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Discrete choice approach for assessing deprivation cost in humanitarian relief operations

Author

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  • Cantillo, Victor
  • Serrano, Iván
  • Macea, Luis F.
  • Holguín-Veras, José
Abstract
One of the key objectives of humanitarian logistics is to guarantee the timely delivery of supplies to people affected by disasters during the response phase. In this regard, it is fundamental to design appropriate models to minimize the social costs of response operations to distribute essential supplies to populations in need. In addition to merely cover logistics cost, social costs include deprivations costs, which are an increasing function of deprivation time, derived from the human suffering caused by the lack of access to a good or a service. This research uses the theory of discrete choices to assess deprivation costs due to the time spent waiting for the delivery of a basket of basic supplies, defined as the changes in the welfare of people affected by disasters. To this end, we designed a stated choice survey, applied to people living in areas affected by floods and earthquakes in Colombia. The estimated models consider the influence of individual's socioeconomic characteristics and random effects on the deprivation cost functions. The functions have a nonlinear structure, strictly increasing, and convex on the deprivation time. The results are useful for estimating the social costs of humanitarian relief operations.

Suggested Citation

  • Cantillo, Victor & Serrano, Iván & Macea, Luis F. & Holguín-Veras, José, 2018. "Discrete choice approach for assessing deprivation cost in humanitarian relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 33-46.
    • Handle: RePEc:eee:soceps:v:63:y:2018:i:c:p:33-46
    DOI: 10.1016/j.seps.2017.06.004
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    Cited by:

    1. Linlin Zhang & Na Cui, 2021. "Pre-Positioning Facility Location and Resource Allocation in Humanitarian Relief Operations Considering Deprivation Costs," Sustainability, MDPI, vol. 13(8), pages 1-26, April.
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    3. Guo, Penghui & Zhu, Jianjun, 2023. "Capacity reservation for humanitarian relief: A logic-based Benders decomposition method with subgradient cut," European Journal of Operational Research, Elsevier, vol. 311(3), pages 942-970.
    4. Victor Cantillo & Luis F. Macea & Miguel Jaller, 2019. "Assessing Vulnerability of Transportation Networks for Disaster Response Operations," Networks and Spatial Economics, Springer, vol. 19(1), pages 243-273, March.
    5. Amaya, Johanna & Serrano, Ivan & Cantillo, Víctor & Arellana, Julián & Pérez, Cinthia C., 2024. "Implications of trust, preparedness, risk perceptions, and local context on deprivation costs and disaster relief planning," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    6. Cotes, Nathalie & Cantillo, Victor, 2019. "Including deprivation costs in facility location models for humanitarian relief logistics," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 89-100.
    7. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.
    8. Fan, Yu & Shao, Jianfang & Wang, Xihui & Liang, Liang, 2024. "Contract design between relief organisations and private-sector vendors: A humanitarian logistics framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    9. Fan, Yu & Wang, Xihui & Zhu, Anqi & Shao, Jianfang & Liang, Liang, 2024. "Measuring the shortage cost through deprivation and envy in collaborating contract between the local authority and the enterprise," International Journal of Production Economics, Elsevier, vol. 271(C).
    10. Sarid, Adi S. & Glynn, Peter W. & Tzur, Michal, 2024. "Power distribution in developing countries — Planning for effectiveness and equity," Omega, Elsevier, vol. 123(C).
    11. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency relief routing models for injured victims considering equity and priority," Annals of Operations Research, Springer, vol. 283(1), pages 1573-1606, December.
    12. Amir Jamali & Amirhossein Ranjbar & Jafar Heydari & Sina Nayeri, 2022. "A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity," Annals of Operations Research, Springer, vol. 319(1), pages 1265-1300, December.
    13. Delgado-Lindeman, Maira & Arellana, Julián & Cantillo, Víctor, 2019. "Willingness to pay functions for emergency ambulance services," Journal of choice modelling, Elsevier, vol. 30(C), pages 28-37.
    14. Fan, Yu & Shao, Jianfang & Wang, Xihui, 2023. "Relief items procurement and delivery through cooperation with suppliers and logistics companies considering budget constraints," International Journal of Production Economics, Elsevier, vol. 264(C).
    15. Hu, Shaolong & Dong, Zhijie Sasha, 2019. "Supplier selection and pre-positioning strategy in humanitarian relief," Omega, Elsevier, vol. 83(C), pages 287-298.
    16. Shao, Jianfang & Fan, Yu & Wang, Xihui & Liang, Changyong & Liang, Liang, 2023. "Designing a new framework agreement in humanitarian logistics based on deprivation cost functions," International Journal of Production Economics, Elsevier, vol. 256(C).
    17. Fernandez Pernett, Stephanie & Amaya, Johanna & Arellana, Julián & Cantillo, Victor, 2022. "Questioning the implication of the utility-maximization assumption for the estimation of deprivation cost functions after disasters," International Journal of Production Economics, Elsevier, vol. 247(C).
    18. Shi, Wenqiang & He, Jie & Wang, Mingyue & Yang, Fang, 2024. "A dynamics model of the emergency medical supply chain in epidemic considering deprivation cost," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).

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