Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case
The study aims to present an agent-based simulation model (ABM) for exploring interorganizational coordination scenarios in local disaster preparedness. This approach includes local actors and logistical processes as agents to compare various strategic coordination mechanisms. Design/methodology/app...
- Autores:
-
López-Vargas, Juan Camilo
Meisel, José D
Cárdenas-Aguirre, Diana María
Medina, Pablo
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2025
- Institución:
- Universidad de Ibagué
- Repositorio:
- Repositorio Universidad de Ibagué
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unibague.edu.co:20.500.12313/5910
- Acceso en línea:
- https://hdl.handle.net/20.500.12313/5910
https://www.emerald.com/jhlscm/article/15/2/87/1247143/Coordination-mechanisms-applied-to-logistical
- Palabra clave:
- Preparación local para desastres
Desastres - Coordinación - Mecanismos estratégicos
Agent-based modeling
Complex systems
Disaster preparedness
Humanitarian logistics
Interorganizational coordination
- Rights
- openAccess
- License
- © 2024, Juan Camilo López-Vargas, José D. Meisel, Diana María Cárdenas-Aguirre and Pablo Medina.
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| dc.title.eng.fl_str_mv |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| title |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| spellingShingle |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case Preparación local para desastres Desastres - Coordinación - Mecanismos estratégicos Agent-based modeling Complex systems Disaster preparedness Humanitarian logistics Interorganizational coordination |
| title_short |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| title_full |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| title_fullStr |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| title_full_unstemmed |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| title_sort |
Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case |
| dc.creator.fl_str_mv |
López-Vargas, Juan Camilo Meisel, José D Cárdenas-Aguirre, Diana María Medina, Pablo |
| dc.contributor.author.none.fl_str_mv |
López-Vargas, Juan Camilo Meisel, José D Cárdenas-Aguirre, Diana María Medina, Pablo |
| dc.subject.armarc.none.fl_str_mv |
Preparación local para desastres Desastres - Coordinación - Mecanismos estratégicos |
| topic |
Preparación local para desastres Desastres - Coordinación - Mecanismos estratégicos Agent-based modeling Complex systems Disaster preparedness Humanitarian logistics Interorganizational coordination |
| dc.subject.proposal.eng.fl_str_mv |
Agent-based modeling Complex systems Disaster preparedness Humanitarian logistics Interorganizational coordination |
| description |
The study aims to present an agent-based simulation model (ABM) for exploring interorganizational coordination scenarios in local disaster preparedness. This approach includes local actors and logistical processes as agents to compare various strategic coordination mechanisms. Design/methodology/approach: The ABM model, developed in the Latin American context, specifically focuses on a case study of Colombia. Three coordination mechanisms (centralized, decentralized and cluster-type) have been evaluated using three performance indicators: effectiveness, efficiency and flexibility. Findings: Simulation results show that the decentralized scenario outperforms in terms of efficiency and flexibility. On the contrary, the centralized and cluster-type scenarios demonstrate higher effectiveness, achieving a greater percentage of requirements coverage during the disaster preparedness stage. The ABM approach effectively evaluates strategical coordination mechanisms based on the analyzed performance indicators. Research limitations/implications: This study has limitations due to the application of results to a single real case. In addition, the focus of the study is primarily on a specific type of disaster, specifically hydrometeorological events such as flash floods, torrential rains and landslides. Moreover, the scope of decision-making is restricted to key actors involved in local-level disaster management within a municipality. Originality/value: The proposed ABM model has the potential as a decision-making tool for policies and local coordination schemes for future disasters. The simulation tool could also explore diverse geographical scenarios and disaster types, demonstrating its versatility and broader applicability for further insights and recommendations. |
| publishDate |
2025 |
| dc.date.accessioned.none.fl_str_mv |
2025-11-06T19:41:23Z |
| dc.date.available.none.fl_str_mv |
2025-11-06T19:41:23Z |
| dc.date.issued.none.fl_str_mv |
2025-04-21 |
| dc.type.none.fl_str_mv |
Artículo de revista |
| dc.type.coar.none.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.coarversion.none.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Text |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
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López-Vargas, J., Meisel, J., Cárdenas-Aguirre, D. y Medina, P. (2025). Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case. Journal of Humanitarian Logistics and Supply Chain Management, 15(2), 87 - 106. DOI: 10.1108/JHLSCM-09-2023-0085 |
| dc.identifier.doi.none.fl_str_mv |
DOI: 10.1108/JHLSCM-09-2023-0085 |
| dc.identifier.eissn.none.fl_str_mv |
20426755 |
| dc.identifier.issn.none.fl_str_mv |
20426747 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12313/5910 |
| dc.identifier.url.none.fl_str_mv |
https://www.emerald.com/jhlscm/article/15/2/87/1247143/Coordination-mechanisms-applied-to-logistical |
| identifier_str_mv |
López-Vargas, J., Meisel, J., Cárdenas-Aguirre, D. y Medina, P. (2025). Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case. Journal of Humanitarian Logistics and Supply Chain Management, 15(2), 87 - 106. DOI: 10.1108/JHLSCM-09-2023-0085 DOI: 10.1108/JHLSCM-09-2023-0085 20426755 20426747 |
| url |
https://hdl.handle.net/20.500.12313/5910 https://www.emerald.com/jhlscm/article/15/2/87/1247143/Coordination-mechanisms-applied-to-logistical |
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eng |
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eng |
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106 |
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2 |
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87 |
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15 |
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Altay, N. and Pal, R. (2014), “Information diffusion among agents: implications for humanitarian operations”, Production and Operations Management, Vol. 23 No. 6, pp. 1015-1027, doi: https://doi.org/10.1111/poms.12102 Anjomshoae, A., Banomyong, R., Azadnia, A.H., Kunz, N. and Blome, C. (2023), “Sustainable humanitarian supply chains: a systematic literature review and research propositions”, Production Planning & Control, doi: https://doi.org/10.1080/09537287.2023.2273451. Anvari, M., Anvari, A. and Boyer, O. (2023), “A prepositioning model for prioritized demand points considering lateral transshipment”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 13 No. 4, pp. 433-455, doi: https://doi.org/10.1108/JHLSCM-01-2023-0005. Aros, S.K. and 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, Vol. 269 No. 2, pp. 451-465, doi: https://doi.org/10.1016/j.ejor.2018.02.013. Bae, J.W., Shin, K., Lee, H.R., Lee, H.J., Lee, T., Kim, C.H., Cha, W.C., Kim, G.W. and Moon, I.C. (2018), “Evaluation of disaster response system using agent-based model with geospatial and medical details”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 48 No. 9, pp. 1454-1469, doi: https://doi.org/10.1109/TSMC.2017.2671340. Bayram, V. and Yaman, H. (2024), “A joint demand and supply management approach to large scale urban evacuation planning: evacuate or shelter-in-place, staging and dynamic resource allocation”, European Journal of Operational Research, Vol. 313 No. 1, pp. 171-191, doi: https://doi.org/10.1016/j.ejor.2023.07.033. Besiou, M., Pedraza-Martinez, A.J. and Van Wassenhove, L.N. (2021), “Humanitarian operations and the UN sustainable development goals”, Production and Operations Management, Vol. 30 No. 12, pp. 4343-4355, doi: https://doi.org/10.1111/poms.13579. Boshuijzen-van Burken, C., Gore, R., Dignum, F., Royakkers, L., Wozny, P. and Shults, F.L. (2020), “Agent-based modelling of values: the case of value sensitive design for refugee logistics”, Journal of Artificial Societies and Social Simulation, Vol. 23 No. 4, p. 6, doi: https://doi.org/10.18564/jasss.4411. Bui, H., Sakurahara, T., Reihani, S., Kee, E. and Mohaghegh, Z. (2020), “Spatiotemporal integration of an agent-based first responder performance model with a fire hazard propagation model for probabilistic risk assessment of nuclear power plants”, ASCE-ASME Journal of Risk and Uncertainty In Engineering Systems Part B-Mechanical Engineering, Vol. 6 No. 1, p. 011011, doi: https://doi.org/10.1115/1.4044793. Calabrò, G., Torrisi, V., Inturri, G. and Ignaccolo, M. (2020), “Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization, 21”, European Transport Research Review, Vol. 12 No. 1, doi: https://doi.org/10.1186/s12544-020-00409-7. Cardona, O.D. (2019), “Gestión del riesgo y adaptación en manizales: una estrategia de desarrollo Para lograr que una ciudad en transición sea resiliente, sostenible y competitiva”, Medio Ambiente y Urbanización, Vol. 90 No. 1, pp. 127-168. Chen, J.W., Zhang, X.L., Peng, X.F., Xu, D.S. and Peng, J.C. (2022), “Efficient routing for multi-AGV based on optimized ant-agent”, Computers & Industrial Engineering, Vol. 167, p. 108042, doi: https://doi.org/10.1016/j.cie.2022.108042. Connelly, E.B., Lambert, J.H. and Thekdi, S.A. (2016), “Robust investments in humanitarian logistics and supply chains for disaster resilience and sustainable communities”, Natural Hazards Review, Vol. 17 No. 1, p. 04015017, doi: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000187. Corbett, C.J., Pedraza-Martinez, A.J. and Van Wassenhove, L.N. (2022), “Sustainable humanitarian operations: an integrated perspective”, Production and Operations Management, Vol. 31 No. 12, pp. 4393-4406, doi: https://doi.org/10.1111/poms.13848 Cozzolino, A. (2012), Humanitarian Logistics: Cross-Sector Cooperation in Disaster Relief Management, Springer, Berlin, Heidelberg. Das, R. and Hanaoka, S. (2014), “An agent-based model for resource allocation during relief distribution”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 4 No. 2, pp. 265-285, doi: https://doi.org/10.1108/JHLSCM-07-2013-0023. Dhingra, R. (2022), “Coordination in practice or performance? The political economy of refugee aid coordination in Jordan”, Journal of Refugee Studies, Vol. 35 No. 4, pp. 1472-1491, doi: https://doi.org/10.1093/jrs/feac002. Echeverri Tafur, L. and Obando Moncayo, F.H. (2010), “Erosividad de las lluvias en la región Centro-Sur del Departamento de Caldas, Colombia”, Revista Facultad Nacional de Agronomía - Medellín, Vol. 63 No. 1, pp. 5307-5318. El-Sayed, A.M., Scarborough, P., Seemann, L. and Galea, S. (2012), “Social network analysis and agent-based modeling in social epidemiology”, Epidemiologic Perspectives & Innovations, Vol. 9 No. 1, pp. 1-9, doi: https://doi.org/10.1186/1742-5573-9-1. Fontainha, T.C., Leiras, A., Bandeira, R.A.D. and Scavarda, L.F. (2017), “Public-private-people relationship stakeholder model for disaster and humanitarian operations”, International Journal of Disaster Risk Reduction, Vol. 22, pp. 371-386, doi: https://doi.org/10.1016/j.ijdrr.2017.02.004. García, J. and 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, Vol. 5, p. 102, doi: https://doi.org/10.3389/frobt.2018.00102 Hammond, R.A. (2015), “Considerations and best practices in agent-based modeling to inform policy”, in Wallace, R., Geller, A. and Ogawa, V.A. (Eds), Assessing the Use of Agent-Based Models for Tobacco Regulation, The National Academies Press, Washington, DC, D.C., pp. 161-193. Hardoy, J. and Velásquez Barrero, L.S. (2014), “Re-thinking ‘biomanizales’: addressing climate change adaptation in Manizales, Colombia”, Environment and Urbanization, Vol. 26 No. 1, pp. 53-68, doi: https://doi.org/10.1177/0956247813518687. Hashemipour, M., Stuban, S. and Dever, J. (2018), “A disaster multiagent coordination simulation system to evaluate the design of a first-response team”, Systems Engineering, Vol. 21 No. 4, pp. 322-344, doi: https://doi.org/10.1002/sys.21437. Hooshangi, N. and 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, Vol. 7 No. 1, p. 27, doi: https://doi.org/10.3390/ijgi7010027 IPCC (2021), “Summary for policymakers”, Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (Eds), Cambridge University Press, Cambridge, United Kingdom and New York, NY, pp. 3-32, doi: https://doi.org/10.1017/9781009157896.001. Jahre, M. and Jensen, L.M. (2021), “Coordination at the 10-year mark of the JHLSCM-from global response to local preparedness”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 11 No. 4, pp. 585-598, doi: https://doi.org/10.1108/JHLSCM-06-2021-0051. Jahre, M., Pazirandeh, A. and Van Wassenhove, L.N. (2016), “Defining logistics preparedness: a framework and research agenda”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 6 No. 3, pp. 372-398, doi: https://doi.org/10.1108/JHLSCM-04-2016-0012. John, L., Gurumurthy, A., Soni, G. and Jain, V. (2019), “Modelling the inter-relationship between factors affecting coordination in a humanitarian supply chain: a case of Chennai flood relief”, Annals of Operations Research, Vol. 283 No. 1-2, pp. 1227-1258, doi: https://doi.org/10.1007/s10479-018-2963-3. Kabra, G., Ramesh, A. and Arshinder, K. (2015), “Identification and prioritization of coordination barriers in humanitarian supply chain management”, International Journal of Disaster Risk Reduction, Vol. 13, pp. 128-138, doi: https://doi.org/10.1016/j.ijdrr.2015.01.011. Kadosh, S.C., Sinuany-Stern, Z. and Bitan, Y. (2023), “Location of emergency treatment sites after earthquake using hybrid simulation”, Tehnički Glasnik, Vol. 17 No. 3, pp. 391-396, doi: https://doi.org/10.31803/tg-20230511184836. Kamyabniya, A., Lotfi, M.M., Cai, H., Hosseininasab, H., Yaghoubi, S. and Yih, Y. (2019), “A two-phase coordinated logistics planning approach to platelets provision in humanitarian relief operations”, IISE Transactions, Vol. 51 No. 1, pp. 1-21, doi: https://doi.org/10.1080/24725854.2018.1479901. Klumpp, M., de Leeuw, S., Regattieri, A. and de Souza, R. (2015), “Sustainability in humanitarian logistics - why and how?”, in Klumpp, M., de Leeuw, S., Regattieri, A. and de Souza, R. (Eds), Humanitarian Logistics and Sustainability, Springer, Cham, pp. 3-9, doi: https://doi.org/10.1007/978-3-319-15455-8_1. Krejci, C.C. (2015), “Hybrid simulation modeling for humanitarian relief chain coordination”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 5 No. 3, pp. 325-347, doi: https://doi.org/10.1108/JHLSCM-07-2015-0033. Kunz, N., Reiner, G. and Gold, S. (2014), “Investing in disaster management capabilities versus pre-positioning inventory: a new approach to disaster preparedness”, International Journal of Production Economics, Vol. 157 No. 1, pp. 261-272, doi: https://doi.org/10.1016/j.ijpe.2013.11.002. Kusumastuti, R.D., Nurmala, N., Arviansyah, A. and Wibowo, S.S. (2022), “Indicators of community preparedness for fast-onset disasters: a systematic literature review and case study”, Natural Hazards, Vol. 110 No. 1, pp. 787-821, doi: https://doi.org/10.1007/s11069-021-04970-9. Lebcir, R.M. and Roy, P. (2023), “Impact of coordination on post-earthquake last mile relief distribution operations in India”, International Journal of Emergency Management, Vol. 18 No. 3, pp. 293-316, doi: https://doi.org/10.1504/IJEM.2023.132390. Lemoine, P.D., Cordovez, J.M., Zambrano, J.M., Sarmiento, O.L., Meisel, J.D., Valdivia, J.A. and Zarama, R. (2016), “Using agent based modeling to assess the effect of increased bus rapid transit system infrastructure on walking for transportation”, Preventive Medicine, Vol. 88, pp. 39-45, doi: https://doi.org/10.1016/j.ypmed.2016.03.015. Liao, H.Y., Holguín-Veras, J. and Calderón, O. (2023), “Comparative analysis of the performance of humanitarian logistic structures using agent-based simulation”, Socio-Economic Planning Sciences, Vol. 90, p. 101751, doi: https://doi.org/10.1016/j.seps.2023.101751. Liu, K.L., Yang, L., Zhao, Y.J. and Zhang, Z.H. (2023), “Multi-period stochastic programming for relief delivery considering evolving transportation network and temporary facility relocation/closure”, Transportation Research Part E: Logistics and Transportation Review, Vol. 180, p. 103357, doi: https://doi.org/10.1016/j.tre.2023.103357 Maghsoudi, A. and Moshtari, M. (2021), “Challenges in disaster relief operations: evidence from the 2017 Kermanshah earthquake”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 11 No. 1, pp. 107-134, doi: https://doi.org/10.1108/JHLSCM-08-2019-0054. Negi, S. (2022), “Humanitarian logistics challenges in disaster relief operations: a humanitarian organisations’ perspective”, Journal of Transport and Supply Chain Management, Vol. 16, pp. 1-11, doi: https://doi.org/10.4102/jtscm.v16i0.691. Nikbakhsh, E. and Zanjirani Farahani, R. (2011), “Humanitarian logistics planning in disaster relief operations”, in Farahani, R.Z., Rezapour, S. and Kardar, L. (Eds), Logistics Operations and Management: Concepts and Models, Elsevier, Amsterdam, pp. 291-332, doi: https://doi.org/10.1016/B978-0-12-385202-1.00015-3. Oksuz, M.K. and Satoglu, S.I. (2023), “Integrated optimization of facility location, casualty allocation and medical staff planning for post-disaster emergency response”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 14 No. 3, doi: https://doi.org/10.1108/JHLSCM-08-2023-0072. Orozco-Álzate, K. and Valencia-Ríos, J. (2021), Inventario de Movimientos de Ladera Recientes, Análisis y Zonificación Preliminar de la Estabilidad de Laderas Para la Ciudad de Manizales (Zona 2 – Comuna 2), Universidad de Caldas, Manizales. www.repositorio.ucaldas.edu.co/handle/ucaldas/17131. Consultation date: 23. Feb. 2023. Rodríguez-Espíndola, O. (2023), “Two-stage stochastic formulation for relief operations with multiple agencies in simultaneous disasters”, Or Spectrum, Vol. 45 No. 2, pp. 477-523, doi: https://doi.org/10.1007/s00291-023-00705-3. Ruesch, L., Tarakci, M., Besiou, M. and Van Quaquebeke, N. (2022), “Orchestrating coordination among humanitarian organizations”, Production and Operations Management, Vol. 31 No. 5, pp. 1977-1996, doi: https://doi.org/10.1111/poms.13660 Scholten, K., Scott, P.S. and Fynes, B. (2014), “Mitigation processes – antecedents for building supply chain resilience”, Supply Chain Management: An International Journal, Vol. 19 No. 2, pp. 211-228, doi: https://doi.org/10.1108/SCM-06-2013-0191 Shalash, A., Abu-Rmeileh, N.M.E., Kelly, D. and Elmusharaf, K. (2022), “The need for standardized methods of data collection, sharing of data and agency coordination in humanitarian settings”, BMJ Global Health, Vol. 7 No. Suppl 8, p. e007249, doi: https://doi.org/10.1136/bmjgh-2021-007249. Shao, J.F., Fan, Y., Wang, X.H., Liang, C.Y. and Liang, L. (2023), “Designing a new framework agreement in humanitarian logistics based on deprivation cost functions”, International Journal of Production Economics, Vol. 256, p. 108744, doi: https://doi.org/10.1016/j.ijpe.2022.108744. Shoham, Y. and Leyton-Brown, K. (2008), Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press, Cambridge Shokr, I., Jolai, F. and Bozorgi-Amiri, A. (2022), “A collaborative humanitarian relief chain design for disaster response”, Computers & Industrial Engineering, Vol. 172, p. 108643, doi: https://doi.org/10.1016/j.cie.2022.108643. Shrivastav, S.K. and Bag, S. (2023), “Humanitarian supply chain management in the digital age: a hybrid review using published literature and social media data”, Benchmarking: An International Journal, Vol. 31 No. 7, doi: https://doi.org/10.1108/BIJ-04-2023-0273. Sopha, B.M., Triasari, A.I. and Cheah, L. (2021), “Sustainable humanitarian operations: multi-method simulation for large-scale evacuation”, Sustainability, Vol. 13 No. 13, p. 7488, doi: https://doi.org/10.3390/su13137488. Stumpf, J., Besiou, M. and Wakolbinger, T. (2023), “Supply chain preparedness: how operational settings, product and disaster characteristics affect humanitarian responses”, Production and Operations Management, Vol. 32 No. 8, pp. 2491-2509, doi: https://doi.org/10.1111/poms.13988. Talebian Sharif, M.T. and Salari, M. (2015), “A GRASP algorithm for a humanitarian relief transportation problem”, Engineering Applications of Artificial Intelligence, Vol. 41, pp. 259-269, doi: https://doi.org/10.1016/j.engappai.2015.02.013. Timperio, G., Kundu, T., Klumpp, M., de Souza, R., Loh, X.H. and Goh, K. (2022), “Beneficiary-centric decision support framework for enhanced resource coordination in humanitarian logistics: a case study from ASEAN”, Transportation Research Part E: Logistics and Transportation Review, Vol. 167, p. 102909, doi: https://doi.org/10.1016/j.tre.2022.102909. UNDP (2015), “Nuevos escenarios de cambio climático Para Colombia 2011 – 2100. The united nations development program – UNDP Colombia, Bogotá”, available at: www.reliefweb.int/report/colombia/nuevos-escenarios-de-cambio-clim-tico-para-colombia-2011-2100-herramientas-cient-0 Consultation date: 1. Oct. 2020. UNDRR (2022), “Global assessment report on disaster risk reduction 2022: our world at risk: transforming governance for a resilient future”, United Nations Office for Disaster Risk Reduction, Geneva. www.undrr.org/gar/gar2022-our-world-risk-gar#container-downloads. Consultation date: 12. Feb. 2024. UNGRD (2016), Plan Nacional de Gestión Del Riesgo de Desastres: Una Estrategia de Desarrollo 2015-2025, Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá. www.reliefweb.int/report/colombia/plan-nacional-de-gesti-n-del-riesgo-de-desastres-2015-2025-una-estrategia-de Consultation date: 23. Oct. 2016. UNGRD (2018), Colombia menos vulnerable: la gestión del riesgo de desastres en nuestra historia, Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá, available at: www.portal.gestiondelriesgo.gov.co/Colombia-menos-vulnerable/index.html Consultation date: 30. Sep. 2020. Wagner, S.M., Ramkumar, M., Kumar, G. and Schoenherr, T. (2024), “Supporting disaster relief operations through RFID: enabling visibility and coordination”, The International Journal of Logistics Management, doi: https://doi.org/10.1108/IJLM-12-2022-0480. Wang, Z. and Zhang, J. (2019), “Agent-based evaluation of humanitarian relief goods supply capability”, International Journal of Disaster Risk Reduction, Vol. 36, p. 101105, doi: https://doi.org/10.1016/j.ijdrr.2019.101105. Wilensky, U. and Rand, W. (2015), An Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo, MIT Press, Cambridge. Xu, W.P., Li, W.Z., Proverbs, D. and Chen, W.B. (2023), “An evaluation of the humanitarian supply chains in the event of flash flooding”, Water, Vol. 15 No. 18, p. 3323, doi: https://doi.org/10.3390/w15183323. Yan, Q.F. (2023), “The use of climate information in humanitarian relief efforts: a literature review”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 13 No. 3, pp. 331-343, doi: https://doi.org/10.1108/JHLSCM-01-2022-0003. Yang, B. and Chen, Y.A. (2019), “Evolution model and simulation of logistics outsourcing for manufacturing enterprises based on multi-agent modeling”, Cluster Computing, Vol. 22 No. S3, pp. S6807-S6815, doi: https://doi.org/10.1007/s10586-018-2657-2. Zain, R.M., Zahari, H.M. and Zainol, N.A.M. (2023), “Inter-agency information sharing coordination on humanitarian logistics support for urban disaster management in Kuala Lumpur”, Frontiers in Sustainable Cities, Vol. 5, p. 1149454, doi: https://doi.org/10.3389/frsc.2023.1149454. Zhang, M. and Kong, Z.J. (2023), “A two-phase combinatorial double auction and negotiation mechanism for socialized joint reserve mode in emergency preparedness”, Socio-Economic Planning Sciences, Vol. 87, p. 101512, doi: https://doi.org/10.1016/j.seps.2023.101512. Zhao, K., Yen, J., Ngamassi, L.M., Maitland, C. and Tapia, A.H. (2012), “Simulating inter-organizational collaboration network: a multi-relational and event-based approach”, SIMULATION, Vol. 88 No. 5, pp. 617-633, doi: https://doi.org/10.1177/0037549711421942. |
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López-Vargas, Juan Camiloa6a91da9-ade8-4429-90ae-7055c843837c-1Meisel, José D7bc033f4-a85f-4e1c-a44e-fdb38040e2c1-1Cárdenas-Aguirre, Diana María2946609b-1de4-4627-9ca2-ef4f7406894c-1Medina, Pablo447ee9d4-c082-45ff-971a-087d2e9fd663-12025-11-06T19:41:23Z2025-11-06T19:41:23Z2025-04-21The study aims to present an agent-based simulation model (ABM) for exploring interorganizational coordination scenarios in local disaster preparedness. This approach includes local actors and logistical processes as agents to compare various strategic coordination mechanisms. Design/methodology/approach: The ABM model, developed in the Latin American context, specifically focuses on a case study of Colombia. Three coordination mechanisms (centralized, decentralized and cluster-type) have been evaluated using three performance indicators: effectiveness, efficiency and flexibility. Findings: Simulation results show that the decentralized scenario outperforms in terms of efficiency and flexibility. On the contrary, the centralized and cluster-type scenarios demonstrate higher effectiveness, achieving a greater percentage of requirements coverage during the disaster preparedness stage. The ABM approach effectively evaluates strategical coordination mechanisms based on the analyzed performance indicators. Research limitations/implications: This study has limitations due to the application of results to a single real case. In addition, the focus of the study is primarily on a specific type of disaster, specifically hydrometeorological events such as flash floods, torrential rains and landslides. Moreover, the scope of decision-making is restricted to key actors involved in local-level disaster management within a municipality. Originality/value: The proposed ABM model has the potential as a decision-making tool for policies and local coordination schemes for future disasters. The simulation tool could also explore diverse geographical scenarios and disaster types, demonstrating its versatility and broader applicability for further insights and recommendations.application/pdfLópez-Vargas, J., Meisel, J., Cárdenas-Aguirre, D. y Medina, P. (2025). Coordination mechanisms applied to logistical systems for local disaster preparedness: a Latin American case. Journal of Humanitarian Logistics and Supply Chain Management, 15(2), 87 - 106. DOI: 10.1108/JHLSCM-09-2023-0085DOI: 10.1108/JHLSCM-09-2023-00852042675520426747https://hdl.handle.net/20.500.12313/5910https://www.emerald.com/jhlscm/article/15/2/87/1247143/Coordination-mechanisms-applied-to-logisticalengEmerald PublishingReino Unido10628715Altay, N. and Pal, R. (2014), “Information diffusion among agents: implications for humanitarian operations”, Production and Operations Management, Vol. 23 No. 6, pp. 1015-1027, doi: https://doi.org/10.1111/poms.12102Anjomshoae, A., Banomyong, R., Azadnia, A.H., Kunz, N. and Blome, C. (2023), “Sustainable humanitarian supply chains: a systematic literature review and research propositions”, Production Planning & Control, doi: https://doi.org/10.1080/09537287.2023.2273451.Anvari, M., Anvari, A. and Boyer, O. (2023), “A prepositioning model for prioritized demand points considering lateral transshipment”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 13 No. 4, pp. 433-455, doi: https://doi.org/10.1108/JHLSCM-01-2023-0005.Aros, S.K. and 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, Vol. 269 No. 2, pp. 451-465, doi: https://doi.org/10.1016/j.ejor.2018.02.013.Bae, J.W., Shin, K., Lee, H.R., Lee, H.J., Lee, T., Kim, C.H., Cha, W.C., Kim, G.W. and Moon, I.C. (2018), “Evaluation of disaster response system using agent-based model with geospatial and medical details”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 48 No. 9, pp. 1454-1469, doi: https://doi.org/10.1109/TSMC.2017.2671340.Bayram, V. and Yaman, H. (2024), “A joint demand and supply management approach to large scale urban evacuation planning: evacuate or shelter-in-place, staging and dynamic resource allocation”, European Journal of Operational Research, Vol. 313 No. 1, pp. 171-191, doi: https://doi.org/10.1016/j.ejor.2023.07.033.Besiou, M., Pedraza-Martinez, A.J. and Van Wassenhove, L.N. (2021), “Humanitarian operations and the UN sustainable development goals”, Production and Operations Management, Vol. 30 No. 12, pp. 4343-4355, doi: https://doi.org/10.1111/poms.13579.Boshuijzen-van Burken, C., Gore, R., Dignum, F., Royakkers, L., Wozny, P. and Shults, F.L. (2020), “Agent-based modelling of values: the case of value sensitive design for refugee logistics”, Journal of Artificial Societies and Social Simulation, Vol. 23 No. 4, p. 6, doi: https://doi.org/10.18564/jasss.4411.Bui, H., Sakurahara, T., Reihani, S., Kee, E. and Mohaghegh, Z. (2020), “Spatiotemporal integration of an agent-based first responder performance model with a fire hazard propagation model for probabilistic risk assessment of nuclear power plants”, ASCE-ASME Journal of Risk and Uncertainty In Engineering Systems Part B-Mechanical Engineering, Vol. 6 No. 1, p. 011011, doi: https://doi.org/10.1115/1.4044793.Calabrò, G., Torrisi, V., Inturri, G. and Ignaccolo, M. (2020), “Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization, 21”, European Transport Research Review, Vol. 12 No. 1, doi: https://doi.org/10.1186/s12544-020-00409-7.Cardona, O.D. (2019), “Gestión del riesgo y adaptación en manizales: una estrategia de desarrollo Para lograr que una ciudad en transición sea resiliente, sostenible y competitiva”, Medio Ambiente y Urbanización, Vol. 90 No. 1, pp. 127-168.Chen, J.W., Zhang, X.L., Peng, X.F., Xu, D.S. and Peng, J.C. (2022), “Efficient routing for multi-AGV based on optimized ant-agent”, Computers & Industrial Engineering, Vol. 167, p. 108042, doi: https://doi.org/10.1016/j.cie.2022.108042.Connelly, E.B., Lambert, J.H. and Thekdi, S.A. (2016), “Robust investments in humanitarian logistics and supply chains for disaster resilience and sustainable communities”, Natural Hazards Review, Vol. 17 No. 1, p. 04015017, doi: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000187.Corbett, C.J., Pedraza-Martinez, A.J. and Van Wassenhove, L.N. (2022), “Sustainable humanitarian operations: an integrated perspective”, Production and Operations Management, Vol. 31 No. 12, pp. 4393-4406, doi: https://doi.org/10.1111/poms.13848Cozzolino, A. (2012), Humanitarian Logistics: Cross-Sector Cooperation in Disaster Relief Management, Springer, Berlin, Heidelberg.Das, R. and Hanaoka, S. (2014), “An agent-based model for resource allocation during relief distribution”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 4 No. 2, pp. 265-285, doi: https://doi.org/10.1108/JHLSCM-07-2013-0023.Dhingra, R. (2022), “Coordination in practice or performance? The political economy of refugee aid coordination in Jordan”, Journal of Refugee Studies, Vol. 35 No. 4, pp. 1472-1491, doi: https://doi.org/10.1093/jrs/feac002.Echeverri Tafur, L. and Obando Moncayo, F.H. (2010), “Erosividad de las lluvias en la región Centro-Sur del Departamento de Caldas, Colombia”, Revista Facultad Nacional de Agronomía - Medellín, Vol. 63 No. 1, pp. 5307-5318.El-Sayed, A.M., Scarborough, P., Seemann, L. and Galea, S. (2012), “Social network analysis and agent-based modeling in social epidemiology”, Epidemiologic Perspectives & Innovations, Vol. 9 No. 1, pp. 1-9, doi: https://doi.org/10.1186/1742-5573-9-1.Fontainha, T.C., Leiras, A., Bandeira, R.A.D. and Scavarda, L.F. (2017), “Public-private-people relationship stakeholder model for disaster and humanitarian operations”, International Journal of Disaster Risk Reduction, Vol. 22, pp. 371-386, doi: https://doi.org/10.1016/j.ijdrr.2017.02.004.García, J. and 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, Vol. 5, p. 102, doi: https://doi.org/10.3389/frobt.2018.00102Hammond, R.A. (2015), “Considerations and best practices in agent-based modeling to inform policy”, in Wallace, R., Geller, A. and Ogawa, V.A. (Eds), Assessing the Use of Agent-Based Models for Tobacco Regulation, The National Academies Press, Washington, DC, D.C., pp. 161-193.Hardoy, J. and Velásquez Barrero, L.S. (2014), “Re-thinking ‘biomanizales’: addressing climate change adaptation in Manizales, Colombia”, Environment and Urbanization, Vol. 26 No. 1, pp. 53-68, doi: https://doi.org/10.1177/0956247813518687.Hashemipour, M., Stuban, S. and Dever, J. (2018), “A disaster multiagent coordination simulation system to evaluate the design of a first-response team”, Systems Engineering, Vol. 21 No. 4, pp. 322-344, doi: https://doi.org/10.1002/sys.21437.Hooshangi, N. and 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, Vol. 7 No. 1, p. 27, doi: https://doi.org/10.3390/ijgi7010027IPCC (2021), “Summary for policymakers”, Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (Eds), Cambridge University Press, Cambridge, United Kingdom and New York, NY, pp. 3-32, doi: https://doi.org/10.1017/9781009157896.001.Jahre, M. and Jensen, L.M. (2021), “Coordination at the 10-year mark of the JHLSCM-from global response to local preparedness”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 11 No. 4, pp. 585-598, doi: https://doi.org/10.1108/JHLSCM-06-2021-0051.Jahre, M., Pazirandeh, A. and Van Wassenhove, L.N. (2016), “Defining logistics preparedness: a framework and research agenda”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 6 No. 3, pp. 372-398, doi: https://doi.org/10.1108/JHLSCM-04-2016-0012.John, L., Gurumurthy, A., Soni, G. and Jain, V. (2019), “Modelling the inter-relationship between factors affecting coordination in a humanitarian supply chain: a case of Chennai flood relief”, Annals of Operations Research, Vol. 283 No. 1-2, pp. 1227-1258, doi: https://doi.org/10.1007/s10479-018-2963-3.Kabra, G., Ramesh, A. and Arshinder, K. (2015), “Identification and prioritization of coordination barriers in humanitarian supply chain management”, International Journal of Disaster Risk Reduction, Vol. 13, pp. 128-138, doi: https://doi.org/10.1016/j.ijdrr.2015.01.011.Kadosh, S.C., Sinuany-Stern, Z. and Bitan, Y. (2023), “Location of emergency treatment sites after earthquake using hybrid simulation”, Tehnički Glasnik, Vol. 17 No. 3, pp. 391-396, doi: https://doi.org/10.31803/tg-20230511184836.Kamyabniya, A., Lotfi, M.M., Cai, H., Hosseininasab, H., Yaghoubi, S. and Yih, Y. (2019), “A two-phase coordinated logistics planning approach to platelets provision in humanitarian relief operations”, IISE Transactions, Vol. 51 No. 1, pp. 1-21, doi: https://doi.org/10.1080/24725854.2018.1479901.Klumpp, M., de Leeuw, S., Regattieri, A. and de Souza, R. (2015), “Sustainability in humanitarian logistics - why and how?”, in Klumpp, M., de Leeuw, S., Regattieri, A. and de Souza, R. (Eds), Humanitarian Logistics and Sustainability, Springer, Cham, pp. 3-9, doi: https://doi.org/10.1007/978-3-319-15455-8_1.Krejci, C.C. (2015), “Hybrid simulation modeling for humanitarian relief chain coordination”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 5 No. 3, pp. 325-347, doi: https://doi.org/10.1108/JHLSCM-07-2015-0033.Kunz, N., Reiner, G. and Gold, S. (2014), “Investing in disaster management capabilities versus pre-positioning inventory: a new approach to disaster preparedness”, International Journal of Production Economics, Vol. 157 No. 1, pp. 261-272, doi: https://doi.org/10.1016/j.ijpe.2013.11.002.Kusumastuti, R.D., Nurmala, N., Arviansyah, A. and Wibowo, S.S. (2022), “Indicators of community preparedness for fast-onset disasters: a systematic literature review and case study”, Natural Hazards, Vol. 110 No. 1, pp. 787-821, doi: https://doi.org/10.1007/s11069-021-04970-9.Lebcir, R.M. and Roy, P. (2023), “Impact of coordination on post-earthquake last mile relief distribution operations in India”, International Journal of Emergency Management, Vol. 18 No. 3, pp. 293-316, doi: https://doi.org/10.1504/IJEM.2023.132390.Lemoine, P.D., Cordovez, J.M., Zambrano, J.M., Sarmiento, O.L., Meisel, J.D., Valdivia, J.A. and Zarama, R. (2016), “Using agent based modeling to assess the effect of increased bus rapid transit system infrastructure on walking for transportation”, Preventive Medicine, Vol. 88, pp. 39-45, doi: https://doi.org/10.1016/j.ypmed.2016.03.015.Liao, H.Y., Holguín-Veras, J. and Calderón, O. (2023), “Comparative analysis of the performance of humanitarian logistic structures using agent-based simulation”, Socio-Economic Planning Sciences, Vol. 90, p. 101751, doi: https://doi.org/10.1016/j.seps.2023.101751.Liu, K.L., Yang, L., Zhao, Y.J. and Zhang, Z.H. (2023), “Multi-period stochastic programming for relief delivery considering evolving transportation network and temporary facility relocation/closure”, Transportation Research Part E: Logistics and Transportation Review, Vol. 180, p. 103357, doi: https://doi.org/10.1016/j.tre.2023.103357Maghsoudi, A. and Moshtari, M. (2021), “Challenges in disaster relief operations: evidence from the 2017 Kermanshah earthquake”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 11 No. 1, pp. 107-134, doi: https://doi.org/10.1108/JHLSCM-08-2019-0054.Negi, S. (2022), “Humanitarian logistics challenges in disaster relief operations: a humanitarian organisations’ perspective”, Journal of Transport and Supply Chain Management, Vol. 16, pp. 1-11, doi: https://doi.org/10.4102/jtscm.v16i0.691.Nikbakhsh, E. and Zanjirani Farahani, R. (2011), “Humanitarian logistics planning in disaster relief operations”, in Farahani, R.Z., Rezapour, S. and Kardar, L. (Eds), Logistics Operations and Management: Concepts and Models, Elsevier, Amsterdam, pp. 291-332, doi: https://doi.org/10.1016/B978-0-12-385202-1.00015-3.Oksuz, M.K. and Satoglu, S.I. (2023), “Integrated optimization of facility location, casualty allocation and medical staff planning for post-disaster emergency response”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 14 No. 3, doi: https://doi.org/10.1108/JHLSCM-08-2023-0072.Orozco-Álzate, K. and Valencia-Ríos, J. (2021), Inventario de Movimientos de Ladera Recientes, Análisis y Zonificación Preliminar de la Estabilidad de Laderas Para la Ciudad de Manizales (Zona 2 – Comuna 2), Universidad de Caldas, Manizales. www.repositorio.ucaldas.edu.co/handle/ucaldas/17131. Consultation date: 23. Feb. 2023.Rodríguez-Espíndola, O. (2023), “Two-stage stochastic formulation for relief operations with multiple agencies in simultaneous disasters”, Or Spectrum, Vol. 45 No. 2, pp. 477-523, doi: https://doi.org/10.1007/s00291-023-00705-3.Ruesch, L., Tarakci, M., Besiou, M. and Van Quaquebeke, N. (2022), “Orchestrating coordination among humanitarian organizations”, Production and Operations Management, Vol. 31 No. 5, pp. 1977-1996, doi: https://doi.org/10.1111/poms.13660Scholten, K., Scott, P.S. and Fynes, B. (2014), “Mitigation processes – antecedents for building supply chain resilience”, Supply Chain Management: An International Journal, Vol. 19 No. 2, pp. 211-228, doi: https://doi.org/10.1108/SCM-06-2013-0191Shalash, A., Abu-Rmeileh, N.M.E., Kelly, D. and Elmusharaf, K. (2022), “The need for standardized methods of data collection, sharing of data and agency coordination in humanitarian settings”, BMJ Global Health, Vol. 7 No. Suppl 8, p. e007249, doi: https://doi.org/10.1136/bmjgh-2021-007249.Shao, J.F., Fan, Y., Wang, X.H., Liang, C.Y. and Liang, L. (2023), “Designing a new framework agreement in humanitarian logistics based on deprivation cost functions”, International Journal of Production Economics, Vol. 256, p. 108744, doi: https://doi.org/10.1016/j.ijpe.2022.108744.Shoham, Y. and Leyton-Brown, K. (2008), Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press, CambridgeShokr, I., Jolai, F. and Bozorgi-Amiri, A. (2022), “A collaborative humanitarian relief chain design for disaster response”, Computers & Industrial Engineering, Vol. 172, p. 108643, doi: https://doi.org/10.1016/j.cie.2022.108643.Shrivastav, S.K. and Bag, S. (2023), “Humanitarian supply chain management in the digital age: a hybrid review using published literature and social media data”, Benchmarking: An International Journal, Vol. 31 No. 7, doi: https://doi.org/10.1108/BIJ-04-2023-0273.Sopha, B.M., Triasari, A.I. and Cheah, L. (2021), “Sustainable humanitarian operations: multi-method simulation for large-scale evacuation”, Sustainability, Vol. 13 No. 13, p. 7488, doi: https://doi.org/10.3390/su13137488.Stumpf, J., Besiou, M. and Wakolbinger, T. (2023), “Supply chain preparedness: how operational settings, product and disaster characteristics affect humanitarian responses”, Production and Operations Management, Vol. 32 No. 8, pp. 2491-2509, doi: https://doi.org/10.1111/poms.13988.Talebian Sharif, M.T. and Salari, M. (2015), “A GRASP algorithm for a humanitarian relief transportation problem”, Engineering Applications of Artificial Intelligence, Vol. 41, pp. 259-269, doi: https://doi.org/10.1016/j.engappai.2015.02.013.Timperio, G., Kundu, T., Klumpp, M., de Souza, R., Loh, X.H. and Goh, K. (2022), “Beneficiary-centric decision support framework for enhanced resource coordination in humanitarian logistics: a case study from ASEAN”, Transportation Research Part E: Logistics and Transportation Review, Vol. 167, p. 102909, doi: https://doi.org/10.1016/j.tre.2022.102909.UNDP (2015), “Nuevos escenarios de cambio climático Para Colombia 2011 – 2100. The united nations development program – UNDP Colombia, Bogotá”, available at: www.reliefweb.int/report/colombia/nuevos-escenarios-de-cambio-clim-tico-para-colombia-2011-2100-herramientas-cient-0 Consultation date: 1. Oct. 2020.UNDRR (2022), “Global assessment report on disaster risk reduction 2022: our world at risk: transforming governance for a resilient future”, United Nations Office for Disaster Risk Reduction, Geneva. www.undrr.org/gar/gar2022-our-world-risk-gar#container-downloads. Consultation date: 12. Feb. 2024.UNGRD (2016), Plan Nacional de Gestión Del Riesgo de Desastres: Una Estrategia de Desarrollo 2015-2025, Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá. www.reliefweb.int/report/colombia/plan-nacional-de-gesti-n-del-riesgo-de-desastres-2015-2025-una-estrategia-de Consultation date: 23. Oct. 2016.UNGRD (2018), Colombia menos vulnerable: la gestión del riesgo de desastres en nuestra historia, Unidad Nacional para la Gestión del Riesgo de Desastres, Bogotá, available at: www.portal.gestiondelriesgo.gov.co/Colombia-menos-vulnerable/index.html Consultation date: 30. Sep. 2020.Wagner, S.M., Ramkumar, M., Kumar, G. and Schoenherr, T. (2024), “Supporting disaster relief operations through RFID: enabling visibility and coordination”, The International Journal of Logistics Management, doi: https://doi.org/10.1108/IJLM-12-2022-0480.Wang, Z. and Zhang, J. (2019), “Agent-based evaluation of humanitarian relief goods supply capability”, International Journal of Disaster Risk Reduction, Vol. 36, p. 101105, doi: https://doi.org/10.1016/j.ijdrr.2019.101105.Wilensky, U. and Rand, W. (2015), An Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo, MIT Press, Cambridge.Xu, W.P., Li, W.Z., Proverbs, D. and Chen, W.B. (2023), “An evaluation of the humanitarian supply chains in the event of flash flooding”, Water, Vol. 15 No. 18, p. 3323, doi: https://doi.org/10.3390/w15183323.Yan, Q.F. (2023), “The use of climate information in humanitarian relief efforts: a literature review”, Journal of Humanitarian Logistics and Supply Chain Management, Vol. 13 No. 3, pp. 331-343, doi: https://doi.org/10.1108/JHLSCM-01-2022-0003.Yang, B. and Chen, Y.A. (2019), “Evolution model and simulation of logistics outsourcing for manufacturing enterprises based on multi-agent modeling”, Cluster Computing, Vol. 22 No. S3, pp. S6807-S6815, doi: https://doi.org/10.1007/s10586-018-2657-2.Zain, R.M., Zahari, H.M. and Zainol, N.A.M. (2023), “Inter-agency information sharing coordination on humanitarian logistics support for urban disaster management in Kuala Lumpur”, Frontiers in Sustainable Cities, Vol. 5, p. 1149454, doi: https://doi.org/10.3389/frsc.2023.1149454.Zhang, M. and Kong, Z.J. (2023), “A two-phase combinatorial double auction and negotiation mechanism for socialized joint reserve mode in emergency preparedness”, Socio-Economic Planning Sciences, Vol. 87, p. 101512, doi: https://doi.org/10.1016/j.seps.2023.101512.Zhao, K., Yen, J., Ngamassi, L.M., Maitland, C. and Tapia, A.H. (2012), “Simulating inter-organizational collaboration network: a multi-relational and event-based approach”, SIMULATION, Vol. 88 No. 5, pp. 617-633, doi: https://doi.org/10.1177/0037549711421942.© 2024, Juan Camilo López-Vargas, José D. 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