The effects of natural disasters on international tourism: A global analysis

A threat to the natural World Heritage site rarely happens alone

This study contributes an empirical investigation of the likelihood that different external threats to a UNESCO Natural World Heritage Site occur in combination with each other when site characteristics and location are controlled for. For the purpose of the analysis, the World Heritage database and the UNESCO State of Conservation Reports are used and the nine most frequently appearing external threats are identified. These databases include 6852 site-year observations and 3316 threats over the period 1979-2023. The most commonly identified external threats are illegal activities, with eleven percent of all observations and mining with six percent. Transport infrastructure, tourism and visitor pressure are also common threats. Estimation results based on the multivariate Probit (equation system) model demonstrate that there are strong positive correlations between many pairs of the nine external threats. Most apparent are the links between illegal activities and loss of identity, social cohesion, changes in local population and community, water infrastructure (dams) and farming, as well as illegal activities and land conversion. There are also clear links between tourism and infrastructure. This emphasises that the various threats seldom appear in isolation from each other. Results also highlight that the threats have different drivers. Among the determinants, site characteristics and location are the most important ones. The likelihood of threats is highest for Natural Heritage Sites covered by forests or those in marine and coastal areas, Africa as well as the Arab region. It is also possible to identify a general increase in threats over time, although with a diminishing rate of growth towards the period 2015-2019. Contrary to this development and the general downturn in threats during the Covid-19 pandemic period of 2020-2023, pressure from tourism continues to grow. Methodologically, the results emphasize the need for multivariate Probit models when research goes beyond analyses of descriptive statistics and single equation approaches.

Non-linear impacts of harmful algae blooms on the coastal tourism economy

Harmful algae blooms (HABs) occur in water bodies throughout the globe and can have multi-faceted impacts on tourism. However, little is known of the magnitude of economic losses to the tourism sector as a result of HABs. There is limited understanding of the empirical relationships between HAB intensity and duration, and the effects of this phenomenon on the tourism sector. This study is based in the state of Florida, USA, a notable sun, sand, and sea destination in the western hemisphere, where blooms of a marine harmful algae are a recurrent threat to coastal tourism. The empirical framework is based on a month and county-level panel database that combines sales by tourism-related businesses with observations from the official HAB surveillance system of the state of Florida. We use time and space fixed-effects regressions to estimate the loss in tourism revenue associated with one additional day of red tide. Results indicate that impacts of HABs on tourism do not follow a linear pattern with increasing HAB concentrations, but rather appear to follow an inverted-U pattern. In other words, higher concentrations of the HAB organism do not necessarily imply higher economic losses, suggesting that the impacts of HABs on tourism are not driven solely by the biophysical element of cell density. Rather, these impacts appear to be mediated and amplified by human dimensions. The loss to tourism-related businesses due to the 2018 Florida red tide bloom was estimated to be $2.7 billion USD, which implies that HABs and their impact on tourism can be considered as a potential 'billion-dollar' disaster.

Public Health and Health System's Responsiveness During the 2022 Floods in Pakistan: What Needs to Be Done?

OBJECTIVE

In 2022, Pakistan witnessed unprecedented flooding, submerging one-third of the country under-water, ruining millions of houses, taking lives, afflicted injuries, and displacing scores of people. Our study documents not only the public health problems that have arisen due to this natural calamity but also the state of health systems' response.

METHODS

We conducted a qualitative study asking key questions around prevalent health problems, health-care seeking, government's response, resource mobilization, and roadmap for the future. We purposively selected 16 key frontline health workers for in-depth interviews.

RESULTS

Waterborne and infectious diseases were rampant posing huge public health challenges. Disaster mitigation efforts and relief operations were delayed and not at scale to cover the entire affected population. Moreover, a weak economy, poverty, and insufficient livelihoods compounded the tribulations of floods. Issues of leadership and governance at state level resulted in disorganized efforts and response.

CONCLUSIONS

Pakistan is famous for its philanthropy; however, lack of transparency and accountability, the actual benefits seldom reach the beneficiaries. Such climatic disasters necessitate a more holistic approach and a greater responsiveness of the health system. In addition to health services, the state must respond to financial, social, and infrastructural needs of the people suffering from the calamity.

Mineral solubilizing microorganisms and their combination with plants enhance slope stability by regulating soil aggregate structure

Introduction

The stability of exposed slopes is prone to natural disasters, seriously threatening socio-economic and human security. Through years of exploration and research, we proposed an active permanent greening (APG) method based on patented mineral solubilizing microorganisms (MSMs) as an improvement over the traditional greening method.

Methods

In this study, we selected two MSMs (Bacillus thuringiensis and Gongronella butleri) and a plant species (Lolium perenne L.) set up six treatments (T1, T2, T3, T4, T5, and T6) to investigate the effectiveness of the MSMs and their combinations with the plant species on the soil stability using APG method.

Results

We noted that both MSMs and the plant species significantly improved soil aggregate stability and organic matter content. Of all the treatments, the T1 treatment exhibited better results, with soil aggregate stability and organic matter content increased to 45.63% and 137.57%, respectively, compared to the control. Soil stability was significant positively correlated with macroaggregate content and negatively with microaggregates. Using structural equation modeling analysis, we further evaluated the mechanism underpinning the influence of organic matter content and fractions on the content of each graded agglomerates. The analysis showed that the macroaggregate content was influenced by the presence of the plant species, primarily realized by altering the content of organic matter and aromatic and amide compounds in the agglomerates, whereas the microaggregate content was influenced by the addition of MSMs, primarily realized by the content of organic matter and polysaccharide compounds. Overall, we observed that the effect of the co-action of MSMs and the plant species was significantly better than that of using MSMs or the plant species alone.

Discussion

The findings of this study provide reliable data and theoretical support for the development and practical application of the APG method to gradually develop and improve the new greening approach.

Exploring the motivations for rural tourism in China during the COVID-19: The existence of a single motivation

The COVID-19 epidemic had an appropriate impact on tourists' trip psychology and their subsequent behavior in participating in rural tourism activities. The purpose of this paper is to explore the types of motivations Chinese tourists have for participating in rural tourism in the context of COVID-19, and to comparatively analyze the similarities and differences in motivations for rural tourism during the epidemic and in normal times. An interpretive paradigm qualitative data collection method was used: semi-structured interviews and focus group discussions. Respondents were 21 tourists, who were selected through purposive and snowball sampling. Through content analysis, we found that rural tourism motivations during the epidemic included both diversified and singular motivations. The pull effect of rural destinations is related to distance and ease of realization. For rural areas in close proximity, a single motivation is sufficient to drive tourists. In addition, we found that there was no "altruistic motivation" for rural tourism during the COVID-19 period, but "altruistic feelings" for the preservation of ancient villages were generated during rural tourism. Finally, we discuss the theoretical and practical significance of this study and make suggestions for future research. The study explains tourists' companionship preferences, activity choices, and affective changes, and provides a basis for the operation and advertising strategies of rural destinations to attract tourists and promote their sustainable development.

Improving disaster management in international tourism

Despite strong interest in tourism during the pandemic, frameworks of disaster management have not been rigorously provided for the international tourism field. The present research aimed to study how to improve disaster management in international tourism toward mitigating human suffering and economic damages. Qualitative content analysis was used as the key methodology in investigating passive and active disaster management. These two approaches were compared considering tourists, tourism industry, regional governments, and international organizations as variables. The main finding has been that stakeholders must shift from passive to active disaster management, while strategically addressing networking, the disaster management cycle, and local education, among other factors. This study provided a systematic framework of disaster management by studying not only the supply but also the demand side in international tourism.

Human Detection and Action Recognition for Search and Rescue in Disasters Using YOLOv3 Algorithm

Drone examination has been overall quickly embraced by NDMM (natural disaster mitigation and management) division to survey the state of impacted regions. Manual video analysis by human observers takes time and is subject to mistakes. The human identification examination of pictures caught by drones will give a practical method for saving lives who are being trapped under debris during quakes or in floods and so on. Drone investigation for research and security and search and rescue (SAR) should involve the drone to filter the impacted area using a camera and a model of unmanned area vehicles (UAVs) to identify specific locations where assistance is required. The existing methods (Balmukund et al. 2020) used were faster-region based convolutional neural networks (F-RCNNs), single shot detector (SSD), and region-based fully convolutional network (R-FCN) for the detection of human and recognition of action. Some of the existing methods used 700 images with six classes only, whereas the proposed model uses 1996 images with eight classes. The proposed model is used YOLOv3 (you only look once) algorithm for the detection and recognition of actions. In this study, we provide the fundamental ideas underlying an object detection model. To find the most effective model for human recognition and detection, we trained the YOLOv3 algorithm on the image dataset and evaluated its performance. We compared the outcomes with the existing algorithms like F-RCNN, SSD, and R-FCN. The accuracies of F-RCNN, SSD, R-FCN (existing algorithms), and YOLOv3 (proposed algorithm) are 53%, 73%, 93%, and 94.9%, respectively. Among these algorithms, the YOLOv3 algorithm gives the highest accuracy of 94.9%. The proposed work shows that existing models are inadequate for critical applications like search and rescue, which convinces us to propose a model raised by a pyramidal component extracting SSD in human localization and action recognition. The suggested model is 94.9% accurate when applied to the proposed dataset, which is an important contribution. Likewise, the suggested model succeeds in helping time for expectation in examination with the cutting-edge identification models with existing strategies. The average time taken by our proposed technique to distinguish a picture is 0.40 milisec which is a lot better than the existing method. The proposed model can likewise distinguish video and can be utilized for real-time recognition. The SSD model can likewise use to anticipate messages if present in the picture.

Characterizing Cold Days and Spells and Their Relationship with Cold-Related Mortality in Bangladesh

This research examined the characteristics of cold days and spells in Bangladesh using long-term averages (1971-2000) of maximum (T_max) and minimum temperatures (T_min) and their standard deviations (SD). Cold days and spells were calculated and their rate of change during the winter months (December-February) of 2000-2021 was quantified. In this research, a cold day was defined as when the daily maximum or minimum temperature is ≤-1.5 the standard deviations of the long-term daily average of maximum or minimum temperature and the daily average air temperature was equal to or below 17 °C. The results showed that the cold days were more in the west-northwestern regions and far less in the southern and southeastern regions. A gradual decrease in cold days and spells was found from the north and northwest towards the south and southeast. The highest number of cold spells (3.05 spells/year) was experienced in the northwest Rajshahi division and the lowest (1.70 spells/year) in the northeast Sylhet division. In general, the number of cold spells was found to be much higher in January than in the other two winter months. In the case of cold spell severity, Rangpur and Rajshahi divisions in the northwest experienced the highest number of extreme cold spells against the highest number of mild cold spells in the Barishal and Chattogram divisions in the south and southeast. While nine (out of twenty-nine) weather stations in the country showed significant trends in cold days in December, it was not significant on the seasonal scale. Adapting the proposed method would be useful in calculating cold days and spells to facilitate regional-focused mitigation and adaptation to minimize cold-related deaths.

Do natural disasters affect economic growth? The role of human capital, foreign direct investment, and infrastructure dynamics

Natural disasters do occur and have become a global problem due to increasing intensity. Developing countries are mostly affected due to natural disasters owing to a poor environment, feeble adaptation, impoverished socioeconomic conditions, poor infrastructure, limited resources, and unstable institutions. The SDG 11.5 target which highlights the mitigation of loss due to natural disasters--remains crucial to achieving sustainable cities and human settlements--but the literature is limited on this scope. Thus, this research contributes to the literature by incorporating an infrastructure index, foreign direct investment (FDI), human capital index, globalization, and capital formation into the disaster-growth debate across four-income groups in 98 countries from 1995 to 2019. We developed infrastructure and human capital indices using a standard procedure across all income groups. The two-step generalized method of moments employed herein confirmed the income reduction effect of natural disasters. While the economic cost of natural disasters is relatively high in low-income countries and mild in high- and upper-middle-income countries. Besides, infrastructural development, FDI, human capital, globalization, and gross fixed capital formation also affect economic growth across income groups. Thus, the enhancement of socio-economic policies could decline economic losses, especially in vulnerable and poor settlements in developing countries.

Construction, Evaluation, and Optimization of a Regional Ecological Security Pattern Based on MSPA-Circuit Theory Approach

Ecological security is crucial for regional sustainable development; however, as modern urbanization highlights ecological security challenges, major challenges have arisen. In this paper, we take the ecological region around Taihu Lake, China, as a typical research site, extract important ecological sources and key nodes using morphological spatial pattern analysis (MSPA) and circuit theory, and propose a regulatory framework for the ecological security pattern (ESP) of the ecological region based on the spatial characteristics of sources, corridors, and nodes. We obtained the following results: (1) The ESP includes 20 ecological sources, 37 ecological corridors, 36 critical ecological protection nodes, and 24 key ecological restoration nodes. (2) Most ecological sources are large and concentrated in western Zhejiang and west of Taihu Lake, which are both important ecological sources and ecological resistance surfaces. (3) The ecological corridors spread east, west, and south from Taihu Lake, with high network connectivity. (4) Shanghai serves as the central node, with the Su-Xi-Chang town cluster and the Qiantang River town cluster serving as the extension axes for the ecological resistance hot-spot area. The center of the elliptical ecological resistance surface (standard deviation) lies in Suzhou City, located on the east shore of Taihu Lake. (5) Ecological nodes were mostly located in ecological corridors or junctions. A "four zones and one belt" pattern is suggested in order to make the land around Taihu Lake more connected and stable ecologically. This study can be used as a guide for building and improving an ecological safety network.

Economic impacts of COVID-19 on inbound and domestic tourism☆

COVID-19 has led to an unprecedented disruption in tourism spending. This has propagated through the whole economy, however the scale of these system-wide consequences can be hard to quantify. We calculate direct reductions in spending across domestic and inbound tourism categories and then use a computable general equilibrium model to quantify their economic impacts. The results – illustrated using a model for Scotland and focusing on 2021 - demonstrate the scale of the losses in the tourism industry and the economy as a whole that are attributable to changes in both domestic and inbound tourism demand. We find that the extent to which domestic tourism demand can mitigate the losses in inbound spending depends on the composition of demand.

Drought-heatwave nexus in Brazil and related impacts on health and fires: A comprehensive review

Climate change is drastically altering the frequency, duration, and severity of compound drought-heatwave (CDHW) episodes, which present a new challenge in environmental and socioeconomic sectors. These threats are of particular importance in low-income regions with growing populations, fragile infrastructure, and threatened ecosystems. This review synthesizes emerging progress in the understanding of CDHW patterns in Brazil while providing insights about the impacts on fire occurrence and public health. Evidence is mounting that heatwaves are becoming increasingly linked with droughts in northeastern and southeastern Brazil, the Amazonia, and the Pantanal. In those regions, recent studies have begun to build a better understanding of the physical mechanisms behind CDHW events, such as the soil moisture-atmosphere coupling, promoted by exceptional atmospheric blocking conditions. Results hint at a synergy between CDHW events and high fire activity in the country over the last decades, with the most recent example being the catastrophic 2020 fires in the Pantanal. Moreover, we show that HWs were responsible for increasing mortality and preterm births during record-breaking droughts in southeastern Brazil. This work paves the way for a more in-depth understanding on CDHW events and their impacts, which is crucial to enhance the adaptive capacity of different Brazilian sectors.

Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting

Even though both symmetric and asymmetric conceptions of news impacts are well-established in the disciplines of economics and financial markets, the effects of combining multiple news shocks on the volatility of tourism demand have not yet been delved into or gauged in any tourist destination. This work hypothesises and verifies that the news impact curve (NIC), conditional heteroscedastic volatility models, and multiple news shocks are suitable for forecasting the volatility of the Malaysian tourist industry. Among them, three primarily volatility models (GARCH, EGARCH, and GJRGARCH) are used in conjunction with five financial news shocks (FFNSs), namely the Kuala Lumpur Composite Index (KLCI), the United States Dollar Index (DXY), the stock performance of 500 large companies listed on stock exchanges (S&P500), Crude Oil (CO), and Gold Price (GP). Among the most significant findings of this study are the demonstration of monthly seasonality using conditional mean equations, asymmetry effects in EGARCH-FFNSs, and GJRGARCH-FFNSs models in conditional variance equations and 50 NICs, and the GARCH-FFNSs model’s evaluation of the persistence influence of news shocks on monthly visitor arrivals in Malaysia. The GJRGARCH-FFNSs model is the best model for Malaysian tourism demand volatility forecasting accuracy. Furthermore, KLCI and Gold Price have the most substantial impact on the number of tourists to Malaysia. In addition, it should be emphasised that the methodological framework utilised in this study can be a useful tool for creating and forecasting the performance of symmetry and asymmetry impacts on tourism demand volatility.

The Effect of Knowledge and Skills of Hospital Staff on the Hospitals’ Alertness and Security in Encountering Earthquake in Palu City, Central Sulawesi, Indonesia

INTRODUCTION: Indonesia is one country that particularly experiences disasters, especially natural disasters. AIM: The current research was carried out aiming to determine the effect of knowledge and skills of hospitals staff on the hospital alertness and security in encountering earthquake. METHODS: This study applied an analytical survey method involving 184 health workers from three major hospitals in Palu City, Indonesia. In this case, data were collected through interviews and questionnaires which were then analyzed using the t-test and f-test to determine the partial and simultaneous effect of the independent on the dependent variable. RESULTS: Based on the analysis of the data collected from 184 questionnaires involving voluntary, contracted, and civil servant health workers, it was revealed that the knowledge of health workers significantly affected the effectiveness of preparedness and security for hospitals in encountering multiple disasters in Palu City with p < 0.01 and T value of 3.467 > T table value 2.60326. Meanwhile, the health workers’ skills on the effectiveness of preparedness and security in hospitals facing multiple disasters in Palu City obtained p < 0.00 and a T value of 4.771 > T table value 2.60326. Meanwhile, the effect of knowledge and skills of health workers simultaneously and significantly affected the effectiveness of preparedness and security of the hospitals in encountering multiple disasters with an F value of 47.459 > F table value 3.89. CONCLUSION: The findings revealed in the current research provided useful basic information indicating the need for regular disaster-related education and training programs for emergency health workers so that they can effectively handle disaster situations and carry out their duties confidently and professionally. Such training and education are aimed to improving the health workers’ knowledge and skills so that they can be more alert and prepared when disaster occurs.

Indigenous Kinabatangan Perspectives on Climate Change Impacts and Adaptations: Factors Influencing Their Support and Participation

Indigenous perspectives on the effects of climate change are frequently elicited through surveys and interviews, and the responses are compared to meteorological data. However, there remains a limited approach to examining the underlying predictors that best determine Indigenous support for adaptation strategies. This study utilizes partial least squares-structural equation modeling (PLS-SEM) to identify the main indicators of Indigenous support for coping with unfavorable climate impacts. Using a case study and a purposive sampling approach, a survey of 328 Indigenous peoples was conducted in rural Kinabatangan, Sabah, Malaysia. Results showed that communities’ attitudes had a large effect on the Indigenous support for adaptation (f2 = 0.380), followed by the communities’ awarenesses (f2 = 0.063), rapid onset events (f2 = 0.051), and climate impacts on tourism (f2 = 0.016). Communities prioritize the impacts of climate change on their health, livelihoods, and environmental resources. Nevertheless, they do not draw a causal link between the effects and responses to climate hazards. Coping strategies such as the inclusion of Indigenous livelihoods, a bottom-up approach, and transparent communication are suggested to cultivate Indigenous support for climate change adaptation. Decision-makers can apply these findings to prepare climate change policies and enhance the adaptation strategies of Indigenous communities.

Development and Validation of Earthquake Fire Response Simulation Protocol for Korean College Students in Health Programs

The purpose of this study is to evaluate the adequacy of the developed protocol by verifying the validity of the expert group for the earthquake and fire response simulation protocol. A protocol development team consisting of one emergency rescue professor, one counseling psychology professor, three paramedics, and one firefighter developed the study's protocols to promote the core response and capabilities required at an earthquake fire site. We checked the content validity for the appropriateness of the contextual connection for each stage for the protocol. We also created an evaluation checklist to measure the items for each stage. The protocol developed in this study consists of earthquake response, fire response, evacuation, and fire suppression. We set the situation for each stage and composed learner activities and learning performance goals. The earthquake response stage included (1) shout "it's an earthquake," (2) protect yourself, (3) turn off electricity and gas, and (4) evacuate to a safe place. In the fire response stage, (1) shout "fire," (2) press the emergency bell and call 119, (3) close the door of a dangerous place where fire can spread, and (4) evacuate to a safe place. In the evacuation stage, (1) open the emergency exit, (2) cover your nose and mouth, (3) lower your posture, and (4) evacuate quickly in one direction. Lastly, in the firefighting stage, (1) pull out the safety pin, (2) hold the nozzle and face the fire, (3) grab the handle, and (4) spray the powder evenly. The protocol contributes to the development of systematic and elaborate simulation education materials in the future. Furthermore, it provides basic data for future disaster simulation operation and protocol development through continuous training and practical exercises.

How natural disasters affect carbon emissions: the global case

The outbreak of the COVID-19 pandemic has once again made the impacts of natural disasters a hot topic in academia. The environmental impacts of natural disasters, however, remain unsettled in the existing literature. This study aims to investigate the impact of natural disasters on CO₂ emissions. For this purpose, we employ a panel dataset covering 138 countries over the period 1990-2018 and two dynamic panel estimation methods. Then, considering the differences in CO₂ emissions across various countries, we run a panel quantile regression to examine the asymmetry in the nexus between natural disasters and CO₂ emissions. We also discuss the mediating effects of energy consumption between natural disasters and CO₂ emissions. After conducting a series of robustness checks, we confirm that our results are stable and convincing. The empirical results indicate that natural disasters significantly reduce CO₂ emissions. Nevertheless, the impact of natural disasters on CO₂ emissions is asymmetric across different quantiles of CO₂ emissions. Furthermore, the technology level serves as an important moderating factor between natural disasters and CO₂ emissions. The mediating effect results reveal that natural disasters not only directly reduce CO₂ emissions but also indirectly promote carbon reduction by restraining energy consumption. Finally, several policy implications are provided to reduce CO₂ emissions and the damage caused by natural disasters.

Were Culture and Heritage Important for the Resilience of Tourism in the COVID-19 Pandemic?

The unprecedented impact of the COVID-19 on the world tourism is clear and obvious. Still, modelling the impact on individual countries faces many problems from data availability to the multitude of underlying variables rather difficult to capture. This study used simple and multiple regression to research possible effects of the recent pandemic to the fall in the volume of tourism in 20 European countries, throughout the 20-month period. The results of this study were rather surprising showing that the relative fall in tourism cannot be explained only by incidence of COVID-19 by countries, while in multiple regression by adding the variables of distance of travel and composition of tourism by facilities coefficients of determination were very low. Adding variables of natural and cultural heritage as well as of cultural activities somewhat improved the baseline model with the best fitting variable of culture visits adding 11.8 percentage points to the explanatory power of the model, while culture employment and culture consumption added a possibly important 5.6 and 2.6 points, respectively. Although these findings are in line with recent literature of resilience and changes in tourism due to pandemic, a more thorough research is needed to further investigate these relations.

COVID-19 and tourism: What can we learn from the past?

The impact of the COVID-19 crisis on tourism flows is without precedent in terms of speed and severity. In this paper, we try to infer a possible future scenario for the tourism sector, evaluating the medium-term effects of past pandemics on tourist arrivals. We find that pandemics lead to a persistent decline in tourist arrivals, with the effects being larger in developing and emerging countries. Interestingly, the effects are heterogeneous across countries and episodes, and depend on several economic conditions such as the overall health system performance, the severity of the shock, and the uncertainty induced by the pandemic event.

Impact of the COVID-19 crisis on European tourism

The COVID-19 pandemic and the containment measures imposed damaged the world economy severely. As a consequence of the stringent restrictions on business and social life, as well as the consequent economic downturn, tourism demand has seen a unique dramatic slump in the year 2020. This study concentrates on analysing and forecasting demand for international travel of the euro area in terms of tourism imports. Starting out from a description of the key macroeconomic factors, it then analyses their effects on tourism demand and develops a forecast model using contemporary approaches considering asymmetric income elasticities of tourism demand. Scenarios are elaborated to project demand for foreign travel of the euro area until 2022.

The mediation of perceived risk's impact on destination image and travel intention: An empirical study of Chengdu, China during COVID-19

Perceived risk clearly impacts travel behavior, including destination selection and satisfaction, but it is unclear how or why its effect is only significant in certain cases. This is because existing studies have undervalued the mediating factors of risk aversion, government initiatives, and media influence as well as the multiple forms or dimensions of risk that can mask its direct effect. This study constructs a structural equation model of perceived risk’s impact on destination image and travel intention for a more nuanced model of the perceived risk mechanism in tourism, based on 413 e-questionnaires regarding travel to Chengdu, China during the COVID-19 pandemic, using the Bootstrap method to analyze suppressing effect. It finds that while perceived risk has a significant negative impact on destination image and travel intention, this is complexly mediated so as to appear insignificant. Furthermore, different mediating factors and dimensions of perceived risk operate differently according to their varied combinations in actual circumstances. This study is significant because it provides a theoretical interpretation of tourism risk, elucidates the mechanisms or paths by which perceived risk affects travel intention, and expands a framework for research on destination image and travel intention into the realms of psychology, political, and communication science. It additionally encourages people to pay greater attention to the negative impact of crises and focuses on the important role of internal and external responses in crisis management, which can help improve the effectiveness of crisis management and promote the sustainable development of the tourism industry.

Impact of the COVID-19 pandemic: Insights from vacation rentals in twelve mega cities

Coronavirus disease 2019 (COVID-19) is a challenging global problem. COVID-19 has caused shocks to various urban systems, and the tourism industry is no exception. We analyzed the impact on vacation rentals by conducting diachronic data mining on nearly 10 GB of rental data (calendar, listings, and reviews) in twelve highly internationalized megacities distributed across Asia, Europe, America, and Oceania based on the data set from the Inside Airbnb website. All twelve cities were adversely affected. The specific time of the impact is related to the pandemic's outbreak and enforced lockdowns policies. Affected by the epidemic, reservation rates decreased, tourists preferred renting in suburbs instead of city centers, the proportion of foreign tourists in all destinations dropped sharply, tourist sentiment scores fluctuated dramatically especially among foreigners, and people focused less on tourism related activities. This study reveals the changing illustrations of vacation rentals in highly internationalized megacities under the pandemic's influence. It offers a methodological assessment framework to monitor the hospitality sector over time and aims to serve as a reference for preparedness in similar cities worldwide.

Impact of Agricultural Drought on Sunflower Production across Hungary

In the last few decades, agricultural drought (Ag.D) has seriously affected crop production and food security worldwide. In Hungary, little research has been carried out to assess the impacts of climate change, particularly regarding droughts and crop production, and especially on regional scales. Thus, the main aim of this study was to evaluate the impact of agricultural drought on sunflower production across Hungary. Drought data for the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) were collected from the CARBATCLIM database (1961–2010), whereas sunflower production was collected from the Hungarian national statistical center (KSH) on regional and national scales. To address the impact of Ag.D on sunflower production, the sequence of standardized yield residuals (SSYR) and yield losses YlossAD was applied. Additionally, sunflower resilience to Ag.D (SRAg.D) was assessed on a regional scale. The results showed that Ag.D is more severe in the western regions of Hungary, with a significantly positive trend. Interestingly, drought events were more frequent between 1990 and 2010. Moreover, the lowest SSYR values were reported as −3.20 in the Hajdu-Bihar region (2010). In this sense, during the sunflower growing cycle, the relationship between SSYR and Ag.D revealed that the highest correlations were recorded in the central and western regions of Hungary. However, 75% of the regions showed that the plantation of sunflower is not resilient to drought where SRAg.Dx < 1. To cope with climate change in Hungary, an urgent mitigation plan should be implemented.

Sustainable and resilient strategies for touristic cities against COVID-19: An agent-based approach

Touristic cities will suffer from COVID-19 emergency because of its economic impact on their communities. The first emergency phases involved a wide closure of such areas to support "social distancing" measures (i.e. travels limitation; lockdown of (over)crowd-prone activities). In the "second phase", individual's risk-mitigation strategies (facial masks) could be properly linked to "social distancing" to ensure re-opening touristic cities to visitors. Simulation tools could support the effectiveness evaluation of risk-mitigation measures to look for an economic and social optimum for activities restarting. This work modifies an existing Agent-Based Model to estimate the virus spreading in touristic areas, including tourists and residents' behaviours, movement and virus effects on them according to a probabilistic approach. Consolidated proximity-based and exposure-time-based contagion spreading rules are included according to international health organizations and previous calibration through experimental data. Effects of tourists' capacity (as "social distancing"-based measure) and other strategies (i.e. facial mask implementation) are evaluated depending on virus-related conditions (i.e. initial infector percentages). An idealized scenario representing a significant case study has been analysed to demonstrate the tool capabilities and compare the effectiveness of those solutions. Results show that "social distancing" seems to be more effective at the highest infectors' rates, although represents an extreme measure with important economic effects. This measure loses its full effectiveness (on the community) as the infectors' rate decreases and individuals' protection measures become predominant (facial masks). The model could be integrated to consider other recurring issues on tourist-related fruition and schedule of urban spaces and facilities (e.g. cultural/leisure buildings).

Spatiotemporal Evolution and Trend Prediction of Tourism Economic Vulnerability in China’s Major Tourist Cities

The evaluation and trend prediction of tourism economic vulnerability (TEV) in major tourist cities are necessary for formulating tourism economic strategies scientifically and promoting the sustainable development of regional tourism. In this study, 58 major tourist cities in China were taken as the research object, and an evaluation index system of TEV was constructed from two aspects of sensitivity and adaptive capacity. On the basis of the entropy weight method, TOPSIS model, obstacle diagnosis model, and BP neural network model, this study analyzed the spatiotemporal patterns, obstacle factors, and future trends of TEV in major tourist cities in China from 2004 to 2019. The results show three key findings: (1) In terms of spatiotemporal patterns, the TEV index of most of China’s tourist cities has been on the rise from 2004 to 2019. Cities throughout the coast of China’s Yangtze River Delta and the Pearl River Delta urban agglomeration show high vulnerability, whereas low vulnerability has a scattered distribution in China’s northeast, central, and western regions. (2) The proportion of international tourists out of total tourists, tourism output density, urban industrial sulfur dioxide emissions per unit area, urban industrial smoke and dust emission per unit area, and discharge of urban industrial wastewater per unit area are the five major obstacles affecting the vulnerability degree of the tourism economy. (3) According to the prediction results of TEV from 2021 to 2030, although the TEV of many tourist cities in China is increasing year by year, cities with low TEV levels occupy the dominant position. Research results can provide reference for tourist cities to prevent tourism crises from occurring and to reasonably improve the resilience of the tourism economic system.

Sustainable Determinants That Affect Tourist Arrival Forecasting

This study considers diversification effects and significant influences on tourist arrivals as a vital export direction. Different quantitative methods, namely a cointegrated-autoregressive model, panels, sentiment and sensitivity analysis, were used in this study. The time-series data for Croatia and Slovenia were isolated from several secondary sources. The variables examined in this approach are tourist arrivals, precipitations, sunny days, earthquakes, microbes and CO2 emissions. The study results showed that there is a severe negative effect on tourist arrivals defined by viruses. Moreover, there is a significant decisive effect of weather conditions on tourist arrivals. Nevertheless, it is necessary to move past Covid-19 pandemic discussions to yield more accurate tourism supply forecasts, while demand is already somehow low since the beginning of 2020. The primary significance is to develop a broader thinking about the impacts of CO2 emissions on the tourism escorted to official tourist websites.

Can We Return to Our Normal Life When the Pandemic Is under Control? A Preliminary Study on the Influence of COVID-19 on the Tourism Characteristics of Taiwan

The COVID-19 pandemic has brought unprecedented destructive impacts and challenges to global industry and has had a wide impact on people’s lives. The threat of the virus has also caused a change in tourist travel consumption behavior. This study preliminarily examines the impact of the COVID-19 pandemic on the tourism consumption characteristics of Taiwanese people. The consumption characteristic changes of 393 people regarding their plans for domestic and outbound tourism during the different stages of the COVID-19 pandemic as well as after the pandemic ends were surveyed and collected. This study also examined and attempted to understand the relationship between people’s satisfaction with the government’s revitalization plan, the pandemic prevention policy, and their domestic tourism frequency during the pandemic period, and the results showed that during the pandemic, people’s tourism characteristics have changed and tend to be conservative. Since the pandemic is over, while there were no significant differences between people’s planned travel expenditures in Taiwan and those before the outbreak, their intended travel time was shortened. Regarding the choice of travel equipment, people had reduced the use of public transportation. Regarding outbound tourism, after the pandemic, as people’s planned travel days will be reduced, it is expected that travel expenditures will be significantly higher than before the pandemic, which shows that the COVID-19 pandemic has an impact on people’s outbound tourism consumption characteristics. During the pandemic, compared with the subsidies for tourism, how to make people feel at ease in the process of tourism is of great importance. Therefore, it is suggested that in the short-term, border control and social pandemic prevention policies should be adopted to enhance people’s confidence in government pandemic prevention, and the general public should be supplemented with travel subsidies in order to promote people’s enthusiasm for tourism. The results of this study provide useful suggestions for government units, tour operators, and related research during the pandemic and offer preliminary insights for the recovery of the tourism industry after the pandemic.

Crisis management research (1985-2020) in the hospitality and tourism industry: A review and research agenda

The global tourism industry has already suffered an enormous loss due to COVID-19 (Coronavirus Disease 2019) in 2020. Crisis management, including disaster management and risk management, has been becoming a hot topic for organisations in the hospitality and tourism industry. This study aims to investigate relevant research domains in the hospitality and tourism industry context. To understand how crisis management practices have been adopted in the industry, the authors reviewed 512 articles including 79 papers on COVID-19, spanning 36 years, between 1985 and 2020. The findings showed that the research focus of crisis management, crisis impact and recovery, as well as risk management, risk perception and disaster management dominated mainstream crisis management research. Look back the past decade (2010 to present), health-related crisis (including COVID-19), social media, political disturbances and terrorism themes are the biggest trends. This paper proposed a new conceptual framework for future research agenda of crisis management in the hospitality and tourism industry. Besides, ten possible further research areas were also suggested in a TCM (theory-context-method) model: the theories of crisis prevention and preparedness, risk communication, crisis management education and training, risk assessment, and crisis events in the contexts of COVID-19, data privacy in hospitality and tourism, political-related crisis events, digital media, and alternative analytical methods and approaches. In addition, specific research questions in these future research areas were also presented in this paper.

Light at the end of the tunnel: Visitors' virtual reality (versus in-person) attraction site tour-related behavioral intentions during and post-COVID-19

Consumer behavior is changing as a result of the COVID-19 pandemic, thus compelling attraction sites to find new ways of offering safe tours to visitors. Based on protection motivation theory, we develop and test a model that examines key drivers of visitors' COVID-19-induced social distancing behavior and its effect on their intent to use virtual reality-based (vs. in-person) attraction site tours during and post-COVID-19. Our analyses demonstrate that visitor-perceived threat severity, response efficacy, and self-efficacy raise social distancing behavior. In turn, social distancing increases (decreases) visitors' intent to use virtual reality (in-person) tours during the pandemic. We find social distancing to boost visitors' demand for advanced virtual tours and to raise their advocacy intentions. Our results also reveal that social distancing has no effect on potential visitors' intent to use virtual reality vs. in-person tours post-the pandemic. We conclude by discussing vital implications that stem from our analyses.

Fog-assisted Energy Efficient Cyber Physical System for Panic-based Evacuation during Disasters

Disasters around the world have adversely affected every aspect of life and panic-health of stranded persons is one such category. An effective and on-time evacuation from disaster-affected areas can avoid any panic-related health problems of the stranded persons. Although the nature of disasters differ in terms of how they occur, the evacuation of stranded persons faces approximately same set of issues related to the communication, time-sensitive computation and energy efficiency of the devices operated in the disaster-affected areas. In this paper, a cyber physical system (CPS) is proposed that takes into account various challenges of the disaster evacuation, so an efficient on-time and orderly evacuation of stranded panicked persons could be realized. The system employs fog-assisted mobile and UAV devices for time-sensitive computation services, data relaying and energy-aware computation. The system uses a fog-assisted two-factor energy-aware computation approach using data reduction, which enables the energy-efficient data reception and transmission (DRecTrans) operations at the fog nodes and compensates to extend the period for other functionalities. The data reduction at fog devices employs Novel Events Identification (NEI) and Principal Component Analysis (PCA) for detecting consecutive duplicate traffic and data summarization of high dimensional data, respectively. The proposed system operates in two spaces: physical and cyber. Physical space facilitates real-world data acquisition and information sharing with the concerned stakeholders (stranded persons, evacuation teams and medical professionals). The cyber space houses various data-analytics layers and comprises of two subspaces: fog and cloud. The fog space helps in providing real-time panic-health diagnostic and alert services and enables the optimized energy consumption of devices operate in disaster-affected areas, whereas the cloud space facilitates the monitoring and prediction of panic severity of the stranded persons, using a conditional probabilistic model and seasonal auto regression integrated moving average (SARIMA), respectively. Cloud space also facilitates the disaster mapping for converging the evacuation map to the actual situation of the disaster-affected area, and geographical population analysis (GPA) for the identification of the panic severity-based critical regions. The performance evaluation of the proposed CPS acknowledges its Logistic Regression-based panic-well being determination and real-time alert generation efficiency. The simulated implementation of NEI and PCA depicts the fog-assisted energy efficiency of the DRecTrans operations of the fog nodes. The performance evaluation of the proposed CPS also acknowledges the prediction efficiency of the SARIMA and disaster mapping accuracy through GPA. The proposed system also discusses a case study related to the pandemic disaster of coronavirus disease 2019 (COVID-19), where the system can help in panic-based selective testing of the persons, and preventing panic due to distressing period of COVID-19 outbreak.

COVID-19 impacts, coping strategies, and management reflection: A lodging industry case

The COVID-19 pandemic has hit the global tourism and hospitality industry with drastic results. Hotels have been experiencing unprecedented challenges, leaving many to temporarily or permanently closed. Employing a case study approach supported by both quantitative and qualitative analysis, this study examined how two hotels in Oklahoma City had coped with challenges presented by the COVID-19 pandemic, from day to day operations, health and safety measures to marketing, human resources and cost-saving strategies. The study contributes to the tourism crisis and disaster literature by providing micro-level coping strategies, a literature gap that needs to be addressed, particularly under the current pandemic.

Memory and forgetfulness in tourism crisis research

Even though academic attention has been paid on the tourism-memory nexus, the concept of forgetfulness in tourism has been largely overlooked and remains unexplored. The aim of this research note is to introduce the concept of forgetfulness alongside memory within tourism scholarship to discuss the way in which it may be integrated with future research. In so doing, the discussion focused on a tourist crisis context as tourists' post-crisis behaviour often reflects forgetfulness as evidenced by their travel resumption patterns. Overall, by linking the concepts of forgetfulness and tourism, this research note contributes to knowledge advancement on tourism crises by shifting attention away from risk perceptions towards an understanding of the cognitive and emotional processes influencing tourist behaviour. The research note also illuminates understanding of how crises are forgotten; hence, contributes to the improvement of crisis management strategies. The research note concludes by proposing an agenda for future research.

COVID-19 impact on the hospitality industry: Exploratory study of financial-slack-driven risk preparedness

The hospitality industry is regarded as one of the most affected by the consequences of COVID-19 pandemic, and the undefined persistence of the pandemic duration raises anxiety about the ability to recover from this dramatic situation. In this regard, the purpose of this exploratory study is to shed light on the COVID-19 risk preparedness of hospitality businesses, as driven by the financial slack holdings and persistence. The empirical findings confirm that their financial-slack-driven risk preparedness should be judged as relatively low. A majority of the examined hospitality businesses demonstrated low or insufficient financial slack holdings and recently have consumed their financial slack resources. Thus, the abilities of hospitality businesses to sustain the liquidity tensions that emerged after the COVID-19 outbreak are questionable. Facing this evidence, we draw conclusions about the necessary design of system interventions that could prevent bankruptcy in the hospitality industry.

Tourism Stakeholder Perspective for Disaster-Management Process and Resilience: The Case of the 2018 Hokkaido Eastern Iburi Earthquake in Japan

The 2018 Eastern Iburi Hokkaido earthquake in Japan caused infrastructural damage and tourism disruption within a natural-hazard-prone country. This research advances the theoretical foundation and development of natural disaster management through a series of in-depth interviews with the local tourism stakeholders on the investigation of how the role of tourism across the pre-to-post earthquake period is considered by the stakeholders. These local tourism stakeholders have performed or expected a range of actions related to the disaster-management process and contributed to destination resilience. The qualitative analysis discovers, firstly, the multi-functionality of tourism resources, spaces, and industries for disaster preparation; secondly, the evacuation and emergency arrangements during the prodromal and emergency phases; and moreover, more possibilities of restoring the affected destination to a state of long-term (re)development during the post-disaster phases. Information and communication barriers are the major difficulties to be tackled for disaster preparedness. Product creation, image improvement, local knowledge enrichment, and, more importantly, people-to-people and people-to-place connections all contribute to the result of sustainable tourism development. From the destination resilience perspective, collaboration is the key determinant of an improved Hokkaido region. This factor could integrate stakeholders through shared local values, experiences, and memories of disaster risk communication and strategies for preparedness.

Methodology and Application of Spatial Vulnerability Assessment for Evacuation Shelters in Disaster Planning

Evacuation shelters are the most important means for safeguarding people in hazardous areas and situations, and thus minimizing losses, particularly those due to a disaster. Therefore, evacuation shelter assignment and evacuation planning are some of the critical factors for reducing vulnerability and increasing resilience in disaster risk reduction. However, an imbalance of shelter distribution and spatial heterogeneity of a population are the critical issues limiting the accessibility of evacuation shelters in real situations. In this study, we propose a methodology for spatial assessment to reduce vulnerability and evaluate the spatial distribution of both shelter demand and resources, considering spatial accessibility. The method was applied to the case study of Mabi, in the context of a disaster caused by the 2018 flooding. We applied this approach to evaluate the area and identified the vulnerability of the evacuation shelters and the residents. The proposed method revealed that 54.55% of the designated evacuation shelters and 59% of the total population were physically vulnerable to the flood. The results highlight, using GIS maps, that the total shelter capacity was significantly decreased to 43.86%. The outcome assessment addressed specific vulnerable shelters and the imbalance between the demand for and resources of each shelter. Accordingly, this study provides practical information and a valuable reference for supporting local governments and stakeholders to improve future disaster planning, prevention, and preparedness.

What are the Factors affecting Tourist Behavior based on the Perception of Risk? Romanian and Serbian Tourists’ Perspective in the Aftermath of the recent Floods and Wildfires in Greece

During the summer season 2018 and 2019, natural hazards (namely, floods and wildfires) have occurred at some of the most popular tourist destinations in Greece, endangering tourists’ safety and vacation quality. These have influenced tourists’ perception of Greece as a “potentially risky destination”, causing a decrease in the number of tourists willing to visit this country. However, the current study assumes that some tourists will show more courageous travel behavior in the aftermath of natural hazards, while others will remain cautious when deciding to travel to risky destinations. Therefore, the questionnaire on a sample group of 431 respondents from Serbia and Romania was conducted to explore the factors influencing such differences. The study aims to explore whether tourists’ individual characteristics influence tourism worries and tourist behavior based on perceived risks. The study also intends to analyze the moderating role of tourists’ nationality, considering the relationship between personality and tourist behavior based on the perceived risk. The findings provide evidence that not only tourists’ personality but also sociodemographic characteristics influence tourism worries and tourist behavior based on the perceived risk. Additionally, the study is the first to explore and confirm the role of nationality in tourist behavior based on the perceived risk, as well as the moderation role of nationality in regression between tourist’s personality and behavior based on the perception of risk. Theoretical and practical implications are discussed in the paper.

The Right to A Clean Environmentꓽ Considering Green Logistics and Sustainable Tourism

The globalization process has yielded various undesirable consequences for the environment and society, including increased environmental pollution, climate change and the exhaustion and destruction of resources. The influence of these processes makes it difficult to guarantee citizens' rights to a clean environment, and the implementation of this right requires complex solutions. The aim of this integrative review article is to discuss the right to a clean environment, as it relates to green logistics and sustainable tourism, by analyzing various scientific and legal sources. Rethinking the possible solutions of green logistics for sustainable tourism, such as tourism mobilities, bicycle tourism, the co-creation of smart velomobility, walkability, and others, can help us also rethink how to balance, respect, protect, and enforce human rights in the present-day context of climate change challenges. The integrative review analysis shows the importance of seeking a balance between the context (the right to a clean environment), the challenge (climate change), and the solutions (green logistics solutions for sustainable tourism).

Comprehensive Spatio-Temporal Analysis of Travel Climate Comfort Degree and Rainstorm-Flood Disaster Risk in the China–Russia Border Region

Infrastructure and tourism is gradually increasing along the China–Russia border with the development of the China–Mongolia–Russia economic corridor. Facing the issues of thermal comfort and rainstorm-flood risk in the neighborhood area between China and Russia, we constructed homologous evaluation models to analyze spatial regularity and internal variations of their effect. Among the results, approximately 55% of the area was classified into the categories of “comfort” and “high comfort” in summer. Oppositely, the situation of most areas in winter corresponds to physical discomfort. On the other hand, the high-risk area of rainstorm-flood in spring and summer is principally located in the northern and southern regions, respectively, while this is further expanded in autumn. After that, the risk level turns to medium and low. Subsequently, a comprehensive assessment coordinate system of the two results was constructed to identify the distribution pattern of a seasonal suitable area for traveling in binary ways. The evaluation shows that Great Khingan Range in the north-western Heilongjiang province is the preferable place among most of seasons, especially in summer. While on the Russian side, the corresponding area is mainly spread over its southern coastal cities. The study is expected to provide recommendations for reasonable year-round travel time, space selection, and risk decision support for millions of people traveling between China and Russia.