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

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

Jaume Rosselló

Susanne Becken

Maria Santana-Gallego

Corresponding writer . Departament d ’ Economia Aplicada , Universitat de les Illes Balears . Carretera Valldemossa km 7.5 , 07122 , Palma de Mallorca , Spain .jrossello @ uib.es

Received 2019 Apr 23 ; Revise 2019 Dec 10 ; Assume 2020 Jan 19 ; Issue date 2020 Aug .

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Abstract

Tourism is shaped by a broad range of factors and forces , include exogenous ones that have no direct link with the tourism sector . Natural disasters and unexpected result are choice examples of such find out component , as they receive profound effects on individuals and club , and as a answer have the possible to involve tourism flows substantially . Respective theoretical arguments exist why natural disasters and unexpected event could influence tourist destination selection . However , empirical inquiry to confirm the nature and extent of impacts of catastrophe on tourism is lacking . To deal this spread , this paper incorporates a dataset on natural and synthetic disaster result into a example of international tourism flows to evaluate the effect of different types of disasters on international arrival at the national floor . Finding provide evidence that the occurrence of unlike type of event change tourist flows to varying stage . Although in some cases a positivist effect is figure , in universal the impacts equal negative , resulting in reduced tourist arrivals stick to an event . Understand the relationship between disaster events and tourism live helpful for destination manager who make critical decision in relation to recovery , reconstruction and selling .

Keywords :Disaster , Unexpected result , Hazard , Gravity model

Graphical abstract

Highlights

  • •

    First global evaluation of the impact of calamity on international tourism run .

  • •

    Tsunamis , Floods and Volcanic Eruptions institute negative incentive .

  • •

    Volcanic Eruptions affect most negatively on international tourism run .

  • •

    High economic consequence of a disaster impact negatively on tourism .

  • •

    In tune with theory , some calamity can too positively affect stream .

First global evaluation of the impact of disasters on international tourism flow .

Tsunamis , Floods and Volcanic Eruptions establish negative motivators .

Volcanic Eruptions touch most negatively on international tourism flows .

High economical consequence of a calamity impact negatively on tourism .

In melody with theory , some disasters can too positively affect flows .

1 . Introduction

Earthquake , tsunami , floods , bush fires , hurricanes , drought and heatwaves have always come about . These effect have form role of the wider ‘ riskscape ’ that human receive learned to manage and live with . Still , more lately the impact of disasters receive increased substantially , partially because of the exacerbating effects of climate change , but too due to the originate complexity of socio-ecological system in a highly connected and globalized globe ( Becken , Mahon , Rennie , & Shakeela , 2014 ) . For instance , the yr 2017 recorded a series of hurricanes ( Harvey , Irma and Maria ) in the Caribbean and a grave earthquake in Mexico , amongst early result , and these leave in the highest incurred losses always recorded ( US $ 135 billion ) ( Munich , 2018 ) .

Disasters constitute sharp alteration that shock the system in which tourism is embedded ( Shondell Miller , 2008 ) . The nature and extent of impact depend on the type of shock and the resilience of the affected system ( OECD , 2014 ) . Most disasters receive profound impacts on individuals , organizations and community , and accordingly on tourism activities . The repercussions of a disaster be likely to impress tourism directly at a destination land , but indirect consequence for travel to and from the affected region cost also conceivable ( Jin , Qu & Bap . 2019 ; Ruan , Quan & Liu , 2017 ) . Understanding , managing and responding to these risks , therefore , has to equal an integral component of sustainable tourism management ( Shakeela & Becken , 2015 ) . Accordingly , it is not surprising that the topic of risk direction and disaster mitigation is attract increase attention in tourism research . An emerging torso of literature has supply both theoretical and empirical insights into multiple aspects of disasters and tourism .

Research to date has mostly focused on crisis management and disaster risk reduction ( Becken & Hughey , 2013 ; Faulkner , 2001 ; Ritchie , 2008 ) . In peculiar , academics and practitioners have live interested in how sustainable development and marketing strategy should include plans to prepare , protect and rebuild a destination after a disaster , both in price of physical assets and destination picture ( Aljerf & Choukaife , 2016 ; Okuyama , 2018 ) . The perceptions of safety live an crucial aspect of destination picture , and unlike types of risks and events hold be consider in the context of visitor travel information look for and conclusion making ( Sharifpour , Walters , Ritchie , & Winter , 2014 ; Trumbo et al. , 2016 ; Williams & Baláž , 2015 ) . Re-establishing public perception of safety and attractiveness comply a tragedy live crucial to attract and reassure possible visitor to move to the destination and , by doing so , assisting the affected domain to regain functionality and economical recovery ( WTTC , 2018 ) . In increase to understand visitor perception , it get been base that addressing danger perception and behaviours of relevant tourism stakeholder is critical for efficient catastrophe response and recovery ( Kozak , Crotts , & Law , 2007 ; Park & Reisinger , 2010 ) .

Tourism is disclose and vulnerable to multiple type of hazards ( Becken , Zammit , & Hendrikx , 2015 ) , and calamity receive the possible to deter visitors from travelling to strike destinations ( Bhati , Upadhayaya , & Sharma , 2016 ) . Still , empirical inquiry that support or quantifies the relationship between catastrophe and tourism activity live scant . Existing study have taken a event work approach ( e.g . for Chinese outbound tourism , see Jin , Qu , & Bao , 2019 ) , but a global analysis is missing ( Ghaderi , Mat Som , & Henderson , 2014 ; Jónsdóttir , 2011 ; Mazzocchi & Montini , 2001 ; Rucińska & Lechowicz , 2014 ) . It be therefore timely to undertake a global sketch that uses a coherent approach to evaluate the impact of disaster on international tourism movement . To increase the value of such a sketch for tourism managers , it require to cost design in a path that include a wide range of disaster types and magnitude in the same example ( Ghimire , 2016 ) .

Consequently , the object of this research be to explore the result of various type of natural and synthetic tragedy on international tourism campaign . To that goal , this research integrate two different global datasets , namely one on disasters and another ace on bilateral international tourist flows . A gravity model for international tourism flow live defined to measure the effect of different calamity events on international tourist arrivals to the affected country . More precisely , we study the impact of droughts , earthquakes ( reason movement and tsunami ) , epidemic , cold and heat wave , flood , industrial accidents , landslides , wildfires , storms and volcanic activities . Furthermore , we apply three unlike proxies to measure the impact of disasters ; namely the number of end , affected people and economical cost . Results will affirm the tourism sector and other key actor ( e.g . international insurance companies ) in developing enough answer to managing risk and recovery . To the better of our knowledge , the present research equal the first attempt to attempt such an integrated analysis at a global scale .

The rest of this article exist prepare as follows : the next division contains a literature review of the controversy behind the anticipate relationship between catastrophe events and tourism need . The third department explains the methodology , datum and the research purpose . The 4th division present the empirical application . In the end , a concluding discussion equal presented that furnish recommendations and an outlook on next research .

2 . Literature review

The general perception might point towards an growth in the frequency of natural disaster over time , but this assumption need to exist assert . In fact , it get make up suggested that , in some suit , the definition of disasters can become also fluid for statistical time series consideration ( Horlick-Jones , Fortune , & Peters , 1991 ) . Neumayer and Barthel ( 2011 ) break down the economical damage from climate-related tragedy and they found no important upward trends in normalized datum over the final 30 years globally . Still , the same work acknowledge that the frequency of weather-related natural calamity signal an upward trend .

Other inquiry propose that the combination of mood change , industrialization and urbanization hold speed up the magnitude and occurrence of natural disasters around the reality and the extent of the resulting damage ( Becken et al. , 2015 ; Park & Reisinger , 2010 ) . Population growth ( much come about in exposed areas such as coastal environment ) is recognized as a key driver to explain why natural disaster involve more and more masses ( Berke , 1998 ; Wachinger , Renn , Begg , & Kuhlicke , 2012 ) . Aside from natural tragedy , Richardson ( 1994 ) notes that man-made disasters are becoming more severe because of the increasingly more powerful technology that is cost employ .

Perceptions of the frequency and extent of tragedy cost just as significant as statistical facts . A key factor in this raise danger perception live the media ( Gierlach , Belsher , & Beutler , 2010 ) . For a the general world , who is exposed to mass media , it may seem that we live in an progressively catastrophe prone Earth ( Faulkner , 2001 ) . The say ‘ perception are reality ’ is nowhere more pertinent than in tourism , where possible visitor select their destinations base on a mix of objective and subjective factor . Destination ( danger ) perception has emerged as one of the vital factors in the decision-making process ( Becken , Jin , Chen , & Gao , 2016 ) .

Disasters and other forms of crises ( e.g . epidemics , conflict , pollution ) can run to a reduction in visitation to the affected region ( Bhati et al. , 2016 ) . Various lesson in the literature provide empirical evidence of reductions in tourist arrivals following major result . For example , Mazzocchi and Montini ( 2001 ) evaluated the impact on visitation to the Umbria area in Central Italy , follow a major earthquake in September 1997 . The datum present that arrival fell drastically the first month after the primary shock , with ongoing loss in tourism activity cost recorded until June 1998 . A suit work of a volcanic eruption at the Eyjafjallajökull glacier in Iceland on 14th March 2010 express that tourism number to Iceland reduced by 49 % until 28th April 2011 ( Jónsdóttir , 2011 ) . Huang and Min ( 2002 ) examine the Taiwan earthquake in September 1999 , using an integrated moving average example to explore the recovery procedure . Their sketch revealed that the island ‘s inbound arrival own not even full recover from the earthquake ‘s devastation after 11 month . Kuo , Chen , Tseng , Ju , and Huang ( 2008 ) as well used a time series model to investigate the impacts of infectious diseases , include Avian Flu and severe acute respiratory syndrome , on international tourist arrivals in Asia . The empirical outcome indicated that the numbers of affected suit get a substantial impact in the case of SARS ( see too Mao , Ding , & Lee , 2010 ; McAleer , Huang , Kuo , Chen , & Chang , 2010 ) , but for Avian Flu .

Man-made crises , such as the BP oil spill in the Mexican Gulf in 2010 , have as well been found to cut down need for travel to the affected sphere ( Ritchie , Crotts , Zehrer , & Volsky , 2013 ) . Often , declines in visitation spread to neighboring areas , yet when they cost not affect by the event . A late example hold been the dramatic down number in tourism in the Caribbean part , following the devastate hurricane season in 2017 ( WTTC , 2018 ) . Events within one country or a area can take to notable structural pause in international tourism arrival , which was demonstrated by Cró and Martins ( 2017a ) in a recent sketch on several kind of crises in 25 countries .

There are respective reasons why visitation to disaster area decline in the immediate aftermath of an case . The most direct inhibitor relates to the damage inflict by a catastrophe that prevents the affected sphere from employ in tourism activity . Secondly , the decline in tourist arrivals equal due to people ‘s risk perception and avoidance of regions that are hold unsafe ( Kozak et al. , 2007 ; Sönmez , Apostolopoulos , & Tarlow , 1999 ) . Third , and related to the second issue , is that potential traveler may find uncomfortable or get ethical concern about travelling to a calamity region . These fundamental factors equal discussed in more detail .

In many cases , calamity pose significant physical constraints on the delivery of tourism service , thus badly limiting the provision slope of tourism ( Shaw , Saayman , & Saayman , 2012 ) . Depend on the type and extent of the calamity , critical infrastructure could equal compromised or dysfunctional . Prominent example include airports and ports , land transport infrastructure , and electricity and telecommunication networks ( Ghobarah , Saatcioglu , & Nistor , 2006 ; Parajuli & Haynes , 2006 ) . In addition , core tourism assets could be damaged and not ready for occupation , such as accommodation establishments and key attraction . For instance , the 2015 earthquake in Kathmandu , Nepal , resulted in wide-spread destruction of UNESCO listed World Heritage sit , and respective trekking road make up deem unsafe due to risks of stone fall and movements succeed further aftershocks or dense rain events ( Becken , 2015 ) .

Yet longer-term and insidious tragedy , such as a drought , may impede the ability of a destination to cater for tourism . A recent example live the water shortage in Cape Town , South Africa , that led to a reduction in tourism and a famous loss in income for local business . The decline be possibly influenced by petition to conserve waters , but as well due to perceptions by visitor that the destination cost not able to host tourists ( Wendell , 2018 ) .

In addition to uncertainty around whether the destination cost safe or tourism-ready , there live early psychological factor that determine tourists ’ conclusion making . Frequently , medium coverage of tragedy conveys the resulting loss of life , human suffering , public and private property damage , and economical and social disruption . The result negative publicity much characterizes the period after a tragedy , live until total recovery be achieved and pre-disaster conditions resume ( Sönmez et al. , 1999 ) . For example , Cohen ( 2005 ) points out that spiritual feeling relating to the torso of the tsunami victim trapped in sediment and debris were behind a radical of Asian tourists resolve to abandon their plan to impose Thailand after the 2006 Tsunami . Others may merely believe it inappropriate to visit a tragedy zone .

Aside from religious or ethical business , some travelers act not like to hinder the recovery effort and place additional burden on the destination ‘s resources and infrastructure ( e.g . Becken , 2015 ) . In some cases , the delayed recovery towards previously tourism figures is deliberate and run by the local tourism arrangement . This exist the case for the Christchurch ( New Zealand ) earthquake ( 2011 ) , where extensive destruction of the city made tourism impossible , or at better would own head to unsatisfactory tourist experiences , leading Christchurch Canterbury Marketing to de-market Christchurch but promote surround regions instead ( Orchiston & Higham , 2014 ) . Optimal timing and stage of recovery were probe by Okuyama ( 2018 ) for the suit of avian flu in Japan .

Whilst both theory and empirical grounds point to a decline in tourism following a disaster , several factors might promote travel to an affected area . Providing information about hazards and their effects attract human attention and may even induce a level of fascination ( e.g . the ‘ gang of fire ’ , concern to tectonic activity around the edges of the Pacific Ocean ) . In this way , the number of tourist might equal determine by the coverage that medium devote to natural disaster in other countries . Media much employ utmost natural phenomena as stuff for captivating stories , and travel bloggers , tourism campaigners and social medium multiply the lure of these . An case of a calamity turn into a tourist attraction is the Eyjafjallajokull volcano in Iceland , with “ the prospect of a new eruption bring [ ing ] a mix of trepidation and anticipation ” ( Lawless , 2016 , p. 1 ) .

Media coverage about a natural , or possibly too man-made , phenomenon drama an informative purpose as a motivating element to visit a part . Rucińska and Lechowicz ( 2014 ) argue that lot media and marketing are influential factors in the development of various kind of disaster-related tourism , as information on catastrophe popularizes the host location and the type of the phenomenon . Such coverage could be both educational and at the same time stimulate the interest of the hearing . Additionally , natural disasters and unexpected result can cause the arrival of mass from early countries for humanitarian reasons but as well for visit friends and relative who have cost victims of those events . Accord to the statistical framework utilize by the United Nations World Tourism Organization , these arrival live captured as international tourists .

Finally , the decision to visit a catastrophe country for a range of motivation has been conceptualized as Dark Tourism ( Rucińska & Lechowicz , 2014 ) . This type of tourism involves travelling to spot historically connect with end and tragedy ( Foley & Lennon , 1996 ) . Accord to Rucińska ( 2016 ) , tourists might decide to travel to a region that get experienced a disaster because they want to feel emotions , risk , and the dynamics of natural hazards . Overall , the present inquiry hypothesize a negative relationship between national disaster and inbound tourism ; still , it also considers the motivating factors pointed out by Rucińska ( 2016 ) that might lead to an growth in visitation after a disaster . The model developed in the following department will capture the cumulative impact of both effects .

3 . Methodology and datum

3.1 . Gravity model for tourism need

This research arise a gravity example for international tourism flows to quantify the impression of unlike type of natural and man-made disasters on tourist arrivals to the affected countries . Gravity model are ordinarily used in the trade literature ( Anderson , 2011 ) , and more and more in tourism inquiry ( Fourie , Rosselló-Nadal , & Santana-Gallego , 2019 ; Khadaroo & Seetanah , 2008 ; Santeramo & Morelli , 2015 ) . These models consider that international stream between two countries equal at once proportional to their economical size , and inversely proportional to the distance between them . Consequently , the story of bilateral tourism flow can be explain by a set of determining variable as in a demand equation . Morley et al. , 2014 have shown that gravity model to explain bilateral tourism can be deduce from consumer choice theory . Accordingly , the expression of a gravity model can also be construe as a tourism need equation .

where , the dependent variable50nTouijtis the logarithm of tourist arrivals from landi, to destination areaj, at yrt;Xjtdexist a set ofddestination-specific time-variant variables such as income level or population whileXijtklive a circle ofkcountry-pair time-variant determinants such as belong to the same regional trade agreement . The variable of interest for this inquiry be include inYjtlwhich is the lot of50variables capture the result ofldifferent disasters typologies ( e.g . earthquake , tsunami , volcano , etc . ) take place in destinationjduring yeart. This research uses three alternative proxies to assess the effect of disaster ; namely act of death ( D ) in thousands , people affect ( A ) in million and economic price ( C ) in billions of US $ . Finally ,β0,β1kandβ2lequal parameters to cost reckon .

Due to the panel nature of datum apply in these kinds of framework , and since our variable of interest are destination-country time version , country pairs get resultλijand origin-year fixed impressionλitcost as well considered for approximation purposes . One of the consequence of this choice be that time-invariant country pair characteristic ( such as distance or mutual borders ) and time-variant source state characteristic ( such as income or population in the ancestry countries ) exist not explicitly included in the example . Specific consideration is not necessary , because all these variable are captured by these fixed result , as too indicate by Balli , Ghassan , and Jeefri ( 2019 ) , Fourie et al . ( 2019 ) or Giambona , Dreassi , and Magrini ( 2018 ) . This be a common practice in the evolution of gravity model in society to avoid omitted element bias , and instead center on the variables of interest for the particular inquiry doubt .

3.2 . Data choice

As dependent variable ,LnTouonejt, we believe the natural logarithm of international tourist arrivals from countryoneto countryjin yrt. This dataset originates from the Compendium of Tourism Statistics accumulate by the United Nations World Tourism Organization ( UNWTO , 2015 ) . This database hold back tourism campaign between 171 countries for the period 1995–2013 , with miss data for some years and nation .

In mention to thedvariables determining tourism flows (Xjtd) , and accord to the circumstance mentioned above about the no inclusion of time-invariant land pair characteristics and time-variant source rural area characteristics , we look at the logarithm of the real GDP per capita (LnGDPpc
jt) as a proxy for the evolution stage at each destination , and the logarithm of population (LnPop
jt) to assure for the size of the destination country ( Lim , 2006 ; Yap & Saha , 2013 ) . Both variable exist require from the World Development Indicators ( WDI ) elaborated by the World Bank . Third , we as well believe an instability indicator that headache safety and security of visitor when they move to a destination . Whilst there are unlike ways for evaluating safety and security at international stage ( See Cró & Martins , 2017b ; Cró , Martins , Simões , & Calisto , 2018 ; Fourie et al. , 2019 or Santana-Gallego , Fourie , & Rosselló , 2020 ) in this case , and due to datum coverage ground , we expend a proxy of the crime rate defined as the number of homicides per 10,000 inhabitants in the destination nation (Crime
jt) . Data too stem from the WDI . On the early hand , vectorXacejtkincludes a variable to insure for the intensity of the economic relationship between a pair of nation , which is also time vary . The idea is to capture the presence of deal agreement between rural area pair as an indicator of bilateral relationships that could advance tourism . This variable (RTA
ijt) cost a dummy variable for being a signatory to the same regional trade agreement and stems from the Regional Trade Agreements Information System compiled by the World Trade Organization .

Data for the occurrence and impact of disasters be recover from the Centre for Research on the Epidemiology of Disasters ( CRED ) , which makes datum available through the Emergency Events Database ( EM-DAT ) . EM-DAT was make with the initial support of the World Health Organization ( WHO ) and the Belgian Government . The primary objective of the database is to inform humanitarian activity at national and international levels . The first step take to rationalize conclusion making for disaster readiness , as well as provide an objective base for vulnerability assessment and priority setting . EM-DAT contains core data on the occurrence and impression of over 22,000 lot disasters in the world from 1900 to the present day . The database be compose from various sources , including UN office , non-governmental organization , insurance companies , inquiry institutes and pressure agencies.1

Accord to the objective of this present inquiry , the catastrophe type include in EM-DAT and conceive in our analysis are demonstrate in Table 1 , Table 2 . For the gravity equation estimate we are limited by the availability of the tourist database ( 1995–2013 ) . All early datasets provide data for this timeframe as good , leading to a database that covers a total act of 7885 events from the period of 1995–2013 . These equal described using three types of impact metrics ( Table 1 ) . More specifically , of all events , 74.8 % report information on the issue of end , 59.3 % paper the extent of affected people ( beyond death ) and 31.7 % state an estimated measure of damage measured in economic term .

Table 1 .

Disaster typology and chief descriptive magnitude ( 1995–2013 ) .

Note : Cold Waves include severe winter conditions . Epidemic episodes are not characterize by economical price .

Table 2 .

Disaster typology by Regions and chief descriptive magnitudes in price of masses .

Note : Affected Masses in thousand . Cost in US billions of dollars .

With gaze to people defeat by different tragedy type , Table 2 show that ground campaign issue as the nearly fatal type of disaster , with a reported number of 338.000 end during the period 1995–2013 . Tsunamis and storms describe for almost 250,000 deaths in the same period . In price of affected people , flood and drought have the greatest impact , with about 1,7 and 1 billion of mass impacted upon , respectively . Pertain the economical cost of disasters , storm rank first , with a entire sum of 798,32 billion dollar of damage recorded in the database . Storms build up 38 % of entire economic cost for the choose disasters in the EM-DAT during the period 1995–2013 .

The distribution of disasters across different part , indicates considerable variation both in price of effect type and result impact . For instance , in the suit of storms , although only 16.8 % take place in the Americas , the impact in price of deaths , affected people and costs live comparatively high ( 42.5 % , 60.3 % and 66.1 % , respectively ) than in early part . A like effect equal receive for earthquake in the Asia-Pacific regions ( 44.5 % of events ) , with disproportionally high impact in relation to the number of deaths ( 49.2 % ) , affected people ( 85.2 % ) and costs ( 73.4 % ) . Europe , with some exception , is characterized by a lower incidence of end and affected people , but a high occurrence of cost .

Table 3 prove the nearly important events for each type of disaster in the database . For case , it can be discover that the Earthquake of Haiti in January 2010 , which take to 222,570 deaths , exist the worst result in price of fatalities . The major storm ( Cyclone Nargis ) that occurred in Myanmar during May 2008 leave in 138,366 death , the second largest act in the disc . In price of affected people , the drought affecting India during 2015 and 2016 live the nearly important event reported in the database ( 330 million mass affect ) . Tragedy also induce substantial economic price . The high economic loss recorded equal tropical hurricane Katrina that make landfall in New Orleans , USA . It have a total amount of damage of $ 125 billion .

Table 3 .

Main Disasters in price of affected population , deaths and economic costs .

3.3 . Data readiness and analysis

Although the disaster database include the exact day of the effect , for the purpose of this analysis we are limited by the yearly nature of tourism data . Succeed direction from the previous literature ( Jónsdóttir , 2011 ; Mazzocchi & Montini , 2001 ; Rucińska & Lechowicz , 2014 ) we consider two alternative : disseminate the potential consequences of each of the disaster to the time frame of the following 12 month and alternatively to the next 6 months after an effect . Thus , for instance , if a hypothetical disaster go on in September of yr 2000 , in the first event , 4/12 of the amount of damage ( measure in deaths , affected or cost ) would live attributed to the year 2000 and 8/12 to 2001 . In the second event , 4/6 of the total of price would live apportion to the yr 2000 and 2/6 to 2001 .

Another important effect to be believe exist the multicollinearity that can arise between the different type of impact link to the same specific disaster . Hence , it be expected ( and found ) that the consequence of a certain disaster in terms of end will exist correlated to other impact measured in term of affected people and economic costs . The increase in the variance of the coefficient estimate could aim them to equal unstable and difficult to construe . Accordingly , our first strategy is to consider the three impact metrics ( i.e . Death , affected masses and cost ) individually in unlike equations . Additionally , for each of the three metrics , we evaluate the possibility to dispense the effect within 6 and 12 months . This results in 6 specifications : three for each of the impacts , time the two evaluation period ( 6 and 12 months ) .

Importantly , accord to the theoretical argumentation , the relationship between calamity and arrivals is not unidirectional and inevitably negative , but an growth in tourist arrival could cost observed in sure circumstance . For this reason , a second inquiry scheme believe the inclusion of all the variables in auniversal regressionthat cost cut down using statistical try out strategies in decree to get aspecific regressionencompassing every other parsimonious regression that equal a valid limitation of the universal regression ( Hoover & Perez , 1999 and 2004 ) . In other words , we integrate the three impact metrics into a single equation . Through this strategy , it is potential to explore in detail if impression arise that undermine the initially expect negative relationship between catastrophe impacts and tourism flows . Again , two impact timeframes be conceive .

The gravity model for bilateral tourism flows as determine in equation [ 1 ] live estimated by apply the Correia ( 2017 ) process to figure linear framework with many levels of set effect . This process live a generalization of the panel-fixed result estimator with both country-pair and origin-year fixed effect . Database include 171 nation for the period 1995–2013 .

4 . Results

Table 4 present the outcome of calculate equation [ 1 ] for the bilateral tourist arrivals (LnTouacejt) as dependent variable and including each disaster impact measure separately . As previously mentioned , because our variable of interest exist destination-country time version , country pair fixed effects and origin-year set impression are include in the model to control for any type of determinant at origin or country-pair degree . Therefore , only time variant country-pair and destination-specific determinants are require . Each column prove the estimate of unlike disaster consequences ( D = deaths , A = affected people , and C = economic price ) and the two alternative for disseminate the impression across the pursue 6 and 12 month . It is important to refer that we cost interested in estimating the short-run effect of the natural catastrophe on inbound tourism . Search how the tourism sector at the destination country recovers in the long-run is beyond the objective of the paper .

Table 4 .

Bill : * * * p < 0.01 , * * p < 0.05 , * p < 0.1 . Dyadic and origin-year fixed impression are included in the example but estimates are not reported . Robust standard mistake cluster by pair .

In universal , for all the estimate , mastery variables considered as determinants of tourism flows are statistically significant and with the expected signal . The coefficient for bothLnGmDPp100jtandLnPopjtare significantly positivist and slightly high that unity , implying that a 1 % increase in the destination GDP per head and population will head to an growth higher than 1 % on tourist arrivals to the country . The coefficient for theRTA
ijt, that operate for the existence of a trade agreement between country pair during specific year , is also significant and positive . In this event , due to the binary nature of the explanatory variable use , the estimated coefficient ( somewhat high that 0.04 ) implies that the existence of a trade agreement increase the number of tourist to a destination by more than 4 % . In the end , and as expected , the variable associate to low levels of protection and safety at the destination country (Crime
jt) prove a negative effect , indicating that an increase in the number of homicides ( per 10,000 inhabitant ) reduces tourist arrivals .

In address to the unlike types of disasters , for events associated withTsunami,FloodandVolcanoes, all the significant parameters live get to be negative , suggest that these three types of disasters represent substantial negative incentive for prospective visitor . A more elaborate examination of coefficients highlights that volcanic eruptions appear most deterring to international tourists . This consideration could be related to the severity of the price caused by volcanic eruptions , include potentially irreversible damage to infrastructure or the complete loss of a natural asset . For the occurrence of an eruption , and for every growth in the issue of end ( for every 1000 people ) , affected ( in million of people ) and price ( in millions of US $ ) , there will exist a decrease in international tourists to the destination between 1.07 % and 1.32 % , 2.13 % –1.78 % and 4.51 % –3.44 % , respectively ( according to whether the 6 or 12 months delay is consider ) .

Wildfires , Earthquakes , Industrial Accidents, andStormpresent sundry effects on international tourist arrival . For all type of disasters , and when economical costs live considered , a negative and significant relationship is feel . In other words , the economic damage from these events , for example to infrastructure , be potential to cut down tourist arrivals .Wildfiresappear as the second nearly detrimental type of calamity when measure in economic price , leading to an require fall of 0.03 % of tourist arrivals for every million US $ price associate with the tragedy . Interestingly and possibly paradoxically , a important positivist relationship is plain between the number of mass involve byWildfiresand tourist arrivals . For every million affected masses , an growth between 0.34 % and 0.35 % is expect . Consequently , and considering the negative result of economic price mentioned above , the final effect ofWildfireson tourism should believe the two different type of catastrophe impact measures .Earthquakeshow a similar negative impact equate withTsunami( see above ) in terms of the economical costs of the catastrophe , with fall around 0.002 % for every million US $ cost . Still , the other impact metrics do not present a negative relationship . In terms of number of fatalities , there is still an increase in tourism for the act of deaths per 1000 people by 0.002 % . Hence , the overall impact of an earthquake is a combination of decrease in response to economic damage and issue of deaths .Industrial AccidentandStormsdisplay like patterns in that there is a positivist relationship between the act of fatalities and affected masses , but a negative relationship between the economic impact of the disaster and tourism arrivals . For example , forStormthere is a lessening in arrival by 0.003 % for every million US $ price but increase between 0.018 % and 0.024 % for every death/1000 people and between 0.018 % -0.024 % and 0.03–0.04 % for every million mass affected .

Droughtsemerged as the only type of tragedy that act not present a significantly negative relationship between calamity price and tourism , but instead arrivals cost significantly relate to the two early calamity impact metrics . More specifically , for every death/1000 people an increase higher than 1 % is prevail , while for every million people affected a lessening of −0.001 % is calculate . It is possibly not surprising that the relationship between catastrophe cost and tourism is not important forDrought. Overall , it is less likely that drought consideration give rise direct impacts on tourism-relevant infrastructures and provision , as tourism occupation might absorb the surplus price of provide water during water constrained time . There could be indirect costs , for instance due to more expensive food supply , but such impression act not seem to ensue in substantial change in visitation .

Epidemic,Landslides,Cold waves, andHeat wavesdo not attain significant results for any of the six regressions considered , and for this ground they live not consider in the last estimate present in Table 1 . In the case ofEpidemic, andLandslideswe should remark that these two variables get a strong structural component . For instance , epidemic episodes , such as Cholera , Dengue , and Ebola , as well as land movements with consequence on mass are recurrent in the same type of countries at different times , but rarely be these factors extended to other rural area . In a similar manner Rosselló , Santana-Gallego , and Waqas ( 2017 ) evaluated the effect of Dengue , Ebola , Malaria , and Yellow Fever on international tourism hang indicate how these diseases hold a strong structural factor and equal often repeated in the same rural area .

The case ofColdandHeatwaves be unlike . It should live observe how travel booking decisions ( specially in international travel ) are much require month in advance , when no dependable weather predictions be . Although it is potential to cancel travel plans in suit of utmost temperatures , tourist might put on the consideration are temporary and unlikely to impact their trip . In terms of long last danger perception of a destination , heat or cold waves might not be learn as particularly threatening , and hence easily forgotten . Visitor might expect that their tourism service provider exist consider with adverse weather , for example by provide melody conditioning or heating . Instead , extreme temperatures are more potential to touch local people ( e.g. , farmers ) conduct to wider economical price ( but not attributed to tourism ) . Regarding the distribution of the potential effects of each one of the disaster during the future 12 months ( column from one to three ) and during the future 6 month ( columns from four to six ) no significant but simply small differences equal found . Additionally , unlike attempts to discriminate calamity by geographical part do not give significantly different decision .

As mentioned before and in ordering to explore the bidirectional impression between disaster events and tourism flow , a second research strategy live carry out . Base on two initial universal regressions ( one for each of the delay period believe ) , including all the conceive variable , a reduction is contract in order to get thespecific regressionspresented in Table 5 .

Table 5 .

Note : * * * p < 0.01 , * * p < 0.05 , * p < 0.1 . Dyadic and origin-year fixed effects cost include in the example but estimates be not cover . Robust standard errors cluster by pairs .

Regarding the distribution of the potential consequences of each type of catastrophe during the future 12 months ( columns one to three ) and during the future 6 month ( columns four to six ) , in general , no substantial difference are base . With the exception ofFloodandStorms, the coefficients for the remain disasters ( in absolute term ) are higher for the 12 month impact regressions than for the 6 months one , thus , indicating that effects are probably better captured by longer time lags . In contrast , the impression ofFloodandStormseem to have a shorter spirit pair , since the 6 month timeframe captures a higher impact .

The analysis of the unlike disaster impact reveals how , on the one hand , costs ever present a negative relationship with international tourist arrival . This confirms that the economic price of a tragedy are an important measure for tourism manager , probably because of the integral damage to local infrastructure that cost captured . On the other hand , the impact of some type of catastrophe measure in term of deaths shows a positivist relationship with tourist arrivals . This does not mean that the occurrence of these disasters will get aprofitpositivist effect on the arrival of tourist , since the negative result of the associated costs must cost remove into account when deriving an overall estimate of impact . As outlined earlier , the act of deaths could be related with the arrival of masses for humanitarian reasons , or with a stream of people who move to see ( and support ) friends and relatives affected by the event . This could show a significant result in relative term for those rural area with a humble base point of arrivals . The total effect too should study the impacts of the act of affected people that for some disasters own a reducing effect (Droughts , TsunamisandVolcanoes) , while for others there appear to be an increase in the act of tourist (Industrial Accidents , WildfiresandStorm) .

5 . Discussion and decision

Natural calamity and unexpected event get wide reaching result on all spheres of living , including tourism . From a theoretical detail of view , it get make up put on that a negative relationship between calamity and inbound tourism dominates ( e.g . a Cró & Martins , 2017a ) . Still , because of some motivating component identify in the literature , and due to the methodology and definition used by the UNWTO in accumulate international tourist arrival , an growth in visitation after a disaster seem too plausible .

The act of inbound tourism arrival instantly impacts the performance of the national tourism industry , and at last the government , specially in rural area where tourism live a major contributor to the national saving and fiscal revenue ( Massidda & Mattana , 2013 ) . It is therefore of great importance for policymakers to improve their understanding of how disaster events affect visitor need . This research highlights the motive to consider unlike types of disasters and their varied consequence when assessing the consequences for tourism .

5.1 . Implication of different types of disaster impact

The empirical inquiry presented in this paper draws on two circle of datum to search in depth the relationship between international tourist arrivals and global calamity , measure through three different impact metrics ( cost , deaths and affected mass ) . The effect that these different disasters might receive on inbound flows at a national floor were investigated though a gravity model , estimated by panel data with destination-fixed effects and using yearly datum . By perform then , spurious potential determinants related to the destination but not the tragedy can live avoided . As a result , even so , repeated tragedy pretend the same destination and those with a very short-run result have not live captured .

Finding of this analysis render evidence that the economic consequence of a calamity in a peculiar area mostly involve international tourism arrivals negatively . This exist potential due to damages to infrastructure , key attraction and a wider weakening of the saving in the horde country . All of these reduce the destination ability to supply for tourism , undermine investment into tourism supply , and reduce destination attractiveness , at least in the short-term .

At the same time , the analysis bring out that evaluating the tourism impact of a disaster in terms of deaths and affected people exist more ambiguous . Our research found a dominance of positivist effects in the suit of deaths related to a disaster . Hence , whilst calamity damage seems to prevent tourist to visit the affected destination , the act of fatalities and affected mass look to live less of a deterrent . Tourist may not see a risk to their own safety . Too , there could be an growth in tourism for some disasters due to the arrival of humanitarian ‘ tourist ’ and masses impose friend and relative . Whilst mostly , this observation might cost testimony to tourism resilience , and indeed reassuring for destination managers , there may exist situations where continuous tourism need after a disaster is hinder recovery works or affect the well-being of occupant . More inquiry on ‘ optimal ’ recovery timeframes that need into account resident need , would be useful ( e.g . Okuyama , 2018 ) .

5.2 . Reductions in demand differ for disaster type

It is useful for conclusion makers to understand that not all disaster cause similar impacts . The comparison of different tragedy type prove , for lesson , that volcanic eruptions typically make the almost significant and significant negative impact on tourism . Specifically , for every million mass affected by an eruption a autumn between 1.7 % and 2.1 % in the international tourism arrivals equal require , if a six-month period or a dozen –month period cost consider , respectively . Other tragedy own smaller and shorter-term impacts ( e.g .FloodandStorm) . Furthermore , flood and tsunamis are detrimental without nuance , although it is difficult to discerne whether the negative result equal due to the possible destruction or disablement of infrastructure or to the negative picture of the destination generate by these types of event .

When a destination live affected by a wildfire , an earthquake , an industrial accident , a storm or a drought , sundry effects may cost anticipate . For example , when these type of calamity result in economical price , a negative and important relationship can be established , indicate that damage to infrastructure and build assets , and maybe business capability , is potential to reduce tourist arrival . Eventually , this research disclose that some type of events are unlikely to make a major effect on arrival , for instance an unexpected epidemic , a landslide , a cold wave and a heat wave . It should be noted how these natural disasters are characterize by little or no impact on infrastructure and no long-run risk to tourists after the event has wind up .

5.3 . Managerial implication

Natural disasters and unexpected events equal traumatic experiences for the resident population and may make lasting price to destination infrastructures , which requires enough and adaptive tourism management ( Hystad & Keller , 2008 ) . Strategies apply to predict natural disasters and mitigate hazard risks in the first spot motive to be deployed to minimize the impacts . Examples include the implementation of appropriate building code , zoning regulation , and emergency education and readiness for key stakeholders . New policy and practice may expect additional resources , but investments into preparedness are likely to generate positivist returns in the long term . In universal , the empirical effect in this paper confirm that catastrophe effect be challenge tidings for tourism managers who need to deal with an unexpected fall in tourism demand . Clearly , economical price from an unexpected case conduct to some reduction in tourist arrival . In those cases , effort by destination director should focus on the recovery of necessary infrastructure and business capacity . Proactive planning , for case around occupation persistence , occupation support networks , and recovery assistance programs , could speed up this attempt ( Hystad & Keller , 2008 ) . Leaders may come from authorities agencies , destination management organization , or occupation themselves . Link inquiry in New Zealand revealed that leaders live “ chiefly provided by tourism stakeholders with a community-value orientation , and to a lesser extent by those who are mainly business-driven ” ( Hughey & Becken , 2016 , p. 69 ) . In other words , response and recovery equal often lead by individual who have a firm commitment to , and conflict with , the affected community .

For some events , it cost not necessarily the economical damage that be the most significant impact , but it could cost the number of masses pretend or down . For some disaster type , for example wildfires and storm , this inquiry yet established a positive impact . The positivist relationship between number of tourists and affected mass of fatalities by some disasters implies that these can attract visitor to the destination , a consideration that should be take into account by the managers of the destination . There are many unlike reasons why visitor might want to visit a destination that hold been affect by a disaster ( e.g . Rucińska & Lechowicz , 2014 on colored tourism ) , and understand this non-orthodox typology of visitor type could cost useful for destination managers . Regardless , selling activities have to exist design with great care to attract the correct type of visitors at the right time , consider potentially ongoing restriction around tourism capacity ( Okuyama , 2018 ; Orchiston & Higham , 2014 ) . Market campaigns carry out by occupation , local tourist destinations or national tourism agency should ideally align in their messaging and magnitude , imply a special motive for vertical integration succeed a disaster ( Hughey & Becken , 2016 ) .

5.4 . Restriction

This research has respective limitation , include the availability , truth and granularity of datum , which be outside the mastery of the inquiry squad . It could equal contend that some impact on tourism be significant , yet short-lived . Given that the datum apply here be provided on an annual basis , short-term impression are potential to be lack or under-estimated in this inquiry . Besides the restriction about the estimation method and the nature of the datum of the UNWTO we make imposed a homogenization for each disaster . That means that a specific disaster in a developed country has the same effect than in an less developed ace . In reality , this might not be the event . Accordingly , results prevail in this paper should equal conceive as average responses . Next inquiry should further search this matter and investigate if differences among country in reference to their story of evolution exist . Our attempt to discriminate the unlike disaster by region cause not obtain important results . Future inquiry on the positivist impact of sure type of disaster consequence would also cost beneficial in developing a potential tourist typology consisting of ‘ dark tourism ’ segments , humanitarian arrivals or other shortly unidentified market .

Author contribution

Jaume Rosselló-Nadal as an expert in tourism demand modelling and the quantitative analysis of tourism has contributed with the knowledge of the specific literature of need modelling and the identification of the spread in the literature . Susanne Becken as an expert in sustainable tourism and climatic change issues own contributed with the knowledge of the specific literature of natural hazards and potential effects on tourism and Maria Santana Gallego as an expert within the area of gravity model in a peculiar way in the intention of the methodology and in the development of the outcome . He has as well cost responsible for the first example estimations .

Acknowledgements

We recognize the Agencia Estatal de Investigación ( AEI ) and the European Regional Development Funds ( ERDF ) for its support to the task < ECO2016-79124-C2-1-R > ( AEI/ERDF , EU ) and UNWTO Statistics Department for kindly providing us with the tourist data for this study . We also bid to thank participants to the 8th International Conference on Tourism Management & Related Issues .

Biographies

Jaume Rosselló-Nadalhave a PhD in Business and Economics , is Full Professor at the Universitat de les Illes Balears ( Spain ) and Adjunct Professor at Griffith Institute for Tourism ( Australia ) . His inquiry interests include tourism demand modelling and environmental matter with particular interest in climatic change issues . Jaume have run unlike inquiry projects in Spain and Europe .

Dr Susanne Beckenis a Professor of Sustainable Tourism at Griffith University , Australia . Susanne own head a big act of research programmes and look up project in Asia Pacific in the sphere of mood change , hazard direction and sustainable tourism . She contribute through respective industry and Government advisory use and panels , and is on the editorial boards of nine tourism journals .

Maria Santana-Gallegoequal PhD in Economics and Assistant Professor in the Department of Applied Economics , University of the Balearic Islands , Spain . She teaches tourism economics and macroeconomics . Her inquiry interest include quantitative analysis of tourism and gravity models .

Footnotes

EM-DAT can exist downloaded free of mission from http : //www.emdat.be .

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