abidi, H., de Leeuw, S., & Klumpp, M. (2013). Measuring success in humanitarian supply chains. International Journal of Business and Management Invention, 2(8), 31–39.Google Scholar
  2. Abidi, H., de Leeuw, S., & Klumpp, M. (2014). Humanitarian supply chain performance management: A systematic literature review. Supply Chain Management: An International Journal, 19(5/6), 592–608.Google Scholar
  3. Abounacer, R., Rekik, M., & Renaud, J. (2014). An exact solution approach for multi-objective locationtransportation problem for disaster response. Computers and Operations Research, 41, 83–93.Google Scholar
  4. Afshar, A., & Haghani, A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-Economic Planning Sciences, 46(4), 327–338.Google Scholar
  5. Altay, N., & Labonte, M. (2014). Challenges in humanitarian information management and exchange: Evidence from haiti. Disasters, 38(s1), S50–S72.Google Scholar
  6. Anaya-Arenas, A. M., Renaud, J., & Ruiz, A. (2014). Relief distribution networks: A systematic review. Annals of Operations Research, 223(1), 53–79.Google Scholar
  7. Baharmand, H., Boersma, K., Meesters, K., Mulder, F., & Wolbers, J. (2016). A multidisciplinary perspective on supporting community disaster resilience in Nepal. In 13th Conference on information systems for crisis response and management, Rio de Janeiro, Brazil. Google Scholar
  8. Baharmand, H., Salvadó, L. L., Comes, T., & Lauras, M. (2015). On the literature divergences of the humanitarian supply chain. Lecture notes in business information processing (Vol. 233, pp. 194–204). Berlin: Springer.Google Scholar
  9. Baharmand, H., Comes, T., & Lauras, M. (2017). Managing in-country transportation risks in humanitarian supply chains by logistics service providers: Insights from the 2015 Nepal earthquake. International Journal of Disaster Risk Reduction, 24, 549.Google Scholar
  10. Beamon, B. M., & Balcik, B. (2008). Performance measurement in humanitarian relief chains. International Journal of Public Sector Management, 21(1), 4–25.Google Scholar
  11. Beskese, A., Demir, H. H., Ozcan, H. K., & Okten, H. E. (2015). Landfill site selection using fuzzy ahp and fuzzy topsis: A case study for istanbul. Environmental Earth Sciences, 73(7), 3513–3521.Google Scholar
  12. Bourne, M., Mills, J., Wilcox, M., Neely, A., & Platts, K. (2000). Designing, implementing and updating performance measurement systems. International Journal of Operations and Production Management, 20(7), 754–771.Google Scholar
  13. Bozorgi-Amiri, A., & Asvadi, S. (2015). A prioritization model for locating relief logistic centers using analytic hierarchy process with interval comparison matrix. Knowledge-Based Systems, 86, 173–181.Google Scholar
  14. Buckley, J., Siler, W., & Tucker, D. (1986). A fuzzy expert system. Fuzzy Sets and Systems, 20(1), 1–16.Google Scholar
  15. Chan, J., & Comes, T. (2014). Innovative research designa journey into the information typhoon. Procedia Engineering, 78, 52–58.Google Scholar
  16. Chandes, J., & Paché, G. (2010). Strategizing humanitarian logistics: The challenge of collective action. Problems and Perspectives in Management, 8(1), 99–107.Google Scholar
  17. Chang, S. C. (1999). Fuzzy production inventory for fuzzy product quantity with triangular fuzzy number. Fuzzy Sets and Systems, 107(1), 37–57.Google Scholar
  18. Charles, A., Lauras, M., & Van Wassenhove, L. (2010). A model to define and assess the agility of supply chains: Building on humanitarian experience. International Journal of Physical Distribution and Logistics Management, 40(8/9), 722–741.Google Scholar
  19. Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1–14.Google Scholar
  20. Comes, T. (2016). Designing for networked community resilience. Procedia Engineering, 159, 6.Google Scholar
  21. Comes, T., & Van de Walle, B. (2016). Information systems for humanitarian logistics: Concepts and design principles (pp. 259–284). London: Kogan Page.Google Scholar
  22. Crum, M., Poist, R., Kovács, G., & Spens, K. M. (2011). Trends and developments in humanitarian logistics-a gap analysis. International Journal of Physical Distribution and Logistics Management, 41(1), 32–45.Google Scholar
  23. Day, J. M. (2014). Fostering emergent resilience: The complex adaptive supply network of disaster relief. International Journal of Production Research, 52(7), 1970–1988.Google Scholar
  24. Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115.Google Scholar
  25. Esmaeilikia, M., Fahimnia, B., Sarkis, J., Govindan, K., Kumar, A., & Mo, J. (2016). A tactical supply chain planning model with multiple flexibility options: An empirical evaluation. Annals of Operations Research, 244(2), 429–454.Google Scholar
  26. Fabbe-Costes, N., & Jahre, M. (2009). Flexible and integrated supply chains towards an innovative research platform. In 21th Annual NOFOMA conference, 2009.Google Scholar
  27. Garcia-Herreros, P., Wassick, J. M., & Grossmann, I. E. (2014). Design of resilient supply chains with risk of facility disruptions. Industrial and Engineering Chemistry Research, 53(44), 17,240–17,251.Google Scholar
  28. Glenn Richey Jr, R., Pettit, S., & Beresford, A. (2009). Critical success factors in the context of humanitarian aid supply chains. International Journal of Physical Distribution and Logistics Management, 39(6), 450–468.Google Scholar
  29. GoN, GoN .(2015). Nepal earthquake 2015 post disaster needs assessment. Report.
  30. Gong, Z. (2008). An economic evaluation model of supply chain flexibility. European Journal of Operational Research, 184(2), 745–758.Google Scholar
  31. Grigore, S. D. (2007). Supply chain flexibility. Romanian Economic and Business Review, 2(1), 66.Google Scholar
  32. Guha-Sapir, D., Hoyois, P., & Below, R. (2015). Annual disaster statistical review 2014. Report, Universit catholique de Louvain, Belgium.
  33. Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain riskdefinition, measure and modeling. Omega, 52, 119–132.Google Scholar
  34. Holguín-Veras, J., Taniguchi, E., Jaller, M., Aros-Vera, F., Ferreira, F., & Thompson, R. G. (2014). The tohoku disasters: Chief lessons concerning the post disaster humanitarian logistics response and policy implications. Transportation Research Part A: Policy and Practice, 69, 86–104.Google Scholar
  35. Husdal, J. (2010). A conceptual framework for risk and vulnerability in virtual enterprise networks. In Managing risk in virtual enterprise networks: implementing supply chain principles (p. 1) Google Scholar
  36. Jahre, M., Persson, G., Kovács, G., & Spens, K. M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution and Logistics Management, 37(2), 99–114.Google Scholar
  37. Kabra, G., & Ramesh, A. (2016). Information technology, mutual trust, flexibility, agility, adaptability: Understanding their linkages and impact on humanitarian supply chain management performance. Risk, Hazards and Crisis in Public Policy, 7(2), 79–103.Google Scholar
  38. Kahraman, C., Kahraman, C., Yasin Ateş, N., Çevik, S., Gülbay, M., & Ayça Erdoǧan, S. (2007). Hierarchical fuzzy topsis model for selection among logistics information technologies. Journal of Enterprise Information Management, 20(2), 143–168.Google Scholar
  39. Kamalahmadi, M., & Mellat-Parast, M. (2015). Developing a resilient supply chain through supplier flexibility and reliability assessment. International Journal of Production Research, 54, 1–20.Google Scholar
  40. Kovács, G., & Spens, K. M. (2012). Relief supply chain management for disasters: Humanitarian aid and emergency logistics. Hershey: Information Science Reference.Google Scholar
  41. Krajewski, L., Wei, J. C., & Tang, L. L. (2005). Responding to schedule changes in build-to-order supply chains. Journal of Operations Management, 23(5), 452–469.Google Scholar
  42. Manoj, U., Kumar, S., & Gupta, S. (2015). An integrated logistic model for predictable disasters. Production and Operations Management, 25, 791.Google Scholar
  43. Maria Jesus Saenz, P., Xenophon Koufteros, D., Hohenstein, N. O., Feisel, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience: A systematic review and paths for further investigation. International Journal of Physical Distribution and Logistics Management, 45(1/2), 90–117.Google Scholar
  44. Moon, K. K. L., Yi, C. Y., & Ngai, E. (2012). An instrument for measuring supply chain flexibility for the textile and clothing companies. European Journal of Operational Research, 222(2), 191–203.Google Scholar
  45. Naim, M. M., Potter, A. T., Mason, R. J., & Bateman, N. (2006). The role of transport flexibility in logistics provision. The International Journal of Logistics Management, 17(3), 297–311.Google Scholar
  46. Najafi, M., Eshghi, K., & Dullaert, W. (2013). A multi-objective robust optimization model for logistics planning in the earthquake response phase. Transportation Research Part E: Logistics and Transportation Review, 49(1), 217–249.Google Scholar
  47. Nudurupati, S. S., Bititci, U. S., Kumar, V., & Chan, F. T. (2011). State of the art literature review on performance measurement. Computers and Industrial Engineering, 60(2), 279–290.Google Scholar
  48. Oguztimur, S. (2011). Why fuzzy analytic hierarchy process approach for transport problems? European Regional Science Association: Ersa Conference Papers.Google Scholar
  49. Oloruntoba, R., & Gray, R. (2006). Humanitarian aid: An agile supply chain? Supply Chain Management: An International Journal, 11(2), 115–120.Google Scholar
  50. Paksoy, T., Pehlivan, N. Y., & Kahraman, C. (2012). Organizational strategy development in distribution channel management using fuzzy ahp and hierarchical fuzzy topsis. Expert Systems with Applications, 39(3), 2822–2841.Google Scholar
  51. Pedraza-Martinez, A. J., & Van Wassenhove, L. N. (2016). Empirically grounded research in humanitarian operations management: The way forward. Journal of Operations Management, 45, 1–10.Google Scholar
  52. Perego, A., Perotti, S., & Mangiaracina, R. (2011). Ict for logistics and freight transportation: A literature review and research agenda. International Journal of Physical Distribution and Logistics Management, 41(5), 457–483.Google Scholar
  53. Perry, M. (2007). Natural disaster management planning: A study of logistics managers responding to the tsunami. International Journal of Physical Distribution and Logistics Management, 37(5), 409–433.Google Scholar
  54. Pettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring supply chain resilience: Development and implementation of an assessment tool. Journal of Business Logistics, 34(1), 46–76.Google Scholar
  55. Prasad, S., Zakaria, R., & Altay, N. (2016). Big data in humanitarian supply chain networks: A resource dependence perspective. Annals of Operations Research. Scholar
  56. Ritchie, J., Lewis, J., Nicholls, C. M., & Ormston, R. (2013). Qualitative research practice: A guide for social science students and researchers. Newcastle upon Tyne: Sage.Google Scholar
  57. Salvadó, L. L., Lauras, M., Comes, T., & Van de Walle, B. (2015). Towards more relevant research on humanitarian disaster management coordination. In B. Palen & H. Comes (Eds.), 12th International conference on information systems for crisis response and management (ISCRAM). Kristiansand: University of Agder.Google Scholar
  58. Santarelli, G., Abidi, H., Regattieri, A., & Klumpp, M. (2013). A performance measurement system for the evaluation of humanitarian supply chains. In POMS, 24th annual conference of the production and operations management society. Google Scholar
  59. Santarelli, G., Abidi, H., Klumpp, M., & Regattieri, A. (2015). Humanitarian supply chains and performance measurement schemes in practice. International Journal of Productivity and Performance Management, 64(6), 784–810.Google Scholar
  60. Scholten, K., Sharkey Scott, P., & Fynes, B. (2010). (Le) agility in humanitarian aid supply chains. International Journal of Physical Distribution and Logistics Management, 40(8/9), 623–635.Google Scholar
  61. Sheffi, Y., & Rice, J. B, Jr. (2005). A supply chain view of the resilient entreprise. MIT Sloan Management Review, 47(1), 41.Google Scholar
  62. Shen, Z., Dessouky, M. M., & Ordóñez, F. (2009). A twostage vehicle routing model for largescale bioterrorism emergencies. Networks, 54(4), 255–269.Google Scholar
  63. Siham, L., Jean-Claude, B., Laurent, G., Yves, D., & Zied, J. (2015). Designing supply chain performance measurement and management systems: A systemic perspective. In 4th International conference on advanced logistics and transport (ICALT) (pp 211–216). IEEE.Google Scholar
  64. Sillanpää, I. (2015). Empirical study of measuring supply chain performance. Benchmarking: An International Journal, 22(2), 290–308.Google Scholar
  65. Slack, N. (2005). The changing nature of operations flexibility. International Journal of Operations and Production Management, 25(12), 1201–1210.Google Scholar
  66. Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy topsis methods. Expert Systems with Applications, 37(12), 7745–7754.Google Scholar
  67. Tchouakeu, L. M., Maitland, C., Tapia, A., & Kvasny, L. (2013). Humanitarian inter-organisational collaboration network: Investigating the impact of network structure and information and communication technology on organisation performance. International Journal of Services, Technology and Management, 19(1–3), 19–42. Scholar
  68. UNWFP .(2015a). Minutes from logistics cluster-20 June 2015. Report,
  69. UNWFP .(2015b). Nepal situation update-15 May 2015. Report,
  70. UNWFP .(2015c). Nepal situation update-20 June 2015. Report,
  71. Vaillancourt, A. (2016). Kit management in humanitarian supply chains. International Journal of Disaster Risk Reduction, 18, 64–71.Google Scholar
  72. Van de Walle, B., & Comes, T. (2015). On the nature of information management in complex and natural disasters. Procedia Engineering, 107, 403–411.Google Scholar
  73. Van de Walle, B., & Turoff, M. (2007). Emergency response information systems: Emerging trends and technologies. Communications of the ACM, 50(3), 29–31.Google Scholar
  74. Van Wassenhove, L. N. (2006). Humanitarian aid logistics: Supply chain management in high gear. Journal of the Operational Research Society, 57(5), 475–489.Google Scholar
  75. Vega, D., & Roussat, C. (2015). Humanitarian logistics: The role of logistics service providers. International Journal of Physical Distribution and Logistics Management, 45(4), 352–375.Google Scholar
  76. Yushimito, W. F., Jaller, M., & Ukkusuri, S. (2012). A voronoi-based heuristic algorithm for locating distribution centers in disasters. Networks and Spatial Economics, 12(1), 21–39.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of ICTUniversity of AgderGrimstadNorway
  2. 2.Department of Multi-Actor SystemsDelft University of TechnologyDelftThe Netherlands
  3. 3.Industrial Engineering DepartmentIMT Mines Albi- University of ToulouseAlbiFrance

Personalised recommendations