tourism related economic strategies

Reimagining the $9 trillion tourism economy—what will it take?

Tourism made up 10 percent of global GDP in 2019 and was worth almost $9 trillion, 1 See “Economic impact reports,” World Travel & Tourism Council (WTTC), wttc.org. making the sector nearly three times larger than agriculture. However, the tourism value chain of suppliers and intermediaries has always been fragmented, with limited coordination among the small and medium-size enterprises (SMEs) that make up a large portion of the sector. Governments have generally played a limited role in the industry, with partial oversight and light-touch management.

COVID-19 has caused an unprecedented crisis for the tourism industry. International tourist arrivals are projected to plunge by 60 to 80 percent in 2020, and tourism spending is not likely to return to precrisis levels until 2024. This puts as many as 120 million jobs at risk. 2 “International tourist numbers could fall 60-80% in 2020, UNWTO reports,” World Tourism Organization, May 7, 2020, unwto.org.

Reopening tourism-related businesses and managing their recovery in a way that is safe, attractive for tourists, and economically viable will require coordination at a level not seen before. The public sector may be best placed to oversee this process in the context of the fragmented SME ecosystem, large state-owned enterprises controlling entry points, and the increasing impact of health-related agencies. As borders start reopening and interest in leisure rebounds in some regions , governments could take the opportunity to rethink their role within tourism, thereby potentially both assisting in the sector’s recovery and strengthening it in the long term.

In this article, we suggest four ways in which governments can reimagine their role in the tourism sector in the context of COVID-19.

1. Streamlining public–private interfaces through a tourism nerve center

Before COVID-19, most tourism ministries and authorities focused on destination marketing, industry promotions, and research. Many are now dealing with a raft of new regulations, stimulus programs, and protocols. They are also dealing with uncertainty around demand forecasting, and the decisions they make around which assets—such as airports—to reopen will have a major impact on the safety of tourists and sector employees.

Coordination between the public and private sectors in tourism was already complex prior to COVID-19. In the United Kingdom, for example, tourism falls within the remit of two departments—the Department for Business, Energy, and Industrial Strategy (BEIS) and the Department for Digital, Culture, Media & Sport (DCMS)—which interact with other government agencies and the private sector at several points. Complex coordination structures often make clarity and consistency difficult. These issues are exacerbated by the degree of coordination that will be required by the tourism sector in the aftermath of the crisis, both across government agencies (for example, between the ministries responsible for transport, tourism, and health), and between the government and private-sector players (such as for implementing protocols, syncing financial aid, and reopening assets).

Concentrating crucial leadership into a central nerve center  is a crisis management response many organizations have deployed in similar situations. Tourism nerve centers, which bring together public, private, and semi-private players into project teams to address five themes, could provide an active collaboration framework that is particularly suited to the diverse stakeholders within the tourism sector (Exhibit 1).

We analyzed stimulus packages across 24 economies, 3 Australia, Bahrain, Belgium, Canada, Egypt, Finland, France, Germany, Hong Kong, Indonesia, Israel, Italy, Kenya, Malaysia, New Zealand, Peru, Philippines, Singapore, South Africa, South Korea, Spain, Switzerland, Thailand, and the United Kingdom. which totaled nearly $100 billion in funds dedicated directly to the tourism sector, and close to $300 billion including cross-sector packages with a heavy tourism footprint. This stimulus was generally provided by multiple entities and government departments, and few countries had a single integrated view on beneficiaries and losers. We conducted surveys on how effective the public-sector response has been and found that two-thirds of tourism players were either unaware of the measures taken by government or felt they did not have sufficient impact. Given uncertainty about the timing and speed of the tourism recovery, obtaining quick feedback and redeploying funds will be critical to ensuring that stimulus packages have maximum impact.

2. Experimenting with new financing mechanisms

Most of the $100 billion stimulus that we analyzed was structured as grants, debt relief, and aid to SMEs and airlines. New Zealand has offered an NZ $15,000 (US $10,000) grant per SME to cover wages, for example, while Singapore has instituted an 8 percent cash grant on the gross monthly wages of local employees. Japan has waived the debt of small companies where income dropped more than 20 percent. In Germany, companies can use state-sponsored work-sharing schemes for up to six months, and the government provides an income replacement rate of 60 percent.

Our forecasts indicate that it will take four to seven years for tourism demand to return to 2019 levels, which means that overcapacity will be the new normal in the medium term. This prolonged period of low demand means that the way tourism is financed needs to change. The aforementioned types of policies are expensive and will be difficult for governments to sustain over multiple years. They also might not go far enough. A recent Organisation for Economic Co-operation and Development (OECD) survey of SMEs in the tourism sector suggested more than half would not survive the next few months, and the failure of businesses on anything like this scale would put the recovery far behind even the most conservative forecasts. 4 See Tourism policy responses to the coronavirus (COVID-19), OECD, June 2020, oecd.org. Governments and the private sector should be investigating new, innovative financing measures.

Revenue-pooling structures for hotels

One option would be the creation of revenue-pooling structures, which could help asset owners and operators, especially SMEs, to manage variable costs and losses moving forward. Hotels competing for the same segment in the same district, such as a beach strip, could have an incentive to pool revenues and losses while operating at reduced capacity. Instead of having all hotels operating at 20 to 40 percent occupancy, a subset of hotels could operate at a higher occupancy rate and share the revenue with the remainder. This would allow hotels to optimize variable costs and reduce the need for government stimulus. Non-operating hotels could channel stimulus funds into refurbishments or other investment, which would boost the destination’s attractiveness. Governments will need to be the intermediary between businesses through auditing or escrow accounts in this model.

Joint equity funds for small and medium-size enterprises

Government-backed equity funds could also be used to deploy private capital to help ensure that tourism-related SMEs survive the crisis (Exhibit 2). This principle underpins the European Commission’s temporary framework for recapitalization of state-aided enterprises, which provided an estimated €1.9 trillion in aid to the EU economy between March and May 2020. 5 See “State aid: Commission expands temporary framework to recapitalisation and subordinated debt measures to further support the economy in the context of the coronavirus outbreak,” European Commission, May 8, 2020, ec.europa.eu. Applying such a mechanism to SMEs would require creating an appropriate equity-holding structure, or securitizing equity stakes in multiple SMEs at once, reducing the overall risk profile for the investor. In addition, developing a standardized valuation methodology would avoid lengthy due diligence processes on each asset. Governments that do not have the resources to co-invest could limit their role to setting up those structures and opening them to potential private investors.

3. Ensuring transparent, consistent communication on protocols

The return of tourism demand requires that travelers and tourism-sector employees feel—and are—safe. Although international organizations such as the International Air Transport Association (IATA), and the World Travel & Tourism Council (WTTC) have developed a set of guidelines to serve as a baseline, local regulators are layering additional measures on top. This leads to low levels of harmonization regarding regulations imposed by local governments.

Our surveys of traveler confidence in the United States  suggests anxiety remains high, and authorities and destination managers must work to ensure travelers know about, and feel reassured by, protocols put in place for their protection. Our latest survey of traveler sentiment in China  suggests a significant gap between how confident travelers would like to feel and how confident they actually feel; actual confidence in safety is much lower than the expected level asked a month before.

One reason for this low level of confidence is confusion over the safety measures that are currently in place. Communication is therefore key to bolstering demand. Experience in Europe indicates that prompt, transparent, consistent communications from public agencies have had a similar impact on traveler demand as CEO announcements have on stock prices. Clear, credible announcements regarding the removal of travel restrictions have already led to increased air-travel searches and bookings. In the week that governments announced the removal of travel bans to a number of European summer destinations, for example, outbound air travel web search volumes recently exceeded precrisis levels by more than 20 percent in some countries.

The case of Greece helps illustrate the importance of clear and consistent communication. Greece was one of the first EU countries to announce the date of, and conditions and protocols for, border reopening. Since that announcement, Greece’s disease incidence has remained steady and there have been no changes to the announced protocols. The result: our joint research with trivago shows that Greece is now among the top five summer destinations for German travelers for the first time. In July and August, Greece will reach inbound airline ticketing levels that are approximately 50 percent of that achieved in the same period last year. This exceeds the rate in most other European summer destinations, including Croatia (35 percent), Portugal (around 30 percent), and Spain (around 40 percent). 6 Based on IATA Air Travel Pulse by McKinsey. In contrast, some destinations that have had inconsistent communications around the time frame of reopening have shown net cancellations of flights for June and July. Even for the high seasons toward the end of the year, inbound air travel ticketing barely reaches 30 percent of 2019 volumes.

Digital solutions can be an effective tool to bridge communication and to create consistency on protocols between governments and the private sector. In China, the health QR code system, which reflects past travel history and contact with infected people, is being widely used during the reopening stage. Travelers have to show their green, government-issued QR code before entering airports, hotels, and attractions. The code is also required for preflight check-in and, at certain destination airports, after landing.

4. Enabling a digital and analytics transformation within the tourism sector

Data sources and forecasts have shifted, and proliferated, in the crisis. Last year’s demand prediction models are no longer relevant, leaving many destinations struggling to understand how demand will evolve, and therefore how to manage supply. Uncertainty over the speed and shape of the recovery means that segmentation and marketing budgets, historically reassessed every few years, now need to be updated every few months. The tourism sector needs to undergo an analytics transformation to enable the coordination of marketing budgets, sector promotions, and calendars of events, and to ensure that products are marketed to the right population segment at the right time.

Governments have an opportunity to reimagine their roles in providing data infrastructure and capabilities to the tourism sector, and to investigate new and innovative operating models. This was already underway in some destinations before COVID-19. Singapore, for example, made heavy investments in its data and analytics stack over the past decade through the Singapore Tourism Analytics Network (STAN), which provided tourism players with visitor arrival statistics, passenger profiling, spending data, revenue data, and extensive customer-experience surveys. During the COVID-19 pandemic, real-time data on leading travel indicators and “nowcasts” (forecasts for the coming weeks and months) could be invaluable to inform the decisions of both public-sector and private-sector entities.

This analytics transformation will also help to address the digital gap that was evident in tourism even before the crisis. Digital services are vital for travelers: in 2019, more than 40 percent of US travelers used mobile devices to book their trips. 7 Global Digital Traveler Research 2019, Travelport, marketing.cloud.travelport.com; “Mobile travel trends 2019 in the words of industry experts,” blog entry by David MacHale, December 11, 2018, blog.digital.travelport.com. In Europe and the United States, as many as 60 percent of travel bookings are digital, and online travel agents can have a market share as high as 50 percent, particularly for smaller independent hotels. 8 Sean O’Neill, “Coronavirus upheaval prompts independent hotels to look at management company startups,” Skift, May 11, 2020, skift.com. COVID-19 is likely to accelerate the shift to digital as travelers look for flexibility and booking lead times shorten: more than 90 percent of recent trips in China  were booked within seven days of the trip itself. Many tourism businesses have struggled to keep pace with changing consumer preferences around digital. In particular, many tourism SMEs have not been fully able to integrate new digital capabilities in the way that larger businesses have, with barriers including language issues, and low levels of digital fluency. The commission rates on existing platforms, which range from 10 percent for larger hotel brands to 25 percent for independent hotels, also make it difficult for SMEs to compete in the digital space.

Governments are well-positioned to overcome the digital gap within the sector and to level the playing field for SMEs. The Tourism Exchange Australia (TXA) platform, which was created by the Australian government, is an example of enabling at scale. It acts as a matchmaker, connecting suppliers with distributors and intermediaries to create packages attractive to a specific segment of tourists, then uses tourist engagement to provide further analytical insights to travel intermediaries (Exhibit 3). This mechanism allows online travel agents to diversify their offerings by providing more experiences away from the beaten track, which both adds to Australia’s destination attractiveness, and gives small suppliers better access to customers.

Governments that seize the opportunity to reimagine tourism operations and oversight will be well positioned to steer their national tourism industries safely into—and set them up to thrive within—the next normal.

Download the article in Arabic  (513KB)

Margaux Constantin is an associate partner in McKinsey’s Dubai office, Steve Saxon is a partner in the Shanghai office, and Jackey Yu  is an associate partner in the Hong Kong office.

The authors wish to thank Hugo Espirito Santo, Urs Binggeli, Jonathan Steinbach, Yassir Zouaoui, Rebecca Stone, and Ninan Chacko for their contributions to this article.

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• Published: 24 February 2024

Modeling the link between tourism and economic development: evidence from homogeneous panels of countries

• Pablo Juan Cárdenas-García   ORCID: orcid.org/0000-0002-1779-392X 1 ,
• Juan Gabriel Brida 2 &
• Verónica Segarra 2  

Humanities and Social Sciences Communications volume  11 , Article number:  308 ( 2024 ) Cite this article

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• Development studies

Having previously analyzed the relationship between tourism and economic growth from distinct perspectives, this paper attempts to fill the void existing in scientific research on the relationship between tourism and economic development, by analyzing the relationship between these variables using a sample of 123 countries between 1995 and 2019. The Dumistrescu and Hurlin adaptation of the Granger causality test was used. This study takes a critical look at causal analysis with heterogeneous panels, given the substantial differences found between the results of the causal analysis with the complete panel as compared to the analysis of homogeneous country groups, in terms of their dynamics of tourism specialization and economic development. On the one hand, a one-way causal relationship exists from tourism to development in countries having low levels of tourism specialization and development. On the other hand, a one-way causal relationship exists by which development contributes to tourism in countries with high levels of development and tourism specialization.

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Introduction

Across the world, tourism is one of the most important sectors. It has undergone exponential growth since the mid-1900s and is currently experiencing growth rates that exceed those of other economic sectors (Yazdi, 2019 ).

Today, tourism is a major source of income for countries that specialize in this sector, generating 5.8% of the global GDP (5.8 billion US$) in 2021 (UNWTO, 2022 ) and providing 5.4% of all jobs (289 million) worldwide. Although its relevance is clear, tourism data have declined dramatically due to the recent impact of the Covid-19 health crisis. In 2019, prior to the pandemic (UNWTO, 2020 ), tourism represented 10.3% of the worldwide GDP (9.6 billion US$), with the number of tourism-related jobs reaching 10.2% of the global total (333 million). With the evolution of the pandemic and the regained trust of tourists across the globe, it is estimated that by 2022, approximately 80% of the pre-pandemic figures will be attained, with a full recovery being expected by 2024 (UNWTO, 2022 ).

Given the importance of this economic activity, many countries consider tourism to be a tool enabling economic growth (Corbet et al., 2019 ; Ohlan, 2017 ; Xia et al., 2021 ). Numerous works have analyzed the relationship between increased tourism and economic growth; and some systematic reviews have been carried out on this relationship (Brida et al., 2016 ; Ahmad et al., 2020 ), examining the main contributions over the first two decades of this century. These reviews have revealed evidence in this area: in some cases, it has been found that tourism contributes to economic growth while, in other cases, the economic cycle influences tourism expansion. Moreover, other works offer evidence of a bi-directional relationship between these variables.

Distinct international organizations (OECD, 2010 ; UNCTAD, 2011 ) have suggested that not only does tourism promote economic growth, it also contributes to socio-economic advances in the host regions. This may be the real importance of tourism, since the ultimate objective of any government is to improve a country’s socio-economic development (UNDP, 1990 ).

The development of economic and other policies related to the economic scope of tourism, in addition to promoting economic growth, are also intended to improve other non-economic factors such as education, safety, and health. Improvements in these factors lead to a better life for the host population (Lee, 2017 ; Todaro and Smith, 2020 ).

Given tourism’s capacity as an instrument of economic development (Cárdenas-García et al., 2015 ), distinct institutions such as the United Nations Conference on Trade and Development, the United Nations Economic Commission for Africa, the United Nations World Tourism Organization and the World Bank, have begun funding projects that consider tourism to be a tool for improved socio-economic development, especially in less advanced countries (Carrillo and Pulido, 2019 ).

This new trend within the scientific literature establishes, firstly, that tourism drives economic growth and, secondly, that thanks to this economic growth, the population’s economic conditions may be improved (Croes et al., 2021 ; Kubickova et al., 2017 ). However, to take advantage of the economic growth generated by tourism activity to boost economic development, specific policies should be developed. These policies should determine the initial conditions to be met by host countries committed to tourism as an instrument of economic development. These conditions include regulation, tax system, and infrastructure provision (Cárdenas-García and Pulido-Fernández, 2019 ; Lejárraga and Walkenhorst, 2013 ; Meyer and Meyer, 2016 ).

Therefore, it is necessary to differentiate between the analysis of the relationship between tourism and economic growth, whereby tourism boosts the economy of countries committed to tourism, traditionally measured through an increase in the Gross Domestic Product (Alcalá-Ordóñez et al., 2023 ; Brida et al., 2016 ), and the analysis of the relationship between tourism and economic development, which measures the effect of tourism on other factors (not only economic content but also inequality, education, and health) which, together with economic criteria, serve as the foundation to measure a population’s development (Todaro and Smith, 2020 ).

However, unlike the analysis of the relationship between tourism and economic growth, few empirical studies have examined tourism’s capacity as a tool for development (Bojanic and Lo, 2016 ; Cárdenas-García and Pulido-Fernández, 2019 ; Croes, 2012 ).

To help fill this gap in the literature analyzing the relationship between tourism and economic development, this work examines the contribution of tourism to economic development, given that the relationship between tourism and economic growth has been widely analyzed by the scientific literature. Moreover, given that the literature has demonstrated that tourism contributes to economic growth, this work aims to analyze whether it also contributes to economic development, considering development in the broadest possible sense by including economic and socioeconomic variables in the multi-dimensional concept (Wahyuningsih et al., 2020 ).

Therefore, based on the results of this work, it is possible to determine whether the commitment made by many international organizations and institutions in financing tourism projects designed to improve the host population’s socioeconomic conditions, especially in countries with lower development levels, has, in fact, resulted in improved development levels.

It also presents a critical view of causal analyses that rely on heterogeneous panels, examining whether the conclusions reached for a complete panel differ from those obtained when analyzing homogeneous groups within the panel. As seen in the literature review analyzing the relationship between tourism and economic development, empirical works using panel data from several countries tend to generalize the results obtained to the entire panel, without verifying whether, in fact, they are relevant for all of the analyzed countries or only some of the same. Therefore, this study takes an innovative approach by examining the panel countries separately, analyzing the homogeneous groups distinctly.

Therefore, this article presents an empirical analysis examining whether a causal relationship exists between tourism and economic development, with development being considered to be a multi-dimensional variable including a variety of factors, distinct from economic ones. Panel data from 123 countries during the 1995–2019 period was considered to examine the causal relationship between tourism and economic development. For this, the Granger causality test was performed, applying the adaptation of this test made by Dumistrescu and Hurlin. First, a causal analysis was performed collectively for all of the countries of the panel. Then, a specific analysis was performed for each of the homogeneous groups of countries identified within the panel, formed according to levels of tourism specialization and development.

This article provides information on tourism’s capacity to serve as an instrument of development, helping to fill the gap in scientific research in this area. It critically examines the use of causal analyses based on heterogeneous samples of countries. This work offers the following main novelties as compared to prior works on the same topic: firstly, it examines the relationship between tourism and economic development, while the majority of the existing works only analyze the relationship between tourism and economic growth; secondly, it analyzes a large sample of countries, representing all of the global geographic areas, whereas the literature has only considered works from specific countries or a limited number of nations linked to a specific country in a specific geographical area, and; thirdly, it analyzes the panel both individually and collectively, for each of the homogenous groups of countries identified, permitting the adoption of specific policies for each group of countries according to the identified relationship, as compared to the majority of works that only analyze the complete panel, generalizing these results for all countries in the sample.

Overall, the results suggest that a relationship exists between tourism and development in all of the analyzed countries from the sample. A specific analysis was performed for homogeneous country groups, only finding a causal relationship between tourism and development in certain country groups. This suggests that the use of heterogeneous country samples in causal analyses may give rise to inappropriate conclusions. This may be the case, for example, when finding causality for a broad panel of countries, although, in fact, only a limited number of panel units actually explain this causal relationship.

The remainder of the document is organized as follows: the next section offers a review of the few existing scientific works on the relationship between tourism and economic development; section three describes the data used and briefly explains the methodology carried out; section four details the results obtained from the empirical analysis; and finally, the conclusions section discusses the main implications of the work, also providing some recommendations for economic policy.

Tourism and economic development

Numerous organizations currently recognize the importance of tourism as an instrument of economic development. It was not until the late 20th century, however, when the United Nations World Tourism Organization (UNWTO), in its Manila Declaration, established that the development of international tourism may “help to eliminate the widening economic gap between developed and developing countries and ensure the steady acceleration of economic and social development and progress, in particular of the developing countries” (UNWTO, 1980 ).

From a theoretical point of view, tourism may be considered an effective activity for economic development. In fact, the theoretical foundations of many works are based on the relationship between tourism and development (Ashley et al., 2007 ; Bolwell and Weinz, 2011 ; Dieke, 2000 ; Sharpley and Telfer, 2015 ; Sindiga, 1999 ).

The link between tourism and economic development may arise from the increase in tourist activity, which promotes economic growth. As a result of this economic growth, policies may be developed to improve the resident population’s level of development (Alcalá-Ordóñez and Segarra, 2023 ).

Therefore, it is essential to identify the key variables permitting the measurement of the level of economic development and, therefore, those variables that serve as a basis for analyzing whether tourism results in improved the socioeconomic conditions of the host population (Croes et al., 2021 ). Since economic development refers not only to economic-based variables, but also to others such as inequality, education, or health (Todaro and Smith, 2020 ), when analyzing the economic development concept, it has been frequently linked to human development (Pulido-Fernández and Cárdenas-García, 2021 ). Thus, we wish to highlight the major advances resulting from the publication of the Human Development Index (HDI) when measuring economic development, since it defines development as a multidimensional variable that combines three dimensions: health, education, and income level (UNDP, 2023 ).

However, despite the importance that many organizations have given to tourism as an instrument of economic development, basing their work on the relationship between these variables, a wide gap continues to exist in the scientific literature for empirical studies that examine the existence of a relationship between tourism and economic development, with very few empirical analyses analyzing this relationship.

First, a group of studies has examined the causal relationship between tourism and economic development, using heterogeneous samples, and without previously grouping the subjects based on homogeneous characteristics. Croes ( 2012 ) analyzed the relationship between tourism and economic development, measured through the HDI, finding that a bidirectional relationship exists for the cases of Nicaragua and Costa Rica. Using annual data from 2001 to 2014, Meyer and Meyer ( 2016 ) performed a collective analysis of South African regions, determining that tourism contributes to economic development. For a panel of 63 countries worldwide, and once again relying on the HDI to define economic development, it was determined that tourism contributes to economic development. Kubickova et al. ( 2017 ), using annual data for the 1995–2007 period, analyzed Central America and Caribbean nations, determining the existence of this relationship by which tourism influences the level of economic development and that the level of development conditions the expansion of tourism. Another work examined nine micro-states of America, Europe, and Africa (Fahimi et al., 2018 ); and 21 European countries in which human capital was measured, as well as population density and tourism income, analyzing panel data and determining that tourism results in improved economic development. Finally, within this first group of works, Chattopadhyay et al. ( 2022 ), using a broad panel of destinations, (133 countries from all geographic areas of the globe) determined that there is no relationship between tourism and economic development.

Studies performed with large country samples that attempt to determine the causal relationship between tourism and economic development by analyzing countries that do not necessarily share homogeneous characteristics, may lead to erroneous conclusions, establishing causality (or not) for panel sets even when this situation is actually explained by a small number of panel units.

Second, another group of studies have analyzed the causal relationship between tourism and economic development, considering the previous limitation, and has grouped the subjects based on their homogeneous characteristics. Cárdenas-García et al. ( 2015 ) used annual data from 1990–2010, in a collective analysis of 144 countries, making a joint panel analysis and then examining two homogeneous groups of countries based on their level of economic development. They determined that tourism contributes to economic development, but only in the most developed group of countries. They determined that tourism contributes to economic development, both for the total sample and for the homogeneous groups analyzed. Pulido-Fernández and Cárdenas-García ( 2021 ), using annual data for the 1993–2017 period, performed a joint analysis of 143 countries, followed by a specific analysis for three groups of countries sharing homogeneous characteristics in terms of tourism growth and development level. They determined that tourism contributes to economic development and that development level conditions tourism growth in the most developed countries.

Finally, another group of studies has analyzed the causal relationship between tourism and economic development in specific cases examined on an individual basis. In a specific analysis by Aruba et al. ( 2016 ), it was determined that tourism contributes to human development. Analyzing Malaysia, Tan et al. ( 2019 ) determined that tourism contributes to development, but only over the short term, and that level of development does not influence tourism growth. Similar results were obtained by Boonyasana and Chinnakum ( 2020 ) in an analysis carried out in Thailand. In this case of Thailand (Boonyasana and Chinnakum, 2020 ), which relied on the HDI, the relationship with economic growth was also analyzed, finding that an increase in tourism resulted in improved economic development. Finally, Croes et al. ( 2021 ), in a specific analysis of Poland, determined that tourism does not contribute to development.

As seen from the analysis of the most relevant publications detailed in Table 1 , few empirical works have considered the relationship between tourism and economic development, in contrast to the numerous works from the scientific literature that have examined the relationship between tourism and economic growth. Most of the works that have empirically analyzed the relationship between tourism and economic development have determined that tourism positively influences the improved economic development in host destinations. To a lesser extent, some studies have found a bidirectional relationship between these variables (Croes, 2012 ; Kubickova et al., 2017 ; Pulido-Fernández and Cárdenas-García, 2021 ) while others have found no relationship between tourism and economic development (Chattopadhyay et al., 2022 ; Croes et al., 2021 ).

Furthermore, in empirical works relying on panel data, the results have tended to be generalized to the entire panel, suggesting that tourism improves economic development in all countries that are part of the panel. This has been the case in all of the examined works, with the exception of two studies that analyzed the panel separately (Cárdenas-García et al., 2015 ; Pulido-Fernández and Cárdenas-García, 2021 ).

Thus, it may be suggested that the use of very large country panels and, therefore, including very heterogeneous destinations, as was the case in the works of Biagi et al. ( 2017 ) using a panel of 63 countries, as well as that of Chattopadhyay et al. ( 2022 ) working with a panel of 133 countries, may lead to error, given that this relationship may only arise in certain destinations of the panel, although it is generalized to the entire panel.

This work serves to fill this gap in the literature by analyzing the panel both collectively and separately, for each of the homogenous groups of countries that have been previously identified.

The lack of relevant works on the relationship between tourism and development, and of studies using causal analyses to examine these variables based on heterogeneous panels, may lead to the creation of rash generalizations regarding the entirety of the analyzed countries. Thus, conclusions may be reached that are actually based on only specific panel units. Therefore, we believe that this study is justified.

Methodological approach

Given the objective of this study, to determine whether a causal relationship exists between tourism and socio-economic development, it is first necessary to identify the variables necessary to measure tourism activity and development level. Thus, the indicators are highly relevant, given that the choice of indicator may result in distinct results (Rosselló-Nadal and He, 2020 ; Song and Wu, 2021 ).

Table 2 details the measurement variables used in this work. Specifically, the following indicators have been used in this paper to measure tourism and economic development:

Measurement of tourist activity. In this work, we decided to consider tourism specialization, examining the number of international tourists received by a country with regard to its population size as the measurement variable.

This information on international tourists at a national level has been provided annually by the United Nations World Tourism Organization since 1995 (UNWTO, 2023 ). This variable has been relativized based on the country’s population, according to information provided by the World Bank on the residents of each country (WB, 2023 ).

Tourism specialization is considered to be the level of tourism activity, specifically, the arrival of tourists, relativized based on the resident population, which allows for comparisons to be made between countries. It accurately measures whether or not a country is specialized in this economic activity. If the variable is used in absolute values, for example, the United States receives more tourists than Malta, so based on this variable it may be that the first country is more touristic than the second. However, in reality, just the opposite happens, Malta is a country in which tourist activity is more important for its economy than it is in the United States, so the use of tourist specialization as a measurement variable classifies, correctly, both Malta as a country with high tourism specialization and to the United States as a country with low tourism specialization.

Therefore, most of the scientific literature establishes the need to use the total number of tourists relativized per capita, given that this allows for the determination of the level of tourism specialization of a tourism destination (Dritsakis, 2012 ; Tang and Abosedra, 2016 ); furthermore, this indicator has been used in works analyzing the relationship between tourism and economic development (for example, Biagi et al., 2017 ; Boonyasana and Chinnakum; 2020 ; Croes et al., 2021 ; Fahimi et al., 2018 ).

Although some works have used other variables to measure tourism, such as tourism income, exports, or tourist spending, these variables are not available for all of the countries making up the panel, so the sample would have been significantly reduced. Furthermore, the data available for these alternative variables do not come from homogeneous databases, and therefore cannot be compared.

Measurement of economic development. In this work, the Human Development Index has been used to measure development.

This information is provided by the United Nations Development Program, which has been publishing it annually at the country level since 1990 (UNDP, 2023 ).

The selection of this indicator to measure economic development is in line with other works that have defended its use to measure the impact on development level (for example, Jalil and Kamaruddin, 2018 ; Sajith and Malathi, 2020 ); this indicator has also been used in works analyzing the relationship between tourism and economic development (for example, Meyer and Meyer, 2016 ; Kubickova et al., 2017 ; Pulido-Fernández and Cárdenas-García, 2021 ).

Although some works have used other variables, such as poverty or inequality, to measure development, these variables are not available for all of the countries forming the panel. Therefore the sample would have been considerably reduced and the data available for these alternative variables do not come from homogenous databases, and therefore comparisons cannot be made.

These indicators are available for a total of 123 countries, across the globe. Thus, these countries form part of the sample analyzed in this study.

As for the time frame considered in this work, two main issues were relevant when determining this period: on the one hand, there is an initial time restriction for the analyzed series, given that information on the arrival of international tourists is only available as of 1995, the first year when this information was provided by the UNWTO. On the other hand, it was necessary to consider the effect of the Covid-19 pandemic and the resulting tourism sector crisis, which also affected the global economy as a whole. Therefore, our time series ended as of 2019, with the overall time frame including data from 1995 to 2019, a 25-year period.

Previous considerations

Caution should be taken when considering causality tests to determine the relationships between two variables, especially in cases in which large heterogeneous samples are used. This is due to the fact that generalized conclusions may be reached when, in fact, the causality is only produced by some of the subjects of the analyzed sample. This study is based on this premise. While heterogeneity in a sample is clearly a very relevant aspect, in some cases, it may lead to conclusions that are less than appropriate.

In this work, a collective causal analysis has been performed on all of the countries of the panel, which consists of 123 countries. However, given that it is a broad sample including countries having major differences in terms of size, region, development level, or tourism performance, the conclusions obtained from this analysis may lead to the generalization of certain conclusions for the entire sample set, when in fact, these relationships may only be the case for a very small portion of the sample. This has been the case in other works that have made generalized conclusions from relatively large samples in which the sample’s homogeneity regarding certain patterns was not previously verified (Badulescu et al., 2021 ; Ömer et al., 2018 ; Gedikli et al., 2022 ; Meyer and Meyer, 2016 ; Xia et al., 2021 ).

Therefore, after performing a collective analysis of the entire panel, the causal relationship between tourism and development was then determined for homogeneous groups of countries that share common patterns of tourism performance and economic development level, to analyze whether the generalized conclusions obtained in the previous section differ from those made for the individual groups. This was in line with strategies that have been used in other works that have grouped countries based on tourism performance (Min et al., 2016 ) or economic development level (Cárdenas-García et al., 2015 ), prior to engaging in causal analyses. To classify the countries into homogeneous groups based on tourism performance and development level, a previous work was used (Brida et al., 2023 ) which considered the same sample of 123 countries, relying on the same data to measure tourism and development level and the same time frame. This guarantees the coherence of the results obtained in this work.

From the entire panel of 123 countries, a total of six country groups were identified as having a similar dynamic of tourism and development, based on qualitative dynamic behavior. In addition, an “outlier” group of countries was found. These outlier countries do not fit into any of the groups (Brida et al., 2023 ). The three main groups of countries were considered, discarding three other groups due to their small size. Table 3 presents the group of countries sharing similar dynamics in terms of tourism performance and economic development level.

Applied methodology

As indicated above, this work uses the Tourist Specialization Rate (TIR) and the Human Development Index (HDI) to measure tourism and economic development, respectively. In both cases, we work with the natural logarithm (l.TIR and l.HDI) as well as the first differences between the variables (d.l.TIR and d.l.HDI), which measure the growth of these variables.

A complete panel of countries is used, consisting of 123 countries. The three main groups indicated in the previous section are also considered (the first of the groups contains 36 countries, the second contains 29 and the last group contains 43).

The Granger causality test ( 1969 ) is used to analyze the relationships between tourism specialization and development level; this test shows if one variable predicts the other, but this should not be confused with a cause-effect relationship.

In the context of panel data, different tests may be used to analyze causality. Most of these tests differ with regard to the assumptions of homogeneity of the panel unit coefficients. While the standard form of the Granger causality test for panels assumes that all of the coefficients are equal between the countries forming part of the panel, the Dumitrescu and Hurlin test (2012) considers that the coefficients are different between the countries forming part of the panel. Therefore, in this work, Granger’s causality is analyzed using the Dumitrescu and Hurlin test (2012). In this test, the null hypothesis is of no homogeneous causality; in other words, according to the null hypothesis, causality does not exist for any of the countries of the analyzed sample whereas, according to the alternative hypothesis, in which the regression model may be different in the distinct countries, causality is verified for at least some countries. The approach used by Dumitrescu and Hurlin ( 2012 ) is more flexible in its assumptions since although the coefficients of the regressions proposed in the tests are constant over time, the possibility that they may differ for each of the panel elements is accepted. This approach has more realistic assumptions, given that countries exhibit different behaviors. One relevant aspect of this type of tests is that they offer no information on which countries lead to the rejection of the lack of causality.

Given the specific characteristics of this type of tests, the presence of very heterogeneous samples may lead to inappropriate conclusions. For example, causality may be assumed for a panel of countries, when only a few of the panel’s units actually explain this relationship. Therefore, this analysis attempts to offer novel information on this issue, revealing that the conclusions obtained for the complete set of 123 countries are not necessarily the same as those obtained for each homogeneous group of countries when analyzed individually.

Given the nature of the variables considered in this work, specifically, regarding tourism, it is expected that a shock taking place in one country may be transmitted to other countries. Therefore, we first analyze the dependency between countries, since this may lead to biases (Pesaran, 2006 ). The Pesaran cross-sectional dependence test (2004) is used for the total sample and for each of the three groups individually.

First, a dependence analysis is performed for the countries of the sample, verifying the existence of dependence between the panel subjects. A cross-sectional dependence test (Pesaran, 2004 ) is used, first for the overall set of countries in the sample and second, for each of the groups of countries sharing homogeneous characteristics.

The results are presented in Table 4 , indicating that the test is statistically significant for the two variables, both for all of the countries in the sample and for each of the homogeneous country clusters, for the variables taken in logarithms as well as their first differences.

Upon rejecting the null hypothesis of non-cross-sectional dependence, it is assumed that a shock occurs in a country that may be transmitted to other countries in the sample. In fact, the lack of dependence between the variables, both tourism and development, is natural in this type of variables, given the economic cycle through the globalization of the economic activity, common regions visited by tourists, the spillover effect, etc.

Second, the stationary nature of the series is tested, given that cross-sectional dependence has been detected between the variables. First-generation tests may present certain biases in the rejection of the null hypothesis since first-generation unit root tests do not permit the inclusion of dependence between countries (Pesaran, 2007 ). On the other hand, second-generation tests permit the inclusion of dependence and heterogeneity. Therefore, for this analysis, the augmented IPS test (CIPS) proposed by Pesaran ( 2007 ) is used. This second-generation unit root test is the most appropriate for this case, given the cross-sectional dependence.

The results are presented in Table 5 , showing the statistics of the CIPS test for both the overall set of countries in the sample and in each of the homogeneous clusters of countries. The results are presented for models with 1, 2, and 3 delays, considering both the variables in the logarithm and their first differences.

As observed, the null hypothesis of unit root is not rejected for the variables in levels, but it is rejected for the first differences. This result is found in all of the cases, for both the total sample and for each of the homogeneous groups, with a significance of 1%. Therefore, the variables are stationary in their first differences, that is, the variables are integrated at order 1. Given that the causality test requires stationary variables, in this work it is used with the variation or growth rate of the variables, that is, the variable at t minus the variable at t−1.

Finally, to analyze Granger’s causality, the test by Dumitrescu and Hurlin ( 2012 ) is used. This test is used to analyze the causal relationship in both directions; that is, whether tourism contributes to economic development and whether the economic development level conditions tourism specialization. Statistics are calculated considering models with 1, 2, and 3 delays. Considering that cross-sectional dependence exists, the p-values are corrected using bootstrap techniques (making 500 replications). Given that the test requires stationary variables, primary differences of both variables were considered.

Table 6 presents the result of the Granger causality analysis using the Dumitrescu and Hurlin test (2012), considering the null hypothesis that tourism does not condition development level, either for all of the countries or for each homogeneous country cluster.

For the entire sample of countries, the results suggest that the null hypothesis of no causality from tourism to development was rejected when considering 3 delays (in other works analyzing the relationship between tourism and development, the null hypothesis was rejected with a similar level of delay: Rivera ( 2017 ) when considering 3–4 delays or Ulrich et al. ( 2018 ) when considering 3 delays). This suggests that for the entire panel, one-way causality exists whereby tourism influences economic development, demonstrating that tourism specialization contributes positively to improving the economic development of countries opting for tourism development. This is in line with the results of Meyer and Meyer ( 2016 ), Ridderstaat et al. ( 2016 ); Biagi et al. ( 2017 ); Fahimi et al. ( 2018 ); Tan et al. ( 2019 ), or Boonyasana and Chinnakum ( 2020 ).

However, the previous conclusion is very general, given that it is based on a very large sample of countries. Therefore, it may be erroneous to generalize that tourism is a tool for development. In fact, the results indicate that, when analyzing causality by homogeneous groups of countries, sharing similar dynamics in both tourism and development, the null hypothesis of no causality from tourism to development is only rejected for the group C countries, when considering three delays. Therefore, the development of generalized policies to expand tourism in order to improve the socioeconomic conditions of any destination type should consider that this relationship between tourism and economic development does not occur in all cases. Thus, it should first be determined if the countries opting for this activity have certain characteristics that will permit a positive relationship between said variables.

In other words, it may be a mistake to generalize that tourism contributes to economic development for all countries, even though a causal relationship exists for the entire panel. Instead, it should be understood that tourism permits an improvement in the level of development only in certain countries, in line with the results of Cárdenas-García et al. ( 2015 ) or Pulido-Fernández and Cárdenas-García ( 2021 ). In this specific work, this positive relationship between tourism and development only occurs in countries from group C, which are characterized by a low level of tourism specialization and a low level of development. Some works have found similar results for countries from group C. For example, Sharma et al. ( 2020 ) found the same relationship for India, while Nonthapot ( 2014 ) had similar findings for certain countries in Asia and the Pacific, which also made up group C. Some recent works have analyzed the relationship between tourism specialization and economic growth, finding similar results. This has been the case with Albaladejo et al. ( 2023 ), who found a relationship from tourism to economic growth only for countries where income is low, and the tourism sector is not yet developed.

These countries have certain limitations since even when tourism contributes to improved economic development, their low levels of tourism specialization do not allow them to reach adequate host population socioeconomic conditions. Therefore, investments in tourism are necessary there in order to increase tourism specialization levels. This increase in tourism may allow these countries to achieve development levels that are similar to other countries having better population conditions.

Therefore, in this group, consisting of 43 countries, a causal relationship exists, given that these countries are characterized by a low level of tourism specialization. However, the weakness of this activity, due to its low relevance in the country, prevents it from increasing the level of economic development. In these countries (details of these countries can be found in Table 3 , specifically, the countries included in Group C), policymakers have to develop policies to improve tourism infrastructure as a prior step to improving their levels of development.

On the other hand, in Table 7 , the results of Granger’s causal analysis based on the Dumitrescu and Hurlin test (2012) are presented, considering the null hypothesis that development level does not condition an increase in tourism, both in the overall sample set and in each of the homogeneous country clusters.

The results indicate that, for the entire country sample, the null hypothesis of no causality from development to tourism is not rejected, for any type of delay. This suggests that, for the entire panel, one-way causality does not exist, with level of development influencing the level of tourism specialization. This is in line with the results of Croes et al. ( 2021 ) in a specific analysis in Poland.

Once again, this conclusion is quite general, given that it has been based on a very broad sample of countries. Therefore, it may be erroneous to generalize that the development level does not condition tourism specialization. Past studies using a large panel of countries, such as the work of Chattopadhyay et al. ( 2022 ) analyzing panel data from 133 countries, have been generalized to all of the analyzed countries, suggesting that economic development level does not condition the arrival of tourists to the destination, although, in fact, this relationship may only exist in specific countries within the analyzed panel.

In fact, the results indicate that, when analyzing causality by homogeneous country groups sharing a similar dynamic, for both tourism and development, the null hypothesis of no causality from development to tourism is only rejected for country group A when considering 2–3 delays. Although the statistics of the test differ, when the sample’s time frame is small, as in this case, the Z-bar tilde statistic is more appropriate.

Thus, development level influences tourism growth in Group A countries, which are characterized by a high level of development and tourism specialization, in accordance with the prior results of Pulido-Fernández and Cárdenas-García ( 2021 ).

These results, suggesting that tourism is affected by economic development level, but only in the most developed countries, imply that the existence of better socioeconomic conditions in these countries, which tend to have better healthcare systems, infrastructures, levels of human resource training, and security, results in an increase in tourist arrivals to these countries. In fact, when traveling to a specific tourist destination, if this destination offers attractive factors and a higher level of economic development, an increase in tourist flows was fully expected.

In this group, consisting of 36 countries, the high development level, that is, the proper provision of socio-economic factors in their economic foundations (training, infrastructures, safety, health, etc.) has led to the attraction of a large number of tourists to their region, making their countries having high tourism specialization.

Although international organizations have recognized the importance of tourism as an instrument of economic development, based on the theoretical relationship between these two variables, few empirical studies have considered the consequences of the relationship between tourism and development.

Furthermore, some hasty generalizations have been made regarding the analysis of this relationship and the analysis of the relationship of tourism with other economic variables. Oftentimes, conclusions have been based on heterogeneous panels containing large numbers of subjects. This may lead to erroneous results interpretation, basing these results on the entire panel when, in fact, they only result from specific panel units.

Given this gap in the scientific literature, this work attempts to analyze the relationship between tourism and economic development, considering the panel data in a complete and separate manner for each of the previously identified country groups.

The results highlight the need to adopt economic policies that consider the uniqueness of each of the countries that use tourism as an instrument to improve their socioeconomic conditions, given that the results differ according to the specific characteristics of the analyzed country groups.

This work provides precise results regarding the need for policymakers to develop public policies to ensure that tourism contributes to the improvement of economic development, based on the category of the country using this economic activity to achieve greater levels of economic development.

Specifically, this work has determined that tourism contributes to economic development, but only in countries that previously had a lower level of tourism specialization and were less developed. This highlights the need to invest in tourism to attract more tourists to these countries to increase their economic development levels. Countries having major natural attraction resources or factors, such as the Dominican Republic, Egypt, India, Morocco, and Vietnam, need to improve their positioning in the international markets in order to attain a higher level of tourism specialization, which will lead to improved development levels.

Furthermore, the results of this study suggest that a greater past economic development level of a country will help attract more tourists to these countries, highlighting the need to invest in security, infrastructures, and health in order for these destinations to be considered attractive and increase tourist arrival. In fact, given their increased levels of development, countries such as Spain, Greece, Italy, Qatar, and Uruguay have become attractive to tourists, with soaring numbers of visitors and high levels of tourism specialization.

Therefore, the analysis of the relationship between tourism and economic development should focus on the differentiated treatment of countries in terms of their specific characteristics, since working with panel data with large samples and heterogenous characteristics may lead to incorrect results generalizations to all of the analyzed destinations, even though the obtained relationship in fact only takes place in certain countries of the sample.

Conclusions and policy implications

Within this context, the objective of this study is twofold: on the one hand, it aims to contribute to the lack of empirical works analyzing the causal relationship between tourism and economic development using Granger’s causality analysis for a broad sample of countries from across the globe. On the other hand, it critically examines the use of causality analysis in heterogeneous samples, by verifying that the results for the panel set differ from the results obtained when analyzing homogeneous groups in terms of tourism specialization and development level.

In fact, upon analyzing the causal relationship from tourism to development, and the causal relationship from development to tourism, the results from the entire panel, consisting of 123 countries, differ from those obtained when analyzing causality by homogeneous country groups, in terms of tourism specialization and economic development dynamics of these countries.

On the one hand, a one-way causality relationship is found to exist, whereby tourism influences economic development for the entire sample of countries, although this conclusion cannot be generalized, since this relationship is only explained by countries belonging to Group C (countries with low levels of tourism specialization and low development levels). This indicates that, although a causal relationship exists by which tourism contributes to economic development in these countries, the low level of tourism specialization does not permit growth to appropriate development levels.

The existence of a causal relationship whereby the increase in tourism precedes the improvement of economic development in this group of countries having a low level of tourism specialization and economic development, suggests the appropriateness of the focus by distinct international organizations, such as the United Nations Conference on Trade and Development or the United Nations Economic Commission for Africa, on funding tourism projects (through the provision of tourism infrastructure, the stimulation of tourism supply, or positioning in international markets) in countries with low economic development levels. This work has demonstrated that investment in tourism results in the attracting of a greater flow of tourists, which will contribute to improved economic development levels.

Therefore, both international organizations financing projects and public administrations in these countries should increase the funding of projects linked to tourism development, in order to increase the flow of tourism to these destinations. This, given that an increase in tourism specialization suggests an increased level of development due to the demonstrated existence of a one-way causal relationship from tourism to development in these countries, many of which form part of the group of so-called “least developed” countries. However, according to the results obtained in this work, this relationship is not instantaneous, but rather, a certain delay exists in order for economic development to improve as a result of the increase in tourism. Therefore, public managers must adopt a medium and long-term vision of tourism activity as an instrument of development, moving away from short-term policies seeking immediate results, since this link only occurs over a broad time horizon.

On the other hand, this study reveals that a one-way causal relationship does not exist, by which the level of development influences tourism specialization level for the entire sample of countries. However, this conclusion, once again, cannot be generalized given that in countries belonging to Group A (countries with a high development level and a high tourism specialization level), a high level of economic development determines a higher level of tourism specialization. This is because the socio-economic structure of these countries (infrastructures, training or education, health, safety, etc.) permits their shaping as attractive tourist destinations, thereby increasing the number of tourists visiting them.

Therefore, investments made by public administrations to improve these factors in other countries that currently do not display this causal relationship implies the creation of the necessary foundations to increase their tourism specialization and, therefore, as shown in other works, tourism growth will permit economic growth, with all of the associated benefits for these countries.

Therefore, to attract tourist flows, it is not only important for a country to have attractive factors or resources, but also to have an adequate level of prior development. In other words, the tourists should perceive an adequate level of security in the destination; they should be able to use different infrastructures such as roads, airports, or the Internet; and they should receive suitable services at the destination from personnel having an appropriate level of training. The most developed countries, which are the destinations having the greatest endowment of these resources, are the ones that currently receive the most tourist flows thanks to the existence of these factors.

Therefore, less developed countries that are committed to tourism as an instrument to improve economic development should first commit to the provision of these resources if they hope to increase tourist flows. If this increase in tourism takes place in these countries, their economic development levels have been demonstrated to improve. However, since these countries are characterized by low levels of resources, cooperation by organizations financing the necessary investments is key to providing them with these resources.

Thus, a critical perspective is necessary when considering the relationship between tourism and economic development based on global causal analysis using heterogeneous samples with numerous subjects. As in this case, carrying out analyses on homogeneous groups may offer interesting results for policymakers attempting to suitably manage population development improvements due to tourism growth and tourism increases resulting from higher development levels.

One limitation of this work is its national scope since evidence suggests that tourism is a regional and local activity. Therefore, it may be interesting to apply this same approach on a regional level, using previously identified homogeneous groups.

And given that the existence of a causal relationship (in either direction) between tourism and development has only been determined for a specific set of countries, future works could consider other country-specific factors that may determine this causal relationship, in addition to the dynamics of tourism specialization and development level.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Cárdenas-García, P.J., Brida, J.G. & Segarra, V. Modeling the link between tourism and economic development: evidence from homogeneous panels of countries. Humanit Soc Sci Commun 11 , 308 (2024). https://doi.org/10.1057/s41599-024-02826-8

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National Travel and Tourism Strategy Overview

2022 national travel and tourism strategy.

The Strategy focuses on U.S. government efforts to promote our nation as a premier destination grounded in the breadth and diversity of its communities, and to foster a travel and tourism sector that drives economic growth, creates good jobs, and bolsters conservation and sustainability. Drawing on engagement and capabilities from across the federal government, the Strategy aims to increase not only the volume but also the value of tourism.

Leverage existing programs and assets to promote the United States to international visitors and broaden marketing efforts to encourage visitation to underserved communities.  

Reduce barriers to trade in travel services and make it safer and more efficient for visitors to enter and travel within the United States.

Extend the benefits of travel and tourism by supporting the development of diverse tourism products, focusing on underserved communities and populations. Address the financial and workplace needs of travel and tourism businesses, supporting destination communities as they expand their tourism economies. Deliver world-class experiences and customer service on federal lands and waters that showcase U.S. assets while protecting them for future generations.

Reduce travel and tourism’s contributions to climate change and build a travel and tourism sector that is resilient to natural disasters, public health threats, and the impacts of climate change. Build a sustainable sector that integrates protecting natural resources, supporting the tourism economy, and ensuring equitable development.

Sustainable tourism

Related sdgs, promote sustained, inclusive and sustainable ....

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Publications.

Tourism is one of the world's fastest growing industries and an important source of foreign exchange and employment, while being closely linked to the social, economic, and environmental well-being of many countries, especially developing countries. Maritime or ocean-related tourism, as well as coastal tourism, are for example vital sectors of the economy in small island developing States (SIDS) and coastal least developed countries (LDCs) (see also: The Potential of the Blue Economy report as well as the Community of Ocean Action on sustainable blue economy).

The World Tourism Organization defines sustainable tourism as “tourism that takes full account of its current and future economic, social and environmental impacts, addressing the needs of visitors, the industry, the environment and host communities".

Based on General assembly resolution 70/193, 2017 was declared as the  International Year of Sustainable Tourism for Development.

In the 2030 Agenda for Sustainable Development SDG target 8.9, aims to “by 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and products”. The importance of sustainable tourism is also highlighted in SDG target 12.b. which aims to “develop and implement tools to monitor sustainable development impacts for sustainable tourism that creates jobs and promotes local culture and products”.

Tourism is also identified as one of the tools to “by 2030, increase the economic benefits to Small Island developing States and least developed countries” as comprised in SDG target 14.7.

In the Rio+20 outcome document The Future We want, sustainable tourism is defined by paragraph 130 as a significant contributor “to the three dimensions of sustainable development” thanks to its close linkages to other sectors and its ability to create decent jobs and generate trade opportunities. Therefore, Member States recognize “the need to support sustainable tourism activities and relevant capacity-building that promote environmental awareness, conserve and protect the environment, respect wildlife, flora, biodiversity, ecosystems and cultural diversity, and improve the welfare and livelihoods of local communities by supporting their local economies and the human and natural environment as a whole. ” In paragraph 130, Member States also “call for enhanced support for sustainable tourism activities and relevant capacity-building in developing countries in order to contribute to the achievement of sustainable development”.

In paragraph 131, Member States “encourage the promotion of investment in sustainable tourism, including eco-tourism and cultural tourism, which may include creating small- and medium-sized enterprises and facilitating access to finance, including through microcredit initiatives for the poor, indigenous peoples and local communities in areas with high eco-tourism potential”. In this regard, Member States also “underline the importance of establishing, where necessary, appropriate guidelines and regulations in accordance with national priorities and legislation for promoting and supporting sustainable tourism”.

In 2002, the World Summit on Sustainable Development in Johannesburg called for the promotion of sustainable tourism development, including non-consumptive and eco-tourism, in Chapter IV, paragraph 43 of the Johannesburg Plan of Implementation.

At the Johannesburg Summit, the launch of the “Sustainable Tourism – Eliminating Poverty (ST-EP) initiative was announced. The initiative was inaugurated by the World Tourism Organization, in collaboration with UNCTAD, in order to develop sustainable tourism as a force for poverty alleviation.

The UN Commission on Sustainable Development (CSD) last reviewed the issue of sustainable tourism in 2001, when it was acting as the Preparatory Committee for the Johannesburg Summit.

The importance of sustainable tourism was also mentioned in Agenda 21.

For more information and documents on this topic,  please visit this link

UNWTO Annual Report 2015

2015 was a landmark year for the global community. In September, the 70th Session of the United Nations General Assembly adopted the Sustainable Development Goals (SDGs), a universal agenda for planet and people. Among the 17 SDGs and 169 associated targets, tourism is explicitly featured in Goa...

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In December 2015, the United Nations General Assembly declared 2017 as the International Year of Sustainable Tourism for Development. This is a unique opportunity to devote a year to activities that promote the transformational power of tourism to help us reach a better future. This important cele...

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The 2012 UNEP Foresight Process on Emerging Global Environmental Issues primarily identified emerging environmental issues and possible solutions on a global scale and perspective. In 2013, UNEP carried out a similar exercise to identify priority emerging environmental issues that are of concern to ...

Transforming our World: The 2030 Agenda for Sustainable Development

This Agenda is a plan of action for people, planet and prosperity. It also seeks to strengthen universal peace in larger freedom, We recognize that eradicating poverty in all its forms and dimensions, including extreme poverty, is the greatest global challenge and an indispensable requirement for su...

15 Years of the UNWTO World Tourism Network on Child Protection: A Compilation of Good Practices

Although it is widely recognized that tourism is not the cause of child exploitation, it can aggravate the problem when parts of its infrastructure, such as transport networks and accommodation facilities, are exploited by child abusers for nefarious ends. Additionally, many other factors that contr...

Towards Measuring the Economic Value of Wildlife Watching Tourism in Africa

Set against the backdrop of the ongoing poaching crisis driven by a dramatic increase in the illicit trade in wildlife products, this briefing paper intends to support the ongoing efforts of African governments and the broader international community in the fight against poaching. Specifically, this...

Status and Trends of Caribbean Coral Reefs: 1970-2012

Previous Caribbean assessments lumped data together into a single database regardless of geographic location, reef environment, depth, oceanographic conditions, etc. Data from shallow lagoons and back reef environments were combined with data from deep fore-reef environments and atolls. Geographic c...

Natural Resources Forum: Special Issue Tourism

The journal considers papers on all topics relevant to sustainable development. In addition, it dedicates series, issues and special sections to specific themes that are relevant to the current discussions of the United Nations Commission on Sustainable Development (CSD)....

Thailand: Supporting Sustainable Development in Thailand: A Geographic Clusters Approach

Market forces and government policies, including the Tenth National Development Plan (2007-2012), are moving Thailand toward a more geographically specialized economy. There is a growing consensus that Thailand’s comparative and competitive advantages lie in amenity services that have high reliance...

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This publication is the product of an international study led by the Division for Sustainable Development (DSD) of the United Nations Department of Economic and Social Affairs (UNDESA) in cooperation with the Ministry of Carriacou and Petite Martinique Affairs and the Ministry of Environment, Foreig...

Natural Resources Forum, a United Nations Sustainable Development Journal (NRF)

  Natural Resources Forum, a United Nations Sustainable Development Journal, seeks to address gaps in current knowledge and stimulate relevant policy discussions, leading to the implementation of the sustainable development agenda and the achievement of the Sustainable...

UN Ocean Conference 2025

Our Ocean, Our Future, Our Responsibility “The ocean is fundamental to life on our planet and to our future. The ocean is an important source of the planet’s biodiversity and plays a vital role in the climate system and water cycle. The ocean provides a range of ecosystem services, supplies us with

UN Ocean Conference 2022

The UN Ocean Conference 2022, co-hosted by the Governments of Kenya and Portugal, came at a critical time as the world was strengthening its efforts to mobilize, create and drive solutions to realize the 17 Sustainable Development Goals by 2030.

58th Session of the Commission for Social Development – CSocD58

22nd general assembly of the united nations world tourism organization, world tourism day 2017 official celebration.

This year’s World Tourism Day, held on 27 September, will be focused on Sustainable Tourism – a Tool for Development. Celebrated in line with the 2017 International Year of Sustainable Tourism for Development, the Day will be dedicated to exploring the contribution of tourism to the Sustainable Deve

World Tourism Day 2016 Official Celebration

Accessible Tourism for all is about the creation of environments that can cater for the needs of all of us, whether we are traveling or staying at home. May that be due to a disability, even temporary, families with small children, or the ageing population, at some point in our lives, sooner or late

4th Global Summit on City Tourism

The World Tourism Organisation (UNWTO) and the Regional Council for Tourism of Marrakesh with support of the Government of Morroco are organizing the 4th Global Summit on City Tourism in Marrakesh, Morroco (9-10 December 2015). International experts in city tourism, representatives of city DMOs, of

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The World Tourism Organisation (UNWTO) and Ulsan Metropolitan City with support of the Government of the Republic of Korea are organizing the 2nd Euro-Asian Mountain Resorts Conference, in Ulsan, Republic of Korea (14 - 16 October 2015). Under the title “Paving the Way for a Bright Future for Mounta

21st General Assembly of the United Nations World Tourism Organization

Unwto regional conference enhancing brand africa - fostering tourism development.

Tourism is one of the Africa’s most promising sectors in terms of development, and represents a major opportunity to foster inclusive development, increase the region’s participation in the global economy and generate revenues for investment in other activities, including environmental preservation.

• January 2017 International Year of Tourism In the context of the universal 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs), the International Year aims to support a change in policies, business practices and consumer behavior towards a more sustainable tourism sector that can contribute to the SDGs.
• January 2015 Targets 8.9, 12 b,14.7 The 2030 Agenda for Sustainable Development commits Member States, through Sustainable Development Goal Target 8.9 to “devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and products”. The importance of sustainable tourism, as a driver for jobs creation and the promotion of local culture and products, is also highlighted in Sustainable Development Goal target 12.b. Tourism is also identified as one of the tools to “increase [by 2030] the economic benefits to Small Island developing States and least developed countries”, through Sustainable Development Goals Target 14.7.
• January 2012 Future We Want (Para 130-131) Sustainable tourism is defined as a significant contributor “to the three dimensions of sustainable development” thanks to its close linkages to other sectors and its ability to create decent jobs and generate trade opportunities. Therefore, Member States recognize “the need to support sustainable tourism activities and relevant capacity-building that promote environmental awareness, conserve and protect the environment, respect wildlife, flora, biodiversity, ecosystems and cultural diversity, and improve the welfare and livelihoods of local communities” as well as to “encourage the promotion of investment in sustainable tourism, including eco-tourism and cultural tourism, which may include creating small and medium sized enterprises and facilitating access to finance, including through microcredit initiatives for the poor, indigenous peoples and local communities in areas with high eco-tourism potential”.
• January 2009 Roadmap for Recovery UNWTO announced in March 2009 the elaboration of a Roadmap for Recovery to be finalized by UNWTO’s General Assembly, based on seven action points. The Roadmap includes a set of 15 recommendations based on three interlocking action areas: resilience, stimulus, green economy aimed at supporting the tourism sector and the global economy.
• January 2008 Global Sustainable Tourism Criteria The Global Sustainable Tourism Criteria represent the minimum requirements any tourism business should observe in order to ensure preservation and respect of the natural and cultural resources and make sure at the same time that tourism potential as tool for poverty alleviation is enforced. The Criteria are 41 and distributed into four different categories: 1) sustainability management, 2) social and economic 3) cultural 4) environmental.
• January 2003 WTO becomes a UN specialized body By Resolution 453 (XV), the Assembly agreed on the transformation of the WTO into a United Nations specialized body. Such transformation was later ratified by the United Nations General Assembly with the adoption of Resolution A/RES/58/232.
• January 2003 1st Int. Conf. on Climate Change and Tourism The conference was organized in order to gather tourism authorities, organizations, businesses and scientists to discuss on the impact that climate change can have on the tourist sector. The event took place from 9 till 11 April 2003 in Djerba, Tunisia.
• January 2002 World Ecotourism Summit Held in May 2002, in Quebec City, Canada, the Summit represented the most important event in the framework of the International Year of Ecosystem. The Summit identified as main themes: ecotourism policy and planning, regulation of ecotourism, product development, marketing and promotion of ecotourism and monitoring costs and benefits of ecotourism.
• January 1985 Tourism Bill of Rights and Tourist Code At the World Tourism Organization Sixth Assembly held in Sofia in 1985, the Tourism Bill of Rights and Tourist Code were adopted, setting out the rights and duties of tourists and host populations and formulating policies and action for implementation by states and the tourist industry.
• January 1982 Acapulco Document Adopted in 1982, the Acapulco Document acknowledges the new dimension and role of tourism as a positive instrument towards the improvement of the quality of life for all peoples, as well as a significant force for peace and international understanding. The Acapulco Document also urges Member States to elaborate their policies, plans and programmes on tourism, in accordance with their national priorities and within the framework of the programme of work of the World Tourism Organization.

Investigating risks and strategies in adopting green tourism practices in developing economy

• Research Article
• Published: 22 November 2023
• Volume 30 , pages 123710–123728, ( 2023 )

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• Zhenrong Luo 1 &
• Laiyan Yun 1  

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In emerging economies, the tourism industry is crucial for economic growth, but it also carries substantial environmental and social risks. Promoting sustainability and reducing the detrimental effects of tourism are two benefits of using green tourism strategies. In order to assess the efficiency of various green tourism practices in reducing these risks, this study will first define the main risks and sub-risks related to implementing green tourist practices in China’s developing economy. The analytic hierarchy process (AHP) and simple additive weighting (SAW) methods are used in the study to assess the multiple risks and strategies of various green tourism initiatives. The results of the AHP method show that economic, environmental, and political risks impede the implementation of green tourism for sustainable development. According to the SAW method findings, clear and effective regulations and guidelines, infrastructure development, and public-private partnerships are top-ranked strategy risks to adopting green tourism practices in China. The study provides implications for policymakers and tourism business owners in developing economies to promote the use of sustainable tourism practices. The study highlights effective strategies to promote sustainability and increase the adoption of sustainable tourism practices. The study offers useful insights for the government, stakeholders, and policymakers to take into account the risks and challenges involved with implementing green tourism practices in the context of China.

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Conceptualization, Zhenrong Luo, Laiyan Yun; Methodology, Zhenrong Luo, Laiyan Yun; Validation, Laiyan Yun; formal analysis, Zhenrong Luo, Laiyan Yun; investigation, Zhenrong Luo; data curation, Laiyan Yun; writing—original draft preparation, Zhenrong Luo, Laiyan Yun; writing—review and editing, Zhenrong Luo, Laiyan Yun. The authors read and approved the final manuscript.

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Luo, Z., Yun, L. Investigating risks and strategies in adopting green tourism practices in developing economy. Environ Sci Pollut Res 30 , 123710–123728 (2023). https://doi.org/10.1007/s11356-023-30700-8

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COVID-19 economic policy response, resilience and tourism recovery

Luke okafor.

a Faculty of Arts and Social Sciences, School of Economics, University of Nottingham Malaysia

Usman Khalid

b Department of Innovation in Government and Society, College of Business and Economics, United Arab Emirates University (UAEU)

Sasidaran Gopalan

Associated data.

This study investigates whether tourism sector recovery from the COVID-19 pandemic is influenced by only the size of the economic stimulus packages or whether a country's resilience plays a moderating influence in the underlying relationship. The results show that while economic stimulus packages help to enhance tourism recovery from the COVID-19 pandemic, it is contingent on the level of a country's resilience. For instance, amongst the less resilient countries, the impact of economic policy response on the tourism recovery is more pronounced, but the effect dissipates as countries become more resilient. These findings have important implications for policymakers, management teams, and relevant stakeholders in their effort to revive the tourism sector from the impact of the COVID-19 pandemic.

1. Introduction

It has been over two years since the COVID-19 outbreak wrought havoc on the global tourism sector. The economic “scarring” suffered by many countries across the world in the form of output losses, particularly by those that are tourism-dependent, has been rather unprecedented ( International Monetary Fund, 2021 ). As the data from the World Travel and Tourism Council (WTTC) reveal, the contribution of the global travel and tourism sector to world output suffered a precipitous decline, with its share of global GDP halving from around 10.5% in 2019 to 5.5% in 2020, resulting in a job loss of 62 million globally ( WTTC, 2021 ). Furthermore, the ongoing pandemic has also significantly impacted the risk perception of individuals towards global travel and changed the way tourists perceive travel and tourism ( da Silva Lopes, Remoaldo, Ribeiro, & Martín-Vide, 2021 ; Meng et al., 2021 ; Zhan, Zeng, Morrison, Liang, & Coca-Stefaniak, 2022 ).

While studies in the extant literature have widely explored the impact of economic and financial crises as well as other types of disasters such as terrorism, conflict, and health-related shocks on the tourism sector, there is sparse literature on what factors help the tourism sector to recover after such events. The tourism sector plays a fundamental role in most economies in terms of employment generation, income creation, being a source of forex earnings, and contributing to growth ( Khalid, Okafor, & Sanusi, 2021 ). In addition to the tourism industry, tourism-affiliated industrial sectors also contribute to the economy in terms of employment and income creation. Therefore, it is pertinent to understand the factors that accelerate the recovery of the tourism sector from shocks such as the COVID-19 pandemic.

Despite the seemingly successful global vaccination drive, the pathway to achieving a full-fledged recovery that would come about from travel normalization seems to be ridden with uncertainties, furthering concerns of an uneven and asymmetric recovery globally. Considering the global uncertainties surrounding the resumption of cross-border travel and tourism, it is no surprise that several countries have continued to respond in a variety of ways to revive their economies. This has largely taken the form of stimulus measures designed to soften the blow inflicted by the pandemic ( Elgin, Basbug, & Yalaman, 2020 ), despite the differing degrees of fiscal space ( Gopalan & Rajan, 2020 ) and monetary leeway available to them. This approach has been particularly true for countries that have a significantly large tourism sector. Indeed, recent empirical studies have confirmed that the responses to tackle the adverse impacts of COVID-19 were larger and more aggressive in tourism-dependent countries relative to low tourism-dependent countries ( Khalid, Okafor, & Burzynska, 2021 ).

While the extent to which these policy responses have aided the tourism sector to recover has not been investigated empirically, it is also pertinent to recognize the central role played by a country's inherent resilience in facilitating such recovery ( Sharma, Thomas, & Paul, 2021 ). Although the notion of resilience is inextricably intertwined with the ability of countries to deal with uncertainties from shocks such as the COVID-19 pandemic, there is very little understanding in the current literature about the links between both resilience and crisis management policies ( Jiang, Ritchie, & Verreynne, 2019 ; Prayag, 2018 ). This is especially true when it comes to empirical quantitative studies examining the relationship between crisis management and resilience ( Ritchie & Jiang, 2019 ). As a result, the extant literature is sparse when it comes to understanding if and how the level of a country's resilience moderates the underlying interplay between tourism recovery from the pandemic and economic stimulus packages.

Given that the potential moderating role of the level of resilience in influencing the impact of economic stimulus policies on tourism sector recovery from the COVID-19 pandemic for a large section of countries has not been studied in the extant literature, this study aims to fill this gap. To this end, the purpose of this study is to investigate whether the recovery of the tourism industry from the COVID-19 outbreak is influenced by only the magnitude of the economic stimulus packages or whether a country's resilience plays a moderating influence in the underlying link. Put differently, the following question is formulated to guide the study: Does the level of a country's resilience moderate the link between its tourism sector recovery from the COVID-19 pandemic and economic policy response?

We use data from 126 countries/territories for the empirical analysis. Information about the tourism sector's recovery from the COVID-19 pandemic is captured using the COVID19tourism index data developed by Yang, Altschuler, Liang, and Li (2020) . Data on economic policy response come from Elgin et al. (2020) , while a country's resilience is captured using the FM Global Resilience index data. We follow the extant literature in specifying the empirical model to examine the interplay between tourism recovery from the COVID-19 pandemic and economic policy response, as well as the moderating influence of resilience in the underlying nexus (see, Elgin et al., 2020 ; Khalid, Okafor, & Burzynska, 2021 ). The baseline and augmented models, as well as the alternative model specifications, are estimated using the Ordinary Least Squares (OLS) estimator while controlling for region-fixed effects.

Our primary contribution to the literature comes from an attempt to disentangle the importance of both the economic policy response of a country as well as its inherent resilience in aiding the recovery of the tourism sector from the COVID-19 pandemic. There have been no prior systematic attempts in the tourism literature that have addressed these issues, albeit the emergence of a nascent strand of qualitative and case-study based articles examining inter-related matters in the specific context of tourism recovery from the COVID-19 outbreak (see, for instance, Kuščer, Eichelberger, & Peters, 2021 ). By tying economic policy response and resilience to tourism recovery from the pandemic, our empirical results would also allow us to draw suitable conclusions at a cross-country level, while factoring in each country's unique characteristics.

The results show that tourism recovery is influenced by the COVID-19 economic policy response. However, the impact of economic policy response on tourism recovery is contingent on the level of resilience of a country. In particular, amongst less resilient countries, the impact of economic policy response on tourism recovery is the largest, but the effect disappears as countries become more resilient. In addition, we find that both fiscal policy response and interest rate cuts are effective in reviving the tourism sector, especially for less resilient countries, but the effect of the interest rate cut is statistically significant for a slightly larger range of resilience scores.

The implications of the findings of this study are important both from a policy as well as a tourism management perspective. From a policy perspective, the findings suggest that a more proactive approach for managing and handling any future crisis is needed, particularly in the tourism industry. This includes but is not restricted to crisis/disaster management protocols that countries can adopt when faced with an unprecedented disaster, such as the COVID-19 outbreak. From a tourism management perspective, the findings of this study highlight the need for tourism businesses to be more resilient and prepared for any adverse shocks in the future. This includes strategies to move towards digitalization of the businesses, such as the adoption of digital payment systems or, in general, a greater presence in the online world.

The rest of the study is structured as follows. Section 2 offers a discussion of the related literature, which forms the basis for the development of empirically testable hypotheses. This section presents a succinct overview of the relevant strands of empirical literature related to both crisis management as well as resilience. Section 3 discusses the details of the empirical model and data used in the study, while section 4 explains the results as well as the robustness checks and discusses the theoretical and practical implications of the results. Section 5 concludes the study with a brief overview of the policy implications emanating from the results.

2. Related literature and hypotheses

There are two important strands of literature that are tangentially relevant to the current discussion in this study. The first pertains to the body of work that has focussed on understanding the impact of extreme events on the tourism industry. The studies that fall under this strand analyze how countries handle tourism related crises arising from extreme events that include terrorist attacks, natural disasters, as well as global or regional pandemics or epidemic events. More specifically, these studies attempt to understand the design and impact of appropriate strategies and policy responses to aid the recovery of the tourism sector to overcome those shocks. The second strand of the literature relates to the resilience-crisis management nexus.

2.1. Extreme events and the tourism sector

It has been well established that the global tourism sector is quite susceptible to different kinds of extreme events and shocks. In the last two decades, up until the COVID-19 pandemic, the tourism sector has been buffeted by various shocks in the forms of the September 11 terrorist attacks in 2001, the severe acute respiratory syndrome (SARS) outbreak in 2003, the global financial crisis of 2008–09, and the Middle East Respiratory Syndrome (MERS) outbreak in 2015.

Numerous studies have thus focused on policy responses to extreme events that resulted in tourism crises. For instance, geopolitical shocks such as domestic political instability and unrest have been shown to have negative ramifications on the tourism industry ( Khan, Bibi, Lyu, Latif, & Lorenzo, 2021 ; Okafor & Khalid, 2021 ). A related body of work has focused on the impact of economic shocks such as financial crises on tourist arrivals ( de Sausmarez, 2007 ; Khalid, Okafor, & Shafiullah, 2020 ); health shocks arising from global and regional pandemics or epidemic events ( Cooper, 2006 ; Gössling, Scott, & Hall, 2020 ); and other geographic shocks arising from natural disasters ( Gurtner, 2016 ).

The most obvious kind of extreme event that has been well-studied in the literature comes from the impact of terrorism related events on the tourism industry ( Khan et al., 2020 ; Kumail, Ali, Sadiq, & Khan, 2021 ). Focusing on South Asia, for instance, Kumail et al. (2021) empirically show the destabilizing impacts of terrorist events spanning over three decades (1980–2016) on tourism demand. The literature has also shown how terrorism can significantly dampen the positive relationship between tourism and well-being (See Khan et al. (2020) for a rich discussion).

Focusing on crisis management policies in the wake of terrorist events, Blake and Sinclair (2003) use a Computable General Equilibrium (CGE) model to analyze the effect of the September 11 terrorist attacks in the United States on tourism demand. They find that the crisis management policies, specifically the provision of sectoral subsidies adopted in the wake of the terrorist attacks, were highly effective in mitigating the negative repercussions on the tourism industry. Other studies such as Bassil, Saleh, and Anwar (2019) have also explored the relationship between terrorism and tourism demand using a case study of Lebanon, Turkey, and Israel, while Gurtner (2016) studied similar issues using a case study of Bali (Indonesia).

2.2. COVID-19 pandemic and the tourism recovery

Since the outbreak of the COVID-19 pandemic in early 2020, there appears to have been a proliferation of country specific studies that have analyzed the potential efficacy of recovery strategies adopted by different countries. For instance, focusing on Taiwan as a case study, Yeh (2020) examines the dynamics of the country's tourism recovery strategies from the COVID-19 pandemic. Using a series of semi-structured interviews, the study concludes that the factors instrumental in handling the pandemic successfully include open communication as well as loans extended by the government.

Focusing on Spain's recovery strategies from the COVID-19 pandemic, Arbulú, Razumova, Rey-Maquieira, and Sastre (2021) assess if a focus on domestic tourism in Spain can be a possible recovery strategy that would help the country make up for the losses of international tourist demand. Despite the regional variations, the results show that a renewed focus on domestic tourism by reorienting outbound tourism could yield positive and significant benefits, especially when inbound tourism is plagued by a crisis. In yet another study on Spain, Rodríguez-Antón and Alonso-Almeida (2020) undertake a SWOT analysis of the Spanish tourism and hospitality sector by focusing on the response and recovery strategies in the wake of the COVID-19 pandemic.

Furthermore, other single country studies that have focused on tourism crisis management in the wake of the COVID-19 pandemic include Zhong, Sun, Law, and Li (2021) for China, Kaushal and Srivastava (2021) for India, and Pongsakornrungsilp, Pongsakornrungsilp, Kumar, and Maswongssa (2021) for Thailand. Focusing on a representative set of seven countries spread geographically across all regions, including Australia, China, and Japan in Asia, Austria and Italy in Europe, Brazil in South America, and Israel in the Middle East, Kreiner and Ram (2020) undertake a qualitative comparison of the different national tourism plans in these countries to deal with the COVID-19 pandemic. Comparing their national tourism plans, the study concludes that all countries were focused on implementing short-term local solutions instead of focusing on a recovery that will be sustainable in the long-run.

In one of the most comprehensive reviews on the subject, Ritchie and Jiang (2019) surveyed 142 articles published over the span of about six decades (1960–2018). They find that a majority of the articles have focussed on the ‘response and recovery’ dimension of crisis and disaster management, relative to a focus on other stages such as ‘preparedness and planning’ or ‘resolution and reflection’ or resilience. As their meta-analysis review points out, despite the abundance of articles examining the varied policy responses aimed at the recovery of the tourism sector to crises, much of the existing literature tends to be largely country specific case studies which are also mostly qualitative in nature. This underlines the fact that there is a dearth of quantitative studies engaging in meaningful cross-country analysis.

One of the most recent studies to undertake a cross-country analysis comes from Khalid, Okafor and Burzynska (2021) , who perform an empirical examination to assess the degree to which the size of the tourism sector influences the economic policy response to the COVID-19 pandemic. This cross-country study, with the findings based on an empirical analysis for 136 countries, reveals that the size of the economic stimulus is directly proportional to the size of the tourism sector, with countries that are heavily dependent on tourism being more aggressive in their stimulus responses.

The foregoing review of the related literature underlines the crucial importance of appropriate economic policy responses in potentially facilitating a full-fledged recovery of the tourism sector from shocks, such as the COVID-19 outbreak, yielding the following hypothesis:

Economic stimulus packages have a positive impact on tourism recovery from the COVID-19 pandemic.

2.3. Resilience and tourism crisis management

The second strand of literature, which is nascent at best, relates to the notion of resilience in the specific context of the tourism industry. The limited number of studies that exist on tourism resilience are largely theoretical in nature, while there is a marked absence of empirical (quantitative) applications, with some exceptions.

Intertwined with tourism crisis management is the issue of resilience, albeit the scarcity of empirical work integrating resilience and tourism crisis management. There is no one universal definition of the term resilience, but broadly it has come to be understood as the ability of a system to withstand shocks and bounce back through a reorganization while essentially retaining its identity ( Walker, Holling, Carpenter, & Kinzig, 2004 ). As Jiang et al. (2019) point out, while there is a lot of established research on resilience in general and in other fields like strategic management, the direct applicability to the tourism sector appears to be mostly theoretical ( Calgaro, Lloyd, & Dominey-Howes, 2014 ; Luthe & Wyss, 2014 ; Prayag, 2018 ; Sharma et al., 2021 ; Strickland-Munro, Allison, & Moore, 2010 ).

There are only a handful of studies that draw on qualitative data to apply resilience frameworks to study specific tourism destinations. For instance, Becken (2013) develops a framework to assess the resilience of tourist destinations to climatic shocks and uses primary data from a tourist location in New Zealand to verify the underlying theoretical framework empirically. Focusing on Phuket (Thailand), Biggs, Hall, and Stoeckl (2012) compare the resilience levels of reef tourism enterprises in Phuket following the 2004 tsunami and the 2008 political crisis.

In one of the few studies to empirically assess the impact of the COVID-19 pandemic on the resilience of the leisure and hospitality sector in the US, Khan et al. (2021) find that the COVID-19 pandemic generated marked negative impacts in terms of employment levels, specifically in the leisure and hospitality sector. As  Prayag (2018)  reiterates, the literature applying resilience thinking in tourism is quite nascent though emerging.

With the COVID-19 pandemic bringing back the spotlight on tourism resilience, it becomes important to understand the links between a country's resilience, economic instruments to mitigate the tourism crisis, and the recovery level of the tourism industry from the pandemic. The question of interest is whether the influence of economic stimulus packages augmented by resilience on tourism recovery differs across countries. Theoretically, it is plausible to argue that when countries migrate to higher levels of resilience, their tourism sectors are potentially less likely to respond more aggressively to economic policy interventions as they may have well-designed crisis management frameworks that allow them to respond effectively to a crisis. In other words, the impact of economic policy interventions potentially facilitates a stronger tourism sector recovery only in countries with lower degrees of resilience and vice versa. To this end, we develop the following testable hypothesis:

A higher level of resilience dampens the positive impact of economic stimulus packages on tourism recovery.

The foregoing review reveals two important gaps in the extant literature. First, despite the popularity of studies examining the economic policy responses and management to tourism crises, the scope largely remains confined to specific country cases, which are mostly qualitative in nature, limiting the ability to draw appropriate cross-country comparisons and/or recommendations. Second, specific to the COVID-19 pandemic, the issue of the efficacy of economic policy response in aiding the tourism sector recovery or the moderating influence of a country's resilience in the underlying relationship has not been explored in the extant literature. We attempt to overcome both gaps in the current study.

3. Methodology and overview of data

3.1. empirical strategy.

We follow the extant literature in specifying the empirical model to examine the association between tourism recovery from the COVID-19 pandemic and economic policy response, as well as the moderating influence of resilience in the underlying nexus (see, Elgin et al., 2020 ; Khalid, Okafor, & Burzynska, 2021 ). The general form of the model can be expressed as follows:

where, COVID 19 tourism index captures the general recovery potential of the tourism sector, F is a function, CESI index is the COVID-19 economic stimulus index, Overall resilience index refers to FM global resilience index, and FIND is financial development index.

Eq. (1) posits that the COVID19tourism index is a function of the CESI index, overall resilience index, global health index, population over 65, total death rate, and the financial development index. The general form of the model can be expressed in a specific form. The specific form can be augmented with region specific effects, notations for parameter estimates, and the error term. Region fixed effects are included in the model to control for any unobservable characteristics at the regional level. This suggests that the empirical model—that is, the baseline model—can be specified as below:

where, Ln denotes the natural logarithm, λ is region fixed effects, ε is the error term, and α ′ s are obtained through estimations.

Furthermore, to gain deeper insights, we also estimated an alternative model specification where we used the fiscal and interest rate cut sub-indices in lieu of a CESI index as explanatory variables. Similarly, we also estimated an alternative model specification where we used supply chain and risk quality resilience indices instead of overall resilience index.

It is likely that the level of resilience in a country has a moderating impact on the influence of economic stimulus packages on tourism recovery. For instance, a country that is highly resilient is likely to have a tourism sector that is more resilient to shock, such as COVID-19 pandemic and thus may not introduce large economic stimulus packages to cushion the effect of the pandemic compared to a country that is less resilient. The general form of the alternative model for the moderating impact can be specified as follows:

Eq. (3) indicates that the level of resilience in a country may have a moderating impact on the tourism recovery-economic stimulus nexus. The specific form of the empirical model—that is, the full model—for the moderating impact can be expressed as follows:

where, β ′ s are parameters to be estimated. The definitions of the remaining notations are the same as Eq. (1) .

Following the approach used with respect to model specification 1, to gain deeper insights, we also estimated alternative model specifications where we interacted the CESI index with risk quality resilience, CESI index with supply chain resilience index, fiscal policy stimulus with the overall resilience index, interest rate cut with overall resilience index, fiscal policy stimulus with risk quality index, interest rate cut with risk quality index, fiscal policy stimulus with supply chain resilience index, and interest rate cut with supply chain resilience index. The base and full models, as well as the alternative model specifications, are estimated with the use of the Ordinary Least Squares (OLS) estimator with controls for region fixed effects.

3.2. Data sources

The data set employed in the analysis is a cross-section of 126 countries. Data availability dictated the number of countries used for the analysis. The analysis was performed using merged data obtained from various sources, as discussed below.

3.2.1. Dependent variable

The COVID19tourism index developed by Yang et al. (2020) measures the general recovery potential of the tourism industry from the COVID-19 outbreak. A number closer to 100 indicates a greater recovery of a country's tourism sector to the normal level. The COVID19tourism index is derived from geometric means of three sub-indices, namely the aviation index, the hotel index, and the pandemic index. 1 The dependent variable in our empirical model is the average of COVID19tourism index data from February 2020 to December 2020.

3.2.2. Explanatory variables

The COVID-19 Economic Stimulus Index, CESI, is one of the explanatory variables. The CESI index measures the economic policy responses of different economies aimed at countering the impact of the pandemic. In general, the economic policy responses include monetary, fiscal, as well as the balance of payment and/or exchange rate.

Data collected mainly from the IMF's COVID-19 policy tracker, 2020, are used for constructing the different sub-indices of the CESI. 2 Utilizing data constructed by as well as following a similar approach as Elgin et al. (2020) , we used the principal component analysis (PCA) to generate the CESI index. More specifically, we combine the data on seven indicators of economic policy response provided by Elgin et al. (2020) to generate the composite index of CESI with the use of PCA. The seven indicators include fiscal policy packages, which capture all the fiscal stimulus packages as a percentage of GDP, the interest rate cut by the central bank as a percentage of the ongoing rate as of February 1st, 2020, reserve requirement, macro-financial packages as a percentage of GDP, the specific balance of payment (BoP) measures as a percentage of GDP, and two additional variables that capture other monetary policies and BoP policies introduced by the country. 3 Furthermore, we also used the fiscal policy and interest rate cut sub-indices in lieu of a CESI index as explanatory variables to gain deeper insights in terms of the role of fiscal policy stimulus and interest cut rate in helping to promote the recovery potential of the tourism industry from the COVID-19 outbreak.

We used the FM Global Resilience index to gauge the influence of the level of resilience of a country to COVID-19 shock as well as the relative enterprise resilience of a country to turbulent occurrences (FM Global, 2020 ). The index is constructed with the use of 12 factors that are broadly classified into economic, risk quality, and supply chain resilience. Factors such as inherent cyber risk, exposure to natural hazards, fire risk quality, and natural hazard risk quality are captured using the risk quality resilience sub-index. The supply chain resilience sub-index is constructed with the use of factors, such as corporate governance, supply chain visibility, control of corruption, and quality of infrastructure. The economic resilience sub-index is measured using factors such as productivity, political risk, urbanization rate, and oil intensity. 4 Additionally, we also used supply chain resilience and risk quality resilience sub-indices in place of the overall resilience index to gain sharper insights into the influence of supply chain and risk quality on the tourism recovery and economic stimulus nexus. The data for the overall resilience and the sub-indices are for the year 2020.

3.2.3. Control variables

Following related studies ( Elgin et al., 2020 ; Khalid, Okafor, & Sanusi, 2021 ), we control for several variables that affect the link between tourism recovery from the COVID-19 pandemic and economic policy response. This extends to the moderating influence of resilience in the underlying nexus. These variables include population over 65, total death rate per 100,000 population, and global health security index (GHS). The data for the population over 65 is collected from the World Development Indicators and for the year 2019, World Bank (2021) . The data for total death from COVID-19 are for the year 2019 and are sourced from the Ourworldindata website. 5

Population over 65 is controlled for in order to avoid potential omitted variable bias ( Khalid, Okafor, & Sanusi, 2021 ), as countries with a larger fraction of older people tend to devote a larger share of resources via economic stimulus packages to alleviate the impact of the COVID-19 outbreak ( Elgin et al., 2020 ). Similarly, the tourism sector in countries with a larger share of old people may not recover faster as older people are more vulnerable to COVID-19. Similarly, the total death rate from COVID-19 is controlled for as economies with higher death rates are more likely to allocate more resources to economic stimulus packages compared to those with a lower death rate. In addition, the tourism sector in these countries is unlikely to rebound faster from the effect of the COVID-19 crisis. The healthcare system in countries with high death rates is likely to be strained, and this could result in the imposition of strict lockdown measures ( Khalid, Okafor, & Sanusi, 2021 ), which could impede the recovery potential of the tourism sector.

The GHS index captures the quality of health security and associated capacities for 195 economies. The data are for the year 2019 ( Global Health Security, 2019 ). GHS is included in the model specification to account for a country's health capabilities, including but not limited to the management and prevention of epidemics and swift response to dampen the spread of epidemics of global concern. This also includes an adequate health infrastructure to treat the sick, provide adequate protection for health workers, adhere to international norms, and general risk environment and susceptibility to biological threats ( Global Health Security, 2019 ). We expect countries with higher GHS to be better prepared to weather and lessen the effect of the COVID-19 outbreak than those with lower GHS.

We also control for the level of financial development of different economies with the use of the financial development index. The index is derived from several indices that capture how advanced financial markets and financial institutions in different countries are in the areas of efficiency, depth, and access. The overall financial development index and the sub-indices are developed for 183 countries. The data are for the year 2018. For more information about the index, please see Svirydzenka (2016) . It is likely that financially developed countries are better placed to devote a larger share of resources to economic support packages aimed at limiting the impact of the pandemic relative to economies with low level of financial development index ( Guru & Yadav, 2019 ; Okafor, Bhattacharya, & Apergis, 2020 ). Similarly, the tourism industry in countries with a higher level of financial development may be better placed to recover faster from the impact of the COVID-19 outbreak due to the potential availability of larger loanable funds, financial tax incentives, and public financial incentives ( Okafor et al., 2020 ). In general, the data for different variables refer to the year 2018 or the most recent available year.

3.2.4. Summary statistics

The summary statistics for the whole sample as well as for high and low resilient countries, are presented in Table 1 . Preliminary evidence indicates that high resilient countries tend to experience greater recovery in their tourism sector compared to low-resilient countries, as captured by the COVID19 tourism index. In addition, highly resilient countries tend to introduce lower economic stimulus packages than low resilient economies. This indicates that, on average, high resilient countries tend to introduce lower economic stimulus and experience greater recovery in their tourism sector. This is consistent with the potential existence of the substitutability between resilience and economic policy for tourism sector recovery.

Summary statistics.

Notes: High-resilient countries are a group of countries whose overall resilience score is greater than the average resilience score for all the countries covered in the sample, while low-resilient countries have an overall resilience score that is smaller than the average for all the countries. Ln denotes natural logarithms. Total death rate: total death rate per 100,000 population. ‘-’ refers to the mean and standard deviation of the CESI index for the whole sample, which are ‘-0.000000004’ and ‘(1.000)’, respectively. Values reported without parenthesis are means, whereas values in parenthesis are standard deviations.

In terms of the components of CESI, high resilient countries are likely to introduce larger interest rate cuts relative to low resilient economies, while the low resilient economies tend to introduce greater fiscal stimulus. The high resilient countries also tend to be better equipped with a health care system. This may help high resilient countries to respond to health emergencies such as the COVID-19 crisis, more efficiently. In contrast, less resilient economies tend to have a lower capacity to manage such situations. This may help explain why the death rate due to COVID-19 has been lower in high resilient countries compared to low resilient countries. The correlation table and variance inflation factor results are reported in Tables S1 and S2 in the supplementary material. The correlations between the explanatory variables are not high, and the variance inflation factor test indicates that there is no serious problem of multicollinearity.

4. Results, discussion and implications

4.1. results.

Table 2 provides the coefficients of the baseline model specified in Eq. (2) . The model specification is designed to explain the links between tourism recovery, economic policy response, and resilience while controlling for relevant variables. In Columns 1–3, the aggregate CESI is used to capture economic policy response, while in Columns 4–6, the two major components of CESI, namely fiscal policy stimulus and interest rate cut, are used in lieu of CESI.

The links between COVID19 tourism index, resilience, and economic policy response (base model).

Notes: Ln denotes natural logarithms. The values in parentheses are robust standard errors. COVID19tourism Index measures the average recovery level of the tourism industry in the year 2020 compared to normal time without COVID-19 pandemic. Significance levels at the 1%, 5%, and 10% level is expressed by ***, ** and *.

The results from the baseline model indicate that CESI has a positive influence on tourism recovery, although the effect is not statistically significant. However, when we disaggregate CESI and use only fiscal policy response and monetary policy response as measured by the interest rate cut, we observe that these factors positively impact tourism recovery. In particular, the interest rate cut is more consistently statistically significant than the fiscal policy measure. As shown in Table 2 , Column 4, a one percentage point increase in the fiscal stimulus is associated with an increase in the tourism recovery index by 0.41 units, albeit the effect is only significant at the 10% level. Similarly, a one percentage point decrease in interest rate cut is associated with an increase in the tourism recovery index by approximately 0.12 units.

The impact of a country's resilience on tourism recovery, on the other hand, is insignificant throughout the baseline model irrespective of whether we used the overall resilience index or the sub-components, namely risk quality resilience or supply chain resilience. Interestingly, the GHS index exerts a negative influence on the tourism recovery index.

The signs of the other co-variates are also in line with the expectation. Countries with an older population and a higher COVID-19 death rate experienced slower tourism recovery, however, the impact of these two variables is not statistically significant. Financial development, on the other hand, has a positive but statistically insignificant impact on tourism recovery.

The results reported in Table 2 highlight the importance of economic policy intervention as captured by fiscal stimulus and interest rate cuts in supporting the tourism sector's recovery vis-à-vis a country's level of resilience. The results do not, however, consider the likely moderating influence of the level of resilience in a country in the underlying relationship between COVID-19 economic policy interventions and the tourism sector recovery. Thus, we estimated the model given by Eq. (4) , where we included an interaction term between economic policy measures and resilience measures. The coefficients of this exercise are reported in Table 3 .

The recovery level of the tourism sector from COVID-19 pandemic and economic policy response: the role of countries' resilience (full model).

Notes: Ln denotes natural logarithms. The values in parentheses are robust standard errors. Significance at the 1%, 5%, and 10% level is expressed by ***, ** and *.

As depicted in Table 3 , the CESI has a positive and significant impact on tourism recovery in all three model specifications (see Columns 1–3). Similarly, the fiscal stimulus and interest rate cut positively impact tourism recovery, irrespective of the model specification and are statistically significant at conventional levels. However, the coefficients on economic policy variables provide an incomplete picture of the impact of economic policy on tourism recovery. To gain deeper insight, we need to look at the marginal effect of the economic policy variable on tourism recovery. This is because the marginal effect is contingent on the level of resilience of a country. The marginal effect of the economic policy variable on tourism recovery based on Eq. (4) is given by the following equation:

Eq. (5) suggests that the impact of economic policy variable on tourism recovery is contingent on the value of the resilience index. This implies that interpreting the coefficient of the economic policy or the interaction term alone can lead to misleading conclusions. Moreover, while interpreting the marginal effect, it is important to remember that it is possible for the total effect to be significant, even if β 1 , β 3 or both are insignificant. This is because the standard error of the marginal effect (given by Eq. (6) ) is also contingent on the value of the resilience index ( Friedrich, 1982 ).

As evident from the above equation, the standard error of the marginal effect varies with the resilience index score. This indicates that the effect of economic policy variable on tourism recovery could be significant at some values of the resilience index score and insignificant at other values. To fully capture the marginal effect of economic policy variable at different levels of the resilience index and visualize the size of the moderating effect of the resilience index, we plot the marginal effects together with the 90% confidence interval.

Fig. 1 , Fig. 2 , Fig. 3 depict the marginal effects of CESI, fiscal stimulus, and interest rate cut, respectively, on tourism recovery for different levels of overall resilience, risk quality resilience, or supply chain resilience. The overall message from these Figures is that economic policy has a positive impact on tourism recovery only in economies that are less resilient. 6 However, this pattern is more pronounced for the fiscal policy stimulus and interest rate cut as compared to the CESI.

Marginal effects of CESI on tourism recovery index for various values of overall, risk quality and supply chain resilience index.

Marginal effects of fiscal policy stimulus on tourism recovery index for various values of overall, risk quality and supply chain resilience index.

Marginal effects of interest rate cut on tourism recovery index for various values of overall, risk quality and supply chain resilience index.

As shown in Fig. 1 , the marginal effect of CESI on tourism recovery is positive and significant at lower levels of all three resilience indices. At higher levels of resilience indices, the marginal effect becomes insignificant and even negative. For instance, the marginal effect is positive and significant for all values of the overall resilience index lower than or equal to 45. This implies that for 48 countries (number of countries having an overall resilience index lower than or equal to 45) in the sample, the effect of CESI on tourism recovery is positive and significant.

A similar pattern emerges from the marginal effect of fiscal policy stimulus on tourism recovery (see Fig. 2 ) and the marginal effect of the interest rate cut on tourism recovery (see Fig. 3 ). The marginal effects of both fiscal policy stimulus and interest rate cut are positive and significant for countries at the lower spectrum of resilience as captured by overall, risk quality, and supply chain resilience. However, the marginal effect of interest rate cuts tends to be significant for countries with slightly higher resilience scores vis-à-vis fiscal policy stimulus and CESI. This suggests that we can accept the second hypothesis of this study.

4.2. Robustness checks

We also perform a battery of sensitivity checks by using different proxies for the control variables to establish the robustness of the results. First, instead of using the financial development index, we use its sub-indices, namely the financial institutions and financial markets index, respectively (Tables S4 and S5 in the supplementary material). In general, the results are qualitatively comparable to the results presented in Table 3 , with no significant differences. The country's resilience measures act as a moderator in the underlying nexus between economic policy response and tourism recovery. Moreover, the moderating influence is more pronounced when we use fiscal and monetary policy indicators to account for policy response as opposed to the CESI.

Similarly, instead of using the overall GHS index, we used two of its sub-components, namely the ability of a country to prevent the spread of pathogens and the quality of the health care system. Table S6 in the supplementary materials reports the results when we use prevention of the emergence or release of pathogens in lieu of the global health index, while Table S7 reports the results when the sufficiency and robustness of the health sector to treat the sick as well as offer protection for health workers is used in lieu of GHS index. Once again, the results remain qualitatively comparable to the ones presented in Table 3 , with the impact of economic policy response on tourism recovery dissipating as the level of resilience of a country increases, as captured by the three resilience variables.

4.3. Discussion

Our results provide key insights for researchers, practitioners, and policymakers alike on the drivers of tourism sector recovery from the COVID-19 pandemic. The results reported in Table 2 suggest that the tourism sector has gained the most from monetary policy interventions compared to fiscal policy response without accounting for the role of resilience in the underlying nexus. This finding is, to some extent, consistent with the first hypothesis and the existing literature, which finds that crisis management policies are highly effective in mitigating the negative impact of various shocks—such as the COVID-19 pandemic—on the tourism industry (see, e.g., Blake & Sinclair, 2003 ; Zhong et al., 2021 ; Kaushal & Srivastava, 2021 , and Pongsakornrungsilp et al., 2021 ).

The results in Table 2 also suggest that the role of resilience in reviving the tourism sector potentially differs across countries and its influence on tourism recovery is likely through its impact on economic stimulus packages. In addition, countries with a stronger health care system and with higher capabilities to respond to a pandemic-like event have experienced slower tourism recovery on average. One possible explanation of the negative impact could be that countries with higher GHS scores are more cautious when it comes to ‘opening up’ their economies, especially the tourism sector.

Results reported in Table 3 provide deeper insights regarding the relative strengths of economic policy response, the level of a country's resilience, and their joint impact in aiding tourism recovery. The results underscore the critical role of economic policy response for the recovery of the tourism sector, especially for countries that are less resilient and are less likely to be prepared to deal with a crisis, such as the COVID-19 pandemic. For instance, a recent study shows that economic policy response is more aggressive in countries that are more tourism-dependent ( Khalid, Okafor, & Sanusi, 2021 ). The findings from the current study suggest that the need for aggressive economic stimulus is particularly relevant in less resilient countries compared to more resilient countries.

Furthermore, the impact of economic stimulus on tourism recovery is reinforced by the level of resilience of a country with possible substitutability between resilience and economic policy response. Thus, at higher levels of resilience, the tourism sector is less likely to respond to economic policy interventions. This suggests that while the tourism sectors in more resilient countries can recover with less support from the public sector in terms of economic stimulus packages, the same is not applicable in less resilient countries.

A possible explanation for this result could be that high resilient countries have automatic stabilization policies and a well-established crisis management framework that automatically triggers a response in the event of a crisis. A case in point is Taiwan, which after the SARS outbreak in 2004, created National Health Command Center (NHCC). The NHCC is an operational command unit that coordinates efforts between central, regional, and local authorities to facilitate a timely response to a health emergency and/or crisis. As a result, the COVID-19 pandemic was managed much more efficiently by the Taiwanese government compared to any other country in the world ( Wang, Ng, & Brook, 2020 ), especially at the initial stages of the pandemic.

4.4. Theoretical and practical implications

The theoretical implications of our findings are twofold. First, the findings of this study highlight the importance of economic policies in mitigating the adverse impact of the crisis and aiding the recovery of the tourism sector. This suggests that the theoretical literature on tourism crisis management should focus more on the role of economic policies as a tool for crisis management in the tourism sector. Second, a comprehensive resilience theoretical framework is lacking in the tourism literature. Given the importance of resilience in tourism recovery after the crisis, as highlighted by our findings, there is a need to develop a tourism-specific resilience theoretical framework.

The findings of this study also offer grounds for several strategic policy agendas to aid the recovery of the tourism industry as the COVID-19 pandemic continues to wreak havoc across the world. This includes policy options for preparing for the next crisis and/or pandemic. These can be grouped under two broad themes. The first is the set of implications for tourism management pertaining to economic policy responses. The second relates to building resilience.

Focusing on the economic policy responses, countries with economic policies that are geared towards improving the liquidity of tourism businesses, especially small and medium tourism enterprises, could go a long way in mitigating the impact of the COVID-19 crisis. Furthermore, aggressive economic policy responses should be used by countries that are less resilient and not well prepared to handle the adverse shocks of the COVID-19 pandemic on the tourism industry. To ensure that stakeholders in the tourism industry benefit from economic policy responses, there has to be a push towards greater formalization of the sector, as informal enterprises may not benefit from economic stimulus packages or face greater difficulties accessing those benefits in a timely manner.

Beyond the implications relating to economic policy responses, the other key aspect of our study relates to the creation of an enabling environment for the emergence of a resilient economy, which includes developing a more elaborate crisis management strategy to respond swiftly to any future crisis, epidemic and/or pandemic event. Moreover, given that the risk perceptions of travelers have also changed due to the pandemic ( da Silva Lopes et al., 2021 ; Zhan et al., 2022 ), policymakers should consider designing targeted policies aimed at attracting visitors with a relatively high-risk appetite. For instance, policies that promote tourism experiences—by providing tourists with timely and diverse travel information, value-added and brand-building promotions—can significantly help the recovery of the tourism sector.

The results of our study provide some practical implications for tourism management and policy on the resilience front as well. As our empirical results have highlighted, countries with greater risk and supply-chain-related resilience are better placed to handle similar future shocks. This reinforces the need for countries to have a systematic policy focus dedicated towards building resilience. To this end, the policy design of such countries with significant tourism dependence should be aligned with resilience thinking which in turn requires the identification of the determining factors that help to promote resilience building in tourism management.

An emerging body of theoretical articles in tourism management (see, for instance, Sharma et al., 2021 ) has provided the contours of a resilience-based framework that would enable a rebound of the tourism industry from the COVID-19 outbreak. Two specific attributes stand out in this theoretical discussion. First is a focus on encouraging domestic tourism. In light of the international travel restrictions and the prevailing uncertainty about travel normalization, countries could revive the tourism sector by focusing on encouraging domestic tourism. To some extent, our empirical results in this study lend indicative support to this proposition as one of the components of the COVID-19 tourism index pertains to the mobility index, which encompasses elements of domestic tourism.

The second attribute that has been featured in the theoretical discussion on resilience relates to a harder push towards achieving greater digitalization of the tourism industry. This could potentially include the digital transformation of the tourism sector as one of the ways of enhancing resilience in the tourism industry, such as devoting more resources to digital presence, such as in-room technologies for entertainment and destination e-shopping. A recent study by Okafor, Khalid, and Gama (2022) has confirmed that economies that are more digitized tend to be more resilient as they introduce smaller COVID-19 economic stimulus packages.

Countries could also do well by resorting to non-traditional policy tools like encouraging digital financial inclusion to promote tourism. In fact, there has been anecdotal evidence that suggests that outbound tourists from China are more likely to use digital channels for tourist activities than other ways ( Dichter, Chen, Saxon, Jackey, & Suo, 2018 ). Thus, it is important for countries to focus on financial sector development—encompassing financial inclusion—more broadly in aiding tourism recovery. This is in line with the results of our study and consistent with the empirical findings of Gopalan and Khalid (2022) , who attribute a critical role for financial inclusion in spurring tourism development.

5. Conclusion, limitations and directions for future research

The COVID-19 pandemic heralded an unprecedented economic “scarring”, especially for the countries heavily dependent on the tourism sector. Consequently, most governments around the world introduced aggressive economic stimulus packages to alleviate economic losses due to the COVID-19 outbreak on different sectors of their economies, especially the tourism sector. This study attempts to understand the impact of these economic policies on the tourism industry's recovery and the role played by a country's resilience in the underlying relationship. More specifically, we explore whether the COVID-19 economic policy response has any impact on tourism recovery across countries and if the level of resilience of a country plays any role in the underlying nexus. To the best of our knowledge, this is one of the first attempts to quantify such impacts in the tourism literature.

Our empirical results indicate that tourism recovery is significantly influenced by the COVID-19 economic policy response. However, the impact of economic policy response on tourism recovery is contingent on the level of resilience of a country. In particular, amongst the less resilient countries, the impact of economic policy response on tourism recovery is the largest, but the impact disappears as countries become more resilient. In addition, we find that both fiscal policy response and interest rate cuts are effective in reviving the tourism sector, especially for less resilient countries. However, the impact of an interest rate cut is statistically significant for a slightly larger range of resilience scores. Furthermore, these results are robust to the addition of extra control variables and the use of different measures of control variables.

Notwithstanding the significance of our results, this study has some limitations, which also provide indicative directions for future research. First, given that the research question is topical in nature, it is not possible to explore the dynamic relationship between economic policies, resilience, and tourism recovery. Future research can address the same issue or similar issues in a dynamic setting as more data become available over time. Second, as discussed earlier, there is a lack of a comprehensive resilience framework in the context of the tourism sector; hence, there is no established resilience measure specific to the tourism sector. Thus, our study cannot specifically disentangle the impact of tourism sector resilience from other sectors in the economy. This also opens the doors for future research, whereby researchers can develop a measure of resilience specific to the tourism sector, drawing on the emerging theoretical literature on resilience in the context of the tourism sector.

To conclude, this study has taken a step towards integrating economic policy response and resilience in the context of tourism recovery from shocks such as the COVID-19 pandemic. This approach allows us to draw appropriate conclusions at a cross-country level. This study also offers several empirically testable propositions for future research to tackle, which could zero in on the factors that would help tourism businesses build resilience and prepare effectively to mount a recovery from similar crisis episodes in the future.

CRediT authorship contribution statement

Luke Okafor: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft, Writing – review & editing. Usman Khalid: Conceptualization, Data curation, Formal analysis, Investigation, Writing – original draft, Writing – review & editing, Funding acquisition. Sasidaran Gopalan: Conceptualization, Writing – original draft, Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study is supported by the United Arab Emirates University under the UPAR grant (# 12B001). The authors would like to thank Laura Elizabeth and Sumaiya Bhura for their assistance in this research.

Biographies

Luke Okafor is an Associate Professor at the University of Nottingham Malaysia. His research interests include international economics, applied economics, tourism economics, industrial economics, development economics.

Usman Khalid is an Assistant Professor at the United Arab Emirates University. His research interests include tourism economics, environmental economics and development economics.

Sasidaran Gopalan is an Assistant Professor at the United Arab Emirates University. His research specialization lies in the intersection of international finance and development policy.

Editor: Kirilova Ksenia

https://sthm.temple.edu/faculty/covid19-tourism-index/ .

2 We used the 13th CESI update (October 2020) by Elgin et al. (2020) in order to capture all the different types of economic support packages initiated by countries to lessen the effect of the COVID-19 outbreak.

3 For more details, see COVID-19 Economic Stimulus index: ( http://web.boun.edu.tr/elgin/COVID.htm ).

4 For more details, please see F.M Global Methodology (FM Global, 2020 ).

5 The dataset is accessible from https://ourworldindata.org/grapher/covid-tests-cases-deaths .

6 Marginal effect is significant if the confidence interval lines (dotted lines) do not include zero. Marginal effect is significant in all three figures at lower resilience index scores as the confidence interval does not include zero for lower values of the resilience index. Marginal effects with their standard errors for different values of resilience index are provided in Table S3.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.annale.2022.100073 .

Appendix A. Supplementary data

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10 Economic impacts of tourism + explanations + examples

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There are many economic impacts of tourism, and it is important that we understand what they are and how we can maximise the positive economic impacts of tourism and minimise the negative economic impacts of tourism.

Many argue that the tourism industry is the largest industry in the world. While its actual value is difficult to accurately determine, the economic potential of the tourism industry is indisputable. In fact, it is because of the positive economic impacts that most destinations embark on their tourism journey.

There is, however, more than meets the eye in most cases. The positive economic impacts of tourism are often not as significant as anticipated. Furthermore, tourism activity tends to bring with it unwanted and often unexpected negative economic impacts of tourism.

In this article I will discuss the importance of understanding the economic impacts of tourism and what the economic impacts of tourism might be. A range of positive and negative impacts are discussed and case studies are provided.

At the end of the post I have provided some additional reading on the economic impacts of tourism for tourism stakeholders , students and those who are interested in learning more.

 Foreign exchange earnings

Contribution to government revenues, employment generation, contribution to local economies, development of the private sector, infrastructure cost, increase in prices, economic dependence of the local community on tourism, foreign ownership and management, economic impacts of tourism: conclusion, further reading on the economic impacts of tourism, the economic impacts of tourism: why governments invest.

Tourism brings with it huge economic potential for a destination that wishes to develop their tourism industry. Employment, currency exchange, imports and taxes are just a few of the ways that tourism can bring money into a destination.

In recent years, tourism numbers have increased globally at exponential rates, as shown in the World Tourism Organisation data below.

There are a number of reasons for this growth including improvements in technology, increases in disposable income, the growth of budget airlines and consumer desires to travel further, to new destinations and more often.

Here are a few facts about the economic importance of the tourism industry globally:

• The tourism economy represents 5 percent of world GDP
• Tourism contributes to 6-7 percent of total employment
• International tourism ranks fourth (after fuels, chemicals and automotive products) in global exports
• The tourism industry is valued at US$1trillion a year
• Tourism accounts for 30 percent of the world’s exports of commercial services
• Tourism accounts for 6 percent of total exports
• 1.4billion international tourists were recorded in 2018 (UNWTO)
• In over 150 countries, tourism is one of five top export earners
• Tourism is the main source of foreign exchange for one-third of developing countries and one-half of less economically developed countries (LEDCs)

There is a wealth of data about the economic value of tourism worldwide, with lots of handy graphs and charts in the United Nations Economic Impact Report .

In short, tourism is an example of an economic policy pursued by governments because:

•      it brings in foreign exchange
•      it generates employment
•      it creates economic activity

Building and developing a tourism industry, however, involves a lot of initial and ongoing expenditure. The airport may need expanding. The beaches need to be regularly cleaned. New roads may need to be built. All of this takes money, which is usually a financial outlay required by the Government.

For governments, decisions have to be made regarding their expenditure. They must ask questions such as:

How much money should be spent on the provision of social services such as health, education, housing?

How much should be spent on building new tourism facilities or maintaining existing ones?

If financial investment and resources are provided for tourism, the issue of opportunity costs arises.

By opportunity costs, I mean that by spending money on tourism, money will not be spent somewhere else. Think of it like this- we all have a specified amount of money and when it runs out, it runs out. If we decide to buy the new shoes instead of going out for dinner than we might look great, but have nowhere to go…!

In tourism, this means that the money and resources that are used for one purpose may not then be available to be used for other purposes. Some destinations have been known to spend more money on tourism than on providing education or healthcare for the people who live there, for example.

This can be said for other stakeholders of the tourism industry too.

There are a number of independent, franchised or multinational investors who play an important role in the industry. They may own hotels, roads or land amongst other aspects that are important players in the overall success of the tourism industry. Many businesses and individuals will take out loans to help fund their initial ventures.

So investing in tourism is big business, that much is clear. What what are the positive and negative impacts of this?

Positive economic impacts of tourism

So what are the positive economic impacts of tourism? As I explained, most destinations choose to invest their time and money into tourism because of the positive economic impacts that they hope to achieve. There are a range of possible positive economic impacts. I will explain the most common economic benefits of tourism below.

One of the biggest benefits of tourism is the ability to make money through foreign exchange earnings.

Tourism expenditures generate income to the host economy. The money that the country makes from tourism can then be reinvested in the economy. How a destination manages their finances differs around the world; some destinations may spend this money on growing their tourism industry further, some may spend this money on public services such as education or healthcare and some destinations suffer extreme corruption so nobody really knows where the money ends up!

Some currencies are worth more than others and so some countries will target tourists from particular areas. I remember when I visited Goa and somebody helped to carry my luggage at the airport. I wanted to give them a small tip and handed them some Rupees only to be told that the young man would prefer a British Pound!

Currencies that are strong are generally the most desirable currencies. This typically includes the British Pound, American, Australian and Singapore Dollar and the Euro .

Tourism is one of the top five export categories for as many as 83% of countries and is a main source of foreign exchange earnings for at least 38% of countries.

Tourism can help to raise money that it then invested elsewhere by the Government. There are two main ways that this money is accumulated.

Direct contributions are generated by taxes on incomes from tourism employment and tourism businesses and things such as departure taxes.

Taxes differ considerably between destinations. I will never forget the first time that I was asked to pay a departure tax (I had never heard of it before then), because I was on my way home from a six month backpacking trip and I was almost out of money!

Japan is known for its high departure taxes. Here is a video by a travel blogger explaining how it works.

According to the World Tourism Organisation, the direct contribution of Travel & Tourism to GDP in 2018 was $2,750.7billion (3.2% of GDP). This is forecast to rise by 3.6% to $2,849.2billion in 2019.

Indirect contributions come from goods and services supplied to tourists which are not directly related to the tourism industry.

Take food, for example. A tourist may buy food at a local supermarket. The supermarket is not directly associated with tourism, but if it wasn’t for tourism its revenues wouldn’t be as high because the tourists would not shop there.

There is also the income that is generated through induced contributions . This accounts for money spent by the people who are employed in the tourism industry. This might include costs for housing, food, clothing and leisure Activities amongst others. This will all contribute to an increase in economic activity in the area where tourism is being developed.

The rapid expansion of international tourism has led to significant employment creation. From hotel managers to theme park operatives to cleaners, tourism creates many employment opportunities. Tourism supports some 7% of the world’s workers.

There are two types of employment in the tourism industry: direct and indirect.

Direct employment includes jobs that are immediately associated with the tourism industry. This might include hotel staff, restaurant staff or taxi drivers, to name a few.

Indirect employment includes jobs which are not technically based in the tourism industry, but are related to the tourism industry. Take a fisherman, for example. He does not have any contact of dealings with tourists. BUT he does sell his fish to the hotel which serves tourists. So he is indirectly employed by the tourism industry, because without the tourists he would not be supplying the fish to the hotel.

It is because of these indirect relationships, that it is very difficult to accurately measure the economic value of tourism.

It is also difficult to say how many people are employed, directly and indirectly, within the tourism industry.

Furthermore, many informal employments may not be officially accounted for. Think tut tut driver in Cambodia or street seller in The Gambia – these people are not likely to be registered by the state and therefore their earnings are not declared.

It is for this reason that some suggest that the actual economic benefits of tourism may be as high as double that of the recorded figures!

All of the money raised, whether through formal or informal means, has the potential to contribute to the local economy.

If sustainable tourism is demonstrated, money will be directed to areas that will benefit the local community most.

There may be pro-poor tourism initiatives (tourism which is intended to help the poor) or volunteer tourism projects.

The government may reinvest money towards public services and money earned by tourism employees will be spent in the local community. This is known as the multiplier effect.

The multiplier effect relates to spending in one place creating economic benefits elsewhere. Tourism can do wonders for a destination in areas that may seem to be completely unrelated to tourism, but which are actually connected somewhere in the economic system.

Let me give you an example.

A tourist buys an omelet and a glass of orange juice for their breakfast in the restaurant of their hotel. This simple transaction actually has a significant multiplier effect. Below I have listed just a few of the effects of the tourist buying this breakfast.

The waiter is paid a salary- he spends his salary on schooling for his kids- the school has more money to spend on equipment- the standard of education at the school increases- the kids graduate with better qualifications- as adults, they secure better paying jobs- they can then spend more money in the local community…

The restaurant purchases eggs from a local farmer- the farmer uses that money to buy some more chickens- the chicken breeder uses that money to improve the standards of their cages, meaning that the chickens are healthier, live longer and lay more eggs- they can now sell the chickens for a higher price- the increased money made means that they can hire an extra employee- the employee spends his income in the local community…

The restaurant purchase the oranges from a local supplier- the supplier uses this money to pay the lorry driver who transports the oranges- the lorry driver pays road tax- the Government uses said road tax income to fix pot holes in the road- the improved roads make journeys quicker for the local community…

So as you can see, that breakfast that the tourist probably gave not another thought to after taking his last mouthful of egg, actually had the potential to have a significant economic impact on the local community!

The private sector has continuously developed within the tourism industry and owning a business within the private sector can be extremely profitable; making this a positive economic impact of tourism.

Whilst many businesses that you will come across are multinational, internationally-owned organisations (which contribute towards economic leakage ).

Many are also owned by the local community. This is the case even more so in recent years due to the rise in the popularity of the sharing economy and the likes of Airbnb and Uber, which encourage the growth of businesses within the local community.

Every destination is different with regards to how they manage the development of the private sector in tourism.

Some destinations do not allow multinational organisations for fear that they will steal business and thus profits away from local people. I have seen this myself in Italy when I was in search of a Starbucks mug for my collection , only to find that Italy has not allowed the company to open up any shops in their country because they are very proud of their individually-owned coffee shops.

Negative economic impacts of tourism

Unfortunately, the tourism industry doesn’t always smell of roses and there are also several negative economic impacts of tourism.

There are many hidden costs to tourism, which can have unfavourable economic effects on the host community.

Whilst such negative impacts are well documented in the tourism literature, many tourists are unaware of the negative effects that their actions may cause. Likewise, many destinations who are inexperienced or uneducated in tourism and economics may not be aware of the problems that can occur if tourism is not management properly.

Below, I will outline the most prominent negative economic impacts of tourism.

Economic leakage in tourism is one of the major negative economic impacts of tourism. This is when money spent does not remain in the country but ends up elsewhere; therefore limiting the economic benefits of tourism to the host destination.

The biggest culprits of economic leakage are multinational and internationally-owned corporations, all-inclusive holidays and enclave tourism.

I have written a detailed post on the concept of economic leakage in tourism, you can take a look here- Economic leakage in tourism explained .

Another one of the negative economic impacts of tourism is the cost of infrastructure. Tourism development can cost the local government and local taxpayers a great deal of money.

Tourism may require the government to improve the airport, roads and other infrastructure, which are costly. The development of the third runway at London Heathrow, for example, is estimated to cost £18.6billion!

Money spent in these areas may reduce government money needed in other critical areas such as education and health, as I outlined previously in my discussion on opportunity costs.

One of the most obvious economic impacts of tourism is that the very presence of tourism increases prices in the local area.

Have you ever tried to buy a can of Coke in the supermarket in your hotel? Or the bar on the beachfront? Walk five minutes down the road and try buying that same can in a local shop- I promise you, in the majority of cases you will see a BIG difference In cost! (For more travel hacks like this subscribe to my newsletter – I send out lots of tips, tricks and coupons!)

Increasing demand for basic services and goods from tourists will often cause price hikes that negatively impact local residents whose income does not increase proportionately.

Tourism development and the related rise in real estate demand may dramatically increase building costs and land values. This often means that local people will be forced to move away from the area that tourism is located, known as gentrification.

Taking measures to ensure that tourism is managed sustainably can help to mitigate this negative economic impact of tourism. Techniques such as employing only local people, limiting the number of all-inclusive hotels and encouraging the purchasing of local products and services can all help.

Another one of the major economic impacts of tourism is dependency. Many countries run the risk of becoming too dependant on tourism. The country sees $ signs and places all of its efforts in tourism. Whilst this can work out well, it is also risky business!

If for some reason tourism begins to lack in a destination, then it is important that the destination has alternative methods of making money. If they don’t, then they run the risk of being in severe financial difficulty if there is a decline in their tourism industry.

In The Gambia, for instance, 30% of the workforce depends directly or indirectly on tourism. In small island developing states, percentages can range from 83% in the Maldives to 21% in the Seychelles and 34% in Jamaica.

There are a number of reasons that tourism could decline in a destination.

The Gambia has experienced this just recently when they had a double hit on their tourism industry. The first hit was due to political instability in the country, which has put many tourists off visiting, and the second was when airline Monarch went bust, as they had a large market share in flights to The Gambia.

Other issues that could result in a decline in tourism includes economic recession, natural disasters and changing tourism patterns. Over-reliance on tourism carries risks to tourism-dependent economies, which can have devastating consequences.

The last of the negative economic impacts of tourism that I will discuss is that of foreign ownership and management.

As enterprise in the developed world becomes increasingly expensive, many businesses choose to go abroad. Whilst this may save the business money, it is usually not so beneficial for the economy of the host destination.

Foreign companies often bring with them their own staff, thus limiting the economic impact of increased employment. They will usually also export a large proportion of their income to the country where they are based. You can read more on this in my post on economic leakage in tourism .

As I have demonstrated in this post, tourism is a significant economic driver the world over. However, not all economic impacts of tourism are positive. In order to ensure that the economic impacts of tourism are maximised, careful management of the tourism industry is required.

If you enjoyed this article on the economic impacts of tourism I am sure that you will love these too-

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Economic Leakage in Tourism: What It Is and How to Prevent It

Tourism is a significant driver of economic and social development. It is responsible for generating income, employment, investment, and ultimately, improving the quality of life for locals. But local communities in different destinations are not fully experiencing the benefits of this activity due to economic leakage in tourism.

When it happens, all the investment and effort put into growing tourism doesn’t pay off once part of the money generated by this industry leaves the host city or country.

This blog covers what economic leakage in tourism is, its consequences and what actions to take in order to keep tourists’ expenditures inside your destination.

What is economic leakage in tourism?

Tourism leakage happens when the revenue generated through tourism is lost to other countries or economies.

Tourism is an activity that traditionally brings foreign currency into a country’s economy. But due to globalization and travel conglomerates , this money is likely to leave the host country preventing the economic and social development of touristic areas.

Historically, economic leakage in tourism is more significant in developing countries . Sometimes it can nearly neutralize the money generated by tourism activity.

In Fiji, it is estimated that 60% of the money earned through tourism ends up leaving the country . In another study, tourism leakage estimates range from 40% in India to 80% in the Caribbean .

What triggers economic leakage in tourism?

Leakage is intrinsic to tourism and is present in all countries. However, its intensity varies in degree depending on how developed the destination is and the actions taken in order to prevent it.

Basically, leakage occurs through six main mechanisms :

1) Good and Service

In order to supply travelers’ demands, many destinations import goods and services. This type of economic leakage in tourism is more noticeable in islands, which are highly dependent on imports.

2) Infrastructure

In this case, tourism leakage happens when the host country doesn’t have the ability or technology to build tourism-related infrastructure and depends on foreign companies for it. For example, to build airports and ports or to implement a new travel technology.

3) Foreign ownership

When the tourism industry is not well-developed in a destination, it’s common for governments to attract foreign investment in order to start the activity in that area. However, when foreigners have ownership of the touristic infrastructure, the profits generated by this activity are taken away from the host market. That is the case in a destination dominated by international resort chains, for example.

4) Promotional expenditures

Having an international presence is paramount for many destinations, on the other hand, it’s a source of tourism leakage. When a destination invests in attracting foreign visitors , the money spent on advertisement and publicity goes abroad.

5) Tax exemptions

When a destination gives tax exemptions to foreign investors it is giving up tourism income. This strategy to grow the tourism industry is common in developing destinations, but it should be well planned in order to not harm the local community.

6) Foreign employment

During the high season, the increase in demand leads to the opening of temporary job opportunities. This often attracts foreign workers interested in making money and leaving the destination after the end of the season.

Why is economic leakage in tourism an issue for destinations?

Although tourism has lots of benefits —it boosts the local economy, creates new jobs, promotes cultural exchange— on the other hand, it also has negative impacts :

• Puts pressure on the local infrastructure
• Impacts the environment
• Changes the daily life of residents
• Drains local resources
• Affects the local production chain
• Increases the demand for goods, services and accommodations, which rises their prices

When the money earned through tourism leaves the host destination, little or nothing can be done in order to mitigate these bad impacts and promote social, cultural and environmental well-being for the local community.

Hence, tourism stops being an attractive investment and turns into an issue for the destination.

How can tourism stakeholders prevent tourists’ expenditures from leaving a destination?

Tourism leakage is harmful to destinations, especially the ones that rely on tourism as the primary source of income.

In order to prevent it, the government, destination managers, travel companies, the local industry, residents and visitors should work together to make sure the money spent on this activity is reaching the right pockets.

Some actions that destination leaders can take in order to reduce economic leakage in tourism are:

• Support local suppliers

The host community is a great source of workforce, services, and products that should be integrated into the local tourism industry. Destination managers should incentivize travel companies to buy from local producers before searching for suppliers abroad.

• Attract conscious travelers

Destination marketers should invest in campaigns to attract conscious travelers . This type of traveler knows the importance of tourism as an economic and social driver for the host community. They make sustainable choices, support the local suppliers and protect the environment.

• Promote niche tourism

Travelers looking for a niched experience are interested in discovering the local culture, history, culinary and hidden gems. Unlike mass tourism, which is usually offered by international companies and associated with overtourism, niche tourism is often offered by locals to a small group of travelers.

• Incentivize local companies

Instead of giving tax exemptions to international companies, try reducing the taxes for local accommodations, operators and producers. A relief in taxes gives a chance for the local tourism ecosystem to flourish.

• Limitate the presence of multinational corporations

All-inclusive packages are very popular among travelers. The issue is that about 80% of travelers’ expenditures on these packages go to international corporations . By restricting the presence of these companies in a destination, travelers should turn to local providers in order to have a complete stay.

• Stimulate the diversification of the local economy

The more dependent on tourism a destination is, the bigger the tourism leakage. A destination with a diversified economy has more bargaining power when dealing with international investors.

• Digitalize the tourism offer

Increasing the online exposure of local travel providers is a way to drive them more bookings. Destinations that are digitalizing their tourism offer, such as Visit Zagorije , not only make local companies more competitive but also facilitate the booking process for visitors.

Tourism leakage is an issue all destinations have to deal with. When not addressed, tourism income is drained out of the local community, preventing its economic, social and environmental development.

In this article, we have presented seven initiatives to fight back economic leakage in tourism :

If you are a destination manager or marketer interested in empowering your local tourism stakeholders, SmartDestination is the right partner for you. We are a group of award-winning tech companies specialized in travel, tourism and hospitality with a complete solution to digitalize your tourism offer.

Contact us if you want to boost your travel and tourism product.

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