2.  Disruption in the effective conduct of operations of an individual, system, organisation or nation. It may result into loss of infrastructure, resources and human lives.  Types of Disaster :

3.  Required to identify and implement some measures in order to reduce the occurrence or rather impact of disaster, as much as possible.  Identification of Critical Success Factors (CSFs)

4.  Preparedness : ◦ Before disaster hits. ◦ T o avoid the gravest possible consequences of a disaster.  Response ◦ Immediate response sub-phase. ◦ Restore sub-phase.  Recovery ◦ Rehabilitation operations for a long-term perspective. ◦ Post-Disaster.  Mitigation ◦ To retain social and economic conditions. ◦ To reduce destruction level by implementing various laws and mechanisms.

6.  Information and Technology Utilization: Crucial as it directly impacts the speed of the response at the time of relief operations and enables better coordination between the actors.  Continuous improvement: Process of benchmarking in which processes and performances of relief operations are evaluated and implemented by comparing it with the best practices from the previous relief operations.  Effective utilisation of resources: It depends upon the collaborative working of disparate teams with a common goal.  Strategic Planning: A long-term approach is adopted which allows an organisation to be prepared for what must be done when an emergency occurs (Long, 1997).  Distribution Strategy: Time and cost are major constraints in emergency relief operations. For the same, it is quite important to adopt some of the standard distribution strategies, such as: Direct shipping, Cross-docking, and Centralized warehouse.  Minimisation of loss of human lives: The objective of the disaster relief operation is always linked to how quickly and conveniently the resources reach the affected people (Roy et al., 2012).

7.  Transport and capacity planning: Transportation is not just about transferring material, it also involves other aspects such as: selecting transport mode, capacity scheduling, maintenance, and intermodality (Pettit, 2009).  Disaster Assessment: Pre-warning system helps in providing the information regarding volume and intensity of disaster that could affect the human lives and infrastructure as well.  Risk Mitigation: Three levels of risk management: Strategic organisational, systematic operational, and dynamic operational. Organisations should adopt a formalised approach towards risk mitigation.  Prompt Response: The challenges include physical destruction, which limits logistical pathways and constrained resources, which limit funding during the disaster.  Restoration: Post-disaster recovery planning can be thought of as providing a blueprint for the restoration of a community after a disaster occurs. This can be done through long and short-term strategies.

8. 1.Interpretive Structural Modeling (ISM) - Depicts hierarchical relationships between various variables identified and produces structural models from poorly articulated mental models so as to make it more visible and well- defined. Steps: ◦ Development of Structural Self Interaction Matrix (SSIM). ◦ Constructing Initial Reachability Matrix ◦ Constructing Final Reachability Matrix. ◦ Level Partitions. ◦ Creation of ISM based model (Diagraph). 2.MICMAC Analysis - T o classify and analyse the critical success factors on the basis of their driving and dependence power. Positioning of factors within four clusters of a graph. Clusters: ◦ First cluster : Weak driver power and weak dependence (autonomous). ◦ Second cluster : Weak driver power but strong dependence (dependent). ◦ Third cluster : Strong driving power and also strong dependence (linkage). ◦ Fourth cluster : Strong driving power but weak dependence (independent). Identification and Modeling

10. Level partitions

11. I. Outcome of ISM

12. II. Outcome of MICMAC : Graphical representation

13.  This research paper has considered only limited number of critical success factors. In real situation, there can be few other critical success factors that may impact the HSCM.  Also, the ISM model developed can be statistically validated using Structural Equation Modelling (SEM) which has a capability to test the already developed hypothetical model.  The consistency among the expert opinions can also be validated using Kappa technique.

14.  Barbarosa G., Arda Y., (2004), “A two-stage stochastic programming framework for transportation planning in disaster response”, The Journal of Operational Research Society, vol. 55, pp 43.  Beamon, B.M. (2004), “Humanitarian relief chains: issues and challenges”, paper presented at the 34th International Conference on Computers & Industrial Engineering, San Francisco, CA, November 14-16.  Beamon B.M., Balcik B., (2008) “Performance measurement in humanitarian relief chains”, International Journal of Public Sector Management”,vol. 21, pp4-25.  Chopra, S., & Meindl, P., (2004) “Supply Chain Management, Strategy, Planning, and Operations 2nd ed. Pearson Education International, USA.  Cozzolino, A. (2012). “Humanitarian Logistics – Cross-Sector Cooperation in Disaster Relief Management”, SpringerBriefs in Business.  De la Torre L. E, Dolinskaya I.S, Smilowitz K.R., (2011), “Disaster relief routing: Integrating research and practice”, Socio- Economic Planning Science, pp 1-10.  Gooley TB (1999), “In times of crisis, logistics is the job”, Logistics Management and Distribution Report, Vol. 38 (9), pp. 82.  Gurnasekaran, A., Ngai, E.W.T (2004), “Information System in Supply Chain Integration and Management”, European Journal of operational research, Vol. 159 pp. 269-295.  Huotari, M-L, Wilson, TD (2001), “Determining organisational information needs: the critical success factors approach”, Information Research, Vol. 6 (3), April.  Korpela, J. and Tuominen, M. (1996), “Benchmarking logistics performance with an application of the analytic hierarchy process”, IEEE Transactions on Engineering Management, Vol. 43 No. 3, pp. 323-33.  Kovacs, G., Spens, K. M. (2007). “Humanitarian logistics in disaster relief operations”, International Journal of Physical Distribution & Logistics Management, Vol. 37, Issue 2, pp. 99-114.

15.  Mandal, A., Deshmukh, S.G., (1993), “Vendor Selection Using Interpretive Structural Modelling (ISM)”, International Journal of Operations and Production Management. Vol. 14, No. 6, pp. 52-59.  Munzberg, T. et.al (2013). “Decision Support for Critical Infrastructure Disruptions: An Integrated Approach to Secure Food Supply”. 10th International ISCRAM Conference – Baden-Baden, Germany, May 2013.  Pettit, S., Beresford A., (2009), “Critical success factors in the context of humanitarian aid supply chains”, International Journal of Physical Distribution & Logistics Management vol. 39 No. 6, pp. 450-468.  Roy, P., Albores, P., Brewster, C., (2012), “Logistical Framework for Last Mile Relief Distribution in Humanitarian Supply Chains: Consideration from the Field” Aston university, available at: http://windermere.aston.ac.uk/~kiffer/papers/Roy_ICMR12.pdf.  Sushil, (2012), “Interpreting the Interpretive Structural Model”, Global Journal of Flexible Systems Management, vol. 13(2), pp.87-106.  Van Wassenhove, L.N. (2006). “Blackett memorial lecture. Humanitarian aid logistics: Supply chain management in high gear”. Journal of Operational Research Society, 57(5), 475-489.