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Deriving rules of thumb for facility decision making in humanitarian operations

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  • TURKEŠ, Renata
  • SÖRENSEN, Kenneth
  • PALHAZI CUERVO, Daniel

Abstract

In this paper,we investigate the factors that have an impact on the choice of facility configuration for inventory pre-positioning in preparation for emergencies - a critical decision faced by humanitarian managers. Current research in the field is rich with mathematical models and solution algorithms for the problem of pre-positioning emergency supplies. However, due to a lack of a strong mathematical background and/or computational infrastructure, the decision makers rely on simpler rules of thumb to guide their planning. Some managerial implications have been offered in the literature, but these have been derived from sensitivity analyses focused on a single factor and using a single case study, and as such can be misleading as they ignore important interactions between many instance characteristics. We carried out a large experimental study that analyses the effect of different instance characteristics and their interactions on the facility decision making. On the one hand, the outcomes of the study help us identify the most important factors and factor interactions that are further used to yield policy recommendations for facility planning. On the other hand, this study also demonstrates the extent of erroneousness of the guidelines derived from simple analyses, and as such hopefully promotes better experimental designs in the field of humanitarian logistics.

Suggested Citation

  • TURKEŠ, Renata & SÖRENSEN, Kenneth & PALHAZI CUERVO, Daniel, 2020. "Deriving rules of thumb for facility decision making in humanitarian operations," Working Papers 2020002, University of Antwerp, Faculty of Business and Economics.
  • Handle: RePEc:ant:wpaper:2020002
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    File URL: https://repository.uantwerpen.be/docstore/d:irua:250
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    References listed on IDEAS

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    1. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.
    2. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    3. Wenjun Ni & Jia Shu & Miao Song, 2018. "Location and Emergency Inventory Pre†Positioning for Disaster Response Operations: Min†Max Robust Model and a Case Study of Yushu Earthquake," Production and Operations Management, Production and Operations Management Society, vol. 27(1), pages 160-183, January.
    4. Burcu Balcik & Deniz Ak, 2014. "Supplier Selection for Framework Agreements in Humanitarian Relief," Production and Operations Management, Production and Operations Management Society, vol. 23(6), pages 1028-1041, June.
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    6. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    7. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    8. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    9. de la Torre, Luis E. & Dolinskaya, Irina S. & Smilowitz, Karen R., 2012. "Disaster relief routing: Integrating research and practice," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 88-97.
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