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This conversation highlights the need to rethink how we approach disaster risk reduction in different South Asian contexts.

This paper is based on the webinar held as part of Asia Week at the University of Copenhagen which was organised by Asian Dynamics Initiative and Copenhagen Centre for Disaster Research on the September 12, 2023.

The prominent themes emerging from this conversation represents hybridity, self-rule and self-recovery. Along with this we suggest a fundamental turn to ensuring hope, solidarity and empathy is part of a post-colonial future.

The conversation contributes to the ongoing discussions on moving away from colonial practices in disaster risk reduction and disaster studies broadly.

The impact of COVID-19 on tourism destinations has been severe, but a future crisis is never far away. How communities can better prepare for disasters to come in the near future continues to be researched. This research aims to understand the tourism community’s responses to the COVID-19 pandemic and present the Tourism Community Resilience Model as a useful instrument to help communities better respond to disasters in the future.

This research uses a qualitative research approach which seeks to understand phenomena, events, social activities, attitudes, beliefs, perceptions and individual and group opinions that are dynamic in character in accordance with the situation in the field. Research primary data is in the form of Kuta Traditional Village local community responses in enduring the COVID-19 pandemic conducted between January and May 2022. These data were obtained through in-depth observations and interviews involving informants based on purposive sampling, including traditional community leaders, village officials, tourism actors (i.e. street vendors, tourist local guides, taxi drivers and art workers) and tourism community members. We selected the informants who are not only directly impacted by the pandemic, but also some of them have to survive during the pandemic because they do not have other job options. The results of previous research and government data concerning the pandemic and community resilience were needed as secondary data, which were obtained through a study of the literature. The data which had been obtained were further analysed based on the Interpretative Phenomenological Analysis (IPA) technique, which seeks to make meaning of something from the participants’ perspective and the researchers’ perspective as a result there occurs a cognition of a central position.

Based on findings from Bali, Indonesia, this resilience model for the tourism community was created in response to the difficulties and fortitude shown by the community during the COVID-19 pandemic. It comprises four key elements, namely the Local Wisdom Foundation, Resource Management, Government Contributions and External Community Support. These elements are all rooted in the concepts of niskala (spirituality) and sekala (real response); it is these elements that give the tourism community in the Kuta Traditional Village a unique approach, which can inspire other tourism destinations in other countries around the world.

A tourism community resilience model based on local community responses has implications for the process of enriching academic research and community management practices in facing future crisis, particularly by involving local wisdom foundation.

A tourism community resilience model based on local community responses has implications for the process of enriching academic research and community management practices in facing future crisis, particularly by involving local wisdom foundation.

The existence of the resilience model strengthens local community social cohesion, which has been made stronger by the bonds of culture and shared faith in facing disaster. This social cohesion then stimulates the strength of sustainable and long-term community collaboration in the post-pandemic period. For tourism businesses, having strong connections with the local communities is an important condition to thrive.

The value of this research is the Tourism Resilience Community Model, which is a helpful tool to optimise and improve future strategies for dealing with disasters. Illustrated by this Balinese example, this paper emphasises the importance of adding social factors such as niskala and sekala to existing community resilience models. Addressing these local characteristics is the innovative aspect of this paper and will help inspire communities around the world to prepare for future disasters better and build more sustainable and resilient tourism destinations elsewhere.

This chapter analyzes the link between the digital divide, infrastructure regulation, and disaster planning and relief through a case study of the flood in San Jose, California triggered by the Anderson dam’s overtopping in February 2017 and an examination of communication failures during the 2018 wildfire in Paradise, California. This chapter theorizes that regulatory decisions construct social and disaster vulnerability. Rooted in the Whole Community approach to disaster planning and relief espoused by the United Nations and the Federal Emergency Management Agency, this chapter calls for leadership to end the digital divide. It highlights the imperative of understanding community information needs and argues for linking strategies to close the digital divide with infrastructure and emergency planning. As the Internet’s integration into society increases, the digital divide diminishes access to societal resources including disaster aid, and exacerbates wildfire, flood, pandemic, and other risks. To mitigate climate change, climate-induced disaster, protect access to social services and the economy, and safeguard democracy, it argues for digital inclusion strategies as a centerpiece of community-centered infrastructure regulation and disaster relief.

The paper aims to assess the impact of weather-induced shocks on household food consumption in the rural Vietnamese Mekong Delta (VMD) through the case of Long An province and evaluate the effectiveness of widely used coping strategies in mitigating weather-related shock impacts.

The system generalized method of moments (GMM) estimation method is applied to explore information on shock incidence, recovery, and time occurrences. The paper uses a sample of 272 repeated farming households from 5-wave survey data from 2008 to 2016, resulting in 1,360 observations.

The paper confirms the robust negative effect of a natural shock on food consumption. Additionally, using savings proves to be the most potent measure to smooth food consumption. Other favorable coping strategies are “getting assistance from relatives, friends” or “getting assistance from the Government, and non-government organizations (NGOs).” The mitigating effects are also traced in the current analysis.

Using caution when generalizing the results from Long An to the whole VMD is reasonable. The rather limited observations of coping strategies do not allow the authors to analyze any specific strategy.

The proposed approach employs the GMM technique and controls for endogenous coping strategies and thus provides accurate estimates of the effects of weather-related shocks and the mitigation effectiveness in the rural VMD.

The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on flight range. In HTDRP-DC, trucks can select and transport various drones to LDs to reduce deprivation time. This study estimates the nonlinear deprivation cost function using a linear two-piece-wise function, leading to MILP formulations. A heuristic-based Benders Decomposition approach is implemented to address medium and large instances. Valid inequalities and a heuristic method enhance convergence boundaries, ensuring an efficient solution methodology.

Research has yet to address critical factors in disaster logistics: minimizing the social and economic costs simultaneously and using drones in relief distribution; deprivation as a social cost measures the human suffering from a shortage of relief supplies. The proposed hybrid truck-drone routing problem minimizing deprivation cost (HTDRP-DC) involves distributing relief supplies to dispersed demand nodes with undamaged (LDs) or damaged (DNs) access roads, utilizing multiple trucks and diverse drones. A Benders Decomposition approach is enhanced by accelerating techniques.

Incorporating deprivation and economic costs results in selecting optimal routes, effectively reducing the time required to assist affected areas. Additionally, employing various drone types and their reuse in damaged nodes reduces deprivation time and associated deprivation costs. The study employs valid inequalities and the heuristic method to solve the master problem, substantially reducing computational time and iterations compared to GAMS and classical Benders Decomposition Algorithm. The proposed heuristic-based Benders Decomposition approach is applied to a disaster in Tehran, demonstrating efficient solutions for the HTDRP-DC regarding computational time and convergence rate.

Current research introduces an HTDRP-DC problem that addresses minimizing deprivation costs considering the vehicle’s arrival time as the deprivation time, offering a unique solution to optimize route selection in relief distribution. Furthermore, integrating heuristic methods and valid inequalities into the Benders Decomposition approach enhances its effectiveness in solving complex routing challenges in disaster scenarios.

As one of its major strategies, China has made a new plan to further expand High Standard Farmland (HSF) to all permanent basic farmland (80% of total farmland) for grain security over the next decade. Yet, what will be the impact of farmland infrastructure investment on agrifood systems? The paper aims to systematically evaluate the multiple effects (food security, economy, nutrition and environment) of expanding HSF construction under the context of the “Big Food vision” using an interdisciplinary model.

An interdisciplinary model – AgriFood Systems Model, which links the China CGE model to diet and carbon emission modules, is applied to assess the multiple effects of HSF construction on agrifood systems, such as food security and economic development, residents’ diet quality and carbon emissions. Several policy scenarios are designed to capture these effects of the past HSF investment based on counterfactual analysis and compare the effects of HSF future investment at the national level under the conditions of different land use policies – restricting to grain crops or allowing diversification (like vegetables, and fruit).

The investments in HSF offer a promising solution for addressing the challenges of food and nutrition security, economic development and environmental sustainability. Without HSF construction, grain production and self-sufficiency would decline significantly, while the agricultural and agrifood systems’ GDP would decrease. The future investment in the HSF construction will further increase both grain production and GDP, improve dietary quality and reduce carbon emissions. Compared with the policy of limiting HSF to planting grains, diversified planting can provide a more profitable economic return, improve dietary quality and reduce carbon emissions.

This study contributes to better informing the impact of land infrastructure expanding investment on the agrifood systems from multiple dimensions based on an interdisciplinary model. We suggest that the government consider applying diversified planting in the future HSF investment to meet nutritional and health demands, increase household income and reduce carbon emissions.

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.

Home insurance is widely recognised as a tool for mitigating economic risk associated with natural disasters. This study aims to analyse the influence of homeowners’ home insurance knowledge (both objective and subjective types), perceived benefits (PB) and perceived vulnerability towards disaster loss (PVUL) on their intention to purchase (ITP).

This research makes use of survey data collected from 394 respondents (the homeowners) residing in various parts of India. The structural equation modelling is used to verify 11 hypotheses proposed in the study.

The findings indicate that both objective knowledge (OK) and subjective knowledge (SK) of home insurance have significant influence on homeowners’ benefit perception and PVUL. The homeowners’ PB of home insurance negatively affect PVUL. The OK of home insurance has a stronger influence on homeowners’ ITP home insurance than SK while the homeowners benefit perceptions and PVUL significantly affects homeowners’ ITP home insurance. These findings confirms that if homeowners are knowledgeable about home insurance, they perceive the plans as more beneficial and feel less vulnerable about catastrophic events, resulting in positive intentions towards purchasing them.

To the best of the authors’ knowledge, this is the first comprehensive research that assesses the Indian homeowners’ knowledge, PB and PVUL in influencing their ITP home insurance. The finding of this paper will assist both public and private insurance companies in India and similar markets in designing and implementing effective strategies to sell home insurance policies.

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.