Risk factors influencing humanitarian operations: a case of temple cart festival

  • Authors

    • Jeevan S
    • M Suresh
    • Rajkumar Ranganathan
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.15539
  • Risk Factors, Humanitarian Operations, Interpretive Structural Modelling, Risk Analysis, Temple Cart Festival
  • Abstract

    The traditional Indian beliefs are concentrated on the strong holy force of positive vibration inside the temples and also during special occa-sions. Hence the human population gathering during the special occasions is uncontrollable. To control and manage the population, effective humanitarian operations are required and hence a framework is also required. In this paper, the objective is finding the risk factors influenc-ing on humanitarian operations in temple cart festivals and analyzing these factors. In order to study this, Interpretive Structural Modelling (ISM) approach is used to analyse the relationship among the risk factors of humanitarian operations. For the case study purpose, the data has been collected from the selected temple cart festival organizers in India. The paper projects forwards the most influential factors of oc-currence, detectability, disaster, preparedness which influences the humanitarian operations.

     

     

  • References

    1. [1] Ambika Devi Amma, T., Radhika, N., & Pramod, V. R. (2015). Major Cloud Computing Threats-An ISM Approach. International Journal of Applied Engineering Research, 10(16), 37804-37808.

      [2] Anson, S., Watson, H., Wadhwa, K., & Metz, K. (2017). Analysing social media data for disaster preparedness: Understanding the opportunities and barriers faced by humanitarian actors. International Journal of Disaster Risk Reduction, 21, 131-139.

      [3] Borade, A. B., &Bansod, S. V. (2012). Interpretive structural modeling-based framework for VMI adoption in Indian industries. The International Journal of Advanced Manufacturing Technology, 58(9), 1227-1242

      [4] Chidambaranathan, S., Muralidharan, C., &Deshmukh, S. G. (2009). Analyzing the interaction of critical factors of supplier development using Interpretive Structural Modeling—an empirical study. The International Journal of Advanced Manufacturing Technology, 43(11-12), 1081-1093.

      [5] Goncalves, P. (2008), “System dynamics modeling of humanitarian relief operationsâ€, research paper no. 4704-08, MIT Sloan, Cambridge, MA.

      [6] Govindan, K., Palaniappan, M., Zhu, Q., & Kannan, D. (2012). Analysis of third party reverse logistics provider using interpretive structural modeling. International Journal of Production Economics, 140(1), 204-211.

      [7] Haavisto, I., &Kovács, G. (2014). Perspectives on sustainability in humanitarian supply chains. Disaster Prevention and Management, 23(5), 610-631.

      [8] Jia, P., Diabat, A., &Mathiyazhagan, K. (2015). Analyzing the SSCM practices in the mining and mineral industry by ISM approach. Resources Policy, 46, 76-85.

      [9] Kannan, D., Diabat, A., & Shankar, K. M. (2014). Analyzing the drivers of end-of-life tire management using interpretive structural modeling (ISM). The International Journal of Advanced Manufacturing Technology, 72(9-12), 1603-1614.

      [10] Kumar, S., Boice, B. C., & Shepherd, M. J. (2013). Risk assessment and operational approaches to manage risk in global supply chains. Transportation Journal, 52(3), 391-411.

      [11] Kuo, T. C., Ma, H. Y., Huang, S. H., Hu, A. H., & Huang, C. S. (2010). Barrier analysis for product service system using interpretive structural model. The International Journal of Advanced Manufacturing Technology, 49(1), 407-417.

      [12] Overstreet, R. E., Hall, D., Hanna, J. B., & Kelly Rainer Jr, R. (2011). Research in humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 1(2), 114-131.

      [13] Patri, R., & Suresh, M. (2017a). Factors influencing lean implementation in healthcare organizations: An ISM approach. International Journal of Healthcare Management, 11(1), 25-37.

      [14] Patri, R., & Suresh, M. (2017b). Modelling the enablers of agile performance in healthcare organization: A TISM approach. Global Journal of Flexible Systems Management, 18(3), 251-272.

      [15] Saleeshya, P. G., Thampi, K. S., &Raghuram, P. (2012). A combined AHP and ISM-based model to assess the agility of supply chain–a case study. International Journal of Integrated Supply Management, 7(1-3), 167-191.

      [16] Van Wassenhove, L. N. (2006). Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational research Society, 57(5), 475-489.

      [17] Vitoriano, B., Ortuño, M. T., Tirado, G., & Montero, J. (2011). A multi-criteria optimization model for humanitarian aid distribution. Journal of Global Optimization, 51(2), 189-208.

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  • How to Cite

    S, J., Suresh, M., & Ranganathan, R. (2018). Risk factors influencing humanitarian operations: a case of temple cart festival. International Journal of Engineering & Technology, 7(2.33), 946-949. https://doi.org/10.14419/ijet.v7i2.33.15539

    Received date: 2018-07-13

    Accepted date: 2018-07-13

    Published date: 2018-06-08