La coordinación inter-organizacional en los procesos logísticos de preparación de emergencias y desastres.

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dc.contributor.advisorCárdenas Aguirre, Diana María
dc.contributor.advisorMeisel Donoso, José David
dc.contributor.authorLópez Vargas, Juan Camilo
dc.coverage.cityManizales
dc.coverage.countryColombia
dc.date.accessioned2021-10-25T13:38:07Z
dc.date.available2021-10-25T13:38:07Z
dc.date.issued2021
dc.description.abstractAnte los registros crecientes de desastres naturales acaecidos a nivel global, junto con otras amenazas que afronta la humanidad en la actualidad, como el aumento incontrolado de la población, los fenómenos de cambio climático, la seguridad alimentaria y la inequidad social, es necesario que desde el sector académico, y particularmente desde la Ingeniería, se aborden estas grandes problemáticas para formular alternativas de solución efectivas y sostenibles para el bienestar de las comunidades en condición de vulnerabilidad y la preservación de los ecosistemas en el mundo. Esta tesis se enmarca en el estudio de los procesos logísticos de preparación para la atención de emergencias y desastres a nivel local. El objetivo principal de la investigación es la formulación de distintos mecanismos de coordinación para que los actores locales clave puedan mejorar el desempeño global del sistema logístico durante los procesos de preparación para los desastres. Para dicho propósito, fue necesario abordar un enfoque metodológico mixto que combinó prácticas tradicionalmente cualitativas como el estudio de expertos y un trabajo de campo basado en entrevistas semi-estrucutradas. Asimismo, desde el enfoque cuantitativo se aplicó el proceso de diseño para la estructuración y simulación de un modelo basado en agentes. Con base en un caso particular –la ciudad de Manizales, en Colombia–, se modelaron las principales decisiones que los actores del nivel local asumen en el marco de la preparación de emergencias causadas por fenómenos hidrometeorológicos. De este modo, y a partir de la formulación de escenarios alternativos basados en mecanismos de coordinación elegidos estratégicamente, se evidencia una mejora en el desempeño global del sistema local de preparación conformado por los principales actores locales. Los resultados obtenidos permiten vislumbrar una posibilidad de proponer e implementar mecanismos de coordinación en contextos reales, así como otras variantes en el modelo diseñado para dirigir futuras líneas de trabajo.spa
dc.description.abstractGiven the growing records of natural disasters that have occurred globally, as well as other threats that humanity endures, such as uncontrolled population growth, climate change, food security and social inequity, it is necessary to address these great problems from the academic sector, and particularly from Engineering, with the aim to formulate effective and sustainable solutions for the well-being of vulnerable communities and the preservation of ecosystems in the world. This thesis is focused on the study of the preparedness logistical processes for emergency and disaster response at the local level. The main research objective is the formulation of coordination mechanisms so that key local actors can improve the overall performance of the logistics system during disaster preparedness processes. For this purpose, it was necessary to apply a mixed methodological approach that combined traditionally qualitative practices such as the study of experts and a field work based on semi-structured interviews. Likewise, from the quantitative approach, the design process was applied for the structuring and simulation of an agent-based model. Based on a particular case –the city of Manizales, in Colombia–, the main decisions that local actors take during preparedness stage for emergencies caused by hydrometeorological phenomena were modeled. Thus, and from the formulation of alternative scenarios based on strategically chosen coordination mechanisms, there is evidence of an improvement in the overall performance of the local preparedness system composed of the key local actors. The results obtained allow for the visualization of the possibility of proposing and implementing coordination mechanisms in real contexts, as well as other variants in the model designed to direct future lines of work.eng
dc.description.degreelevelDoctoradospa
dc.description.degreenameDoctor en Ingenieríaspa
dc.description.researchareaMétodos y modelos de optimización y estadística en Ingeniería Industrial y Administrativaspa
dc.format.extentxvi, 358 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/80604
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Manizalesspa
dc.publisher.departmentDepartamento de Ingeniería Industrialspa
dc.publisher.facultyFacultad de Ingeniería y Arquitecturaspa
dc.publisher.placeManizales, Colombiaspa
dc.publisher.programManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Industria y Organizacionesspa
dc.relation.referencesAbidi, H., & Scholten, K. (2015). Applicability of Performance Measurement Systems to Humanitarian Supply Chains. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 235-260. Doi: https://doi.org/10.1007/978-3-319-15455-8_13spa
dc.relation.referencesAcimovic, J., & Goentzel, J. (2016). Models and metrics to assess humanitarian response capacity. Journal of Operations Management, 45, 11-29. Doi: https://doi.org/10.1016/j.jom.2016.05.003spa
dc.relation.referencesAfsar, H. M., Prins, C., & Santos, A. C. (2014). Exact and heuristic algorithms for solving the generalized vehicle routing problem with flexible fleet size. International Transactions in Operational Research, 21 (1), 153-175. Doi: https://doi.org/10.1111/itor.12041spa
dc.relation.referencesAfshar, A., & Haghani, A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-Economic Planning Sciences, 46 (4), 327-338. Doi: https://doi.org/10.1016/j.seps.2011.12.003spa
dc.relation.referencesAkhtar, P., Marr, N. E., & Garnevska, E. V. (2012). Coordination in humanitarian relief chains: chain coordinators. Journal of Humanitarian Logistics and Supply Chain Management, 2 (1), 85-103. Doi: https://doi.org/10.1108/20426741211226019spa
dc.relation.referencesAksu, D. T., & Ozdamar, L. (2014). A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation. Transportation Research Part E: Logistics and Transportation Review, 61, 56-67. Doi: https://doi.org/10.1016/j.tre.2013.10.009spa
dc.relation.referencesAllen, T. T. (2011). Introduction to Discrete Event Simulation and Agent-based Modeling: Voting Systems, Health Care, Military, and Manufacturing. Londres: Springer.spa
dc.relation.referencesAltay, N., & Green, W. G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, 175 (1), 475–493. Doi: https://doi.org/10.1016/j.ejor.2005.05.016spa
dc.relation.referencesAltay, N., & Pal, R. (2014). Information Diffusion among Agents: Implications for Humanitarian Operations. Production and Operations Management, 23 (6), 1015-1027. Doi: https://doi.org/10.1111/poms.12102spa
dc.relation.referencesAnaya-Arenas, A. M., Renaud, J., & Ruiz, A. (2014). Relief distribution networks: a systematic review. Annals of Operations Research, 223 (1), 53-79. Doi: https://doi.org/10.1007/s10479-014-1581-yspa
dc.relation.referencesAnjomshoae, A., Hassan, A., Kunz, N., Wong, K. Y., & de Leeuw, S. (2017). Toward a dynamic balanced scorecard model for humanitarian relief organizations’ performance management. Journal of Humanitarian Logistics and Supply Chain Management, 7 (2), 194-218. Doi: https://doi.org/10.1108/JHLSCM-01-2017-0001spa
dc.relation.referencesArnette, A. N., & Zobel, C. W. (2019). A Risk-Based Approach to Improving Disaster Relief Asset Pre-Positioning. Production and Operations Management, 28 (2), 457-478. Doi: https://doi.org/10.1111/poms.12934spa
dc.relation.referencesAros, S. K., & Gibbons, D. E. (2018). Exploring communication media options in an inter-organizational disaster response coordination network using agent-based simulation. European Journal of Operational Research, 269 (2), 451-465. Doi: https://doi.org/10.1016/j.ejor.2018.02.013spa
dc.relation.referencesBae, J. W., Shin, K., Lee, H. R., Lee, H. J., Lee, T., Kim, C. H., Cha, W. C., Kim, G. W., & Moon, I. C. (2018). Evaluation of Disaster Response System Using Agent-Based Model With Geospatial and Medical Details. IEEE Transactions on Systems Man Cybernetics-Systems, 48 (9), 1454-1469. Doi: https://doi.org/10.1109/TSMC.2017.2671340spa
dc.relation.referencesBalcik, B., & Beamon, B. M. (2008). Facility location in humanitarian relief. International Journal of Logistics: Research and Applications, 11 (2), 101-121. Doi: https://doi.org/10.1080/13675560701561789spa
dc.relation.referencesBalcik, B., Beamon, B. M., Krejci, C. C., Muramatsu, K. M., & Ramirez, M. (2010). Coordination in humanitarian relief chains: Practices, challenges and opportunities. International Journal of Production Economics, 126 (1), 22-34. Doi: https://doi.org/10.1016/j.ijpe.2009.09.008spa
dc.relation.referencesBaldini, G., Oliveri, F., Braun, M., Seuschek, H., & Hess, E. (2012). Securing disaster supply chains with cryptography enhanced RFID. Disaster Prevention and Management: An International Journal, 21 (1), 51-70. Doi: https://doi.org/10.1108/09653561211202700spa
dc.relation.referencesBanco Mundial. (2012). Análisis de la gestión del riesgo de desastres en Colombia: un aporte para la construcción de políticas públicas. Banco Mundial Colombia, Bogotá. Disponible en http://gestiondelriesgo.gov.co/sigpad/archivos/GESTIONDELRIESGOWEB.pdf Consultado: 30. Sep. 2020.spa
dc.relation.referencesBanomyong, R., & Julagasigorn, P. (2017). The potential role of philanthropy in humanitarian supply chains delivery: the case of Thailand. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 284-303. Doi: https://doi.org/10.1108/JHLSCM-05-2017-0017spa
dc.relation.referencesBarbarosoğlu, G. & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society, 55 (1), 43-53. Doi: https://doi.org/10.1057/palgrave.jors.2601652spa
dc.relation.referencesBasak, B. A., & Gupta, S. (2017). Developing an agent-based model for pilgrim evacuation using visual intelligence: A case study of Ratha Yatra at Puri. Computers Environment and Urban Systems, 64, 118-131. Doi: https://doi.org/10.1016/j.compenvurbsys.2017.01.006spa
dc.relation.referencesBeamon, B. M., & Balcik, B. (2008). Performance measurement in humanitarian relief chains. International Journal of Public Sector Management, 21 (1), 4-25. Doi: https://doi.org/10.1108/09513550810846087spa
dc.relation.referencesBesiou, M., Pedraza-Martinez, A. J., & Van Wassenhove, L. N. (2014). Vehicle Supply Chains in Humanitarian Operations: Decentralization, Operational Mix, and Earmarked Funding. Production and Operations Management, 23 (11), 1950-1965. Doi: https://doi.org/10.1111/poms.12215spa
dc.relation.referencesBesiou, M., Stapleton, O., & Van Wassenhove, L. N. (2011). System dynamics for humanitarian operations. Journal of Humanitarian Logistics and Supply Chain Management, 1 (1), 78-103. Doi: https://doi.org/10.1108/20426741111122420spa
dc.relation.referencesBharandev, S., Mukul Ali, S. K., & Sindhu. (2016). Logistics Planning in Natural Disasters. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 23-31. Doi: https://doi.org/10.1007/978-81-322-2416-7_2spa
dc.relation.referencesBID. (2002). An improbable city. Inter-American Development Bank, Washington. Disponible en https://www.iadb.org/en/news/webstories/2002-03-01/an-improbable-city%2C8310.html. Consultado: 30. Sep. 2020.spa
dc.relation.referencesBlome, C., Tobias, S., & Dominik, E. (2014). The impact of knowledge transfer and complexity on supply chain flexibility: A knowledge-based view. International Journal of Production Economics, 147, 307-316. Doi: https://doi.org/10.1016/j.ijpe.2013.02.028spa
dc.relation.referencesBohtan, A., Vrat, P., & Vij, A. K. (2016). Peculiarities of Disaster Management in a High-Altitude Area. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 273-296. Doi: https://doi.org/10.1007/978-81-322-2416-7_19spa
dc.relation.referencesBorshchev, A., & Filippov, A. (2004). From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools. The 22nd International Conference of the System Dynamics Society. Oxford, Inglaterra, Julio 25-29 2004, pp. 1-23.spa
dc.relation.referencesBrito Jr., I., Rosis, C. H. V., Carneiro, P. V., Leiras, A., & Yoshizaki, H. T. Y. (2014). Proposal of a natural disaster training program by considering the previous victims’ profile. Ambiente & Sociedade, 17 (4), 153-176. Doi: https://doi.org/10.1590/1809-4422ASOC1092V1742014spa
dc.relation.referencesBurnard, K., & Bhamra, R. (2011). Organisational resilience: development of a conceptual framework for organisational responses. International Journal of Production Research, 49 (18), 5581-5599. Doi: https://doi.org/10.1080/00207543.2011.563827spa
dc.relation.referencesCampos, A., Mossbrucker, H., & Karremans, J. (2009). La gestión local del riesgo en una ciudad andina: Manizales, un caso integral, ilustrativo y evaluado. Lima, Perú: Editorial Secretaría General de La Comunidad Andina. Disponible en https://repositorio.gestiondelriesgo.gov.co/handle/20.500.11762/19760. Consultado: 2. Oct. 2020.spa
dc.relation.referencesCardona, O. D. (2006). A System of Indicators for Disaster Risk Management in the Americas. En Birkmann, J. (Ed.), Measuring Vulnerability to Natural Hazards—Towards Disaster Resilient Societies. Tokyo, Nueva York, París: UNUPress. pp. 189-209.spa
dc.relation.referencesCastrillón, O. D., Giraldo, J. A., & Sarache, W. (2009). Técnicas de programación de la producción: aplicación en ambientes job shop. Manizales: Editorial Universidad Nacional de Colombia.spa
dc.relation.referencesCaunhye, A. M., Zhang, Y., Li, M., & Nie, X. (2016). A location-routing model for prepositioning and distributing emergency supplies. Transportation Research Part E: Logistics and Transportation Review, 90, 161-176. Doi: https://doi.org/10.1016/j.tre.2015.10.011spa
dc.relation.referencesCepeda-Susatama, K. D., Durango-Ruiz, K. A., & Bohórquez-Arévalo, L. E. (2017). Modelación y simulación en agentes como alternativa para el estudio de las organizaciones empresariales. Ingeniería Solidaria, 13 (22), 103-119. Doi: https://doi.org/10.16925/in.v13i22.1838spa
dc.relation.referencesChakravarty, A. K. (2014). Humanitarian relief chain: Rapid response under uncertainty. International Journal of Production Economics, 151 (1), 146-157. Doi: https://doi.org/10.1016/j.ijpe.2013.10.007spa
dc.relation.referencesChan, H. K., & Chan, F. T. S. (2010). A review of coordination studies in the context of supply chain dynamics. International Journal of Production Research, 48 (10), 2793-2819. Doi: https://doi.org/10.1080/00207540902791843spa
dc.relation.referencesCharbonneau, D., Dornhaus, A. (2015). When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents. Journal of Bioeconomics, 17, 217-242. Doi: https://doi.org/10.1007/s10818-015-9205-4spa
dc.relation.referencesCharles, A. (2010). Improving the design and management of agile supply chains: feedback and application in the context of humanitarian aid. Tesis Doctoral. Université de Toulouse, Toulouse (Francia).spa
dc.relation.referencesCharles, A., & Lauras, M. (2011). An enterprise modelling approach for better optimisation modelling: application to the humanitarian relief chain coordination problem. OR Spectrum, 33 (3), 815-841. Doi: https://doi.org/10.1007/s00291-011-0255-2spa
dc.relation.referencesCharles, A., Lauras, M., Van Wassenhove, L. N., & Dupont, L. (2016). Designing an efficient humanitarian supply network. Journal of Operations Management, 47-48, 58-70. Doi: https://doi.org/10.1016/j.jom.2016.05.012spa
dc.relation.referencesChong, M., Lazo, J. G., Pereda, M. C., & Machuca, J. M. (2019). Goal programming optimization model under uncertainty and the critical areas characterization in humanitarian logistics management. Journal of Humanitarian Logistics and Supply Chain Management, 9 (1), 82-107. Doi: https://doi.org/10.1108/JHLSCM-04-2018-0027spa
dc.relation.referencesCollins, A. J., & Frydenlund, E. (2016). Agent-based modeling and strategic group formation: a refugee case study. En Proceedings of the 2016 Winter Simulation Conference. Arlington, USA, 11-14 Diciembre 2016, pp. 1289-1300. Doi: https://doi.org/10.1109/WSC.2016.7822184spa
dc.relation.referencesConnelly, E. B., Lambert, J. H., & Thekdi, S. A. (2016). Robust Investments in Humanitarian Logistics and Supply Chains for Disaster Resilience and Sustainable Communities. Natural Hazards Review, 17 (1), Número de artículo: 04015017, 11 páginas. Doi: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000187spa
dc.relation.referencesCórdova, C. A. (2007). Consideraciones sobre metodología de la investigación. Centro de Estudios sobre Cultura e Identidad, Universidad de Holguín “Oscar Lucero Moya”, Holguín, Cuba. Disponible en https://studylib.es/doc/3172532/consideraciones-sobre-metodologia-de-la-investigacion. Consultado: 16. Oct. 2018.spa
dc.relation.referencesCorpocaldas. (2013). Plan de ordenación y manejo ambiental de la cuenca hidrográfica del río Chinchiná en el departamento de Caldas – POMCA Chinchiná. Corporación Autónoma Regional de Caldas, Manizales. Disponible en http://www.corpocaldas.gov.co/publicaciones/1508/1-SintesisPOMCARioChinchina_.pdf. Consultado: 9. Abr. 2017.spa
dc.relation.referencesCotes, N., & Cantillo, V. (2019). Including deprivation costs in facility location models for humanitarian relief logistics. Socio-Economic Planning Sciences, 65, 89-100. Doi: https://doi.org/10.1016/j.seps.2018.03.002spa
dc.relation.referencesCozzolino, A. (2012). Humanitarian Logistics: Cross-Sector Cooperation in Disaster Relief Management. Nueva York: Springer.spa
dc.relation.referencesCozzolino, A., Wankowicz, E., & Massaroni, E. (2017). Logistics service providers' engagement in disaster relief initiatives: An exploratory analysis. International Journal of Quality and Service Sciences, 9 (3-4), 269-291. Doi: https://doi.org/10.1108/IJQSS-04-2017-0040spa
dc.relation.referencesCrooks, A. T., & Wise, S. (2013). GIS and agent-based models for humanitarian assistance. Computers Environment and Urban Systems, 41, 100-111. Doi: https://doi.org/10.1016/j.compenvurbsys.2013.05.003spa
dc.relation.referencesCruz, M., & Martínez, M. C. (2012). Perfeccionamiento de un instrumento para la selección de expertos en las investigaciones educativas. Revista Electrónica de Investigación Educativa, 14 (2), 167–179.spa
dc.relation.referencesCruz-Castro, O., Vertiz-Camaron, G., & Apolonio-Oro, S. (2019). Third and fourth-party logistics providers groups formation focused on humanitarian logistics in the face of coastal flooding. International Journal of Combinatorial Optimization Problems and Informatics, 10 (1), 32-40.spa
dc.relation.referencesDalkey, N. (1969). The Delphi method: An experimental study of group opinion. Futures, 1 (5), 408-426. Doi: http://doi.org/10.1016/S0016-3287(69)80025-Xspa
dc.relation.referencesDANE. (2020). Colombia – Censo Nacional de Población y Vivienda – CNPV – 2018. Departamento Administrativo Nacional de Estadística, Bogotá. Disponible en https://sitios.dane.gov.co/cnpv/#!/. Consultado: 30. Oct. 2020.spa
dc.relation.referencesDas, R. (2018). Disaster preparedness for better response: Logistics perspectives. International Journal of Disaster Risk Reduction, 31, 153-159. Doi: https://doi.org/10.1016/j.ijdrr.2018.05.005spa
dc.relation.referencesDas, R., & Hanaoka, S. (2014). An agent-based model for resource allocation during relief distribution. Journal of Humanitarian Logistics and Supply Chain Management, 4 (2), 265-285. Doi: https://doi.org/10.1108/JHLSCM-07-2013-0023spa
dc.relation.referencesDavis, L. B., Samanlioglu, F., Qu, X., & Root, S. (2013). Inventory planning and coordination in disaster relief efforts. International Journal of Production Economics, 141 (2), 561-573. Doi: https://doi.org/10.1016/j.ijpe.2012.09.012spa
dc.relation.referencesDay, J. M. (2014). Fostering emergent resilience: the complex adaptive supply network of disaster relief. International Journal of Production Research, 52 (7), 1970-1988. Doi: https://doi.org/10.1080/00207543.2013.787496spa
dc.relation.referencesDay, J. M., Melnyk, S. A., Larson, P. D., Davis, E. W., & Whybark, D. C. (2012). Humanitarian and disaster relief supply chains: a matter of life and death. Journal of Supply Chain Management, 48 (2), 21-36. Doi: https://doi.org/10.1111/j.1745-493X.2012.03267.xspa
dc.relation.referencesDe Leeuw, S., Vis, I. F. A., & Jonkman, S. N. (2012). Exploring Logistics Aspects of Flood Emergency Measures. Journal of Contingencies and Crisis Management, 20 (3), 166-179. Doi: https://doi.org/10.1111/j.1468-5973.2012.00667.xspa
dc.relation.referencesDíaz, A., & Olaya, C. (2017). An Engineering View for Social Systems: Agency as an Operational Principle for Designing Higher Education Access Policies. Systemic Practice and Action Research, 30 (6), 627-649. Doi: https://doi.org/10.1007/s11213-017-9412-0spa
dc.relation.referencesDiaz, R., Kumar, S., & Behr, J. (2015). Housing recovery in the aftermath of a catastrophe: Material resources perspective. Computers & Industrial Engineering, 81, 130-139. Doi: https://doi.org/10.1016/j.cie.2014.12.036spa
dc.relation.referencesDiedrichs, D. R., Phelps, K., & Isihara, P. A. (2016). Quantifying communication effects in disaster response logistics: A multiple network system dynamics model. Journal of Humanitarian Logistics and Supply Chain Management, 6 (1), 24-45. Doi: https://doi.org/10.1108/JHLSCM-09-2014-0031spa
dc.relation.referencesDomínguez-Machuca, J. A., García, G. S., Domínguez-Machuca, M. A., Ruiz, J. A., & Álvarez, G. M. J. (1995). Dirección de Operaciones: Aspectos estratégicos en la producción y los servicios. Madrid: McGraw-Hill.spa
dc.relation.referencesDrakaki, M., Gören, H. G., & Tzionas, P. (2018). An intelligent multi-agent based decision support system for refugee settlement siting. International Journal of Disaster Risk Reduction, 31, 576-588. Doi: https://doi.org/10.1016/j.ijdrr.2018.06.013spa
dc.relation.referencesDubey, R., & Gunasekaran, A. (2015). The sustainable humanitarian supply chain design: agility, adaptability and alignment. International Journal of Logistics: Research and Applications, 19 (1), 62-82. Doi: https://doi.org/10.1080/13675567.2015.1015511spa
dc.relation.referencesEco, U. (2001). Cómo se hace una tesis: Técnicas y procedimientos de estudio, investigación y escritura. Barcelona: Gedisa Editorial.spa
dc.relation.referencesEftekhar, M., Li, H. M., Van Wassenhove, L. N., & Webster, S. (2017). The Role of Media Exposure on Coordination in the Humanitarian Setting. Production and Operations Management, 26 (5), 802-816. Doi: https://doi.org/10.1111/poms.12669spa
dc.relation.referencesEftekhar, M., Masini, A., Robotis, A., & Van Wassenhove, L. N. (2014). Vehicle Procurement Policy for Humanitarian Development Programs. Production and Operations Management, 23 (6), 951-964. Doi: https://doi.org/10.1111/poms.12108spa
dc.relation.referencesEM-DAT: Centre for Research on the Epidemiology of Disasters. (2018). The OFDA/CRED International Disaster Database. Université Catholique de Louvain, Bruselas, Bélgica. Disponible en http://www.emdat.be/. Consultado: 19. Dic. 2018.spa
dc.relation.referencesErgun, Ö., Gui, L., Stamm, J. L. H., Keskinocak, P., & Swann, J. (2014). Improving Humanitarian Operations through Technology-Enabled Collaboration. Production and Operations Management, 23 (6), 1002-1014. Doi: https://doi.org/10.1111/poms.12107spa
dc.relation.referencesFEMA. (2010). The Four Phases Of Emergency Management. Federal Emergency Management Agency, Washington. Disponible en https://training.fema.gov/emiweb/downloads/is10_unit3.doc. Consultado: 26. Feb. 2016.spa
dc.relation.referencesFernando, R. L. S., & Muthulingam, A. (2015). Effectiveness of Administrative Preparedness: A Case Study on Flooding Conditions in Ambagamuwa Korale Division of Nuwara Eliya District in Sri Lanka. En Ha, H., Fernando, R. L. S., & Mahmood, A. (Eds.), Strategic Disaster Risk Management in Asia. Nueva Delhi: Springer. pp. 87-98. Doi: https://doi.org/10.1007/978-81-322-2373-3_7spa
dc.relation.referencesFerrer, J. M., Ortuño, M. T., & Tirado, G. (2015). A GRASP metaheuristic for humanitarian aid distribution. Journal of Heuristics, 22 (1), 55-87. Doi: https://doi.org/10.1007/s10732-015-9302-5spa
dc.relation.referencesFikar, C., Gronalt, M., & Hirsch, P. (2016). A decision support system for coordinated disaster relief distribution. Expert Systems with Applications, 57, 104-116. Doi: https://doi.org/10.1016/j.eswa.2016.03.039spa
dc.relation.referencesFikar, C., Hirsch, P., & Nolz, P. C. (2018). Agent-based simulation optimization for dynamic disaster relief distribution. Central European Journal of Operations Research, 26 (2), 423-442. Doi: https://doi.org/10.1007/s10100-017-0518-3spa
dc.relation.referencesFontainha, T. C., Leiras, A., Bandeira, R. A. D., Scavarda, L. F. (2017). Public-Private-People Relationship Stakeholder Model for disaster and humanitarian operations. International Journal of Disaster Risk Reduction, 22, 371-386. Doi: https://doi.org/10.1016/j.ijdrr.2017.02.004spa
dc.relation.referencesGalán, J. M. (2007). Evaluación integradora de políticas de agua: modelado y simulación con sociedades artificiales de agentes. Tesis Doctoral. Universidad de Burgos, Burgos (España).spa
dc.relation.referencesGalindo, G., & Batta, R. (2013). Review of recent developments in OR/MS research in disaster operations management. European Journal of Operational Research, 230 (2), 201-211. Doi: https://doi.org/10.1016/j.ejor.2013.01.039spa
dc.relation.referencesGanguly, K. K., & Rai, S. S. (2016). Managing the humanitarian relief chain: the Uttarakhand disaster issues. Journal of Advances in Management Research, 13 (1), 92-111. Doi: https://doi.org/10.1108/JAMR-09-2014-0052spa
dc.relation.referencesGanguly, K. K., Padhy, R. K., & Rai, S. S. (2017). Managing the humanitarian supply chain: a fuzzy logic approach. International Journal of Disaster Resilience in the Built Environment, 8 (5), 521-536. Doi: https://doi.org/10.1108/IJDRBE-07-2015-0038spa
dc.relation.referencesGarcía, J. (2011). The Moral Herd: Groups and the Evolution of Altruism and Cooperation. Tesis Doctoral. Vrije Universiteit Amsterdam, Amsterdam (Países Bajos).spa
dc.relation.referencesGarcía, J., & Van Veelen, M. (2018). No Strategy Can Win in the Repeated Prisoner's Dilemma: Linking Game Theory and Computer Simulations. Frontiers in Robotics and AI, 5, Número de artículo: 102, 14 páginas. Doi: https://doi.org/10.3389/frobt.2018.00102spa
dc.relation.referencesGarrido, R. A., Lamas, P., & Pino, F. J. (2015). A stochastic programming approach for floods emergency logistics. Transportation Research Part E: Logistics and Transportation Review, 75, 18-31. Doi: https://doi.org/10.1016/j.tre.2014.12.002spa
dc.relation.referencesGavidia, J. V. (2017). A model for enterprise resource planning in emergency humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 246-265. Doi: https://doi.org/10.1108/JHLSCM-02-2017-0004spa
dc.relation.referencesGiachetti, R. E., Martinez, L. D., Saenz, O. A., & Chen, C. S. (2003). Analysis of the Structural Measures of Flexibility and Agility Using a Measurement Theoretical Framework. International Journal of Production Economics, 86 (1), 47-62. Doi: https://doi.org/10.1016/S0925-5273(03)00004-5spa
dc.relation.referencesGibbons, D. E., & Samaddar, S. (2009). Designing Referral Network Structures and Decision Rules to Streamline Provision of Urgent Health and Human Services. Decision Sciences, 40 (2), 351-371. Doi: https://doi.org/10.1111/j.1540-5915.2009.00230.xspa
dc.relation.referencesGoldman, S. L. (2017). Compromised Exactness and the Rationality of Engineering. En García‐Díaz, C., & Olaya, C. (Eds.), Social Systems Engineering: The Design of Complexity. New York: John Wiley & Sons. pp. 11-30. Doi: https://doi.org/10.1002/9781118974414.ch1spa
dc.relation.referencesGolicic, S. L., Davis, D. F., & McCarthy, T. M. (2005). A Balanced Approach to Research in Supply Chain Management. En Kotzab, H., Seuring, S., Müller, M., & Reiner, G. (Eds.), Research Methodologies in Supply Chain Management. Heidelberg: Physica-Verlag. pp.15-29. Doi: https://doi.org/10.1007/3-7908-1636-1_2spa
dc.relation.referencesGómez-Ramírez, D. M. (2017). Evaluación de las capacidades de logística humanitaria para la atención de desastres naturales en la red de ayuda humanitaria. El caso de Manizales. Tesis de Maestría. Universidad Nacional de Colombia, Manizales (Colombia).spa
dc.relation.referencesGösling, H., & Geldermann, J. (2014). A Framework to Compare OR Models for Humanitarian Logistics. Procedia Engineering, 78, 22-28. Doi: https://doi.org/10.1016/j.proeng.2014.07.034spa
dc.relation.referencesGranberg, T. A. (2013). Preparedness Measures for Emergency and Disaster Response. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 59-75. Doi: https://doi.org/10.1007/978-1-4614-7007-6_4spa
dc.relation.referencesGuerrero, W. J. (2013). Models and Optimization Methods for the Inventory-Location-Routing Problem. Tesis Doctoral. Universidad de los Andes, Bogotá (Colombia).spa
dc.relation.referencesGuo, X. S., & Kapucu, N. (2020). Engaging Stakeholders for Collaborative Decision Making in Humanitarian Logistics Using System Dynamics. Journal of Homeland Security And Emergency Management, 17 (1), Número de artículo: 20180061, 13 páginas. Doi: https://doi.org/10.1515/jhsem-2018-0061spa
dc.relation.referencesGutjahr, W. J., & Dzubur, N. (2016). Bi-objective bilevel optimization of distribution center locations considering user equilibria. Transportation Research Part E: Logistics and Transportation Review, 85, 1-22. Doi: https://doi.org/10.1016/j.tre.2015.11.001spa
dc.relation.referencesGutjahr, W. J., & Nolz, P. C. (2016). Multicriteria optimization in humanitarian aid. European Journal of Operational Research, 252 (2), 351-366. Doi: https://doi.org/10.1016/j.ejor.2015.12.035spa
dc.relation.referencesHaavisto, I., & Goentzel, J. (2015). Measuring humanitarian supply chain performance in a multi-goal context. Journal of Humanitarian Logistics and Supply Chain Management, 5 (3), 300-324. Doi: https://doi.org/10.1108/JHLSCM-07-2015-0028spa
dc.relation.referencesHabib, M. S., Lee, Y. H., & Memon, M. S. (2016). Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review. Mathematical Problems in Engineering, 2016, Número de artículo: 3212095, 20 páginas. Doi: https://doi.org/10.1155/2016/3212095spa
dc.relation.referencesHadiguna, R. A., Kamil, I., Delati, A., & Reed, R. (2014). Implementing a web-based decision support system for disaster logistics: A case study of an evacuation location assessment for Indonesia. International Journal of Disaster Risk Reduction, 9, 38-47. Doi: https://doi.org/10.1016/j.ijdrr.2014.02.004spa
dc.relation.referencesHaghani, A., & Oh, S. C. (1996). Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A: Policy and Practice, 30 (3), 231-250. Doi: https://doi.org/10.1016/0965-8564(95)00020-8spa
dc.relation.referencesHaghi, 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. Doi: https://doi.org/10.1016/j.jclepro.2017.03.102spa
dc.relation.referencesHammond, R. A. (2015). Considerations and Best Practices in Agent-Based Modeling to Inform Policy. En Wallace, R., Geller, A., & Ogawa, V. A. (Eds.), Assessing the Use of Agent-Based Models for Tobacco Regulation. Washington, D.C.: The National Academies Press. pp. 161-193.spa
dc.relation.referencesHardoy, J., & Velásquez, L. S. (2014). Re-thinking "Biomanizales": addressing climate change adaptation in Manizales, Colombia. Environment and Urbanization, 26 (1), 53-68. Doi: https://doi.org/10.1177/0956247813518687spa
dc.relation.referencesHasanzadeh, H., & Bashiri, M. (2016). An efficient network for disaster management: Model and solution. Applied Mathematical Modelling, 40 (5-6), 3688-3702. Doi: https://doi.org/10.1016/j.apm.2015.09.113spa
dc.relation.referencesHashemipour, M., Stuban, S., & Dever, J. (2018). A disaster multiagent coordination simulation system to evaluate the design of a first-response team. Systems Engineering, 21 (4), 322-344. Doi: https://doi.org/10.1002/sys.21437spa
dc.relation.referencesHawe, G. I., Coates, G., Wilson, D. T., & Crouch, R. S. (2015). Agent-based simulation of emergency response to plan the allocation of resources for a hypothetical two-site major incident. Engineering Applications of Artificial Intelligence, 46, 336-345. Doi: https://doi.org/10.1016/j.engappai.2015.06.023spa
dc.relation.referencesHe, F., & Zhuang, J. (2016). Balancing pre-disaster preparedness and post-disaster relief. European Journal of Operational Research, 252 (1), 246-256. Doi: https://doi.org/10.1016/j.ejor.2015.12.048spa
dc.relation.referencesHeaslip, G., Kovács, G., & Grant, D. B. (2018). Servitization as a competitive difference in humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 8 (4), 497-517. Doi: https://doi.org/10.1108/JHLSCM-08-2017-0042spa
dc.relation.referencesHeaslip, G., Sharif, A. M., & Althonayan, A. (2012). Employing a systems-based perspective to the identification of inter-relationships within humanitarian logistics. International Journal of Production Economics, 139 (2), 377-392. Doi: https://doi.org/10.1016/j.ijpe.2012.05.022spa
dc.relation.referencesHellingrath, B., Babun, T. A., Smith, J. F., & Link, D. (2015). Disaster Management Capacity Building at Airports and Seaports. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 87-112. Doi: https://doi.org/10.1007/978-3-319-15455-8_6spa
dc.relation.referencesHerlin, H., & Pazirandeh, A. (2015). Avoiding the pitfalls of cooperative purchasing through control and coordination: Insights from a humanitarian context. International Journal of Procurement Management, 8 (3), 303-325. Doi: https://doi.org/10.1504/IJPM.2015.069155spa
dc.relation.referencesHernández-Sampieri, R., Fernández-Collado, C., & Baptista-Lucio, P. (2014). Metodología de la investigación. 6a. ed. México D.F.: McGraw-Hill.spa
dc.relation.referencesHolguín-Veras, J., Jaller, M., Van Wassenhove, L. N., Pérez, N., & Wachtendorf, T. (2012). On the unique features of post-disaster humanitarian logistics. Journal of Operations Management, 30 (7-8), 494-506. Doi: https://doi.org/10.1016/j.jom.2012.08.003spa
dc.relation.referencesHolguín-Veras, J., Pérez, N., Jaller, M., Van Wassenhove, L. N., & Aros-Vera, F. (2013). On the appropriate objective function for post-disaster humanitarian logistics models. Journal of Operations Management, 31 (5), 262-280. Doi: https://doi.org/10.1016/j.jom.2013.06.002spa
dc.relation.referencesHolguín-Veras, J., Taniguchi, E., Jaller, M., Aros-Vera, F., Ferreira, F., & Thompson, R. G. (2014). The Tohoku disasters: Chief lessons concerning the post disaster humanitarian logistics response and policy implications. Transportation Research Part A: Policy and Practice, 69, 86-104. Doi: https://doi.org/10.1016/j.tra.2014.08.003spa
dc.relation.referencesHong, X., Lejeune, M. A., & Noyan, N. (2015). Stochastic Network Design for Disaster Preparedness. IIE Transactions, 47 (4), 329-357. Doi: https://doi.org/10.1080/0740817X.2014.919044spa
dc.relation.referencesHooshangi, N., & Alesheikh, A. A. (2018). Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents. ISPRS International Journal of Geo-Information, 7 (1), Número de artículo: 27, 22 páginas. Doi: https://doi.org/10.3390/ijgi7010027spa
dc.relation.referencesHoyos, M. C., Morales, R. S., & Akhavan-Tabatabaei, R. (2015). OR models with stochastic components in disaster operations management: A literature survey. Computers & Industrial Engineering, 82, 183-197. Doi: https://doi.org/10.1016/j.cie.2014.11.025spa
dc.relation.referencesHu, S. L., & Dong, Z. S. (2019). Supplier selection and pre-positioning strategy in humanitarian relief. Omega-International Journal of Management Science, 83, 287-298. Doi: https://doi.org/10.1016/j.omega.2018.10.011spa
dc.relation.referencesIFRC. (2012). The disaster relief emergency fund. International Federation of Red Cross and Red Crescent Societies, Ginebra. Disponible en http://www.ifrc.org/dref. Consultado: 28. Dic. 2018.spa
dc.relation.referencesIGAC. (2012). Mapa Oficial Físico-político de Colombia. Instituto Geográfico Agustín Codazzi, Bogotá. Disponible en https://geoportal.igac.gov.co/contenido/mapas-nacionales. Consultado: 1. Oct. 2020.spa
dc.relation.referencesIPCC. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation - Summary for policymakers. The Intergovernmental Panel on Climate Change, Ginebra. Disponible en https://www.ipcc.ch/site/assets/uploads/2018/03/SREX_FD_SPM_final-2.pdf. Consultado: 20. Dic. 2018.spa
dc.relation.referencesIqbal, S., Sardar, M. U., Lodhi, F. K., & Hasan, O. (2018). Statistical model checking of relief supply location and distribution in natural disaster management. International Journal of Disaster Risk Reduction, 31, 1043-1053. Doi: https://doi.org/10.1016/j.ijdrr.2018.04.010spa
dc.relation.referencesIzquierdo, L. R., Galán, J. M., Santos, J. I., & Del Olmo, R. (2008). Modelado de sistemas complejos mediante simulación basada en agentes y mediante dinámica de sistemas. Empiria. Revista de metodología de ciencias sociales, 16, 85-112. Doi: https://doi.org/10.5944/empiria.16.2008.1391spa
dc.relation.referencesJahre, M. (2017). Humanitarian supply chain strategies – a review of how actors mitigate supply chain risks. Journal of Humanitarian Logistics and Supply Chain Management, 7 (2), 82-101. Doi: https://doi.org/10.1108/JHLSCM-12-2016-0043spa
dc.relation.referencesJahre, M., & Jensen, L. M. (2010). Coordination in humanitarian logistics through clusters. International Journal of Physical Distribution & Logistics Management, 40 (8-9), 657-674. Doi: https://doi.org/10.1108/09600031011079319spa
dc.relation.referencesJahre, M., Ergun, O., & Goentzel, J. (2015). One Size Fits All? Using Standard Global Tools in Humanitarian Logistics. Procedia Engineering, 107, 18-26. Doi: https://doi.org/10.1016/j.proeng.2015.06.054spa
dc.relation.referencesJahre, M., Pazirandeh, A., & Van Wassenhove, L. N. (2016). Defining logistics preparedness: a framework and research agenda. Journal of Humanitarian Logistics and Supply Chain Management, 6 (3), 372-398. Doi: https://doi.org/10.1108/JHLSCM-04-2016-0012spa
dc.relation.referencesJensen, L. M., & Hertz, S. (2016). The coordination roles of relief organisations in humanitarian logistics. International Journal of Logistics Research and Applications, 19 (5), 465-485. Doi: https://doi.org/10.1080/13675567.2015.1124845spa
dc.relation.referencesJohn, L., & Ramesh, A. (2016). Modeling the barriers of humanitarian supply chain management in India. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 61-82. Doi: https://doi.org/10.1007/978-81-322-2416-7_5spa
dc.relation.referencesKabra, G., & Ramesh, A. (2015). Segmenting critical factors for enhancing the use of IT in humanitarian supply chain management. Procedia - Social and Behavioral Sciences, 189, 144-152. Doi: https://doi.org/10.1016/j.sbspro.2015.03.208spa
dc.relation.referencesKabra, G., Ramesh, A., & Arshinder, K. (2015). Identification and prioritization of coordination barriers in humanitarian supply chain management. International Journal of Disaster Risk Reduction, 13, 128-138. Doi: https://doi.org/10.1016/j.ijdrr.2015.01.011spa
dc.relation.referencesKabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34 (7), 1250-1261. Doi: https://doi.org/10.1016/j.tele.2017.05.010spa
dc.relation.referencesKaneberg, E. (2017). Managing military involvement in emergency preparedness in developed countries. Journal of Humanitarian Logistics and Supply Chain Management, 7 (3), 350-374. Doi: https://doi.org/10.1108/JHLSCM-04-2017-0014spa
dc.relation.referencesKimms, A., & Maiwald, M. (2018). Bi-objective safe and resilient urban evacuation planning. European Journal of Operational Research, 269 (3), 1122-1136. Doi: https://doi.org/10.1016/j.ejor.2018.02.050spa
dc.relation.referencesKleijnen, J. P. C. (1995). Verification and validation of simulation models. European Journal of Operational Research, 82 (1), 145-162. Doi: https://doi.org/10.1016/0377-2217(94)00016-6spa
dc.relation.referencesKlumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (2015). Sustainability in Humanitarian Logistics - Why and How? En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 3-9. Doi: https://doi.org/10.1007/978-3-319-15455-8_1spa
dc.relation.referencesKovács, G., & Moshtari, M. (2019). A roadmap for higher research quality in humanitarian operations: A methodological perspective. European Journal of Operational Research, 276 (2), 395-408. Doi: https://doi.org/10.1016/j.ejor.2018.07.052spa
dc.relation.referencesKovács, G., & Spens, K. M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37 (2), 99-114. Doi: https://doi.org/10.1108/09600030710734820spa
dc.relation.referencesKovács, G., & Spens, K. M. (2009). Identifying challenges in humanitarian logistics. International Journal of Physical Distribution & Logistics Management, 39 (6), 506-528. Doi: https://doi.org/10.1108/09600030910985848spa
dc.relation.referencesKovács, G., & Tatham, P. (2009). Responding to disruptions in the supply network - From dormant to action. Journal of Business Logistics, 30 (2), 215-229. Doi: https://doi.org/10.1002/j.2158-1592.2009.tb00121.xspa
dc.relation.referencesKrejci, C. C. (2015). Hybrid simulation modeling for humanitarian relief chain coordination. Journal of Humanitarian Logistics and Supply Chain Management, 5 (3), 325-347. Doi: https://doi.org/10.1108/JHLSCM-07-2015-0033spa
dc.relation.referencesKrick, E. V. (1979). Fundamentos de ingeniería: métodos, conceptos y resultados. 1a. ed. México D.F.: Editorial Limusa.spa
dc.relation.referencesKrishnamurthy, A., Roy, D., & Bhat, S. (2013). Analytical Models for Estimating Waiting Times at a Disaster Relief Center. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 21-41. Doi: https://doi.org/10.1007/978-1-4614-7007-6_2spa
dc.relation.referencesKumar, R. (2011). Research methodology: A step-by-step guide for beginners. 3a. ed. Londres: SAGE Publications Ltd.spa
dc.relation.referencesKumar, S., & Havey, T. (2013). Before and after disaster strikes: A relief supply chain decision support framework. International Journal of Production Economics, 145 (2), 613-629. Doi: https://doi.org/10.1016/j.ijpe.2013.05.016spa
dc.relation.referencesKunz, N., & Gold, S. (2015). Sustainable humanitarian supply chain management – exploring new theory. International Journal of Logistics Research and Applications, 20 (2), 85-104. Doi: https://doi.org/10.1080/13675567.2015.1103845spa
dc.relation.referencesKunz, N., Reiner, G., & Gold, S. (2014). Investing in disaster management capabilities versus pre-positioning inventory: A new approach to disaster preparedness. International Journal of Production Economics, 157, 261-272. Doi: https://doi.org/10.1016/j.ijpe.2013.11.002spa
dc.relation.referencesKusumastuti, R. D., Wibowo, S. S., & Insanita, R. (2013). Modeling Facility Locations for Relief Logistics in Indonesia. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 183-205. Doi: https://doi.org/10.1007/978-1-4614-7007-6_10spa
dc.relation.referencesLabarthe, O., Espinasse, B., Ferrarini, A., & Montreuil, B. (2007). Toward a methodological framework for agent-based modelling and simulation of supply chains in a mass customization context. Simulation Modelling Practice and Theory, 15 (2), 113-136. Doi: https://doi.org/10.1016/j.simpat.2006.09.014spa
dc.relation.referencesLandeta, J., Barrutia, J., & Lertxundi, A. (2011). Hybrid Delphi: A methodology to facilitate contribution from experts in professional contexts. Technological Forecasting & Social Change, 78 (9), 1629-1641. Doi: https://doi.org/10.1016/j.techfore.2011.03.009spa
dc.relation.referencesLangellier, B. A., Bilal, U., Montes, F., Meisel, J. D., Cardoso, L. O., & Hammond, R. (2019). Complex Systems Approaches to Diet: A Systematic Review. American Journal of Preventive Medicine, 57 (2), 273-281. Doi: https://doi.org/10.1016/j.amepre.2019.03.017spa
dc.relation.referencesLarson, P. D., & Foropon, C. (2018). Process improvement in humanitarian operations: an organisational theory perspective. International Journal of Production Research, 56 (21), 6828-6841. Doi: https://doi.org/10.1080/00207543.2018.1424374spa
dc.relation.referencesLiberatore, F., Ortuño, M. T., Tirado, G., Vitoriano, B., & Scaparra, M. P. (2014). A hierarchical compromise model for the joint optimization of recovery operations and distribution of emergency goods in Humanitarian Logistics. Computers & Operations Research, 42, 3-13. Doi: https://doi.org/10.1016/j.cor.2012.03.019spa
dc.relation.referencesLiu, Y., & Guo, B. (2014). A Lexicographic Approach to Postdisaster Relief Logistics Planning Considering Fill Rates and Costs under Uncertainty. Mathematical Problems in Engineering, 2014, Número de artículo: 939853, 17 páginas. Doi: https://doi.org/10.1155/2014/939853spa
dc.relation.referencesLorca, Á., Çelik, M., Ergun, Ö., & Keskinocak, P. (2015). A decision-support tool for post-disaster debris operations. Procedia Engineering, 107, 154-167. Doi: https://doi.org/10.1016/j.proeng.2015.06.069spa
dc.relation.referencesLu, Q., Goh, M., & de Souza, R. (2018). An empirical investigation of swift trust in humanitarian logistics operations. Journal of Humanitarian Logistics and Supply Chain Management, 8 (1), 70-86. Doi: https://doi.org/10.1108/JHLSCM-07-2017-0033spa
dc.relation.referencesMacal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4 (3), 151-162. Doi: https://doi.org/10.1057/jos.2010.3spa
dc.relation.referencesMacal, C. M., & North, M. J. (2014). Introductory Tutorial: Agent-Based Modeling and Simulation. En Proceedings of the 2014 Winter Simulation Conference. Savannah, USA, 7-10 Diciembre 2014, pp. 6-20. Doi: https://doi.org/10.1109/WSC.2014.7019874spa
dc.relation.referencesMaghsoudi, A., & Pazirandeh, A. (2016). Visibility, resource sharing and performance in supply chain relationships: insights from humanitarian practitioners. Supply Chain Management: An International Journal, 21 (1), 125-139. Doi: https://doi.org/10.1108/SCM-03-2015-0102spa
dc.relation.referencesManopiniwes, W., & Irohara, T. (2017). Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response. International Journal of Production Research, 55 (4), 979-996. Doi: https://doi.org/10.1080/00207543.2016.1211340spa
dc.relation.referencesMarcelin, J. M., Horner, M. W., Ozguven, E. E., & Kocatepe, A. (2016). How does accessibility to post-disaster relief compare between the aging and the general population? A spatial network optimization analysis of hurricane relief facility locations. International Journal of Disaster Risk Reduction, 15, 61-72. Doi: https://doi.org/10.1016/j.ijdrr.2015.12.006spa
dc.relation.referencesMarcinkowski, J.M. (2017). Japanese and American Approach to Humanitarian Logistics in Natural Disasters' Prevention. Logforum, 13 (2), 171-182. Doi: https://doi.org/10.17270/J.LOG.2017.2.5spa
dc.relation.referencesMejia-Argueta, C., Gaytán, J., Caballero, R., Molina, J., & Vitoriano, B. (2018). Multicriteria optimization approach to deploy humanitarian logistic operations integrally during floods. International Transactions in Operational Research, 25 (3), 1053-1079. Doi: https://doi.org/10.1111/itor.12508spa
dc.relation.referencesMendenhall, W., & Reinmuth, J. (1981). Estadística para la administración y economía. 3a. ed. México D.F.: Grupo Editorial Iberoamérica.spa
dc.relation.referencesMendenhall, W., Beaver, R. J., & Beaver, B. M. (2010). Introducción a la probabilidad y estadística. 13a. ed. México D.F.: Cengage Learning Editores.spa
dc.relation.referencesMenth, M. (2014). An Agent-Based Modeling Approach To Assess Coordination Among Humanitarian Relief Providers. Tesis de Maestría. Kansas State University, Manhattan (Estados Unidos).spa
dc.relation.referencesMeredith, J. (1993). Theory Building through Conceptual Methods. International Journal of Operations & Production Management, 13 (5), 3-11. Doi: https://doi.org/10.1108/01443579310028120spa
dc.relation.referencesMohan, S., Gopalakrishnan, M., & Mizzi, P. J. (2013). Improving the efficiency of a non-profit supply chain for the food insecure. International Journal of Production Economics, 143 (2), 248-255. Doi: https://doi.org/10.1016/j.ijpe.2011.05.019spa
dc.relation.referencesMora-Ochomogo, E. I., Mora-Vargas, J., & Serrato, M. (2016). A Qualitative Analysis of Inventory Management Strategies in Humanitarian Logistics Operations. International Journal of Combinatorial Optimization Problems and Informatics, 7 (1), 40-53. Disponible en http://www.redalyc.org/articulo.oa?id=265245553006. Consultado: 18. Jul. 2016.spa
dc.relation.referencesMoreno, A., Alem, D., & Ferreira, D. (2016). Heuristic approaches for the multiperiod location-transportation problem with reuse of vehicles in emergency logistics. Computers & Operations Research, 69, 79-96. Doi: https://doi.org/10.1016/j.cor.2015.12.002spa
dc.relation.referencesMoshtari, M. (2016). Inter-Organizational Fit, Relationship Management Capability, and Collaborative Performance within a Humanitarian Setting. Production and Operations Management, 25 (9), 1542-1557. Doi: https://doi.org/10.1111/poms.12568spa
dc.relation.referencesMoshtari, M., & Gonçalves, P. (2017). Factors Influencing Interorganizational Collaboration within a Disaster Relief Context. Voluntas, 28 (4), 1673-1694. Doi: https://doi.org/10.1007/s11266-016-9767-3spa
dc.relation.referencesMuggy, L., & Stamm, J. L. H. (2017). Dynamic, robust models to quantify the impact of decentralization in post-disaster health care facility location decisions. Operations Research for Health Care, 12, 43-59. Doi: https://doi.org/10.1016/j.orhc.2017.01.002spa
dc.relation.referencesMuskat, M., Blackman, D., & Muskat, B. (2012). Mixed methods: Combining expert interviews, cross-impact analysis and scenario development. Electronic Journal of Business Research Methods, 10 (1), 9-21.spa
dc.relation.referencesNadi, A., & Edrisi, A. (2017). Adaptive multi-agent relief assessment and emergency response. International Journal of Disaster Risk Reduction, 24, 12-23. Doi: https://doi.org/10.1016/j.ijdrr.2017.05.010spa
dc.relation.referencesNi, C., de Souza, R., Lu, Q., & Goh, M. (2015). Emergency Preparedness of Humanitarian Organizations: A System Dynamics Approach. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 113-127. Doi: https://doi.org/10.1007/978-3-319-15455-8_7spa
dc.relation.referencesNikbakhsh, E. & Farahani, R. Z. (2011). Humanitarian Logistics Planning in Disaster Relief Operations. En Farahani, R. Z., Rezapour, S., & Kardar, L. (Eds.), Logistics Operations and Management: Concepts and Models. Amsterdam: Elsevier. pp. 291-332. Doi: https://doi.org/10.1016/B978-0-12-385202-1.00015-3spa
dc.relation.referencesNoham, R., & Tzur, M. (2018). Designing humanitarian supply chains by incorporating actual post-disaster decisions. European Journal of Operational Research, 265 (3), 1064-1077. Doi: https://doi.org/10.1016/j.ejor.2017.08.042spa
dc.relation.referencesNurmala, N., de Vries, J., & de Leeuw, S. (2018). Cross-sector humanitarian-business partnerships in managing humanitarian logistics: an empirical verification. International Journal of Production Research, 56 (21), 6842-6858. Doi: https://doi.org/10.1080/00207543.2018.1449977spa
dc.relation.referencesOCHA. (2012). Coordination to Save Lives - History and Emerging Challenges. United Nations Office for the Coordination of Humanitarian Affairs, Nueva York y Ginebra. Disponible en https://www.unocha.org/publication/policy-briefs-studies/coordination-save-lives-history-and-emerging-challenges. Consultado: 20. Dic. 2017.spa
dc.relation.referencesOchoa, A., Rudomin, I., Vargas-Solar, G., Espinosa-Oviedo, J. A., Perez, H., & Zechinelli-Martini, J. L. (2017). Humanitarian Logistics and Cultural Diversity within Crowd Simulation. Computación y Sistemas, 21 (1), 7-21. Doi: https://doi.org/10.13053/CyS-21-1-2583spa
dc.relation.referencesOlaya, C. (2012a). Models that include cows: the significance of operational thinking. En Proceedings of the 30th International Conference of the System Dynamics Society. St Gallen, Suiza, 22-26 Julio 2012, pp. 1-28.spa
dc.relation.referencesOlaya, C. (2012b). The Importance of Being Atheoretical: Management as Engineering. En Groesser, S. & Zeier, R. (Eds.), Systemic Management for Intelligent Organizations: Concepts, Model-Based Approaches and Applications. Heidelberg: Springer. pp. 21-46. Doi: https://doi.org/10.1007/978-3-642-29244-6_2spa
dc.relation.referencesOlaya, C. (2013). Más ingeniería y menos ciencia por favor. En Proceedings of the 11th Latin American System Dynamics Conference. México D.F., México, 6-8 Noviembre 2013, pp. 1-6.spa
dc.relation.referencesOloruntoba, R., & Gray, R. (2006). Humanitarian aid: an agile supply chain? Supply Chain Management-An International Journal, 11 (2), 115-120. Doi: https://doi.org/10.1108/13598540610652492spa
dc.relation.referencesOloruntoba, R., & Gray, R. (2009). Customer service in emergency relief chains. International Journal of Physical Distribution & Logistics Management, 39 (6), 486-505. Doi: https://doi.org/10.1108/09600030910985839spa
dc.relation.referencesOsorio-Ramírez, C. (2016). Mecanismos de coordinación para la optimización del desempeño de la cadena logística humanitaria mediante modelamiento estocástico. Caso colombiano. Tesis Doctoral. Universidad Nacional de Colombia, Bogotá (Colombia).spa
dc.relation.referencesOwusu-Kwateng, K., Hamid, M. A., & Debrah, B. (2017). Disaster relief logistics operation: an insight from Ghana. International Journal of Emergency Services, 6 (1), 4-13. Doi: https://doi.org/10.1108/IJES-10-2016-0022spa
dc.relation.referencesÖzdamar, L., & Ertem, M. A. (2015). Models, solutions and enabling technologies in humanitarian logistics. European Journal of Operational Research, 244 (1), 55-65. Doi: https://doi.org/10.1016/j.ejor.2014.11.030spa
dc.relation.referencesÖzdamar, L., Ekinci, E., & Küçükyazici, B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, 129 (1-4), 217-245. Doi: https://doi.org/10.1023/B:ANOR.0000030690.27939.39spa
dc.relation.referencesOzguven, E. E., & Ozbay, K. (2015). An RFID-based inventory management framework for emergency relief operations. Transportation Research Part C: Emerging Technologies, 57, 166-187. Doi: https://doi.org/10.1016/j.trc.2015.06.021spa
dc.relation.referencesPaul, J. A., & MacDonald, L. (2016). Location and capacity allocations decisions to mitigate the impacts of unexpected disasters. European Journal of Operational Research, 251 (1), 252-263. Doi: https://doi.org/10.1016/j.ejor.2015.10.028spa
dc.relation.referencesPaul, J. A., & Wang, X. F. (2019). Robust location-allocation network design for earthquake preparedness. Transportation Research Part B: Methodological, 119, 139-155. Doi: https://doi.org/10.1016/j.trb.2018.11.009spa
dc.relation.referencesPeng, M., Chen, H., & Zhou, M. (2014b). Modelling and simulating the dynamic environmental factors in post-seismic relief operation. Journal of Simulation, 8 (2), 164-178. Doi: https://doi.org/10.1057/jos.2013.27spa
dc.relation.referencesPeng, M., Peng, Y., & Chen, H. (2014a). Post-seismic supply chain risk management: A system dynamics disruption analysis approach for inventory and logistics planning. Computers & Operations Research, 42, 14-24. Doi: https://doi.org/10.1016/j.cor.2013.03.003spa
dc.relation.referencesPettit, S., & Beresford, A. (2009). Critical success factors in the context of humanitarian aid supply chains. International Journal of Physical Distribution & Logistics Management, 39 (6), 450-468. Doi: https://doi.org/10.1108/09600030910985811spa
dc.relation.referencesPNUD. (2015). Nuevos Escenarios de Cambio Climático para Colombia 2011 – 2100. Programa de las Naciones Unidas para el Desarrollo – PNUD Colombia, Bogotá. Disponible en https://reliefweb.int/report/colombia/nuevos-escenarios-de-cambio-clim-tico-para-colombia-2011-2100-herramientas-cient-0. Consultado: 1. Oct. 2020.spa
dc.relation.referencesPomerol, J. C., & Barba-Romero, S. (2000). Multicriterion Decision in Management: principles and practice. Boston: Kluwer Academic Publishers.spa
dc.relation.referencesPonte, B., Costas, J., Puche, J., Pino, R., & De la Fuente, D. (2018). The value of lead time reduction and stabilization: A comparison between traditional and collaborative supply chains. Transportation Research Part E: Logistics and Transportation Review, 111, 165-185. Doi: https://doi.org/10.1016/j.tre.2018.01.014spa
dc.relation.referencesPowell, J. H., Mustafee, N., Chen, A. S., & Hammond, M. (2016). System-focused risk identification and assessment for disaster preparedness: Dynamic threat analysis. European Journal of Operational Research, 254 (2), 550-564. Doi: https://doi.org/10.1016/j.ejor.2016.04.037spa
dc.relation.referencesPradhananga, R., Mutlu, F., Pokharel, S., Holguín-Veras, J., & Seth, D. (2016). An integrated resource allocation and distribution model for pre-disaster planning. Computers & Industrial Engineering, 91, 229-238. Doi: https://doi.org/10.1016/j.cie.2015.11.010spa
dc.relation.referencesQuezada, A., & Canessa, E. (2010). Modelado basado en agentes: una herramienta para complementar el análisis de fenómenos sociales. Avances en Psicología Latinoamericana, 28 (2), 226-238.spa
dc.relation.referencesRachaniotis, N. P., Dasaklis, T., Pappis, C. P., & Van Wassenhove, L. N. (2013). Multiple Location and Routing Models in Humanitarian Logistics. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 43-57. Doi: https://doi.org/10.1007/978-1-4614-7007-6_3spa
dc.relation.referencesRaghukumar, B. R., Agarwal, A., & Sharma, M. K. (2016). An Agile and Flexible Supply Chain for Efficient Humanitarian Logistics in a Disaster Management System. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 129-139. Doi: https://doi.org/10.1007/978-81-322-2416-7_9spa
dc.relation.referencesRansikarbum, K., & Mason, S. J. (2014). Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations. International Journal of Production Research, 54 (1), 49-68. Doi: https://doi.org/10.1080/00207543.2014.977458spa
dc.relation.referencesRegis-Hernández, F., Mora-Vargas, J., & Ruiz, A. (2017). A Multi-Criteria Vertical Coordination Framework for a Reliable Aid Distribution. Journal of Industrial Engineering and Management, 10 (4), 789-815. Doi: https://doi.org/10.3926/jiem.2253spa
dc.relation.referencesRekik, M., Ruiz, A., Renaud, J., Berkoune, D., & Paquet, S. (2013). A Decision Support System for Humanitarian Network Design and Distribution Operations. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 1-20. Doi: https://doi.org/10.1007/978-1-4614-7007-6_1spa
dc.relation.referencesRemida, A. (2015). A Systemic Approach to Sustainable Humanitarian Logistics. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 11-29. Doi: https://doi.org/10.1007/978-3-319-15455-8_2spa
dc.relation.referencesRezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Bozorgi-Amiri, A. (2016). An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Computers & Industrial Engineering, 94, 201-215. Doi: https://doi.org/10.1016/j.cie.2016.01.014spa
dc.relation.referencesRichardson, D. A., De Leeuw, S., & Dullaert, W. (2016). Factors Affecting Global Inventory Prepositioning Locations in Humanitarian Operations – A Delphi Study. Journal of Business Logistics, 37 (1), 59-74. Doi: https://doi.org/10.1111/jbl.12112spa
dc.relation.referencesRodon, J., Maria-Serrano, J. F., & Giménez, C. (2012). Managing cultural conflicts for effective humanitarian aid. International Journal of Production Economics, 139 (2), 366-376. Doi: https://doi.org/10.1016/j.ijpe.2011.08.029spa
dc.relation.referencesRodríguez, J. T., Vitoriano, B., & Montero, J. (2012). A general methodology for data-based rule building and its application to natural disaster management. Computers & Operations Research, 39 (4), 863-873. Doi: https://doi.org/10.1016/j.cor.2009.11.014spa
dc.relation.referencesRodríguez-Espíndola, O., & Gaytán, J. (2015). Scenario-based preparedness plan for floods. Natural Hazards, 76 (2), 1241-1262. Doi: https://doi.org/10.1007/s11069-014-1544-2spa
dc.relation.referencesRodríguez-Espíndola, O., Albores, P., & Brewster, C. (2018a). Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods. European Journal of Operational Research, 264 (3), 978-993. Doi: https://doi.org/10.1016/j.ejor.2017.01.021spa
dc.relation.referencesRodríguez-Espíndola, O., Albores, P., & Brewster, C. (2018b). Dynamic formulation for humanitarian response operations incorporating multiple organisations. International Journal of Production Economics, 204, 83-98. Doi: https://doi.org/10.1016/j.ijpe.2018.07.023spa
dc.relation.referencesRodríguez-Zoya, L. G., & Roggero, P. (2015). Modelos basados en agentes: aportes epistemológicos y teóricos para la investigación social. Revista Mexicana de Ciencias Políticas y Sociales, 60 (225), 227-262. Doi: https://doi.org/10.1016/S0185-1918(15)30025-8spa
dc.relation.referencesRottkemper, B., Fischer, K., Blecken, A., & Danne, C. (2011). Inventory relocation for overlapping disaster settings in humanitarian operations. OR Spectrum, 33, 721-749. Doi: https://doi.org/10.1007/s00291-011-0260-5spa
dc.relation.referencesSaharan, V. (2015). Disaster Management and Corruption: Issues, Interventions and Strategies. En Ha, H., Fernando, R. L. S., & Mahmood, A. (Eds.), Strategic Disaster Risk Management in Asia. Nueva Delhi: Springer. pp. 193-206. Doi: https://doi.org/10.1007/978-81-322-2373-3_13spa
dc.relation.referencesSahay, B. S., Menon, V. C., & Gupta, S. (2016). Humanitarian Logistics and Disaster Management: The Role of Different Stakeholders. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 3-21. Doi: https://doi.org/10.1007/978-81-322-2416-7_1spa
dc.relation.referencesSahebi, I. G., Arab, A., & Moghadam, M. R. S. (2017). Analyzing the barriers to humanitarian supply chain management: A case study of the Tehran Red Crescent Societies. International Journal of Disaster Risk Reduction, 24, 232-241. Doi: https://doi.org/10.1016/j.ijdrr.2017.05.017spa
dc.relation.referencesSahin, H., Kara, B. Y., & Karasan, O. E. (2016). Debris removal during disaster response: A case for Turkey. Socio-Economic Planning Sciences, 53, 49-59. Doi: https://doi.org/10.1016/j.seps.2015.10.003spa
dc.relation.referencesSantos, F. C., Pacheco, J. M., & Lenaerts, T. (2006). Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proceedings of the National Academy of Sciences, 103 (9), 3490-3494. Doi: https://doi.org/10.1073/pnas.0508201103spa
dc.relation.referencesSarache, W., & Morales, M. M. (2016). Localización, transporte e inventarios: tres decisiones estructurales en el diseño de cadenas de abastecimiento. Bogotá: Editorial Universidad Nacional de Colombia.spa
dc.relation.referencesSarache, W., Cárdenas-Aguirre, D. M., & Giraldo, J. A. (2005). Procedimiento para la definición y jerarquización de prioridades competitivas de fabricación. Aplicaciones en las pymes de la industria metalmecánica. Ingeniería y Competitividad, 7 (2), 84-91.spa
dc.relation.referencesSarache, W., Costa-Salas, Y. J., & Martínez-Giraldo, J. P. (2015). Environmental performance evaluation under a green supply chain approach. DYNA, 82 (189), 207-215. https://doi.org/10.15446/dyna.v82n189.48550spa
dc.relation.referencesSauser, B., Baldwin, C., Pourreza, S., Randall, W., & Nowicki, D. (2018). Resilience of small- and medium-sized enterprises as a correlation to community impact: an agent-based modeling approach. Natural Hazards, 90 (1), 79-99. Doi: https://doi.org/10.1007/s11069-017-3034-9spa
dc.relation.referencesSchaffernicht, M. (2009). Indagación de situaciones dinámicas mediante la Dinámica de Sistemas. 1a. ed. Talca, Chile: Editorial Universidad de Talca.spa
dc.relation.referencesScholten, K., Scott, P. S., & Fynes, B. (2014). Mitigation processes – antecedents for building supply chain resilience. Supply Chain Management: An International Journal, 19 (2), 211-228. Doi: https://doi.org/10.1108/SCM-06-2013-0191spa
dc.relation.referencesSchulz, S. F. (2009). Disaster Relief Logistics: Benefits of and Impediments to Horizontal Cooperation between Humanitarian Organizations. Tesis Doctoral. Technischen Universität Berlin, Berlin (Alemania).spa
dc.relation.referencesSchulz, S. F., & Blecken, A. (2010). Horizontal cooperation in disaster relief logistics: benefits and impediments. International Journal of Physical Distribution & Logistics Management, 40 (8-9), 636-656. Doi: https://doi.org/10.1108/09600031011079300spa
dc.relation.referencesSebbah, S., Boukhtouta, A., Berger, J., & Ghanmi, A. (2013). Military Logistics Planning in Humanitarian Relief Operations. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 77-110. Doi: https://doi.org/10.1007/978-1-4614-7007-6_5spa
dc.relation.referencesSeuring, S., Müller, M., Reiner, G., & Kotzab, H. (2005). Is There a Right Research Design for Your Supply Chain Study? En Kotzab, H., Seuring, S., Müller, M., & Reiner, G. (Eds.), Research Methodologies in Supply Chain Management. Heidelberg: Physica-Verlag. pp.1-12. Doi: https://doi.org/10.1007/3-7908-1636-1_1spa
dc.relation.referencesShafiee, M. E., & Berglund, E. Z. (2016). Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies. Computers, Environment and Urban Systems, 57, 12-25. Doi: https://doi.org/10.1016/j.compenvurbsys.2016.01.001spa
dc.relation.referencesShannon, R. E. (1998). Introduction to the Art and Science of Simulation. En Proceedings of the 30th Conference on Winter Simulation. Washington, D.C., USA, 13-16 Diciembre 1998, pp. 7-14. Doi: https://doi.org/10.1109/WSC.1998.744892spa
dc.relation.referencesSharif, M. T., & Salari, M. (2015). A GRASP algorithm for a humanitarian relief transportation problem. Engineering Applications of Artificial Intelligence, 41, 259-269. Doi: https://doi.org/10.1016/j.engappai.2015.02.013spa
dc.relation.referencesSheffi, Y. (2015). The Power of Resilience: How the Best Companies Manage the Unexpected. Cambridge, Mass.: MIT Press.spa
dc.relation.referencesShendarkar, A., Vasudevan, K., Lee, S., & Son, Y. J. (2008). Crowd simulation for emergency response using BDI agents based on immersive virtual reality. Simulation Modelling Practice and Theory, 16 (9), 1415-1429. Doi: https://doi.org/10.1016/j.simpat.2008.07.004spa
dc.relation.referencesSheppard, A., Tatham, P., Fisher, R., & Gapp, R. (2013). Humanitarian logistics: enhancing the engagement of local populations. Journal of Humanitarian Logistics and Supply Chain Management, 3 (1), 22-36. Doi: https://doi.org/10.1108/20426741311328493spa
dc.relation.referencesSheu, J. B. (2007). An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E: Logistics and Transportation Review, 43 (6), 687-709. Doi: https://doi.org/10.1016/j.tre.2006.04.004spa
dc.relation.referencesSheu, J. B., & Pan, C. (2015). Relief supply collaboration for emergency logistics responses to large-scale disasters. Transportmetrica A: Transport Science, 11 (3), 210-242. Doi: https://doi.org/10.1080/23249935.2014.951886spa
dc.relation.referencesShoham, Y., & Leyton-Brown, K. (2008). Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge: Cambridge University Press.spa
dc.relation.referencesSiegel, S. (1978). Estadística no paramétrica aplicada a las ciencias de la conducta. 2a. ed. México D.F.: Ed. Trillas.spa
dc.relation.referencesSimões-Marques, M., & Nunes, I. L. (2013). A Fuzzy Multicriteria Methodology to Manage Priorities and Resource Assignment in Critical Situations. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 129-153. Doi: https://doi.org/10.1007/978-1-4614-7007-6_7spa
dc.relation.referencesSingh, A. (2016). Supplier Selection and Multi-period Demand Allocation in a Humanitarian Supply Chain. En Sahay, B. S., Gupta, S., & Menon, V. C. (Eds.), Managing humanitarian logistics. Nueva Delhi: Springer. pp. 189-207. Doi: https://doi.org/10.1007/978-81-322-2416-7_14spa
dc.relation.referencesSingh, R. K., Gupta, A., & Gunasekaran, A. (2018). Analysing the interaction of factors for resilient humanitarian supply chain. International Journal of Production Research, 56 (21), 6809-6827. Doi: https://doi.org/10.1080/00207543.2018.1424373spa
dc.relation.referencesSmadi, H., Al Theeb, N., & Bawa’neh, H. (2018). Logistics system for drinking water distribution in post disaster humanitarian relief, Al-Za'atari camp. Journal of Humanitarian Logistics and Supply Chain Management, 8 (4), 477-496. Doi: https://doi.org/10.1108/JHLSCM-12-2017-0072spa
dc.relation.referencesSterman, J. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: McGraw Hill.spa
dc.relation.referencesSuárez-Moreno, J. D., Osorio-Ramírez, C., & Adarme-Jaimes, W. (2016). Agent-based model for material convergence in humanitarian logistics. Revista Facultad de Ingeniería-Universidad de Antioquia, 81, 24-34. Doi: https://doi.org/10.17533/udea.redin.n81a03spa
dc.relation.referencesSwanson, R. D., & Smith, R. J. (2013). A Path to a Public–Private Partnership: Commercial Logistics Concepts Applied to Disaster Response. Journal of Business Logistics, 34 (4), 335-346. Doi: https://doi.org/10.1111/jbl.12031spa
dc.relation.referencesTang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain risks. International Journal of Production Economics, 116 (1), 12-27. Doi: https://doi.org/10.1016/j.ijpe.2008.07.008spa
dc.relation.referencesTang, J., Zhu, K. J., Guo, H. X., Gong, C. Z., Liao, C., & Zhang, S. W. (2018). Using auction-based task allocation scheme for simulation optimization of search and rescue in disaster relief. Simulation Modelling Practice and Theory, 82, 132-146. Doi: https://doi.org/10.1016/j.simpat.2017.12.014spa
dc.relation.referencesTang, J., Zhu, K., Guo, H., Liao, C., & Zhang, S. (2017). Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism. Algorithms, 10 (4), Número de artículo: 125, 17 páginas. Doi: https://doi.org/10.3390/a10040125spa
dc.relation.referencesTatham, P., & Kovács, G. (2010). The application of "swift trust" to humanitarian logistics. International Journal of Production Economics, 126 (1), 35-45. Doi: https://doi.org/10.1016/j.ijpe.2009.10.006spa
dc.relation.referencesTatham, P., & Rietjens, S.B. (2016). Integrated disaster relief logistics: A stepping stone towards viable civil-military networks? Disasters, 40 (1), 7-25. Doi: https://doi.org/10.1111/disa.12131spa
dc.relation.referencesTatham, P., & Spens, K. (2011). Towards a humanitarian logistics knowledge management system. Disaster Prevention and Management, 20 (1), 6-26. Doi: https://doi.org/10.1108/09653561111111054spa
dc.relation.referencesTatham, P., & Spens, K. (2016). Cracking the humanitarian logistic coordination challenge: Lessons from the urban search and rescue community. Disasters, 40 (2), 246-261. Doi: https://doi.org/10.1111/disa.12139spa
dc.relation.referencesTatham, P., Spens, K., & Kovács, G. (2017). The humanitarian common logistic operating picture: a solution to the inter-agency coordination challenge. Disasters, 41 (1), 77-100. Doi: https://doi.org/10.1111/disa.12193spa
dc.relation.referencesTavana, M., Abtahi, A. R., Di Caprio, D., Hashemi, R., & Yousefi-Zenouz, R. (2018). An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences, 64, 21-37. Doi: https://doi.org/10.1016/j.seps.2017.12.004spa
dc.relation.referencesThe Guardian. (2018). Quakes, mudslides, an active volcano: inside the world's riskiest city. Guardian Media Group, Londres. Disponible en https://www.theguardian.com/cities/2018/nov/08/earthquakes-mudslides-active-volcano-worlds-riskiest-city-manizales-colombia. Consultado: 30. Sep. 2020.spa
dc.relation.referencesThomas, A., & Kopczak, L. (2005). From logistics to supply chain management: The path forward in the humanitarian sector, white paper, Fritz Institute, San Francisco, CA.spa
dc.relation.referencesTian, Y., Zhou, T. S., Yao, Q., Zhang, M., & Li, J. S. (2014). Use of an Agent-Based Simulation Model to Evaluate a Mobile-Based System for Supporting Emergency Evacuation Decision Making. Journal of Medical Systems, 38 (12), Número de artículo: 149, 13 páginas. Doi: https://doi.org/10.1007/s10916-014-0149-3spa
dc.relation.referencesTimperio, 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. Doi: https://doi.org/10.1108/JHLSCM-11-2016-0040spa
dc.relation.referencesTofighi, S., Torabi, S. A., & Mansouri, S. A. (2016). Humanitarian logistics network design under mixed uncertainty. European Journal of Operational Research, 250 (1), 239-250. Doi: https://doi.org/10.1016/j.ejor.2015.08.059spa
dc.relation.referencesTomasini, R. M., & Van Wassenhove, L. N. (2009). Humanitarian Logistics. Londres: Palgrave Macmillan.spa
dc.relation.referencesTrecarichi, G., Rizzi, V., Marchese, M., Vaccari, L., & Besana, P. (2010). Enabling information gathering patterns for emergency response with the OpenKnowledge system. Computing and Informatics, 29 (4), 537-555.spa
dc.relation.referencesTzeng, G. H., Cheng, H. J., & Huang, T. D. (2007). Multi-objective optimal planning for designing relief delivery systems. Transportation Research Part E: Logistics and Transportation Review, 43 (6), 673-686. Doi: https://doi.org/10.1016/j.tre.2006.10.012spa
dc.relation.referencesUNESCO. (2010). Engineering: Issues, Challenges and Opportunities for Development. Paris. Disponible en http://unesdoc.unesco.org/images/0018/001897/189753e.pdf. Consultado: 31. Mar. 2018.spa
dc.relation.referencesUNGRD. (2014). Documento de priorización de líneas estratégicas y zonas de intervención en gestión del riesgo de desastres en Colombia. Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá. Disponible en http://cedir.gestiondelriesgo.gov.co/dvd/archivospdf/priorizaci%C3%B3n_ungrd.pdf. Consultado: 5. May. 2016.spa
dc.relation.referencesUNGRD. (2018). Colombia menos vulnerable: la gestión del riesgo de desastres en nuestra historia. Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá. Disponible en https://repositorio.gestiondelriesgo.gov.co/handle/20.500.11762/27176. Consultado: 30. Sep. 2020.spa
dc.relation.referencesUNISDR. (2004). Living with Risk. A Global Review of Disaster Reduction Initiatives. United Nations Office for Disaster Risk Reduction, Ginebra. Disponible en http://www.unisdr.org/eng/about_isdr/bd-lwr-2004-eng.htm. Consultado: 26. Feb. 2016.spa
dc.relation.referencesUNISDR. (2015). Sendai Framework for Disaster Risk Reduction 2015 – 2030. United Nations Office for Disaster Risk Reduction, Ginebra. Disponible en https://www.unisdr.org/we/inform/publications/43291. Consultado: 14. May. 2017.spa
dc.relation.referencesUNISDR. (2017). The secretariat of the international strategy for disaster reduction. United Nations Office for Disaster Risk Reduction, Ginebra. Disponible en http://www.unisdr.org/we/inform/terminology. Consultado: 23. Dic. 2017.spa
dc.relation.referencesVaillancourt, A., & Haavisto, I. (2016). Country logistics performance and disaster impact. Disasters, 40 (2), 262-283. Doi: https://doi.org/10.1111/disa.12146spa
dc.relation.referencesVan der Laan, E. A., de Brito, M. P., Van Fenema, P. C., & Vermaesen, S. C. (2009). Managing information cycles for intra-organisational coordination of humanitarian logistics. International Journal of Services, Technology and Management, 12 (4), 362-390. Doi: https://doi.org/10.1504/IJSTM.2009.025814spa
dc.relation.referencesVan Wassenhove, L. N. (2006). Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational Research Society, 57 (5), 475-489. Doi: https://doi.org/10.1057/palgrave.jors.2602125spa
dc.relation.referencesVega, D., & Roussat, C. (2015). Humanitarian logistics: the role of logistics service providers. International Journal of Physical Distribution & Logistics Management, 45 (4), 352-375. Doi: https://doi.org/10.1108/IJPDLM-12-2014-0309spa
dc.relation.referencesVerma, A., & Gaukler, G. M. (2015). Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches. Computers & Operations Research, 62, 197-209. Doi: https://doi.org/10.1016/j.cor.2014.10.006spa
dc.relation.referencesVitoriano, B., Rodríguez, J. T., Tirado, G., Martín-Campo, J. M., Ortuño, M. T., & Montero, J. (2015). Intelligent Decision-Making Models for Disaster Management. Human and Ecological Risk Assessment: An International Journal, 21 (5), 1341-1360. Doi: https://doi.org/10.1080/10807039.2014.957947spa
dc.relation.referencesVon Bertalanffy, L. (1976). Teoría General de los Sistemas. México D.F.: Fondo de Cultura Económica.spa
dc.relation.referencesVoyer, J., Dean, M. D., & Pickles, C. B. (2016). Hospital evacuation in disasters: uncovering the systemic leverage using system dynamics. International Journal of Emergency Management, 12 (2), 152-167.spa
dc.relation.referencesWallace, R., Geller, A., & Ogawa, V. A. (2015). Assessing the Use of Agent-Based Models for Tobacco Regulation. Washington, D.C.: The National Academies Press.spa
dc.relation.referencesWang, Z. L., & Zhang, J. H. (2019). Agent-based evaluation of humanitarian relief goods supply capability. International Journal of Disaster Risk Reduction, 36, Número de artículo: 101105, 11 páginas. Doi: https://doi.org/10.1016/j.ijdrr.2019.101105spa
dc.relation.referencesWei, X., Al-Refaie, A., Robles, M., & Noche, B. (2015). A Sustainable Humanitarian Relief Network Study for the Wenchuan Earthquake. En Klumpp, M., de Leeuw, S., Regattieri, A., & de Souza, R. (Eds.), Humanitarian Logistics and Sustainability. Cham: Springer. pp. 193-213. Doi: https://doi.org/10.1007/978-3-319-15455-8_11spa
dc.relation.referencesWilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: Modeling natural, social and engineered complex systems with NetLogo. Cambridge: MIT Press.spa
dc.relation.referencesWilson, M. M. J., Tatham, P., Payne, J., L'Hermitte, C., & Shapland, M. (2018). Best practice relief supply for emergency services in a developed economy: Evidence from Queensland Australia. Journal of Humanitarian Logistics and Supply Chain Management, 8 (1), 107-132. Doi: https://doi.org/10.1108/JHLSCM-03-2017-0008spa
dc.relation.referencesXanthopoulos, A. S., & Koulouriotis, D. E. (2013). A Multi-agent Based Framework for Vehicle Routing in Relief Delivery Systems. En Zeimpekis, V., Ichoua, S., & Minis, I. (Eds.), Humanitarian and Relief Logistics: Research Issues, Case Studies and Future Trends. Nueva York: Springer. pp. 167-182. Doi: https://doi.org/10.1007/978-1-4614-7007-6_9spa
dc.relation.referencesXu, J. P., Dai, J. Z., Rao, R. Q., & Xie, H. D. (2016). Critical Systems Thinking on the Inefficiency in Post-Earthquake Relief: A Practice in Longmen Shan Fault Area. Systemic Practice and Action Research, 29 (5), 425-448. Doi: https://doi.org/10.1007/s11213-016-9374-7spa
dc.relation.referencesXu, L., & Beamon, B. M. (2006). Supply chain coordination and cooperation mechanisms: An attribute-based approach. Journal of Supply Chain Management, 42 (1), 4-12. Doi: https://doi.org/10.1111/j.1745-493X.2006.04201002.xspa
dc.relation.referencesYadav, D. K., & Barve, A. (2015). Analysis of critical success factors of humanitarian supply chain: An application of Interpretive Structural Modeling. International Journal of Disaster Risk Reduction, 12, 213-225. Doi: https://doi.org/10.1016/j.ijdrr.2015.01.008spa
dc.relation.referencesYao, X., Huang, R. T., Song, M. L., & Mishra, N. (2018). Pre-positioning inventory and service outsourcing of relief material supply chain. International Journal of Production Research, 56 (21), 6859-6871. Doi: https://doi.org/10.1080/00207543.2018.1495853spa
dc.relation.referencesYi, W., & Özdamar, L. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities. European Journal of Operational Research, 179 (3), 1177-1193. Doi: https://doi.org/10.1016/j.ejor.2005.03.077spa
dc.relation.referencesZagorecki, A., Ko, K., & Comfort, L. K. (2010). Interorganizational Information Exchange and Efficiency: Organizational Performance in Emergency Environments. JASSS-The Journal of Artificial Societies and Social Simulation, 13 (3), Número de artículo: 3, 6 páginas. Doi: https://doi.org/10.18564/jasss.1589spa
dc.relation.referencesZhao, K., Yen, J., Ngamassi, L. M., Maitland, C., & Tapia, A. H. (2012). Simulating inter-organizational collaboration network: a multi-relational and event-based approach. Simulation-Transactions of The Society for Modeling and Simulation International, 88 (5), 617-633. Doi: https://doi.org/10.1177/0037549711421942spa
dc.relation.referencesZhu, K. J., Tang, J., Guo, H. X., Gong, C. Z., & Li, J. L. (2018). Using a combinatorial auction-based approach for simulation of cooperative rescue operations in disaster relief. International Journal of Modeling Simulation and Scientific Computing, 9 (4), Número de artículo: 1850035, 21 páginas. Doi: https://doi.org/10.1142/S1793962318500356spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/spa
dc.subject.ddc360 - Problemas y servicios sociales; asociaciones::363 - Otros problemas y servicios socialesspa
dc.subject.lcshNatural disasters.
dc.subject.lembDesastres naturales -- Manizales -- Colombia
dc.subject.proposalLogística humanitariaspa
dc.subject.proposalPreparación para los desastresspa
dc.subject.proposalCoordinación inter-organizacionalspa
dc.subject.proposalModelación basada en agentesspa
dc.subject.proposalHumanitarian logisticseng
dc.subject.proposalDisaster preparednesseng
dc.subject.proposalInter-organizational coordinationeng
dc.subject.proposalAgent-based modelingeng
dc.titleLa coordinación inter-organizacional en los procesos logísticos de preparación de emergencias y desastres.spa
dc.title.translatedInter-organizational coordination in logistics processes for emergency and disaster preparednesseng
dc.typeTrabajo de grado - Doctoradospa
dc.type.coarhttp://purl.org/coar/resource_type/c_db06spa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
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dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/doctoralThesisspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentMaestrosspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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