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Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

Built environments are highly vulnerable to climatic disasters such as extreme floods, droughts and storms. Inaccurate decisions in adopting emerging construction technologies can result in missed opportunities to improve the resilience of built environments. Therefore, understanding the effectiveness of emerging construction technologies in improving built environment resilience can help in making better strategic decisions at the national and organizational levels. This study aims to evaluate the effectiveness of Construction 4.0 technologies in improving built environment resilience.

A list of Construction 4.0 technologies was adopted from a national strategic plan. Then, the data were collected using the fuzzy technique for order preference by similarity to ideal solution technique from selected built environment experts to determine the relative effectiveness of Construction 4.0 technologies in improving built environment resilience.

Six Construction 4.0 technologies are critical in improving built environment resilience (in rank order): building information modeling, autonomous construction, advanced building materials, big data and predictive analytics, internet of Things and prefabrication and modular construction. In addition, adopting Construction 4.0 technologies collectively is crucial, as moderate to strong connections exist among the technologies in improving built environment resilience.

To the best of the authors’ knowledge, this is one of the first papers that evaluate the effectiveness of Construction 4.0 technologies in improving built environment resilience. Industry professionals, researchers and policymakers can use the study findings to make well-informed decisions on selecting Construction 4.0 technologies that improve built environment resilience to climatic disasters.

This study aimed to address the underexplored domain of organisational vulnerability, with a specific focus on understanding how vulnerability is understood in organisations and the underlying pathways leading to vulnerability.

This study utilised a narrative literature review methodology, using Google Scholar as the primary source, to analyse the concepts of organisational vulnerability in the context of disaster risk studies. The review focused on relevant documents published between the years 2000 and 2022.

The analysis highlights the multifaceted nature of organisational vulnerability, which arises from both inherent weaknesses within the organisation and external risks that expose it to potential hazards. The inherent weaknesses are rooted in internal vulnerability pathways such as organisational culture, managerial ignorance, human resources, and communication weaknesses that compromise the organisation’s resilience. The external dimension of vulnerability is found in cascading vulnerability pathways, e.g. critical infrastructure, supply chains, and customer relationships.

As the frequency and severity of disasters continue to increase, organisations of all sizes face heightened vulnerability to unforeseen disruptions and potential destruction. Acknowledging and comprehending organisational vulnerability is a crucial initial step towards enhancing risk management effectiveness, fostering resilience, and promoting sustainable success in an interconnected global environment and an evolving disaster landscape.

Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.

This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.

The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.

The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.

Authorities have set up numerous security checkpoints during times of armed conflict to control the flow of commercial and humanitarian trucks into and out of areas of conflict. These security checkpoints have become highly utilized because of the complex security procedures and increased truck traffic, which significantly slow the delivery of relief aid. This paper aims to improve the process at security checkpoints by redesigning the current process to reduce processing time and relieve congestion at checkpoint entrance gates.

A decision-support tool (clearing function distribution model [CFDM]) is used to minimize the effects of security checkpoint congestion on the entire humanitarian supply network using a hybrid simulation-optimization approach. By using a business process simulation, the current and reengineered processes are both simulated, and the simulation output was used to estimate the clearing function (capacity as a function of the workload). For both the AS-IS and TO-BE models, key performance indicators such as distribution costs, backordering and process cycle time were used to compare the results of the CFDM tool. For this, the Kerem Abu Salem security checkpoint south of Gaza was used as a case study.

The comparison results demonstrate that the CFDM tool performs better when the output of the TO-BE clearing function is used.

The efforts will contribute to improving the planning of any humanitarian network experiencing congestion at security checkpoints by minimizing the impact of congestion on the delivery lead time of relief aid to the final destination.

This study aims to provide an overview, the state-of-the-art “research fronts”, the emerging themes of investigation and a research agenda of crisis communication for destinations’ image.

This research is conducted with a bibliographic coupling study, complemented with an H-Classic classification and a thematic analysis of the articles included in the four clusters provided by the bibliometric methodology (papers dating from 2017 to 2021, both years included).

Based on the bibliometric analysis, four thematic clusters were identified. Two of these clusters supply the “research fronts”, the most current themes in a scientific field: Cluster 1 addresses communication related to tourists’ safety, and cluster 2 enhances the role of stakeholders’ collaboration to create destinations resilience in crisis communication. The other two clusters highlight emerging themes for future investigation: Cluster 3 focuses on recovery marketing communication strategies for a post-crisis era, and cluster 4 analyses how crisis communication strategies contribute to reduce tourists’ risk perception and boosting travel intention. Finally, a future research agenda is proposed, based on the emerging themes from this study.

To the best of the authors’ knowledge, this is the first bibliometric study to analyse crisis communication for destinations’ image (pre-crisis, crisis and post-crisis). This study, which covers the most recent academic literature in this field, provides insights of communication strategies from recent crises and disasters within the “research fronts”. Besides, a research agenda useful for future scholar investigation is proposed with its emerging themes. These rising topics and learnings from past events could be used by destination marketing organisations in crisis communication for destination image recovery in the current post-pandemic scenario or in upcoming crises or disasters.

本研究提供了目的地形象危机沟通的概述、最先进的“研究前沿”、新兴的研究主题以及研究议程。

本文进行了书目耦合研究, 辅以 H-经典分类和对文献计量方法提供的四个集群中包含的文章的主题分析 (论文日期为 2017–2021 年间)。

根据文献计量分析, 确定了四个主题集群。 其中两个集群提供“研究前沿”, 这是科学领域的最新主题：集群 一 解决与游客安全相关的沟通, 集群 二 加强利益相关者合作的作用, 以在危机沟通中创造目的地恢复力。 其他两个集群突出了未来调查的新兴主题：集群 三 侧重于后危机时代的复苏营销传播策略, 集群 四分析危机传播策略如何有助于降低游客的风险感知和提高旅行意愿。最后, 本文提出了基于新兴主题的未来研究议程。

据我们所知, 这是第一个分析了目的地形象的危机传播（危机前、危机和危机后）的, 独特的文献计量研究。该研究涵盖了该领域最新的学术文献, 通过其“研究前沿”提供了有关近期危机和灾难的沟通策略的见解。此外, 本文还提出了具有新兴主题的研究议程。这些新兴话题以及从过去事件中吸取的教训, 可以被目的地营销组织 (DMO) 用来进行灾难沟通, 以便在当前的大流行后情景或未来的危机或灾难中恢复目的地的形象。

Este estudio proporciona una perspectiva general, los “research fronts”- los temas más actuales de una disciplina científica-, los temas emergentes y una agenda de investigación sobre comunicación de crisis de la imagen de los destinos turísticos.

La investigación está basada en un análisis bibliográfico coupling, complementado con una clasificación h-Classics y un análisis temático de todos los artículos examinados con esta metodología bibliométrica (artículos fechados entre 2017 y 2021, ambos años incluidos).

Con este análisis bibliométrico, se identifican cuatro clusters temáticos. Dos de ellos, presentan los “research fronts”, los temas más vigentes de un campo científico: el cluster 1 se refiere a la comunicación realizada para transmitir el concepto de seguridad a los turistas, y el cluster 2 destaca la relevancia de la colaboración de todos los agentes turísticos para crear resiliencia en los destinos en la comunicación de crisis. Los otros dos clusters recogen los temas emergentes de investigación futura: el cluster 3 se centra en las estrategias de marketing para la época de postcrisis y el cluster 4 analiza cómo la comunicación contribuye a reducir la percepción de riesgo de los turistas y, por tanto, a potenciar su intención de viaje. Por último, el artículo propone una agenda de investigación basada en estos temas emergentes.

Hasta donde tenemos conocimiento, éste es el primer estudio bibliométrico especialmente enfocado a la comunicación de crisis para la imagen de los destinos turísticos (con sus tres etapas, precrisis, crisis y poscrisis). Esta investigación, que analiza la literatura más reciente en este campo, proporciona conocimiento sobre la comunicación de las crisis y desastres más recientes, a través de sus “research fronts”. Asimismo, propone una agenda con nuevos temas que están surgiendo en esta disciplina, útil para futuras investigaciones académicas. Dichos temas, junto con los aprendizajes de incidentes pasados, pueden ser usados por las Organizaciones de Marketing de Destinos (DMO, en sus siglas en inglés) para incorporarlos en su comunicación de crisis destinada a la recuperación de la imagen de los destinos turísticos en el actual escenario post pandemia o en futuras crisis o desastres.

This work conducts a comprehensive analysis of how to incorporate resilience and sustainability into capacity expansion strategies for business-to-business (B2B) chemical supply chains. This study aims to guide both researchers and managers on ensuring profitability in B2B chemical supply chains while minimizing environmental impacts, complying with regulations and mitigating disruptions and risks.

A systematic literature review is conducted to analyze the interplay between sustainability and resilience in chemical B2B supply chains, specify the quantitative and qualitative methods used to tackle this challenge and identify the drivers and barriers concerning capacity expansion. In addition, a comprehensive conceptual framework is suggested to outline a compelling research agenda.

The findings emphasize the increasing importance of modeling and resolving decision-making challenges related to sustainable and resilient supply chains, particularly in capital-intensive chemical industries. Yet, there is no standardized strategy for addressing these challenges. The predominant solution methods are heuristic and metaheuristic, and the selection of performance metrics tends to be empirical and tailored to specific cases. The main barriers to achieving sustainability and resilience arise from resource limitations within the supply chain. Conversely, the key drivers of performance focus on enhancing efficiency, competitiveness, cost effectiveness and risk management.

This work offers practitioners a conceptual framework that synthesizes the knowledge and tackles the challenges of designing sustainable and resilient supply chains as well as managing their operations in the context of B2B chemical supply chains. Results provide a practical guide for navigating the complex interplay of sustainability, resilience and chemical supply chain expansion.

The key concepts and dimensions associated with capacity expansion planning for a resilient and sustainable chemical supply chain are identified through structured and comprehensive analyses of existing literature. A conceptual framework is proposed for delineating the intersections among sustainability, resilience and chemical supply chain expansions. This mapping endeavor aims to facilitate a future characterized by the deployment of a nexus of resilience and sustainability in chemical supply chains. To this end, a promising future research agenda is accordingly outlined.

To address the challenges encountered in disaster responses, optimize resource utilization, minimize environmental and social impact, and ensure transparency and accountability, it is essential to review humanitarian supply chains and incorporate sustainability considerations. Humanitarian organizations can enhance their ability to deliver timely and effective assistance to those in need by continuously improving supply chain practices. Consequently, this work explores the convergence of two fast-growing domains: sustainability and humanitarian supply chain management (HSCM).

The authors conducted a systematic literature review of peer-reviewed articles to identify the prominent research trends and themes from the two domains' interactions. The extant literature is represented under the theory, context, characteristics, and research method (TCCM) framework. The authors have utilized a stakeholder theory perspective to identify coordination and collaboration among the various stakeholders.

This study's review findings reveal five future research directions formulating this study's central themes: the role of environmental sustainability, coordination, and collaboration in building effective HSCs; the role of humanitarian aid for the responsive HSC; the influence of big data predictive analytics on the HSC performance; development and empirical validation of sustainable HSC performance framework; the role of HSC stakeholders in building effective and efficient HSCs.

There is no existing academic literature review available on sustainable HSCM. This review fills this void by fostering discussion about sustainable humanitarian supply chains where the authors notably propose the TCCM framework in the context of sustainable HSCM, followed by a stakeholder network.

This research proposes a novel risk assessment model to elucidate the risk propagation process of industrial safety accidents triggered by natural disasters (Natech), identifies key factors influencing urban carrying capacity and mitigates uncertainties and subjectivity due to data scarcity in Natech risk assessment.

Utilizing disaster chain theory and Bayesian network (BN), we describe the cascading effects of Natechs, identifying critical nodes of urban system failure. Then we propose an urban carrying capacity assessment method using the coefficient of variation and cloud BN, constructing an indicator system for infrastructure, population and environmental carrying capacity. The model determines interval values of assessment indicators and weights missing data nodes using the coefficient of variation and the cloud model. A case study using data from the Pearl River Delta region validates the model.

(1) Urban development in the Pearl River Delta relies heavily on population carrying capacity. (2) The region’s social development model struggles to cope with rapid industrial growth. (3) There is a significant disparity in carrying capacity among cities, with some trends contrary to urban development. (4) The Cloud BN outperforms the classical Takagi-Sugeno (T-S) gate fuzzy method in describing real-world fuzzy and random situations.

The present research proposes a novel framework for evaluating the urban carrying capacity of industrial areas in the face of Natechs. By developing a BN risk assessment model that integrates cloud models, the research addresses the issue of scarce objective data and reduces the subjectivity inherent in previous studies that heavily relied on expert opinions. The results demonstrate that the proposed method outperforms the classical fuzzy BNs.

This study aims to use geographical information on social media for public opinion risk identification during a crisis.

This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.

In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.

Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.