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Framework proposal to support the suppliers’ selection of Humanitarian assistance items: a Flood Case Study in Brazil

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Abstract

Humanitarian Logistics (HL) is comprised of processes and involved systems in the mobilization of people, resources, and knowledge to help affected communities when they are faced with natural disasters. In this study, the Reference Task Model (RTM) provides an overview of these processes and supports Business Process Management (BPM). This article aims to evaluate from a proposed framework the selection of suppliers to guarantee indispensable material resources in the fastest way. We apply a BPM procedure to support the supplier selection process following a flood disaster. We describe each of the stages that make up the proposal of the BPM life cycle applied to the HL. We employ some tools as Balanced Scorecard (BSC) to achieve consensus on objectives, indicators, targets, and actions to be defined for a disaster situation. For balancing the allocation of supplies, the network flow problem is adapted for the quantitative model. That model contains the variables of time, demand, and capacity, and includes the set of adequate suppliers. For the application, we describe a flood disaster case study from a state located in southern Brazil. The main results of the application of the proposed framework are obtained from an optimized holistic view; they represent the selection of suppliers of humanitarian items and consider delivery times, resources, and deprivation costs. One contribution of the proposed framework is the ease of its implementation from process-based technologies and its emphasis on being strategy focused. Further, it concentrates experiences and good practices from humanitarian organizations.

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References

  • ABPMP. (2013). BPM CBOK Version 3.0: Guide to the Business Process Management Common Body Of Knowledge (1st ed.). CreateSpace Independent Publishing Platform

  • Agarwal, S., Kant, R., & Shankar, R. (2019). Humanitarian supply chain management frameworks: A critical literature review and framework for future development. Benchmarking, 26(6), 1749–1780. https://doi.org/10.1108/BIJ-08-2018-0245

    Article  Google Scholar 

  • Alem, D., Clark, A., & Moreno, A. (2016). Stochastic network models for logistics planning in disaster relief. European Journal of Operational Research, 255(1), 187–206

    Article  Google Scholar 

  • Anjomshoae, A., Hassan, A., Kunz, N., Wong, K. Y., & Leeuw, S. (2017). Towards a Dynamic Balanced Scorecard Model for Humanitarian Relief Organizations’ Performance Management. Journal of Humanitarian Logistics, 7(2), 194–218

    Google Scholar 

  • Anparasan, A. A., & Lejeune, M. A. (2017a). Data laboratory for supply chain response models during epidemic outbreaks. Annals of Operations Research, 1–12

  • Anparasan, A. A., & Lejeune, M. A. (2017b). Resource deployment and donation allocation for epidemic outbreaks. Annals of Operations Research, 1–24

  • Balcik, B., & Ak, D. (2014). Supplier selection for framework agreements in humanitarian relief. Production and Operations Management, 23(6), 1028–1041. https://doi.org/10.1111/poms.12098

    Article  Google Scholar 

  • Barbarosoglu, G., & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. The Journal of the Operational Research Society, 55(1), 43–53

    Article  Google Scholar 

  • Beamon, B. M. (2004). Humanitarian Relief Chains: Issues and Challenges. Proceedings of the 34th International Conference on Computers & Industrial Engineering, 77–82

  • Becker, J., Rosemann, M., & von Uthmann, C. (2000). Guidelines of Business Process Modeling. In van der W. Aalst, J. Desel, & A. Oberweis (Eds.), Business Process Management - Models, Techniques, and Empirical Studies. Springer

  • Behl, A., & Dutta, P. (2019). Humanitarian supply chain management: a thematic literature review and future directions of research. Annals of Operations Research, 283(1), 1001–1044

    Article  Google Scholar 

  • Blecken, A. (2010). Supply chain process modelling for humanitarian organizations. International Journal of Physical Distribution & Logistics Management, 40(8/9), 675–692

    Article  Google Scholar 

  • Clark, A., & Culkin, B. (2013). A network transhipment model for planning humanitarian relief operations after a natural disaster. Decision aid models for disaster management and emergencies (pp. 233–257). Atlantis Press

  • Dewangan, D. K., Agrawal, R., & Sharma, V. (2016). An approach of modeling for humanitarian supplies. Managing Humanitarian Logistics (pp. 153–163). Springer India

  • Dumas, M., La Rosa, M., Mendling, J., & Reijers, A., H (2013). Fundamentals of business process management. Springer

  • Ertem, M. A., Buyurgan, N., & Rossetti, M. D. (2010). Multiple-buyer procurement auctions framework for humanitarian supply chain management. International Journal of Physical Distribution and Logistics Management, 40(3), 202–227. https://doi.org/10.1108/09600031011035092

    Article  Google Scholar 

  • Esmaeili, V., & Barzinpour, F. (2014). Integrated decision making model for urban disaster management: Amulti-objective genetic algorithm approach. International Journal of Industrial Engineering Computations, 5(1), 55–70

    Article  Google Scholar 

  • Falasca, M., & Zobel, C. W. (2011). A two-stage procurement model for humanitarian relief supply chains. Journal of Humanitarian Logistics and Supply Chain Management, 1(2), 151–169

    Article  Google Scholar 

  • Ghorbani, M., & Ramezanian, R. (2020). Integration of carrier selection and supplier selection problem in humanitarian logistics. Computers and Industrial Engineering, 144(June 2019), 106473. https://doi.org/10.1016/j.cie.2020.106473

  • Gonzalez-Feliu, J., Chong, M., Vargas-Florez, J., de Brito, I. Jr., Osorio-Ramirez, C., Piatyszek, E., & Altamirano, R. Q. (2020). The Maturity of Humanitarian Logistics against Recurrent Crises. Social Sciences, 9(6), 90

    Article  Google Scholar 

  • Gösling, H., & Geldermann, J. (2014). A framework to compare OR models for humanitarian logistics. Procedia Engineering, 78, 22–28. https://doi.org/10.1016/j.proeng.2014.07.034

    Article  Google Scholar 

  • Grass, E., & Fischer, K. (2020). Case study design for short-term predictable disasters. Journal of Humanitarian Logistics and Supply Chain Management, 10(3), 391–419. https://doi.org/10.1108/JHLSCM-11-2019-0077

    Article  Google Scholar 

  • Gupta, S., Sahay, B. S., & Charan, P. (2016a). Relief network model for efficient disaster management and disaster recovery. Managing humanitarian logistics (pp. 85–104). Springer India

  • Gupta, S., Starr, M. K., Farahani, R. Z., & Matinrad, N. (2016b). Disaster management from a POM perspective: Mapping a new domain. Production and Operations Management, 25(10), 1611–1637

    Article  Google Scholar 

  • Habib, M. S., & Sarkar, B. (2017). n integrated location-allocation model for temporary disaster debrismanagement under an uncertain environment. Sustainability, 9(5), 716

    Article  Google Scholar 

  • Haghi, M., Ghomi, S. M. T. F., & Jolai, F. (2017). Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource. Journal of Cleaner Production, 154, 188–202

    Article  Google Scholar 

  • Hasani, A., & Mokhtari, H. (2018). Redesign strategies of a comprehensive robust relief network for disaster management. Socio-Economic Planning Sciences, 64, 92–102

    Article  Google Scholar 

  • Hu, S., & Dong, Z. S. (2019). Supplier selection and pre-positioning strategy in humanitarian relief. Omega (United Kingdom), 83, 287–298. https://doi.org/10.1016/j.omega.2018.10.011

    Article  Google Scholar 

  • Jabbour, C. J. C., Sobreiro, V. A., Jabbour, A. B. L. S., Campos, L. M. S., Mariano, E. B., & Renwick, D. W. S. (2019). An analysis of the literature on humanitarian logistics and supply chain management: paving the way for future studies. Annals of Operations Research, 283(1), 289–307

    Article  Google Scholar 

  • Jahre, M., Jensen, L., & Listou, T. (2009). Theory development in humanitarian logistics: a framework and three cases. Management Research News, 32(11), 1008–1023

    Article  Google Scholar 

  • Kennington, J. L., & Helgason, R. V. (1980). Algorithm for Network Programming. Spring

  • Khoshsirat, M., Dabbagh, R., & Bozorgi-Amiri, A. (2021). A multi-objective robust possibilistic programming approach to coordinating procurement operations in the disaster supply chain using a multi-attribute reverse auction mechanism. Computers & Industrial Engineering, 158

  • Kim, S., Ramkumar, M., & Subramanian, N. (2019). Logistics service provider selection for disaster preparation: a socio-technical systems perspective. Annals of Operations Research, 283(1–2), 1259–1282. https://doi.org/10.1007/s10479-018-03129-3

    Article  Google Scholar 

  • Kirac, E., & Milburn, A. B. (2018). A general framework for assessing the value of social data for disaster response logistics planning. European Journal of Operational Research, 269(2), 486–500

    Article  Google Scholar 

  • Kınaya, Ö. B., Kara, B. Y., Saldanha-da-Gama, F., & Correia, I. (2018). Modeling the shelter site location problem using chance constraints: A case study for Istanbul. European Journal of Operational Research, 270(1), 132–145

    Article  Google Scholar 

  • Lauras, M., Vargas, J., Dupont, L., & Charles, A. (2014). A location-allocation model for more consistent humanitarian supply chains. International Conference on Information Systems for Crisis Response and Management in Mediterranean Countries, 1–12

  • Lima, F. S., Oliveira, D., & Gonçalves, M. B. (2014). Methodology for Clustering Cities Affected by Natural Disasters. Advances in Intelligent Systems and Computing (pp. 97–106). Springer

  • Lima, F. S., Gonçalves, M. B., Samed, M. M. A., & Hellingrath, B. (2015). Integration of a mathematical model within reference task model at the procurement process using BPMN for disasters events. International Conference in Swarm Intelligence, 440–452

  • Lu, Q., Wu, J., Goh, M., & De Souza, R. (2019). Agility and resource dependency in ramp-up process of humanitarian organizations. International Journal of Logistics Management, 30(3), 845–862. https://doi.org/10.1108/IJLM-05-2018-0119

    Article  Google Scholar 

  • McGuire, G. A. (2006). Development of a supply chain management framework for health care goods provided as humanitarian assistance in complex political emergencies. WU Vienna University of Economics and Business

  • Nagurney, A., Flores, E. A., & Soylu, C. (2016). A generalized nash equilibrium network model for postdisaster humanitarian relief. Transportation Research Part E: Logistics and Transportation Review, 95, 1–18

    Article  Google Scholar 

  • Olaogbebikan, J. E., & Oloruntoba, R. (2019). Similarities between disaster supply chains and commercial supply chains: a SCM process view. Annals of Operations Research, 283(1–2), 517–542. https://doi.org/10.1007/s10479-017-2690-1

    Article  Google Scholar 

  • Oloruntoba, R., & Gray, R. (2006). Humanitarian aid: An agile supply chain? Supply Chain Management, 11(2), 115–120. https://doi.org/10.1108/13598540610652492

    Article  Google Scholar 

  • Oloruntoba, R., Sridharan, R., & Davison, G. (2018). A proposed framework of key activities and processes in the preparedness and recovery phases of disaster management. Disasters, 42(3), 541–570. https://doi.org/10.1111/disa.12268

    Article  Google Scholar 

  • Ozguven, E. E., & Ozbay, K. (2015). An RFID-based inventory management framework for emergency relief operations. Transportation Research Part C: Emerging Technologies, 57, 166–187. https://doi.org/10.1016/j.trc.2015.06.021

    Article  Google Scholar 

  • Ransikarbum, K., & Mason, S. J. (2016a). Goal programming-based post-disaster decision making for integrated relief distribution and early-stage network restoration. International Journal of Production Economics, 182, 324–341

    Article  Google Scholar 

  • Ransikarbum, K., & Mason, S. J. (2016b). Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations. International Journal of Production Research, 54(1), 49–68

    Article  Google Scholar 

  • Salam, M. A., & Khan, S. A. (2020). Lessons from the humanitarian disaster logistics management: A case study of the earthquake in Haiti. Benchmarking, 27(4), 1455–1473. https://doi.org/10.1108/BIJ-04-2019-0165

    Article  Google Scholar 

  • Scholten, K., Scott, S., P., & Fynes, B. (2014). Mitigation processes – antecedents for building supply chain resilience. Supply Chain Management, 19(2), 211–228

    Article  Google Scholar 

  • Schulz, S. F., & Heigh, I. (2009). Logistics performance management in action within a humanitarian organization.Management Research News, 32(11)

  • Shehabuddeen, N., Probert, D., Phaal, R., & Platts, K. (2000). Representing and approaching complex management issues: part 1 – role and definition. Working Paper UC

  • Smith, R. F. (2007). Business Process Management and the Balanced Scorecard: using processes as strategic drivers. John Wiley & Sons, Inc.

  • Souza, P., Souza, R. M., Petri, S. M., & Lunkes, R. J. (2015). Development of Balanced Scorecard as a Strategic Management for a Graduate Program. Journal IEEE América Latina, 13, 277–283

    Google Scholar 

  • Stewart, M., & Ivanov, D. (2019). Design redundancy in agile and resilient humanitarian supply chains.Annals of Operations Research,1–27

  • Tachini, M., Kobyiama, M., Loesch, C., Severo, D. L., Silva, H. S., & Cordero, A. (2009). Avaliação de danos de inundações ocorridas em Blumenau/SC nos anos 1983, 1984, 1992 e 2001. XVIII Simpósio Brasileiro de Recursos Hídricos

  • Thomas, A. (2004). Elevating Humanitarian Logistics. International Aid & Trade Review

  • Timperio, G., Panchal, G. B., Samvedi, A., Goh, M., & De Souza, R. (2017). Decision support framework for location selection and disaster relief network design. Journal of Humanitarian Logistics and Supply Chain Management, 7(3), 222–245

    Article  Google Scholar 

  • Timperio, G., Tiwari, S., Lee, C. K., Samvedi, A., & de Souza, R. (2020). Integrated decision support framework for enhancing disaster preparedness: A pilot application in Indonesia.International Journal of Disaster Risk Reduction, 51

  • Tomasini, R., & Van Wassenhove, L. (2009). Humanitarian logistics. INSEAD Business Press Series. Palgrave Macmillan

  • Trestrail, J., Paul, J., & Maloni, M. (2009). Improving bid pricing for humanitarian logistics. International Journal of Physical Distribution & Logistics, 39(5), 428–441

    Article  Google Scholar 

  • Tufinkgi, P. (2006). Logistik im Kontext internationaler Katastrophenhilfe: Entwicklung eines logistischen Referenzmodells für Katastrophenfälle (1st ed.). Haupt Verlag

  • Vaillancourt, A. (2016). A theoretical framework for consolidation in humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 6(1), 2–23

    Article  Google Scholar 

  • van der Laan, E., van Dalen, J., Rohrmoser, M., & Simpson, R. (2016). Demand forecasting and order planning for humanitarian logistics: An empirical assessment. Journal of Operations Management, 45, 114–122. https://doi.org/10.1016/j.jom.2016.05.004

    Article  Google Scholar 

  • Voyer, J., Dean, M., & Pickles, C. (2015). Understanding humanitarian supply chain logistics with system dynamics modeling. Proceedings System Dynamics

  • Wang, X., Fan, Y., Liang, L., De Vries, H., & Van Wassenhove, L. N. (2019). Augmenting Fixed Framework Agreements in Humanitarian Logistics with a Bonus Contract.Production and Operations Management Society, 28(8)

  • Widera, A., & Hellingrath, B. (2011). Improving Humanitarian Logistics - Towards a Tool-based Process Modeling Approach. In E. Sucky, B. Asdecker, A. Dobhan, S. Haas, & J. Wiese (Eds.), Logistik und Supply Chain Management. University of Bamberg Press

  • Yilmaz, Z., Aydemir-Karadag, A., & Erol, S. (2019). Finding Optimal Depots and Routes in Sudden-Onset Disasters: An Earthquake Case for Erzincan. Transportation Journal, 58(3), 168–196

    Article  Google Scholar 

  • Zejli, K., Azmani, A., & Khalissa, S. (2012). Applying Fuzzy Analytic Hierarchy Process (FAHP) to Evaluate Factors Locating Emergency Logistics Platforms. International Journal of Computer Applications, 57(21), 17–23

    Google Scholar 

  • Zhang, L., & Cui, N. (2021). Pre-Positioning Facility Location and Resource Allocation in Humanitarian Relief Operations Considering Deprivation Costs. Sustainability, 13(8), 4141

    Article  Google Scholar 

  • Zimmermann, K. D. (2011). As enchentes de 1983 em Santa Catarina: as cidades atingidas, cidades esquecidas. Revista Santa Catarina Em História, 5(2), 137–141

    Google Scholar 

  • Zokaee, S., Bozorgi-Amiri, A., & Sadjadi, S. J. (2016). A robust optimization model for humanitarian relief chain design under uncertainty. Applied Mathematical Modelling, 40(17–18), 7996–8016

    Article  Google Scholar 

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Authors and Affiliations

  1. Postgraduate Program in Information and Communication Technologies, Federal University of Santa Catarina (UFSC), Campus Araranguá, 88905-120, Araranguá, SC, Brazil

    Fabiana Santos Lima & Andréa Cristina Trierweiller

  2. Department of Production Engineering and Systems, Federal University of Santa Catarina (UFSC), Campus Trindade, 88040-900, Florianópolis, SC, Brazil

    Ricardo Villarroel Dávalos & Lucila M. S. Campos

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  1. Fabiana Santos Lima
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  2. Ricardo Villarroel Dávalos
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  3. Lucila M. S. Campos
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  4. Andréa Cristina Trierweiller
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Correspondence to Fabiana Santos Lima.

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Lima, F.S., Dávalos, R.V., Campos, L.M.S. et al. Framework proposal to support the suppliers’ selection of Humanitarian assistance items: a Flood Case Study in Brazil. Ann Oper Res 315, 317–340 (2022). https://doi.org/10.1007/s10479-022-04617-3

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