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This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic focus in the Indian Ocean, particularly on the Bay of Bengal region.

Present research assimilates the secondary non-classified data on the Tsunami warning system installed in the Indian Ocean. Qualitative review and exploratory research methodology have been followed to provide a holistic profile of the Tsunami rarly warning system (TEWS) and its role in coastal resilience.

The study finds the need for strategic focus to expand and interlink regional early warning cooperation mechanisms and partnerships to enhance capacities through cooperation and international assistance and mobilize resources necessary to maintain the TEWS in the Indian Ocean region. The enhanced capacity of the TEWS certainly improves the resilience of Indian Ocean coastal communities and infrastructures.

The study is original research and useful for policy planning and regional cooperation on data interlinkages for effective TEWS in the Indian Ocean region.

Each stage in disaster management faces different challenges concerning information gathering, sharing, interpretation and dissemination. However, a comprehensive understanding of different information and communication technology (ICT) systems utilised for humanitarian disaster management is limited. Therefore, the paper follows a systems thinking approach to examine ten major man-made and/or natural disasters to comprehend the influence of ICT systems on humanitarian relief operations.

A longitudinal, multi-case study captures the use of ICT tools, stakeholders involvement, disaster stages and zones of operations for relief operations over the past two decades. A systems thinking approach is utilised to draw several inferences and develop frameworks.

Multiple ICT tools such as geographic information systems, online webpages/search engines, social media, unmanned aerial vehicles/robots and artificial intelligence are used for rapid disaster response and mitigation. Speed and coordination of relief operations have significantly increased in recent years due to the increased use of ICT systems.

Secondary data on the past ten disasters is utilised to draw inferences. The developed ICT-driven model must be validated during upcoming humanitarian relief operations.

A holistic understanding of a complex inter-relationship between influential variables (stakeholders, disaster stages, zones of operation, ICT systems) is beneficial for effectively managing humanitarian disasters.

Broadly classifying the ICT systems into surveillance, decision support and broadcasting systems, a novel ICT-enabled model for humanitarian relief operations is developed.

The purpose of this study is to provide the location of natural disasters that are poured into maps by extracting Twitter data. The Twitter text is extracted by using named entity recognition (NER) with six classes hierarchy location in Indonesia. Moreover, the tweet then is classified into eight classes of natural disasters using the support vector machine (SVM). Overall, the system is able to classify tweet and mapping the position of the content tweet.

This research builds a model to map the geolocation of tweet data using NER. This research uses six classes of NER which is based on region Indonesia. This data is then classified into eight classes of natural disasters using the SVM.

Experiment results demonstrate that the proposed NER with six special classes based on the regional level in Indonesia is able to map the location of the disaster based on data Twitter. The results also show good performance in geocoding such as match rate, match score and match type. Moreover, with SVM, this study can also classify tweet into eight classes of types of natural disasters specifically for the Indonesian region, which originate from the tweets collected.

This study implements in Indonesia region.

(a)NER with six classes is used to create a location classification model with StanfordNER and ArcGIS tools. The use of six location classes is based on the Indonesia regional which has the large area. Hence, it has many levels in its regional location, such as province, district/city, sub-district, village, road and place names. (b) SVM is used to classify natural disasters. Classification of types of natural disasters is divided into eight: floods, earthquakes, landslides, tsunamis, hurricanes, forest fires, droughts and volcanic eruptions.

This study aims to explore the perception among the tourism stakeholders about Halal tourism competitiveness, challenges and opportunities in Aceh, a Sharia-law tourism destination.

This study adopted the qualitative research method and used in-depth interviews with purposively selected 13 Halal tourism stakeholders in Aceh.

This study found that the Indonesian Government has aggressively promoted Aceh as one of its main Halal tourist destinations. Despite its popularity in the growing and lucrative Muslim market, the understanding of Halal tourism in Aceh among its stakeholders is still at its infancy level. Besides, although Aceh is a Muslim-majority region, its Halal facilities and services, especially the Halal certification for their foodservice industry, are still lacking compared to their neighbouring competitors.

This study confirms the scarcity of stakeholder understanding and support challenged and undermined Aceh’s Halal tourism competitiveness. As such, this study sheds light on the original insight that stakeholders’ limited comprehension and backing can hinder Aceh’s Halal tourism competitiveness.

This study aims to clarify the following research questions: to what extent do people consider natural disaster risks as important for residential selection? what personal demographics and attitudes toward natural disaster risks are associated with the relative importance of natural disasters for residential selection? and to what extent do the associated personal attributes influence the relative importance of natural disasters for residential selection?

An internet-based survey was performed to collect 2,000 responses from residents of Osaka Prefecture, Japan, to gauge people’s relative importance of safety against natural disasters regarding residential preference. The obtained results were analysed using two types of statistical analysis, specifically chi-square test and multivariable logistic regression analyses.

It was found that 37.3% of the respondents in Osaka Prefecture, Japan, considered the “safety against natural disasters” relatively important when selecting a residential location. The statistical analysis also demonstrated that those having a relatively higher level of disaster awareness and preparedness were 1.41 times more likely to prefer to live in a place that is safer from natural disasters. Thus, it was suggested that disaster education aimed at raising the level of people’s disaster awareness could be effective to increase the number of people who choose to live in a safer place from natural disasters.

Living in an area that is safer from natural disasters can effectively minimize human and property damage. Recently, several measures have been taken in Japan to guide people to live in a safer place. The clarification of the extent to which people consider natural disaster risks as important for residential selection and the understanding of the categories of the people who are likely to do so is important to develop more effective natural disaster measures; however, there has been less attention on such investigation. Therefore, this study conducted an internet-based survey and examined it.

This research aims to specialise in the investigation of risk management for service-oriented manufacturing supply chains via two stages, highlighting its differences from manufacturing. The research article is commenced by executing an encyclopedic review of earlier research to ascertain the distinctive traits of service-oriented manufacturing supply chains and identify prevalent risks. Secondly, an empirical study in the construction field, amongst the industry hardest struck in the mist of the COVID-19 epidemic, is conducted to thoroughly inspect the resonant effect of these risks on service-oriented manufacturing supply chain performance.

In this study, to validate the resonant effect mechanism, a thorough assessment is undertaken by juxtaposing theoretical model to a newly constructed comparative model that encompasses the single effects of risks on supply chain performance.

63% variance of service-oriented manufacturing supply chain performance was showcased by the resonant effect model, compared with 46.3% in the comparative model. Moreover, each risk exerts a more glaringly significant impact on supply chain performance, asserting the mechanism of the resonant influence. Another noteworthy result involves the demand risk possessing a low effect on supply chain performance, thus emphasising the superiority of service-oriented manufacturing supply chains.

Future research endeavours should hinge on the optimal “resonant” model explosion, thereby foreseeing and alleviating worst-case scenarios to guarantee the robustness and resilience of supply chain networks.

Indubitably, reducing the intensity of the resonant effect revolves around lowering the coefficient of “a,” thereby restricting/eliminating the link among risks. Therefore, the suggested resonant impact model might thus serve as “a road map”. In light of the aforementioned considerations, it is advisable that supply chain executives employ supply chain management tactics namely avoidance, prediction, and postponement, but only after meticulous consideration the costs and benefits of adopting such strategies.

The service-oriented manufacturing supply chain features and advantages have been analysed and explained throughout the article. The data gathered during the COVID-19 pandemic is a captivating and topical point of this paper.

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.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

The purpose is to derive the most effective place in the air for an aerial robot, viz., drone to use as an alternative communication system during disasters.

In this technology-driven era, various concepts are becoming the area of interest for multiple researchers. Drone technology is also one of them. The researchers, with interest in drones, are therefore trying to understand the various uses of employing drones in diverse applications which are mind-boggling, starting from civil applications (viz., an inspection of power lines, counting wildlife, delivering medical supplies to inaccessible regions, forest fire detection, and landslide measurement) to military applications (viz., real-time monitoring, surveillance, patrolling, and demining). However, one area where its usage is still to be exploited in many countries is using drones as a relay when communication lines are disrupted due to natural calamities. This will be particularly helpful in rescuing the affected people as the aerial node will enable them to communicate to the rescue team using mobiles/ordinary landline telephones even when regular communication towers are destroyed due to disastrous natural calamities, for example, tsunamis, earthquakes, and floods. Various algorithms, namely, water filling algorithm, advanced water filling algorithm, equal power distribution algorithm, and particle swarm optimization, were therefore studied and analyzed using simulation in addition to various path loss models to realize the desired place for an aerial robot, viz., drone in the air, which will eventually be used as an alternative communication system for badly hit ground users due to any disaster.

It was found that the effective combination of the water filling algorithm and particle swarm optimization algorithm may be done to place the drone in the air to increase the overall throughput of the affected ground users.

The research is original. None of the parts of this research paper has been published anywhere.