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Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

Community centers play a socio-economic and urban role of combining different communal necessities, that serve inhabitants, at different neighborhoods in cities. Their role emerged in importance as being a hub for improving and customizing quality of life experiences of the public. This research presents a code-based risk assessment tool for evaluating fire safety measures that can be adapted in the context of community centers. It also provides an exemplary case study to demonstrate its application.

The study identified the factors that render community centers as a high-risk type of facilities in fire events. Various fire codes and standards were reviewed to describe the relevant fire safety measures. A code-based fire risk assessment tool was developed and implemented, through a case study. A set of recommendations were developed to improve the fire safety conditions of the case study facility.

Several violations to fire safety were identified in the case study building. The findings led to identifying a set of recommendations to improve its fire safety conditions.

This research introduced a systematic approach to raise awareness about fire incidences and consequences in community centers, and provides facilities managers with a tool, to assess compliance based on international fire code requirements.

In fire events, community centers are considered as high-risk facilities that may lead to significant losses of human lives and damages to assets. It is significant to study the causes of fire, for ensuring effective prevention and safe operations.

This study aims to track and integrate past research concerning how tourism might improve natural disaster management, detect thematic research areas and develop an agenda for future research.

Using a systematic literature review methodology, this research synthesises academic papers indexed in the Scopus, Web of Science and EBSCOhost (Hospitality & Tourism Complete) databases. A total of 34 articles published in peer-reviewed English journals were systematically selected for review and analysed using a thematic approach.

This review highlights a growing interest in the potential and value of tourism for disaster management. Eight key themes emerged in the review, including education and information communication about disasters; tourism facilities for disaster preparation; tourism resources in emergency conditions; livelihoods and economic recovery; disaster-related tourism attractions for recovery; destination re-branding and re-framing; community reinvigoration in tourism-driven disaster recovery; and special-interest tourism for recovery. A natural disaster management schematic empowered by tourism highlights tourism industry opportunities to positively impact the entire disaster management process.

To the best of the authors’ knowledge, this work offers the first systematic review of the research on how tourism might support multiple stages of natural disaster management. This study thus complements and enriches extant literature reviews on the nexus between tourism and disaster management. The framework presents timely guidelines for planners, developers and other key stakeholders to leverage tourism initiatives to improve disaster management outcomes.

本研究旨在追溯和整合以往研究中关于旅游业如何提升自然灾害管理的实践和发现, 明确主要研究领域并提出未来研究议程。

通过系统文献综述方法, 本研究综合了Scopus, Web of Science和EBSCOhost（Hospitality & Tourism Complete）数据库中索引的学术论文。共有34篇发表在同行评审的英文期刊上的文章被系统地筛选出来, 随后使用主题分析方法进行分析。

文献综述发现, 学者和行业实践者对旅游业在灾害管理方面的潜力和价值越来越感兴趣。综述分析发现了八个关键领域：灾害的教育和信息交流; 旅游设施用于备灾; 旅游资源用于紧急情况; 生计和经济复苏; 灾难相关的旅游吸引物; 灾难地品牌重塑和重构; 旅游业驱动的社区灾后重振; 灾后重建中的特殊兴趣旅游。本文设计了由旅游业赋权的自然灾害管理示意图, 突出了旅游业对整个灾害管理进程产生的积极影响和潜在机会。

本文首次系统地回顾了旅游业如何支持多个自然灾害管理阶段的相关研究。此项研究补充和丰富了关于旅游业与灾害管理之间关系的现有文献综述。该框架为规划者、开发商和其他主要利益相关者在利用旅游举措来改善灾害管理方面提供了及时的指导方针。

Este estudio identifica e integra las investigaciones anteriores sobre cómo el turismo podría mejorar la gestión de desastres naturales, detecta áreas temáticas de investigación y elabora una agenda para la investigación futura.

Usando una metodología de revisión sistemática de la literatura, esta investigación sintetiza artículos académicos indexados en las bases de datos Scopus, Web of Science y EBSCOhost (Hospitality & Tourism Complete). Se seleccionaron sistemáticamente un total de 34 artículos publicados en revistas inglesas con revisión por pares para su revisión y análisis mediante un enfoque temático.

Esta revisión pone de relieve el creciente interés por el potencial y el valor del turismo en la gestión de desastres. En la revisión surgieron ocho temas clave: la educación y la comunicación de información sobre desastres; instalaciones turísticas para la preparación ante desastres; recursos turísticos en condiciones de emergencia; medios de subsistencia y recuperación económica; atracciones turísticas relacionadas con los desastres para la recuperación; cambio de marca y replanteamiento del destino; revitalización de la comunidad en la recuperación de desastres impulsada por el turismo; y el turismo de interés especial para la recuperación. Un esquema de gestión de desastres naturales potenciado por el turismo pone de relieve las oportunidades de la industria turística para influir positivamente en todo el proceso de gestión de desastres.

Este trabajo ofrece la primera revisión sistemática de la investigación sobre cómo el turismo podría apoyar las múltiples etapas de la gestión de desastres naturales. Este estudio complementa y enriquece la bibliografía existente sobre el nexo entre el turismo y la gestión de desastres. El marco presenta directrices oportunas para que los planificadores, los promotores y otras partes interesadas clave aprovechen las iniciativas turísticas para mejorar los resultados de la gestión de desastres.

Finding an appropriate place for temporary housing after an earthquake is one of the main challenges of disaster risk management, especially in developing countries. Therefore, it is necessary to create pre-disaster location plans for the homeless population. This study aims to systematically find safe places and select suitable sites according to influential factors.

The research methodology used is a descriptive–analytical method. A field survey with a quantitative–qualitative approach is applied to recognize physical vulnerabilities and select suitable sites for temporary settlements. Due to the occurrence of several earthquakes in recent decades around the city of Isfahan, Iran, this area has been studied. Fuzzy analytic hierarchy process, geographic information system and rapid visual screening have been used for data analysis.

According to the site selection and vulnerability criteria and their prioritization, the findings indicate that 60% of the study area is vulnerable. Moreover, vacant lots, stadiums and public green spaces that can be used as multi-purpose sites are the most appropriate options for the temporary settlement.

The research criteria are generalizable and can be used for decision-making, concerning urban fabric vulnerability and site selection of temporary housing in cities exposed to earthquake risk.

Cultural features, accessibility, land conditions, the slope and type of land, availability and construction materials were addressed in locating temporary settlements. In addition to vacant lots and open spaces, safe buildings were also identified for temporary housing, and religious minorities and similar communities were considered.

This study aims to review the stages of the traditional disaster timeline, propose an extended version of this timeline and discuss the disaster strategies relevant to the different stages of the extended timeline.

An extensive review of the existing literature was made to discuss the need for an extended version of the conventional disaster timeline and to explain the differences between the various disaster management strategies. The research approach was based on theoretical and practical reasoning underpinned by the literature.

The proposed extended disaster timeline allows better allocation of a wider range of management strategies. Successful disaster management depends on prioritisation of efforts and the use of the right strategy(s) at the right time: before, during and after an incident.

This study provides a better conceptualisation of the disaster stages and corresponding strategies. It clarifies the role of each strategy, thus linking it more effectively with the disaster timeline. Subsequently, this study is expected to improve decision-making associated with the disaster management process. In the end, it is expected to help transforming the conventional disaster timeline into a more practical one that is result-oriented more than only being a conceptual model.

Disaster management strategies are used interchangeably very often in the literature. A few attempts were made to capture multiple strategies in one study to demonstrate what constitutes effective disaster management without mixing irrelevant strategies with the different disaster stages.

Tehran’s health-care system is growing, yet it lacks emergency planning procedures. The premise of this study is that the urban environment around a hospital is just as robust as the hospital itself. This study aims to look at hospital resilience in an urban setting to see where it may be improved to keep the hospital operational during a disaster.

The urban resilience (UR) of Amir-Alam Hospital was analyzed in this study using a customized version of the United Nations Office for Disaster Risk Reduction’s City Resilience Profiling Tool. The 34 indications were broken down into five categories.

The result revealed that the hospital’s UR score was 51.75 out of 100, indicating medium resilience. The results of this study enable the decision-makers to determine what measures they may take to improve the hospital’s resilience in terms of its surrounding urban context.

The originality of this research is based on the surrounding urban environment’s resilience as an integral part of hospital resilience.

This study aims to review the features and challenges of the flood relief chain, identifies administrative measures during and after the flood occurrence and prioritizes them using two machine learning (ML) and analytic hierarchy process (AHP) methods. This paper aims to provide a prioritization program based on flood conditions that optimize flood management and improves society’s resilience against flood occurrence.

The collected database in this paper has been trained by using ML algorithms, including support vector machine (SVM), Naive Bayes (NB) and k-nearest neighbors (kNN), to create a prioritization program. Furthermore, the administrative measures in two phases of during and after the flood are prioritized by using the AHP method and questionnaires completed by experts and relief workers in flood management.

Among the ML algorithms, the SVM method was selected with 91.37% accuracy. The prioritization program provided by the model, which distinguishes it from other existing models, considers five conditions of the flood occurrence to prioritize actions (season, population affected, area affected, damage to houses and human lives lost). Therefore, the model presents a specific plan for each flood with different occurrence conditions.

The main limitation is the lack of a comprehensive data set to determine the effect of all flood conditions on the prioritization program and the relief activities that have been done in previous flood disasters.

The originality of this paper is the use of ML methods to prioritize administrative measures during and after the flood and presents a prioritization program based on each flood’s conditions. Therefore, through this program, the authority and society can control the adverse impacts of flood more effectively and help to reduce human and financial losses as much as possible.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

This paper investigates how agile capabilities in humanitarian settings work in combination, and its effects on performance outcome. The study was conducted in the frame of reference of response operations during cyclones and floods, which is considered most complex and with the most widespread impact.

A survey-based method was used to collect empirical data on response operations from 131 field officers who were involved in disaster response during cyclones or floods. A partial least square based structural equation model was used to study the path model of interaction of agile capabilities, and their effect on performance outcomes.

The results show that integration of agile capabilities is important for enhancing effectiveness of humanitarian response. The results indicated a serial mediation effect involving visibility, responsiveness and flexibility capability on the effectiveness of emergency response.

This research has implications for response units of humanitarian organisations. This includes capacity building for key agile capabilities, integration, supply chain re-configuration and differential positioning of response phase as against preparedness and recovery phases.

This study is unique for the chosen humanitarian setting, which is considered most difficult. The authors demonstrate from empirical evidence the interaction effects of agile capabilities during response phase for cyclones and floods, and their impact. The research insights will help practitioners to configure and position supply chains for better effectiveness during response operations, which have markedly different objectives vis-à-vis other phases or types of humanitarian settings.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.