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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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Tourism Review

ISSN : 1660-5373

Article publication date: 16 June 2020

Issue publication date: 26 February 2021

Tourism review (TR) celebrates its 75th anniversary in 2020. The purpose of this paper is to proffer a holistic overview of TR based on bibliometric analyses of the publications from 2001 to 2019.

Design/methodology/approach

The research method entails performance analyses and science mapping analyses on TR. The performance analyses engage a sequence of bibliometric statistics, including citation analysis, most cited authors and papers, most influential and productive authors, countries and institutions to name a few. The authors also used visualization of similarities viewer to perform the science mapping analysis of TR based on co-citations of cited authors, bibliographic couplings of authors and countries and co-occurrences of authors’ keywords from 2001 to 2019 and from 2014 to 2019. To examine the thematic evolution using SciMAT, a de-duplicating process was conducted in which 1,485 keywords were refined to 128 word groups before thematic evolution map and strategic diagrams for the three sub-periods were generated.

The thematic evolution map revealed ten thematic areas. The key themes of each of these thematic areas are destination studies, tourism destination and hospitality tourism; destination studies, competitiveness and innovations, co-operations and experience tourism; business studies, sports tourism, tourism destination and satisfaction; quality studies, networks, social studies and co-operation; business model and sports tourism; tourism management and tourism destination; political studies, perception and satisfaction; political studies, sustainability studies, social studies and health tourism; behavior, perception and satisfaction; and cultural tourism and tourism destination.

Research limitations/implications

The study has managed to unveil the key trends of publications, authors, affiliations, nations and authors’ keywords. The findings are useful for potential authors to have a quick snapshot of what is expected from and what is happening in TR.

Originality/value

The study serves as a historical record of TR’s publications. It presents comprehensive bibliometric analyses of the publications in TR and identifying the key research trends.

Tourism Review（TR）将于2020年庆祝其成立75周年。本论文研究的目的是基于2001年至2019年出版的相关文献数量加以分析, 并对TR进行全面概述。

研究方法需要对TR进行性能分析和科学映射分析。绩效分析涉及一系列的文献数量统计, 包括引用分析：引用最多的作者和论文, 最具影响力和生产力的作者, 国家和机构。作者们还使用VOSviewer对引用作者的共同引用, 作者与国家/地区的书目耦合以及2001年至2019年以及2014年至2019年共同出现的作者关键词来进行TR的科学制图分析, 并使用SciMAT, 进行了重复数据删除过程, 将1485个关键字简化为128个词组, 进行随后三个阶段主题性的进化图与策略图的制作。

从2001年到2019年, TR的出版物和其引用率出现了巨大的飞跃, 因为它引起了全世界各项研究人员, 机构和国家的极大兴趣。被引用最多的文献和最有影响力的作者多来自发达国家的机构, 包括美国（US）, 英国（UK）以及其他欧洲和大洋洲国家。但是, 亚洲和非洲大陆的国家也正在加入潮流, 并开始在TR中树立影响力。

该研究设法揭示了出版物, 作者, 隶属关系, 国家和作者的关键词的主要趋势。这些发现对于有潜能的作者快速了解TR预期和正在发生的事情很有帮助。

这项研究可作为TR出版物的历史记录。它将提供TR出版物的综合文献计量分析, 并确定了关键的研究趋势。

旅游期刊, 文献计量分析, 科学制图, 书目耦合, 共引, 共现, VOSviewer, SciMAT

Tourism Review (TR) celebra su 75 aniversario en 2020. El objetivo de esta investigación es ofrecer una visión global de TR basada en análisis bibliométricos de las publicaciones de 2001 a 2019.

Diseño / metodología / enfoque

el método de investigación implica análisis de rendimiento y análisis de mapeo científico en TR. Los análisis de desempeño involucran una secuencia de estadísticas bibliométricas, que incluyen análisis de citas, autores y artículos más citados, autores más influyentes y productivos, países e instituciones, por nombrar algunos. Los autores también utilizaron el VOSviewer para realizar el análisis de mapeo científico de TR basado en citas compartidas de autores citados, acoplamientos bibliográficos de autores y países y co-ocurrencias de las palabras clave de los autores desde 2001 hasta 2019 y desde 2014 hasta 2019. Para examinar el evolución temática utilizando SciMAT, se llevó a cabo un proceso de desduplicación en el que se refinaron 1485 palabras clave a 128 grupos de palabras antes de que se generaran mapas de evolución temáticos y diagramas estratégicos para los tres subperíodos.

hay un salto gigantesco en las publicaciones, así como las citas de TR de 2001 a 2019, ya que ha ganado mucho interés por parte de varios investigadores, instituciones y países de todo el mundo. La mayoría de los autores más citados e influyentes provienen de instituciones de países desarrollados, incluidos los Estados Unidos (EE. UU.), El Reino Unido (Reino Unido) y otras naciones europeas y de Oceanía. Sin embargo, países de los continentes asiático y africano se están uniendo al carro y comenzaron a establecer su influencia en TR.

Limitaciones / implicaciones de la investigación

el estudio ha logrado revelar las tendencias clave de publicaciones, autores, afiliaciones, naciones y palabras clave de los autores. Los hallazgos son útiles para que los autores potenciales tengan una instantánea rápida de lo que se espera de lo que está sucediendo en TR.

Originalidad / valor

el estudio sirve como un registro histórico de las publicaciones de TR. Presenta análisis bibliométricos exhaustivos de las publicaciones en TR e identifica las tendencias de investigación clave.

• Bibliometric analysis
• Science mapping
• Bibliographic coupling
• Co-citations
• Citation structure analysis
• Tourism journals
• Co-occurrence
• Revistas de turismo
• Análisis bibliométrico
• Mapeo científico
• Acoplamiento bibliográfico
• Co-ocurrencia
• Trabajo de investigación

Leong, L.-Y. , Hew, T.-S. , Tan, G.W.-H. , Ooi, K.-B. and Lee, V.-H. (2021), "Tourism research progress – a bibliometric analysis of tourism review publications", Tourism Review , Vol. 76 No. 1, pp. 1-26. https://doi.org/10.1108/TR-11-2019-0449

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Tourism and economic growth: A global study on Granger causality and wavelet coherence

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

Affiliation SLIIT Business School, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing – original draft

Roles Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Writing – original draft

Roles Conceptualization, Formal analysis, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Information Management, SLIIT Business School, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

Roles Supervision, Validation, Writing – original draft

• Chathuni Wijesekara, 
• Chamath Tittagalla, 
• Ashinsana Jayathilaka, 
• Uvinya Ilukpotha, 
• Ruwan Jayathilaka, 
• Punmadara Jayasinghe

• Published: September 12, 2022
• https://doi.org/10.1371/journal.pone.0274386
• Reader Comments

This paper empirically investigates the relationship between tourism and economic growth by using a panel data cointegration test, Granger causality test and Wavelet coherence analysis at the global level. This analysis examines 105 nations utilising panel data from 2003 to 2020. The findings indicates that in most regions, tourism contributes significantly to economic growth and vice versa. Developing trade across most of the regions appears to be a major influencer in the study, as a bidirectional association exists between trade openness and economic growth. Additionally, all regions other than the American region showed a one-way association between gross capital formation and economic growth. Therefore, it is crucial to highlight that using initiatives to increase demand would advance tourism while also boosting the economy.

Citation: Wijesekara C, Tittagalla C, Jayathilaka A, Ilukpotha U, Jayathilaka R, Jayasinghe P (2022) Tourism and economic growth: A global study on Granger causality and wavelet coherence. PLoS ONE 17(9): e0274386. https://doi.org/10.1371/journal.pone.0274386

Editor: Vu Quang Trinh, Newcastle University Business School, UNITED KINGDOM

Received: July 18, 2022; Accepted: August 26, 2022; Published: September 12, 2022

Copyright: © 2022 Wijesekara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its with Supporting information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Tourism is one of the world’s major industries, and people have been travelling for pleasure since the dawn of time. It has become one of the fastest expanding sectors of the global economy in recent years. Tourism arose as a result of modernisation and contributed significantly to shaping the experience of modernity. Economic growth and tourism development are intertwined, according to previous literature, therefore, an increase in the general economy will support tourism development [ 1 ]. As a result, it’s critical to investigate how tourism and other factors (including macroeconomic) are linked to economic growth. Economic growth can be defined as an increase in the real gross domestic product (GDP) or GDP per capita. Global tourism, as a key contributory business, has contributed to approximately 10% of global GDP through possible employment opportunities, extending client markets, encouraging export trades, and gains from foreign exchanges [ 2 , 3 ]. Another study that looked at the relationship between tourism and economic growth using variables like tourist receipts and tourism spending added to the literature by suggesting that tourism receipts impacted economic growth [ 4 ]. Additionally, according to Marin [ 5 ], tourism receipts have an upward link to the country’s economy and can thus aid in economic growth. Globally developed tourism business fosters economic growth over time, supporting the economy more than anticipated.

In recent years, research studies analysing the direction of the relationship between economic growth and tourism have been a popular area of interest in literature. A study of 12 Mediterranean nations in 2015 demonstrated a bidirectional causality relationship between tourism development and economic growth [ 6 ]. In a study conducted in Romania [ 7 ], a bidirectional causal relationship exists between GDP and the number of international tourist arrivals, whereas in an African study, a unidirectional causal relationship exists between international tourism earnings and real GDP, both in the short and long run [ 8 ]. According to previous research, this link appears to be both unidirectional and bidirectional.

Some of the processes by which tourism contributes to socioeconomic development include creating jobs, decreasing unemployment rates, and introducing of new tax income streams. In research conducted to investigate the relationship between tourism spending and economic growth in 49 nations, it was discovered that the two are inextricably linked, with a bidirectional causal relationship [ 9 ]. Investigating this relationship could be a useful for prioritising resource allocation across industries to improve overall tourism and economic outcomes.

Furthermore, a study based on 11 Asian regions discovers a close link between real international tourist revenues, capital formation, and GDP, confirming the tourism industry’s contribution to GDP [ 10 ]. Another study that looked at the relationship between tourism and economic growth based on tourist arrivals found that tourism is a good driver of economic growth [ 11 ]. This study looked into data of 94 countries, although there was no geographical examination of this association. Similarly, as previously mentioned, many authors have focused their research on a few countries or a single region when exploring the link between tourism and economic growth. The present study will contribute to filling the above-said research gap whilst providing an overall picture of the relationship between tourism and economic growth at the global level.

Many research papers have been written to determine the relationship between tourism demand and economic growth in diverse regions of the world. Based on certain regions, this link has been demonstrated to be bidirectional as well as unidirectional in the literature. The investigation of the relationship between tourism demand and global economic growth would provide a broad view of the relationship between these two factors. However, limited research has been done to examine this connection, which spans 18 years and includes regional data worldwide. Furthermore, because tourism is not the only element that influences GDP, other factors that considerably influence economic growth too must be considered. In the past, there hasn’t been much research conducted on the moderate impact of tourism on GDP. To address this gap in the literature, this research will examine the relationship between tourism demand and economic growth, as well as the moderating impact of variables such as gross capital formation and trade openness on economic growth in nations around the world. As a result, the current study focuses on all five regions, as there hasn’t been much research done on this topic.

The goal of this research paper is to examine the empirical relationship between tourism and economic growth along with the moderate impact of trade openness and gross capital formation for the worldwide regions. In four ways, the goals of this study can help improve the existing literature. Firstly, this study will be the most recent addition to the literature, focusing on an eighteen-year timeframe using panel data from 2003 to 2020. Secondly, this study will collect and analyse valid data from 105 countries including 42 countries in Europe, 25 countries in Asia & the Pacific, 18 countries in the Americas, and 20 countries from Africa and the Middle East region. The study’s emphasis on an 18-year time period and data from 105 countries allow the conclusions to be generalised and applied to any country. As a result, the study addresses one of the most significant flaws in the literature. Thirdly, in addition to the direct relationship between tourism on economic growth, this study attempts to examine the relationship between tourist receipts modulated by trade openness and gross capital formationon a region’s per capita GDP. These moderating effects on a country’s and region’s economic growth have yet to be investigated. Moreover, to the author’s knowledge, the wavelet technique hasn’t been used in previous research to analyse the relationship between per capita GDP and international tourist receipts. Additionally, analysis of this would produce precise and reliable data for future research and decision-making.

The next sections of the article are organised as follows: the first part analyses the existing literature, followed by the data used and the technique used in this investigation, then the findings and discussion, and lastly, the general conclusion of the study.

Literature review

This section includes contributions to the literature by a variety of scholars from various nations and locations. The conclusions of the study done for a particular region were segregated into regions, whilst studies were divided according to the manner of causal relationship.

Bidirectional causality between tourism and economic growth

The majority of earlier studies investigated the impact of tourism on economic growth in the European region. By adopting the Granger causality test Bilen, Yilanci [ 6 ] analysed the bidirectional causal connection between tourism development and economic growth, in the 12 Mediterranean countries with data from 1995-to 2012. Dritsakis [ 12 ] examined the impact of tourism on Greece’s economic development between 1960 and 2000, by using the Multivariate autoregressive and Granger causality tests. Here, the data revealed a ’Granger causal’ relationship between international tourism earnings and economic growth, a ’strong causal’ relationship between real exchange rate and economic growth, as well as simple ’causal’ relationships between economic growth and international tourism earnings, and real exchange rate and international tourism earnings. However, the above study conducted their research only for Greece. Further, the results of the above stated investigations based on 20 th century data, can vary with time. It is noteworthy that specially with the Eurozone crisis that started in 2009, Greece economy was among the severely affected in the region and hence, data do not reflect this situation. Surugiu and Surugiu [ 13 ] conducted a study using Romanian data, identified a long-term correlation between tourism development and economic growth.

According to the literature, several studies were conducted related to Tourism and economic growth. However, only a few studies have been conducted to analyse the causal relationship of both variables for countries worldwide. Most commonly utilised analytical tool is the Granger Causality test to identify the relationship between these two variables. A study conducted for 135 countries by Şak, Çağlayan [ 14 ] revealed that tourism revenue and GDP show bidirectional causality in Europe in contrast to unidirectional causality in America, Latin America, East Asia, South Asia, Oceania, Caribbean, and countries worldwide. However, the results of the above investigation were conducted based on data from 1995 to 2008, which can vary with time. Economic upheavals changes to economic policies in East Asia (including China, India) where geopolitical strategies are dominant, the impact of tourism revenue on GDP may not be significant. Moreover, Fahimi, Akadiri [ 15 ] tested the causality between tourism, economic growth, and investment in human capital in the microstates using data from 1995 to 2015. The results indicate that there is a bidirectional relationship between tourism and GDP. In the same period, Sokhanvar, Çiftçioğlu [ 16 ] performed a Granger causality analysis on 16 countries to investigate the causal relationship between tourism and economic development. The results proved bidirectional causality only in Chile. Further, this study found that seven countries do not show causality between variables. But as both studies were conducted only for selected countries, these results cannot be generalised about the global situation. Most recently, Pulido-Fernández and Cárdenas-García [ 17 ] explained the bidirectional link between tourism growth and economic development in 143 countries. According to them, tourism supports economic growth in the countries where tourism occurs. However, the study employed the level of economic development and tourism growth as a factor to cluster the countries for analysis; the results would most possibly change if another factor was used to cluster the countries.

Unidirectional causality between tourism and economic growth

In the European region, a long-run link was tested between economic growth and tourism based on international tourist receipts, real GDP, and the real effective exchange rate for Croatian nations using quarterly data from 2000-to 2008. Using the Granger causality test as the analysis tool, the results proved that a positive unidirectional causal relationship exists between economic growth and foreign tourism revenues [ 18 ]. Moreover, by adopting the Granger causality test for the annual GDP, the number of foreign visitors to South Tyrol and the relative prices (RP) between South Tyrol and Germany from 1980 to 2006, Brida and Risso [ 19 ] proved that the causation from tourism and RP to real GDP is unidirectional. A study published in 2013 asserted the link between tourist spending and economic growth. For Cyprus, Latvia, and Slovakia, the study discovered a growth hypothesis. whereas a negative relationship for Czech Republic and Poland [ 20 ]. Furthermore, Lee and Brahmasrene [ 21 ] found that tourism has a positive impact on economic growth and is inversely related to carbon dioxide emissions, using the panel cointegration technique and Fixed Effect (FE) model for the European region. Besides, the majority of previous investigators employed the Granger causality test to determine whether a bidirectional or unidirectional link exists between tourism and economic growth among European regions.

For the Asian Region, Oh [ 22 ] conducted on the Korean economy revealed that there is a one-way causal relationship between economy-driven tourism growth by using the Granger causality test for the period from the first quarter of 1975 to the first quarter of 2001. Furthermore, according to the Granger causality test and co-integration, no co-integration exists between tourism and economic growth in the long run and Tourism-Led Growth Hypothesis (TLGH) did not exist in the short term. However, the author noted that in order to generalise the study’s findings, it is necessary to investigate the TLGH under economic conditions of numerous nations. Examining the most recent study in further detail, Wu, Wu [ 10 ] used a multivariate panel Granger causality test to show a growth hypothesis between real GDP and real international tourism receipt in China, Cambodia, and Malaysia. However, an opposite growth hypothesis has been validated in the Philippines, Hong Kong, Indonesia, and South Korea. In Macau and Singapore, an inverse growth theory has been discovered.

Many researchers have studied the relationship between tourism and the African continent’s economic growth, with various kinds of dimensions and methodologies. In the early 20s, Akinboade and Braimoh [ 8 ] used the Granger causality test to assert the link between international tourism and economic expansion in Southern Africa, where the findings demonstrated a one-way causal relationship between international tourism earnings to real GDP with the use of data from 1980 to 2005. Providing more evidence in the same period utilising the same method, Belloumi [ 23 ] too disclosed that tourism has a beneficial influence unidirectionally on economic growth. Moreover, Ahiawodzi [ 24 ] employed the Augmented Dickey-Fuller (ADF) test for unit root, cointegration test, and Granger Causality to investigate the cointegration and causality of tourism revenues and economic growth. It found a unidirectional causality from economic growth to tourism in Ghana as well as a positive relationship and cointegration in the long run. Similarly, Bouzahzah and El Menyari [ 25 ] also discovered significant unidirectional causation from economic growth to international tourist receipts in the long term by analysing data of Morocco and Tunisia. However, since these studies are limited to one or two countries in the region, researchers were unable to view the bigger picture as a region. The most recent study by Kyara, Rahman [ 26 ] was conducted based on data from Tanzania from 1989 to 2018, considering the country’s international tourist receipts, real GDP, and the real effective exchange rate as variables. Here, findings of Granger Causality, and the Wald test supported the existence of one-way causation between tourism and economic expansion.

Only a few researchers have studied the causation between tourism and economic growth in the Middle East region. Countries such as Bahrain, Saudi Arabia, and Jordan should implement strategies to boost tourist arrivals with receipts by uplifting their tourism to tourists from outside the Middle East region [ 27 ]. Also, the scholars conducted panel cointegration and causality test based on data from 1981 to 2008, which revealed that tourism has a long-term relationship with economic growth. However, this research might be improved to include additional countries in the region, allowing for a more realistic comparison. In the meantime, the impact of tourism on economic growth in oil-rich nations was stated by Alodadi and Benhin [ 28 ]. In Jordan, Kreishan [ 29 ] discovered a unidirectional causal relationship between tourism earnings and economic growth by investigating data from 39 years up to 2009 using the Granger causality test. The importance of tourism to economic growth was explained by Tang and Abosedra [ 30 ] using annual data for the period 1995–2010 in Lebanon. Their findings demonstrated that tourism and economic expansion in Lebanon have a long-term association as tourism and growth are cointegrated and the results supported that the Tourism led Growth hypothesis is valid in this country. However, this analysis was performed with a small sample without considering additional variables apart from tourist arrivals and the real GDP. Providing more evidence, the same conclusion was provided [ 31 , 32 ], who tested data for Iran and Saudi Arabia, respectively. In addition, Ozcan and Maryam [ 33 ] claimed that measures to boost economic growth and development in the tourism sector of Qatar should be continued since a positive link exists between the said two factors. Ozcan and Maryam [ 33 ]. It may be determined from previous literature that the Middle East region exhibits a link between tourism and economic growth. Moreover, previous studies found that the tourism sector makes a small contribution to economic growth in oil-rich countries.

Many studies focusing on the countries of the American continent have deliberated the link between tourism and economic growth. According to Risso, Brida [ 34 ] the expenditure of international tourists has a favourable impact on Chile’s economic growth. The elasticity of real GDP to tourism spending (0.81) demonstrates that a 100% increase in tourism expenditure results in a long-run growth increase of more than 80%. With an elasticity of 0.35, the actual exchange rate also has a beneficial influence. This was examined using the Granger causality test as a basis for analysis using data from 1988 to 2009. Another study which was conducted by Brida and Risso [ 35 ], discovers that the causality of tourism and the real exchange rate to real GDP is unidirectional. Analysis of this study used the Granger test and the cointegrated vector model over data during the period 1988–2008. However, the above study only looked into data up to 2008. Similarly, Brida, Lanzilotta [ 36 ] analysed the causal relationship between Uruguay by adopting a Granger causality test. This study used variables such as GDP, Argentinean tourism expenditure, and the real exchange rate from 1987-to 2006, where it showed a positive relationship among the variables. However, this study was limited to Uruguay and Argentina. Using panel data from nine Caribbean nations from 1995 to 2007, a long-run relationship between economic growth and tourism was investigated by Payne and Mervar [ 18 ]. Here, researchers used international tourist arrivals per capita, real GDP per capita, and the real effective exchange rate. It proved that tourism has a large impact on per capita real GDP. Research conducted in Jamaica from 1970 to 2005 unveiled that increasing visitor receipts positively impacted on GDP. As a result, it was suggested that strategies should be focused on attracting more tourists, as this scenario would enhance not only tourism receipts but also Jamaica’s total economic growth [ 37 ]. However, the study described above, solely considered tourism receipts and GDP, excluding the other factors that affect GDP. Sánchez López [ 38 ] confirmed that international tourism has a positive influence on the Mexican economy by considering quarterly data from 1993 to 2017 and utilising GDP and tourist arrivals as variables.

Focusing on the worldwide studies, the case of Mediterranean countries, Tugcu [ 39 ] found a substantial and favourable correlation between tourism and economic growth. As these scholars affirmed, the relationship between economic growth and tourism has been studied for several groups of countries or nations. According to, the relationship between travel and economic growth varies per country, although European nations can experience economic growth through travel to European, Asian, and African nations. The most recent research, Enilov and Wang [ 40 ] examined the causal relationship between foreign tourist arrivals and economic growth using 23 developing and developed countries, in 1981–2017. It used a bootstrap mixed-frequency Granger causality approach using a rolling window technique to evaluate the approach’s stability and persistency over time concerning economic growth. The findings demonstrated that, in contrast to wealthy nations, the tourism industry in developing nations continues to be a major contributor in future economic growth.

In conclusion, many scholars have examined the connection between tourism and economic growth. However, the moderating impact of gross capital formation and trade openness with tourism receipts is yet to be studied. Moreover, limited studies were conducted to analyse the causal relationship between tourism and economic growth by employing the Granger Causality test. To fill this gap, this research investigates the direction of the causality between economic growth and demand for tourism whilst analysing the effect of gross capital formation and trade openness for the world regions.

Conceptual framework

To address the gaps in this analysis, the conceptual framework was developed to investigate the relationship between tourism and economic growth, including the moderate effect of gross capital formation and trade openness, for worldwide regions as stated in the study’s objectives. Fig 1 depicts the conceptual framework for investigating the empirical relationship between tourism and economic growth, as well as the moderate influence of gross capital formation and trade openness, globally and for each region separately.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

Source: Authors’ illustrations.

https://doi.org/10.1371/journal.pone.0274386.g001

The endogenous growth theory, which often views economic growth as an endogenous product of an economic system rather than the result of factors that affect it from the outside, serves as the theoretical foundation [ 41 ]. In comparison to non-high-tech service industries like tourism, the endogenous growth theory tends to highlight the benefits of high-tech industries as possibly more favourable for high long-run growth. Yet, specialising in tourism can be strongly linked to higher returns, which in turn reinforces the benefits enjoyed by marketplaces, firms, and sectors.

Data and methodology

This section presents a detailed view of the data, the statistical models employed in this study, and descriptive statistics for the variables.

This study was reviewed and approved by the SLIIT Business School and the SLIIT ethical review board. The following Table 1 illustrates the secondary data sources from which the information was gathered. The data file used for the study is presented in S2 Appendix .

https://doi.org/10.1371/journal.pone.0274386.t001

To measure economic growth across all regions, the current study employs yearly GDP per capita data from 2003. The amount of a country’s entire volume of goods and services produced relative to its total population is per capita GDP. To measure tourism growth, we use tourist receipts from 2003 until 2020. Tourism receipts were chosen over tourist arrivals because they incorporate both visitor arrivals and expenditure levels, resulting in a more accurate reflection of information on crucial aspects. Furthermore, the moderate impact on GDP per capita will be measured using gross capital formation and trade openness. Gross capital formation is a measure of a country’s yearly net capital accumulation as a proportion of GDP. The sum of goods and services and imports and exports represented as a percentage of GDP is known as trade openness. All the variables were converted as natural logarithms.

Methodology

The causal link between PGDP and TOUR by analysing the moderating effect of GCF and TRADE is tested using the panel Granger causality test [ 42 ]. According to Wang, Zhang [ 43 ], to assess if the sequence of data is stationary the unit root test will be performed and the co-integration tests will be used to analyse the connection between the variables if they are non-stationary. Based on the co-integration test, the Panel Granger causality test will be adopted to determine the existence of the direction and the causal connection between tourism and economic growth by analysing the moderate effect of GCF and TRADE .

The CUSUM test was carried out to assess the stability of the parameters for countries in the regions separately. Brown, Durbin [ 45 ], Hawkins [ 46 ], Koshti [ 47 ] and Rasool, Maqbool [ 48 ] provided more explanation on how to identify and analyse the plot of CUSUM.

With the help of the above-mentioned equation and to prove the dynamics between the PGDP and TOUR from 2010 to 2020, the Wavelet Coherence approach is used in order to deeply analyse the existence of a correlation among the variables discussed. Goupillaud, Grossmann [ 49 ] developed the wavelet technique in its natural form, and the concept’s foundation is based on their expertise knowledge. A time series is decomposed into a frequency-time domain using the wavelet technique. Pal and Mitra [ 50 ], Adebayo and Beton Kalmaz [ 51 ], Kalmaz and Kirikkaleli [ 52 ] and Adebayo, Onyibor [ 53 ] explained how to analyse and the explanation of the wavelet coherence. The wavelet method is used in this study to further visually confirm the existence of a causal relationship among PGDP and TOUR .

The panel granger causality test was carried out using STATA whereas R Studio was used for the CUSUM test and Wavelet coherence.

Empirical results and discussions

Before analysing Granger causality, Table 2 shows descriptive statistics for the major variables concerning worldwide countries and each region separately. This includes 1,890 total observations, of which 360, 324, 450, and 756 observations are for Africa & Middle East, America, Europe, and Asia & Pacific, respectively.

https://doi.org/10.1371/journal.pone.0274386.t002

Fig 2 illustrates the mean PGDP and the mean TOUR for the world’s countries from 2003 to 2020, discovering the trend and patterns of key factors.

Note: The data points were converted as natural logarithms. Source: Authors’ illustration based on data from the world bank, UNWTO, and WorldData.info.

https://doi.org/10.1371/journal.pone.0274386.g002

According to Fig 2(A) , the African & the Middle East region has the lowest PGDP when compared to other regions, while the European regions have the highest PGDP . The PGDP of the Americas and Asia & Pacific areas fluctuated similarly until 2017, thereafter, the gap between these two countries narrowed. As indicated in Fig 2(B) , the disparity in tourist receipts between America and the Asia-Pacific area has been nearly identical throughout the years. The European region has recorded the highest tourist receipts when compared to other regions. The graph shows that tourist revenues have dropped sharply after 2019. This is because tourism has been one of the most affected industries due to the covid pandemic. A massive drop in demand due to increased worldwide travel restrictions, including the closure of several borders worldwide led to tourism sector collapse.

The unit root tests are used in this study to determine if the data set of PGDP , TOUR , TRADE , and GCF is stationary or non-stationary. The following Table 3 shows the test results for unit roots.

https://doi.org/10.1371/journal.pone.0274386.t003

The variables PGDP , TRADE , and GCF are stationary, according to the findings of the unit root tests. The Fisher-type unit-root test shows that some panels of the variable TOUR are stationary, but according to the Levin-Lin-Chu unit root test, the variable TOUR is nonstationary. As a result, the cointegration test is used to identify whether there is a long-term link between the variables PGDP and TOUR .

Table 4 presents the panel data cointegration test and results of the unit root tests proved that the variable TOUR is nonstationary. The findings of all the tests, except the Kao cointegration test, indicated that PGDP has a long-term connection with TOUR . It is possible to claim that there is at least a one-way Granger causality as the variables are co-integrated. According to the results of the stability test in Fig 3 , the blue line in in the plot of recursive CUSUM does not cross the red line, it provides strong support that the model fits the data and that the variables are stable for all regions.

Source: Authors’ illustration using R-Software.

https://doi.org/10.1371/journal.pone.0274386.g003

https://doi.org/10.1371/journal.pone.0274386.t004

According to Table 5 , a bidirectional causal relationship exists between PGDP and TOUR for all the regions. However, the existence of a bidirectional relationship between TRADE and PGDP was discovered for all the regions except for the European region. On the other hand, a one-way causal connection (unidirectional) between PGDP and GCF was discovered for the American region, whereas all other regions proved the existence of a two-way relationship (bidirectional) between PGDP and GCF .

https://doi.org/10.1371/journal.pone.0274386.t005

Based on the findings of all countries, it can be observed that all the estimated z values of the variables PGDP , TOUR , TRADE , and GCF are significant at 0.001. Therefore, with the current estimators, it can be stated that in most countries worldwide, tourism growth Granger causes economic growth and vice versa. Subsequently, it could be assumed that tourism can drive economic growth in a majority of countries and economic growth can boost tourism growth. Fahimi, Akadiri [ 15 ] asserted that tourism to real GDP has a bidirectional causality relationship, where GDP Granger causes tourism and vice versa. However, Enilov and Wang [ 40 ] provide evidence for the validity of the economic-driven tourist growth in developing economies, while providing less support for developed ones. Similarly, according to Tugcu [ 39 ], Mediterranean area shows a favourable correlation between tourism and economic growth. This is likely attributable to a change in sample size, since our data set includes 105 nations and data spanning 12 years. But the research described above used a sample fewer than 25 nations. Furthermore, at the 1% significant level, the empirical findings prove that the PGDP Granger causes TRADE , GCF , and vice versa. Implications of these are that in most nations, the variables TRADE and GCF in PGDP have predictive ability amongst each other.

Similar to the worldwide countries, the values of the African and the Middle East region along with the Asia and Pacific region showed a significant relationship. At the 1% significance level, a Granger causal link between PGDP and tourist receipts was discovered, i.e., This means that tourism leads to economic growth and vice versa in the African and Middle East regions, as well as the countries in the Asia and the Pacific region. This finding was reconfirmed in a previous study conducted in Lebanon where it concluded that a bidirectional Granger causality exists between tourism and economic growth in the short run [ 30 ] in the Middle East Region. Similarly, these results were validated in South Africa by Odhiambo and Nyasha [ 54 ]. Moreover, for the Asian and Pacific region, Wang, Zhang [ 43 ] confirmed that there is a bidirectional Granger connection between China’s domestic tourism and economic growth. Additionally, using the Granger causality test, Mohapatra [ 4 ] proved the same results for the Asian and Pacific regions. According to the findings of these studies, the governments of these regions should promote practices and policies that would benefit the tourism industry and the economy, as tourism growth stimulates general growth in the economy and vice versa. Tourist revenues have surged across the Asia-Pacific region along with PGDP , as the region has evolved into a popular tourism destination for all sorts of diverse tourists. The rich biodiversity of several countries in the Asia and Pacific region has sparked the development of numerous sectors that have increased GDP, which in turn has had a substantial influence on tourism. A few countries in the Asia and Pacific area offer as much natural beauty, which makes them popular tourist destinations. The hospitality, infrastructure, convenient accommodation, and variety of attractions in these countries offer a solid basis for the Asia and Pacific region’s tourism industry. The proportion of international tourist arrivals in the African region is relatively low due to the region’s political unrest, yet tourism is one of Africa’s most promising industries concerning economic growth. The Middle Eastern nations are situated in the middle of important geographical locations. This aspect made it easier to establish global economic connections, which helped the economic growth of the countries over time. The Middle East led urbanisation and other development strategies that gave the region the required infrastructure and setting for the tourist destinations to begin providing of travel and tourism services. As a result, the Middle Eastern countries are increasingly opening their doors to tourists. Moreover, according to the finding, the null hypothesis of the Granger Causality test for the variables PGDP to TRADE , TRADE to PGDP , PGDP to GCF and GCF to PGDP can be rejected at a 1% significant level.

In contrast to countries worldwide, the American region revealed that a significant connection exists between PGDP , TOUR , and TRADE . Findings of this study affirmed that a one-way causal connection exists only from GCF to PGDP in the Americas region. These results mainly indicate that an increase in tourism could increase economic growth in the American region and vice versa. Several American countries, such as the United States and Canada, have a well-established tourism industry that contributes significantly to their GDP and, in turn, their highly developed economic systems encourage the development of infrastructure and tourist destinations. Governments are actively implementing regulations that intend to improve the economic, biological, and social advantages that tourist industry may offer, whilst lessening the challenges that occur when this expansion is unprepared and uncontrolled. Overall, tourist growth patterns in the Americas area are favourable. For the nations of the Americas region, in order to guarantee that their measures to improve tourism are conducted within the larger framework of local, regional, and country’s economic targets. Furthermore, to assist the shift to a green and low-emissions, additional initiatives are also being made to incorporate sustainability in tourism policy and industry regulations.

Considering the European region, a significant connection exists only among the variables PGDP , TOUR , and GCF . As a result, these findings show that tourist revenue and PGDP are mutually influenced. Furthermore, a significant link between TRAD E and PGDP was identified only in European region nations, demonstrating that PGDP does not cause TRADE, but TRADE has the predictive potential over PGDP at a 1% significance level. Europe is regarded as the overall dominant participant in the tourism industry, which fosters economic growth, due to the increasing affordability of travel for bigger groups of people. As tourism directly affects economic growth, it is possible to obtain economic growth in the European region by safeguarding the environment, preserving natural resources, generating jobs, enhancing cultural variety, and respecting cultural traditions. Authorities should focus on developing the tourist industry to obtain high economic growth, and to improve tourism, essential efforts should be taken to enhance economic growth. This is because bidirectional causation exists between tourism development and economic growth of the 12 Mediterranean countries [ 6 ].

The summary of Granger-causality analysis results for PGDP – TOUR , PGDP – TRADE and PGDP – GCF were presented in Table 6 .

https://doi.org/10.1371/journal.pone.0274386.t006

All four regions show a bidirectional causal relationship between PGDP and TOUR . Furthermore, for the Africa & Middle East, America, Asia & Pacific areas, a two-way causal (bidirectional) link between PGDP and TRADE is demonstrated, whereas there is a one-way causal (unidirectional) link between PGDP and TRADE for the European area nations. When considering the causative relationship between PGDP and GCF , it is discovered that there is a bidirectional causal relationship in all regions except the Americas. In order to examine the relationship between variables among country’s separately, this study summarised the results of Granger Causality for the countries in each region separately in S1 Appendix .

Table 7 interprets the direction of the arrows and the frequency. The direction of the arrows will indicate whether the variables move in phase (rightward arrow indicating a positive correlation), or anti phase (leftward arrow indicating a negative correlation) and the cold (blue) regions of the figure indicates no correlation while the warm (red) regions depict the analysed variables are correlated. The wavelet coherence graph is identified according to the scale as the upper portion, middle portion, and lower portion which represents the short term, medium term and long term respectively.

https://doi.org/10.1371/journal.pone.0274386.t007

The correlation between PGDP and TOUR for each region individually from 2003 to 2020 is shown in Fig 4 . When considering the entire period, the arrows in Fig 4(A) are pointing right in the short and medium terms (high and medium frequencies), indicating a worldwide positive impact between PGDP and TOUR when assessing the entire period.

Source: Authors’ compilation using R-Software.

https://doi.org/10.1371/journal.pone.0274386.g004

In Africa & Middle east region Fig 4(B) between 2009 and 2020, there are rightward arrows indicating a positive connection in the short and medium term with a high and medium frequency. Additionally, the rightward and downward arrows between 2009 to 2011 and 2016 to 2020 show that PGDP led TOUR in the short term with high frequencies. However, there is a negative association between 2006 to 2008 because of the existence of leftward arrows in the short with high frequency.

Overall, in American Region, Fig 4(C) demonstrates a favourable relationship with a high and medium frequency in all terms from 2003 to 2020. Furthermore, the rightward and downward arrows between 2008 to 2012 PGDP is leading to TOUR , in the short and long term (high and low frequencies).

Fig 4(D) illustrates a positive impact between Asia & Pacific Regions PGDP and TOUR in the short term with high and medium frequency over the years from 2003 to 2019, expect 2005 to 2006, 2008 to 2009, 2012 to 2013 and 2017 to 2018. There is a negative association in mentioned years because of the existence of leftward arrows in the short term with high frequency.

Fig 4(E) indicates a positive impact in the short and medium term (high and low frequencies) from 2003 to 2020 for the European region. Moreover, between 2006 and 2010, the arrows pointing right and up show a positive influence from TOUR to PGDP in the long term with low frequency. Similarly, the arrows in the medium term (medium frequency) between 2008 to 2011 and 2016 to 2018 are pointing downward and right, indicating that PGDP leads to TOUR .

Table 8 summarises the results of our Granger-causality analysis and wavelet coherence for PGDP and TOUR .

https://doi.org/10.1371/journal.pone.0274386.t008

As the wavelet coherence technique captures the time dependence of the variables which is conjointly captured under the Granger causality approach, the findings revealed that overall finding of both techniques brings unanimous results, bringing justifications to the study. Both Granger Causality and Wavelet Coherence methods demonstrated that PGDP and TOUR had a bidirectional link in each region separately and globally. Where it demonstrates that tourism drove economic expansion and vice versa.

This research was conducted to obtain evidence supporting the connection between tourism and global economic growth, using the panel Granger causality test with panel data from 2003 to 2020. The results of the link between TOUR and PGDP revealed a strong bidirectional connection. The results, firstly, indicated that tourism has the ability to boost economic growth in all regions, and vice versa. Secondly, a bidirectional relationship between TRADE and PGDP was observed in all regions except in the European region countries. Thirdly, the American area indicated a one-way causal association between PGDP and GCF , whereas the other regions revealed a two-way relationship between PGDP and GCF . Thus, based on these results, it is evident that tourism plays a substantial role in economic growth and vice versa across most regions. Therefore, it is important to emphasize that the use of demand-creation strategies to progress tourism would also boost economic growth.

Further to the bidirectional relationship between TRADE and PGDP , developing trade appears to be a powerful influencer in this study. Having said that, countries with increased tourism also have achieved developed trade and according to analysis, these two variables seem interrelated and mutually beneficial. It also suggests that in most countries, the variables TRADE and GCF in PGDP have the potential to forecast one another since the empirical findings show that the PGDP Granger causes TRADE , GCF , and vice versa. This paper differs from previous research in that it examines the relationship over 18 years, as well as the moderating impact of variables such as GCF and TRADE on economic growth in countries worldwide. Since the data set utilised in this study has a significant number of records, the analysis is more accurate, as the statistical soundness of results grows with the number of observations. As a result, the findings derived from this study could be generalised to the larger population including the entire world. In conclusion, it can be argued that tourism may be used as a catalyst for economic growth and vice versa. It is advised that nations in all regions proceed with caution when deploying more measures to attract visitors, as tourism has a strong influence PGDP . Moreover, the governments of these regions should support practices and policies that would benefit the tourism sector and eventually, the economy. The decision-makers should focus more effective tourism policies on addressing the demand generated by the rise in tourism-related businesses. Additionally, governments should promote investments in tourism-related industries to all types of investors as these ultimately boost the nation’s GDP. Global events such as the pandemic, economic downturns, and the war eruptions have triggered an unprecedented tourism economic crisis, due to the rapid and massive shock to the tourist industry. Due to this, tourism can be a vulnerable channel attracting refugees. This scenario can be risky as the increased pressure on the public finances exerts a higher burden on tax income and economic growth due to the migration of refuges in some countries. In this context, it is critical to overcome this predicament, as the negative repercussions could have a significant impact on the industry, and recovery will take time.

Here by examining the Wavelet Coherence graphs which had been drawn for the regions, American Region has the highest correlation between PGDP and TOUR from 2010 to 2017 compared to the other regions. Most of the graphs indicate a Bidirectional link, which is line with the findings of the panel granger causality. The visual representation of the bidirectional association between TOUR and PGDP in these results reflects the conclusions of the panel granger causality.

Limitations

For this study, data were collected from 105 countries over 18 years, from 2003 to 2020. Other potential variables that influence tourism demand and economic growth, such as the real effective exchange rate, destination attractiveness, seasons, people’s spending capacity, security, urbanization, weather patterns etc., were not included in this study, which is a significant limitation. Moreover, the negative externalities of tourism and economic growth were not taken into account in this study due to the availability of data. For study purposes, countries were divided into regions, and those that depend heavily on tourism were not considered specific. As a result, the limitations mentioned above will need to be addressed in future studies. Future research studies should target to analyse the impact of tourism on economic growth and vice versa by adopting methodologies like the panel regression or generalised method of moments (GMM) which would further clarify the behaviour of these two variables more richly. Additionally, future study might assess the connection between tourism and economic development for each country in the relevant region independently.

Supporting information

S1 appendix. granger causality test results for the countries in each region..

https://doi.org/10.1371/journal.pone.0274386.s001

S2 Appendix. Data file.

https://doi.org/10.1371/journal.pone.0274386.s002

Acknowledgments

The authors would like to thank Ms. Gayendri Karunarathne for proof-reading and editing this manuscript.

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Travel & Tourism Development Index 2021: Rebuilding for a Sustainable and Resilient Future

4. Key findings

Several key findings have been identified in the Travel & Tourism Development Index (TTDI) 2021 results and research. First, the need for T&T development has never been greater as it plays a critical role in helping the global economic recovery by supporting the livelihoods of some of the populations hardest hit by the pandemic and by building resilience, especially when it comes to lower-income countries. Moreover, by investing in the factors that help drive T&T, many economies can leverage tourism to further their overall development. The need for T&T development has never been greater as it plays a critical role in helping the global economic recovery.

Second, the key findings show not only how ongoing challenges such as reduced capacity and labour shortages are tempering the recovery but also how shifting demand has created opportunities, forcing many T&T businesses and destinations to adapt, highlighting the sector’s impressive flexibility. Third, the analysis explores in more detail how various aspects and drivers of T&T development can be more thoughtfully and effectively considered and employed to bolster the recovery and build a more inclusive, sustainable and resilient T&T sector.

4.1 The need for Travel and Tourism development has never been greater

The case for t&t development.

As already alluded to in the global context section above, the T&T sector’s significant contribution to global economic and social development makes its recovery and long-term growth paramount. In 2019, the sector’s direct, indirect and induced output accounted for about 10% of global GDP. Moreover, for many emerging economies, T&T is a major source of export revenue, foreign exchange earnings and investment. On average, out of the economies covered by the TTDI, T&T contributed 70% more towards the exports of middle-income economies than to the exports of high-income economies in 2019. 10 Consequently, restoring T&T sector growth will be particularly vital for developing economies’ recovery. For instance, the World Bank forecasts that emerging markets and developing economies (EMDEs) will not return to pre-pandemic economic output trends until after 2023, with more than 80% of tourism-reliant EMDEs still below their 2019 economic output at the end of 2021. 11 Recent concerns about the slowdown in globalization and trade due to the impact of the pandemic and geopolitical tensions 12 further enforce how important T&T is for global connectivity.

It is also important to note that T&T is vital not only to overall economic performance but also to the livelihood of some of the populations and businesses most vulnerable to, and hardest hit by, the pandemic. This sector contributed to about 10% of global jobs in 2019, 13 employs almost twice as many women as other sectors, has a large share of youth employment and is a major source of jobs for minorities, migrants, informal workers and low-skilled workers. 14 Moreover, SMEs account for more than 80% of T&T businesses. 15 Unsurprisingly, research has shown that T&T growth can support social progress and create opportunities and well-being for communities. 16 Consequently, investing in T&T could not only mitigate the impact of the pandemic but also improve socioeconomic progress and resilience.

Enabling the T&T development landscape

With the case for T&T’s recovery and development clear, it will be critical to focus on and invest in the factors and policies (beyond the critical need for vaccine distribution) that can help enable these goals, many of which are measured by the TTDI. World Economic Forum research shows that TTDI performance correlates with direct T&T GDP, international tourist arrivals and receipts. 17

Figure 3: Travel and Tourism economic and enabling development landscape

Figure 3 can help us understand which economies are likely to be best positioned from a T&T recovery and resiliency point of view, and which may need to prioritize greater investment in T&T enabling factors. This is illustrated by comparing the TTDI scores to economic dependence on T&T. Low- and middle-income economies tend to score below the TTDI average, indicating a potential constraining factor for their economic recovery. In particular, economies in the bottom-right quadrant would gain the most by investing in the drivers of T&T development because they are more dependent on the sector for economic development. Such investment will help their economic recovery by enabling stronger tourism growth as well as supporting their overall economies to be more robust and resilient. On the other hand, while economies in the bottom left are less dependent on T&T, their below-average TTDI score may indicate that their conditions are leading to an underuse of the sector’s ability to drive development, weakening their economic potential – a resiliency issue in itself.

Higher TTDI scores for economies in the top two quadrants indicate that they are more mature markets and are best positioned for the sector’s recovery. Countries in the top-left quadrant are in a more optimal position from a resiliency point of view as they have favourable conditions for T&T operations but are also less reliant on it for their overall economic performance. However, that is not to say that T&T does not play an important role in their overall economic development, especially at the local level and for specific segments of the labour force and SMEs. Meanwhile, economies in the top-right quadrant, like those below them, have also been more vulnerable to the impact of the pandemic, especially given that analysis shows they are typically more reliant on the export of T&T services. These factors may limit their ability to recover economically from the pandemic, but they are also better positioned to generate tourism-led economic growth as international tourism returns. In general, for the most mature T&T countries such as those higher in the top quadrants, sector performance and resilience may be less about making major improvements in aspects of T&T development such as infrastructure and more about continuously calibrating their T&T strategies to adapt to changing demand dynamics, local needs and overall T&T trends.

Figure 4: TTDI 2021 pillar performance

Figure 4 shows in more detail what gaps remain to achieving improved T&T performance and development for various countries. High-income economies and countries in the Europe and Eurasia (Europe) and Asia-Pacific (APAC) regions tend to lead the overall index in results. Among the largest differentiators between index leaders and laggards are: the distribution and promotion of natural, cultural and non-leisure assets and activities; the availability of quality transport and tourist service infrastructure; the degree of international openness; and favourable factors such as (increasingly important) ICT readiness and health and hygiene. However, as shown in the Travel and Tourism Competitiveness Report 2019, because T&T growth is so dependent on factors such as infrastructure and health and hygiene, which if improved bring benefits to more than the tourism sector, sector leaders can play a valuable role in encouraging investment that benefits a country’s economy as a whole. This is especially true for developing economies that have innate natural and cultural assets around which to mobilize investment. 18 The next section detailing key findings will use the TTDI results to discuss the T&T challenges and opportunities created over the past few years, as well as examining how various drivers of T&T development can be employed to bolster T&T recovery and build a more inclusive, sustainable and resilient T&T sector, thereby unleashing its potential for economic and social progress.

4.2 Recovery challenges and shifting demand dynamics

The results highlight difficult operating conditions.

While varying greatly based on local, segment, national and regional conditions, the TTDI results and research help highlight some of the various and common operational challenges the T&T sector faces in its recovery.

With T&T activities being severely restricted over the past few years, the greatest decline in index performance has come from the contraction of related operations and investment. As such, average scores fell in the Air Transport Infrastructure (-9.4%), Prioritization of Travel and Tourism (-6.7%) and Tourist Service Infrastructure (-1.5%) pillars. Air route capacity and airport connectivity plummeted, especially in more mature and high-income economies. Similarly, the decline in tourist service infrastructure reflects initially reduced capacity in the accommodation and related segments. The average number of per capita short-term rental units dropped by about one-fifth between mid-2019 and 2021 across economies ranked in the index. 19 While not reflected in the TTDI results, STR data indicates that, over a similar timespan, the number of hotel rooms did not recover to pre-pandemic levels in many countries. 20 In line with these trends, both T&T capital investment and government T&T expenditures also fell. The decline in sector capacity has also been compounded by the fact that most businesses are SMEs and do not have the means to survive prolonged drops in demand or restrictions on person-to-person contact. The disproportionate impact of the pandemic on the sector is indicated by the direct T&T contribution to global GDP falling from 3.2% to 1.6% and the contribution to global employment falling from 3.8% to 3.1% between 2019 and 2020. 21

Figure 5: Select pillar 2019 to 2021 average score change

Yet, as demand resumes in line with easing travel restrictions and somewhat improving COVID-19 conditions, the initial reductions in capacity increase the potential for supply-side constraints. In advanced economies, in particular, rising demand, earlier layoffs that disproportionality hit T&T, and competition for talent with other sectors have resulted in widespread labour shortages. A WTTC report focusing on the United States, the United Kingdom, France, Spain, Italy and Portugal estimates that the T&T sectors in these countries experienced staff shortfalls ranging from 9% to 18% in 2021. 22 The interconnected nature of the T&T supply chain and ecosystem has also created challenges. Hotels, airlines, car rental firms, tour operators, cruise lines and others all form a chain of service providers dependent on each other along the traveller journey. Bankruptcies or other disruption issues at any point along this chain have the potential to negatively affect the others.

"In addition to labour shortages and capacity constraints, the sector has also been exposed to broader global disruptions that are complicating recovery."

Over the course of the pandemic, growth in merchandise trade coincided with production, worker, equipment and space shortages to create a global supply-chain crisis. For instance, hotels have faced shortages of items ranging from slippers for clients to kitchen equipment. 23

The recent outbreak of war in Ukraine and resulting sanctions and travel restrictions related to Russia have added further pressure on the recovery. Airlines around the world have had to reroute operations, increasing travel times and costs. Meanwhile, the still fragile recovery in international tourism demand could be tempered by increased hesitancy among travellers when it comes to visiting Europe. 24 Many T&T economies in Europe, Eurasia and beyond may also be hard hit due to reduced demand from Russia and Ukraine. Combined, these two economies account for about 3% of international tourism spending, with Russia having been a major source of visitors to destinations ranging from Azerbaijan, Georgia and Turkey to Israel, the United Arab Emirates and Thailand. 25

While not yet fully reflected in the TTDI’s Price Competitiveness pillar, rising travel demand, the stated labour, capacity and other shortages, global supply-chain disruptions and rises in fuel prices and inflation caused by factors such as the war in Ukraine will likely increase costs and service prices throughout the entire T&T supply chain and ecosystem. For example, as of 13 May 2022, jet fuel prices were more than double what they were a year ago, 26 and if they remain high, airline yields and ticket prices will likely rise. 27 Recent UNWTO analysis cites how conflict-induced uncertainty, higher energy and food prices and inflation, in general, are putting pressure on consumer purchasing power and tempering global economic growth, potentially affecting T&T sector performance. Moreover, as economies such as the United States combat inflation by increasing interest rates, consumer demand and T&T investment may be further hit by the rising cost of credit. 28

The pandemic shifts demand dynamics, creating opportunities and driving adaptation

With travel restrictions still common and traveller confidence hampered by pandemic concerns, the past few years have also seen a shift in demand trends in global T&T. According to the UNWTO Panel of Experts, the major trends driving the T&T recovery include domestic tourism, travel close to home, open-air activities, nature-based products and rural tourism. 29 The World Travel and Tourism Council (WTTC) data shows that, on average for the 117 economies covered by the index, domestic spending’s share of T&T spending increased from 50.8% in 2019 to 62.6% in 2020 as domestic demand fared better than collapsing international demand. 30 Moreover, current projections for 2021 show that domestic spending growth is expected to substantially outpace international spend in every region outside of the Caribbean and Middle East. 31

The TTDI results further reinforce the shift in demand dynamics that the world has witnessed. The second most improved pillar is Natural Resources (+2.5% average score increase). While this was driven largely by an expansion in the number of recognized UNESCO World Heritage natural sites and protected areas, such as national parks, the greatest improvement has come from destinations’ ability to garner interest in nature-related segments as illustrated by the 20.8% average growth in natural tourism Digital Demand value, a measure of online searches for topics such as natural wonders, outdoor activities and rural accommodation.

On the other hand, the Non-Leisure Resources pillar had one of the greatest declines in average performance (-1.9%) as business travel declined. While this sector is recovering, it has rebounded at a slower rate than leisure, with factors such as workplace flexibility and the availability of virtual alternatives for in-person meetings tempering demand and potentially leading to some permanent loss in corporate travel. This will force many T&T segments to adapt. For example, operators in the meetings, incentives, conferences and events (MICE) area may have to rely more on smaller and hybrid events. 32 T&T businesses and destinations are increasingly looking to capture opportunities offered by the changing nature of work. Over the course of the pandemic, more businesses have gone virtual, and an increasing share of the labour force is becoming independent.

"In 2020, 10.9 million Americans said they were digital nomads, a 49% increase from 2019."

This sample of independent workers is also increasingly willing to travel. A recent survey showed that the share of US independent workers doing business outside the country jumped from 12% in 2013 to 28% in 2020. 33 Additionally, the trend in “bleisure” travel – the addition of leisure activities to business trips – is also growing. 34

To cater to these growing markets, T&T businesses will have to become more flexible and create new, innovative products. For instance, some major hospitality groups are creating new long-stay properties that include kitchens and living spaces, while other have introduced packages that offer reduced rates for those staying longer, which include IT and boardroom services. 35 Furthermore, while virtual business may require less office space, corporations and their employees may need options for occasional company meetings and events that the sector could provide. However, it is important to note that these new market opportunities are primarily for the high-end travel market and are not likely to replace the overall loss in business travel. Lastly, T&T operators have also had to introduce more flexible booking and cancellation policies in order to address uncertainty about travel regulations and the pandemic, in addition to increased consumer desire to make last-minute changes or to add leisure stays to their business trips. 36

From a destination point of view, many governments have also adapted to changing conditions to take advantage of shifting demand dynamics. For one thing, many countries have provided various incentives to boost domestic tourism. For example, Hong Kong, Singapore, South Korea and Japan have rolled out various programmes that provide discounts, coupons and subsidies for domestic travel. 37 Meanwhile, Aruba targeted the digital nomad market through extended work visas and other benefits via its One Happy Workation programme. 38 The trends towards more rural and nature-based tourism also offer an opportunity for less-developed economies to harness the benefits of T&T given that the distribution and quality of natural assets are less tied to overall economic development, with Natural Resources being one of the few pillars where non- high-income economies typically outperform high- income countries (see Figure 6).

Figure 6: Composition of top quartile, by income group

Overall, the above adaptations to shifting demand and COVID-19 conditions help highlight how flexible T&T business and destinations can be in times of crisis. As the sector rebuilds and addresses future risks, its adaptability will become more crucial than ever. In particular, as can be seen in the key findings that follow, the shift to domestic and nature-based travel, as well as other trends, coincides with an increased emphasis on sustainable and safe travel. Therefore, T&T development will have to become increasingly sustainability-oriented.

4.3 Building back better

Given the current challenges, shifting demand dynamics and future opportunities and risks, it is vital that T&T development strategies are employed to rebuild the sector in a more inclusive, sustainable and resilient manner.

Restoring and accelerating international openness and consumer confidence, including investment in health and security

For starters, as travel restrictions are removed, ensuring that T&T markets are open to visitors and investors will become vital. In particular, it is important that the historical trend of ever greater international openness in T&T continues. Reduced visa requirements fuel international tourism and additional air service agreements open up markets to more airlines, routes, competition and, ultimately, better service (see Figure 7). Given the recent decline in international route capacity and travel demand, prioritizing visa and air service agreement liberalization will be important – with those economies most dependent on tourism exports and lacking large domestic markets standing to benefit the most. Financial openness and an increase in regional trade agreements can also help to facilitate necessary cross-border investment in T&T and beyond, which may also help encourage more international and intra-regional travel.

TTDI results indicate that Western, Southern and Northern Europe are usually the most internationally open subregions due to the close integration that the European Union, the Schengen Area and similar blocs and agreements provide. Such systems allow T&T operators to benefit from factors such as a larger and more diverse consumer base and common market rules. It is also important to recognize that despite the pandemic and disrupted global trade, 83 economies ranked in the index increased their number of regional trade agreements in force between 2019 and 2021. Relevant recent developments include the African Continental Free Trade Area (AfCFTA), which came into force in 2021. Combined with related efforts such as the Free Movement Protocol and Single African Air Transport Market (SAATM), the sub-Saharan Africa region has the potential to unlock its untapped T&T potential and grow its underdeveloped intra- regional T&T market and air route capacity. 39

Figure 7: Correlation between air service agreement liberalization and air transport infrastructure, 2019

Endnotes 40 , 41

Of course, the pandemic, along with the recent rise in geopolitical tensions, also highlights just how important health and security conditions are to protecting the openness on which T&T relies and to restoring consumer confidence in travel. Economies with sophisticated healthcare systems are better equipped to mitigate the impact of pandemics on T&T and the wider economy by protecting their populations, including the T&T workforce and visitors, thus reducing the need for travel and lockdown restrictions. Meanwhile, access to clean water and sanitation facilities helps prevent diseases or their spread. Lastly, consumers and business travellers are likely to remain more sensitive to the health and hygiene conditions at destinations for some time. A recent survey shows that the majority of travellers consider safety protocols, restrictions and cleanliness to be key factors in travel decision- making. 42 In the short term, T&T business, destinations and international organizations have responded to these issues via actions such as the introduction of various protocols and certifications. For instance, the World Travel & Tourism Council has introduced the Safe Travels protocols and certification stamp that can be used by T&T to show customers they are following standardized global health and hygiene practices. 43

In general, underdeveloped health and hygiene infrastructure and access represents an acute challenge for many developing countries, with low- and lower-middle-income economies scoring 50.0% and 25.6% below average in the Health and Hygiene pillar. These states lack physicians and hospital beds (in terms of ratio to population size) and access to basic sanitation and drinking water, and such issues, combined with lower vaccination rates, mean that these economies will struggle to recover at the same pace as others and will have difficulty building adequate resilience against future health security risks. It is therefore crucial for the success of the global T&T sector that the challenges related to vaccine distribution and roll-out are addressed in an equitable and inclusive fashion. While further effort is required, public-private cooperation can provide a useful avenue to address this challenge. For example, the World Economic Forum’s Supply Chain & Transport Industry Action Group community, which consists of leading supply-chain companies, is supporting UNICEF and the COVAX Vaccine Distribution programme with “planning, preparedness and prioritized transportation and distribution of COVID-19 vaccines and related supplies”. 44

The above-mentioned introduction of travel bans, flight-route adjustments, increasing fuel and food prices and potentially hindered international travel demand caused by the war in Ukraine have also shown the degree to which international T&T can be affected by geopolitical tension and conflict. Overall, it is well established that crime and security issues such as terrorism and conflict have a negative impact on tourist arrivals and sector revenue. 45 The 2021 TTDI data shows that economies in the Americas, sub-Saharan Africa and South Asia tend to score the lowest for safety and security, thereby creating a further obstacle to the future development of T&T in these areas.

On the other hand, research has also shown that a sustainable and open tourism sector can be resilient to violence and conflict and that it may help foster positive peace, namely the “attitudes, institutions and structures that create and sustain peaceful societies”. More specifically, the mechanisms through which tourism can accomplish this include cultural and information exchange, encouragement of tolerance, better government functioning, human capital development, and local and cross-border economic gain that can reduce the risks to peace. 46 It is now more important than ever to leverage the T&T sector’s potential for peace through sustainable development.

"It is crucial for the success of the global T&T sector that the challenges related to vaccine distribution and roll- out are addressed in an equitable and inclusive fashion. While further effort is required, public- private cooperation can provide a useful avenue to address this challenge."

Building favourable and inclusive labour, business and socioeconomic conditions

Over the course of the pandemic, the T&T sector has received substantial support in the form of debt financing, tax policies, assistance with business costs, public-sector investment, employment support, incentivization of tourism demand and easing of regulations. 47 In the future, continued investment in human capital and the creation of more favourable labour, business and socioeconomic conditions will be vital components in making the sector more inclusive, addressing ongoing challenges such as labour shortages and driving T&T growth and resilience.

Factors such as accessible and quality education and staff training, supportive hiring and firing practices, programmes to source skilled labour, flexible working arrangements and efforts to improve labour productivity can help equip T&T companies with a workforce that can improve operating efficiency, provide quality services, maintain flexibility in the face of evolving business needs and challenges and take advantage of the growing role of ICT tools. For example, according to the World Economic Forum’s The Future of Jobs Report 2020 , skills gaps in the local labour market were the number one barrier to adoption of new technologies in the transport and storage, and consumer sectors, the two sectors most closely tied to T&T. 48 Furthermore, according to the WTTC, factors such as facilitation of labour mobility, upskilling and reskilling and promotion of education are vital elements in addressing the current labour shortage. 49 Meanwhile, the past few years have shown how important policy stability, access to credit and creating more business- friendly regulatory and tax environments have been in supporting the T&T sector, especially SMEs that typically do not have the same resources and access to capital as larger firms. 50

The 2021 TTDI results partially reflect some efforts by policy-makers to support their economies, with the average Business Environment score climbing 1.7% since 2019. In particular, perceptions of the burden of government regulations and SME access to finance were areas that saw some of the largest improvements. The average Human Resource and Labour Market pillar also improved by 1.5% between 2019 and 2021, due to overall progress made in areas such as staff training. Nonetheless, less developed economies still score well below the TTDI average for most indicators for both pillars.

The pandemic has also highlighted how important an economy’s socioeconomic resilience is for the T&T sector. In general, the ability of an economy to support its population through social protections such as unemployment and maternity benefits, keep youth employed or in training, effectively uphold workers’ rights and support a diverse and inclusive workforce may potentially help strengthen employee productivity, expand the labour pool and make it more resilient to risks such as pandemics. 51 This is particularly true for the T&T sector because it provides income for a large number of youth, women, informal workers, the self-employed and small enterprises, who do not always have access to social or worker protections. Figure 8 shows that there is a relationship between socioeconomic resilience and conditions and labour productivity in T&T. Recent survey data also reinforces how important issues such as benefits and working conditions are for attracting talent and addressing the ongoing labour shortage in the sector. One poll of former US hospitality workers showed that more than half won’t return to their old jobs and over a third are not planning on returning to the industry as they seek higher pay, better working conditions and benefits, and more flexibility. 52

Figure 8: Correlation between socioeconomic resilience and conditions and tourism labour productivity

The 2021 TTDI results show that, across the board, socioeconomic resilience has tended to improve due to the expansion of social protection coverage and spending in line with global efforts to mitigate the impact of COVID-19. High-income economies do tend to score far higher on the Socioeconomic Resilience and Conditions pillar, putting them in a better position to deal with future challenges and maximize their workforce potential. Conversely, low- and lower-middle-income countries have far lower socioeconomic resilience due to more limited social protection, higher rates of youth not in education, employment or training (NEET), fewer workers rights and greater inequality of opportunity for all. As a result, the T&T sector in these economies may face more obstacles to recovery and may be more vulnerable to future risks.

While rising interest rates and debt levels represent a growing obstacle, government responses to the pandemic demonstrated their capacity to provide more comprehensive socioeconomic support, and the benefits of doing so, albeit during an unprecedented situation. While the pandemic has certainly disproportionately affected SMEs, entrepreneurs or more vulnerable populations, strengthening such mechanisms, especially in the T&T sector, could have compound benefits for the sector and economies as a whole.

The growing role of environmental sustainability

In the coming years, the success of T&T businesses and destinations will be increasingly tied to their ability to manage and operate under ever greater ecological and environmental threats. According to surveys conducted for the World Economic Forum’s Global Risks Report 2022 , environmental risks represent half of the top 10 global risks, with climate action failure, extreme weather and biodiversity role natural assets play in generating T&T demand and spend, these environmental risks represent a serious threat to long-term growth for the sector. Moreover, within this context, travellers increasingly value environmentally sustainable options. 54 df

The 2021 TTDI results indicate the extent of environmental sustainability threats and challenges. For instance, comparing the Natural Resources and Environmental Sustainability pillar scores helps to pinpoint where some of the greatest risks to nature-based tourism might lie. Out of the 30 economies that rank in the top quartile for natural resources, 17 score below the global average for environmental sustainability and eight rank in the bottom 25.

Figure 9 provides a regional view of the challenge. While most economies in the Americas and Asia- Pacific and almost half of those in sub-Saharan Africa score above average for natural resources, they commonly underperform in environmental sustainability, making it a critical problem for future T&T development. Environmental issues differ in these regions, but some examples include elevated climate-related risk (as measured by the Global Climate Risk Index), air and sea pollution, deforestation, poor wastewater treatment and inadequate preservation policies. In the Middle East and North Africa, common problems include water stress and air pollution. On the other hand, economies in the Europe and Eurasia region are world leaders in environmental sustainability, accounting for more than half of countries in the TTDI that score above average for this pillar. Combined with the fact that natural resources are not its greatest strength or dependency, the region and its tourism sector may be the better positioned to deal with future ecological risks.

Figure 9: Share of regional economies scoring above average for natural resources and environmental sustainability

Nonetheless, while there are some economies that have better environmental conditions, the challenge is widespread and is not easing. The difference in average score between the top and bottom quartiles for the Environmental Sustainability pillar is the second-lowest among the pillars. Moreover, performance for many indicators in this pillar has been mixed. For example, scores for deforestation continued to worsen. On the other hand, efforts to preserve the environment and T&T-generating natural assets got a boost from continued expansion in the share of protected territories and the number of environmental treaties signed.

A recent UNWTO and One Planet report reiterated the importance of a healthy environment for T&T competitiveness and development and recommended several actions to help the T&T sector produce a greener recovery. This included biodiversity protection actions such as putting tourism at the forefront of conservation efforts and ensuring that the value tourism provides for conservation efforts via monitoring mechanisms and investing in nature-based solutions is captured. Climate action efforts in T&T can be accelerated through the likes of monitoring and reporting emissions from tourism operations, accelerating decarbonization through the development of low-carbon transport options and greener infrastructure, and engaging in carbon removal via the restoration of carbon-density ecosystems and carbon-removal technologies. Finally, circular economy actions are recommended.

These include investing in transforming tourism value chains by reducing, reusing, repairing, refurbishing, remanufacturing, recycling and repurposing whenever possible; prioritizing sustainable food approaches such as local and organic procurement; creating sustainable menus and focusing on reducing food loss; and shifting towards a circularity of plastic in tourism. 55

At the World Economic Forum, efforts in this field are plentiful, and cover multistakeholder actions on decarbonizing transportation, accelerating action on plastics, ensuring the long-term, sustainable use of the ocean, and developing the circular economy. In particular, the Clean Skies for Tomorrow Coalition 56 is working with stakeholders in the aviation ecosystem, including buyers of corporate travel, to accelerate the production and use of sustainable aviation fuels, all while better distributing the green premium for these fuels. The Forum also hosts the Global Future Council on Sustainable Tourism, 57 a community of experts from academia, business, civil society and governments who are developing a set of principles for sustainable destinations to guide decision-making on rebuilding the sector in the wake of the pandemic. The Council is also researching customer behaviour changes that can incentivize the development and delivery of more sustainable travel products and services, articulating the value of investment in the blue and green economies in tourism, and providing guidance on the ambition of achieving net-zero emissions across the various verticals in the T&T sector.

Managing tourism demand and impact

Sustainable management of tourism demand that maximizes benefits for local communities, while also mitigating negative side effects such as overcrowding, will also become a vital component of T&T development as the sector recovers.

The TTCR 2019 discussed how long-term T&T growth was starting to put pressure on local infrastructure and housing, as well as degrading cultural and natural assets that attract visitors and fuelling uneven distribution of T&T benefits. This ultimately led to falling liveability standards for residents, local backlash against tourism and diminished visitor experience. 58 Although recent lockdowns and travel restrictions led to this sustainability challenge being discussed less, it is likely to become a more common topic as demand continues to recover. In many areas, the pandemic-fuelled travel demand push towards outdoor attractions, rural communities and secondary destinations has already revealed capacity constraints. For instance, the rise in nature travel had already led to more overcrowding at many national parks, with many US national parks monthly visitation number hitting all-time highs, leading to issue such as littering, wildlife disruption and traffic jams. 59 Visitors also show signs of wanting to reduce their footprint and improve the social impact on the destinations they visit, with just over half of global travellers in a recent survey indicating that they would be willing to switch their original destination for a lesser-known one if it led to a reduced footprint and greater community impact. 60

While issues such as overcrowding and other effects of T&T on communities are typically a local rather than national-level concern, the TTDI looks at the existence of, or risk related to, overcrowding and demand volatility, as well as the quality and impact of T&T via the T&T Demand Pressure and Impact pillar. In general, pillar results indicate that T&T Demand Pressure and Impact challenges affect economies of all levels of development. For instance, the difference in the average pillar score between low- and lower-middle-income and high-income economies covered by the index is just 0.8% and 2.5%, respectively.

High-income European countries tend to be some of the top TTDI performers and include rich cultural and non-leisure assets and quality transport and tourism infrastructure that allow for the absorption of large quantities of visitors. However, they still tend to score below average for the T&T Demand Pressure and Impact pillar due to factors such as shorter lengths of stay, higher seasonality and a very high level of concentration of interest in a small number of attractions, as shown by Tripadvisor page views and backed by at times unfavourable perceptions of the dispersions of tourism. Unsurprisingly, this region has often claimed headlines for tourism overcrowding. On the other hand, less-developed economies and those ranking lower on the TTDI tend to bring in fewer tourists, but still score below average for perception of tourism dispersion and town- and city-centre accessibility and crowding, an issue that may be partially explained by these economies’ typically below-average scores for transport infrastructure.

Figure 10: T&T Demand Pressure and Impact pillar component scores, 1–7 (best)

In summary, the relatively close distribution of T&T Demand Pressure and Impact pillar scores among economies of different incomes and tourist arrival levels highlights the fact that challenges such as overcrowding have less to do with visitor numbers and more to do with local conditions and policies.

Yet, as the sector rebuilds, there is an opportunity to use increasing domestic and nature-based T&T demand, consumers’ rising preference to manage their footprint and the need to address historical issues such as overcrowding by making investments and policies that help disperse T&T, thus making the sector more resilient. For one, proper care must be paid to developing transport, tourism, health and ICT infrastructure in rural, nature and secondary destinations. This can help funnel tourism and its benefits to more communities, make them more attractive destinations and increase their capacity to absorb more visitors. Within urban centres, improved road and public transport infrastructure and access to efficient, accessible, safe and affordable transport options can reduce the chances of overcrowding and lead to both greater liveability for residents and a better visitor experience (see Figure 11).

Figure 11: Correlation between public transport and quality of town and city centres

In general, TTDI 2021 results show an improvement in the Ground and Port Infrastructure pillar (+2.2%) since 2019. In particular, middle-income economies have experienced some of the strongest growth in areas such as perceptions of road quality and efficiency of train services. Nevertheless, as already alluded to, less-developed economies still have gaps in their infrastructure, ranging from lower road and rail density to a lack of access to efficient and quality public transport. Combined with lower marks for factors such as tourist and health infrastructure, these economies will face some of the greatest challenges in distributing tourism and its benefits throughout their communities. However, they also have the most to gain from overcoming these obstacles.

Aside from investment in infrastructure, policies are also a fundamental part of proper tourism demand management and dispersion. The above subsections of the key findings section explored how governments and destinations can institute policies to develop domestic and other forms of tourism. Moreover, there are specific efforts that can be made to manage T&T to prevent overcrowding and efficiently use a destination’s carrying capacity. For instance, the UNWTO has set out strategies and measures that can combat challenges such as these in cities. Some of these include the promotion of attractions and events that disperse visitors so they are not concentrated only in certain areas, time-based dynamic pricing, the creation of pedestrian-only zones, defining the carrying capacity of city areas, focusing on lower-impact visitor segments, ensuring local communities benefit from tourism, engaging with local stakeholders and monitoring the impact of tourism, including through the use of big data. 61

T&T stakeholders can also play a more active role in broader sustainable mobility efforts and trends that can help to reduce the sector’s environmental impact, manage demand and make destinations more attractive for visitors and residents. For example, the World Economic Forum’s Global New Mobility Coalition (GNMC) is a multistakeholder community for “accelerating the shift to a Shared, Electric and Autonomous Mobility (SEAM) system”. The synchronization of high-occupancy, electric and autonomous transport options can lead to better traffic flow, higher efficiency of road usage, more equitable mobility systems, better air quality, lower carbon emissions and improved grid resilience. More specifically, SEAM may reduce carbon emissions by 95%, improve mobility efficiency by 70% and decrease commuting costs by 40%. Given SEAM’s clear potential to create more sustainable destinations, a case can be made for T&T sector involvement this area. 62

The crucial role of digital technology

All of the aforementioned efforts to build back a better T&T sector will depend on effective leveraging of the growing role of digitalization in T&T.

More T&T services are being accessed by digital systems through online travel agencies (OTAs) and sharing economy platforms, direct online bookings, digital payment systems and mobile devices, and thus consumers tend to expect the greater convenience, increased options, reduced person- to-person contact and seamless experience that these systems provide. Furthermore, digitalization enables T&T businesses to gather consumer insights and preferences, optimize operations, cut transaction costs and automate processes. 63 Online platforms also enable T&T service providers, including SMEs, to reach beyond their local markets and connect with broader domestic and international markets. Due to the above- mentioned factors, it is not surprising that a positive relationship has been found between ICT readiness and international tourism receipts. 64 In the context of shifting demand dynamics, destinations with greater ICT readiness will be better positioned to diversify their markets and take advantage of trends such as the rising numbers of digital nomads and growth in nature-related travel. For instance, research shows a clear relationship between the ICT Readiness pillar and natural tourism online searches in economies with rich natural resources. 65

A recent report by the Asia Development Bank (ADB) and UNWTO outlines how the T&T sector can use big data and digitalization for better and more sustainable tourism management and recovery. Tourism-specific data coming from sources such as T&T operators and online platforms, and non-tourism-specific data coming from sources such as credit card transactions, mobility services and sensors can help T&T stakeholders track and manage the social, economic and environmental impacts of T&T, complement more traditional data-collection efforts, manage tourism flows and target preferred source markets, thereby helping to create smart destinations.

For instance, the Macao Government Tourism Office has worked with a major Chinese multinational technology company to “optimize visitors’ travel experiences before, during and after trips; obtain insights into travellers’ behaviour through in-depth analysis of big data; and monitor, divert and disperse visitor flows at tourist districts and congested areas”. The use of big data and various digital platforms and technology can also help seamless travel and act as health and security tools by enabling safety protocols, biosecurity technologies and digital health certificates, thereby boosting traveller confidence. However, the report also highlights the various barriers to greater use of big data and digitalization within the T&T sector. Some of these challenges include privacy concerns, data reliability, governance issues, disincentives for public-private collaboration, the digital divide, skills gaps and greater efforts to include SMEs. 66

Figure 12: ICT Readiness by economic income group, 2019–2021

Figure 12 helps to illustrate the digital divide among economic income groups. Developing economies typically lag when it comes to ICT infrastructure, internet connectivity and mobile network coverage, which hampers the use of digital platforms in financial services, transport and tourism activities. On the other hand, the ICT Readiness pillar is the most improved (+3.0%) since 2019 largely due to continued improvement in low- and middle-income economies. These results indicate that while high-income economies are best positioned to leverage digitalization and create smart destinations, developing economies are building capacity. In addition, as already mentioned, creating a more highly skilled labour force will be an essential element and challenge in maximizing the use of ICT tools in T&T.

The growing role of digitalization and, in particular, digital platforms, within the T&T space can also create other labour and socioeconomic challenges. Globally, the number of active digital labour platforms, which include ride-hailing taxi and delivery services, has grown from fewer than 200 in 2010 to at least 777 at the start of 2021. As stated, these platforms create new avenues for flexible employment for people, allow business to access wider markets and talent pools, improve productivity and provide convenience for customers. However, they could also lead to greater income and job insecurity. Commonly raised issues include less favourable working conditions, deficient social protection and employment benefits and a lack of access to fundamental rights of freedom of association and collective bargaining. 67 The growth in popularity of digital platforms offering short-term rentals has also led to concerns about residents’ access to housing at destinations where housing capacity is increasingly taken up by the T&T sector. 68 The concentration of market share in the hands of digital platforms may also lead to imbalances in the bargaining and pricing power of the various stakeholders, including workers and SMEs. 69

If proper efforts are made, from employee training and supporting SMEs’ use of ICT to fair and effective regulation of digital platforms and their impact on workers and destination communities, digitalization in T&T will become one of the driving forces in growing the sector’s role in inclusive, sustainable and resilient development. However, failing in these areas could also transform this key aspect of T&T operations into an increasingly acute barrier to future T&T growth.

4.4 Conclusion to the key findings

The COVID-19 pandemic and its impact have underscored the T&T sector’s vital role in global connectivity and development. In the coming years it will therefore be crucial for T&T stakeholders to devise strategies that make the sector more inclusive, sustainable and resilient.

As the TTDI 2021 results reveal, any such enterprise will require a comprehensive and holistic approach. Creating a better T&T economy is not just about improving infrastructure or offering favourable pricing. It also involves creating better health and hygiene conditions, ensuring natural resources are protected and that the workforce on which the sector depends has access to training and social protection. This necessitates the active participation and coordination of sector and non-sector business, employers and employees, government agencies ranging from tourism and health ministries to local authorities, environmental and conservation groups, and international organizations. Over the course of the pandemic, often uncoordinated travel restrictions and health protocols revealed the difficulty and necessity of such cooperation.

In the future, efforts will need to be made to devise common frameworks for defining and measuring T&T sustainability, including the creation of commonly accepted environment, social and governance metrics. The safe and ethical use of big data will prove fundamental to this cause. Moreover, in an increasingly complex and technology-enabled environment, it will be vital to ensure that developing economies, workers and SMEs are not left behind.

While these challenges may be difficult, the flexibility and adaptation the T&T sector has shown in the past few years also indicates that sector stakeholders are more than capable of rising to the occasion.

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The perceived image of multi-asset tourist destinations: investigating congruence across different content types

• Empirical article
• Published: 30 November 2021
• Volume 16 , pages 57–75, ( 2022 )

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• Narcís Bassols-Gardella   ORCID: orcid.org/0000-0001-5769-5323 1 &
• Lluís Coromina   ORCID: orcid.org/0000-0003-0769-0633 2  

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Destination image has become a crucial topic in tourism studies. However, research has scarcely considered multiple online content sources when studying the image of destinations. This paper examines different types of user-generated content in order to evaluate whether and how this content reflects the evolution of a destination’s image, and its congruence therein. The research focuses on a multi-asset tourist destination, i.e., one which draws different market segments. The results show a relatively high degree in congruence and evolution of the destination’s attractions, but also questions bits of theories on communication congruence as well as attractions’ evolution theories.

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1 Introduction and goals

Destination image perception is a fundamental matter for destination managers, and consequently it has been widely investigated. Extant research underscores that communication directed towards potential visitors must be ‘congruent,’ as consistency in messaging increases the chances of the destination being chosen. This congruence must be achieved across all communication channels the organization uses (see Van Rompay et al. 2010 , who study the congruence of text and pictures on web sites). In the case of destinations, it is crucial that this congruence is achieved over time, as the local attractions evolve from basic assets to more complex and rich pullers (Richards 2018 ).

Despite the important role image congruence and its evolution play in destination management, studies on both subjects in multi-asset destinations are limited, as is the investigation into multi-channel UGC (user-generated content). The literature review section examines the wealth of studies on perceived destination image generally using a single type of UGC, which usually support their findings in either photos or text, but exposes the gap in understanding the question when related to multi-source UGC.

The objective of this article is therefore to better study the congruence between the promoted image by a local DMO (Destination Management Organization) and how this image is perceived by visitors taking also into account longitudinal issues. This is researched with a quantitative, massive-data approach. Thus, this work contributes to the literature on UGC, destination image and communication congruence from an empirical point of view. The authors processed 9213 photos, 24,610 video seconds and 359,350 textual mentions from different social networks in order to understand discrepancies among different sources of UGC. Framed by congruence and evolution theories, and layering a longitudinal analysis, the shift in perception of attractions as they relate to the point of view of multi-channel UGC is examined. Therefore, the conclusions of this research will have theoretical as well as managerial implications as they relate to destination image strategy. While not the central research topic of the paper, it is a truism to say that the COVID-19 pandemic has hit the studied destination. Therefore, some comments on that matter are put forth in Sect.  4 (Context) as well as in the final section as a possible topic for further research.

2 Literature and theory review

How a tourist destination is photographed, videographed, or written about on websites or social media networks via UGC has been so amply studied since the 2000s that only a state-of-the-art article may render the width of the topic, see for example Camprubí and Coromina ( 2016 ) or Picazo and Moreno-Gil ( 2017 ). For their part, Lee and Rha ( 2018 ) confirm the interest of studies like the present one when they state that “tourism research is expanding into research on communication, CSR, and marketing.”

UGC has become a valuable tool for studying different aspects of a destination’s image, for example to better understand the destination’s image formation (Serna et al. 2013 ; Llodrà Riera et al. 2015 ; Micera and Crispino 2017 ), to compare the image projected by DMO versus the one perceived by visitors (Stepchenkova and Zhan 2013 ; Nechita et al. 2019 ; Mariné-Roig and Ferrer-Rossell 2018 ), to better understand managerial challenges in the destination (Alcázar et al. 2014 ; Stepchenkova et al. 2015 ; Mariné-Roig and Anton Clavé 2016 ; Rahman et al. 2016 ), to better market the place (Zhang et al. 2015 ; Doosti et al. 2016 ; Moro and Rita 2018 ; Luna-Cortés 2018 ; Tan 2018 ; Mohamed et al. 2019 ) and to improve visitors’ segmentation (Moliner-Velázquez et al. 2021 ).

These research efforts have not only resulted in recommendations that industry professionals may follow, but have on occasion generated new theories or refined existing ones (Munar 2011 ; Llodrà Riera et al. 2015 ) by comparing different image formation dynamics.

In their field work, researchers have used different techniques and data sources. For example, website mining (Hellemans and Govers 2005 ; Költringer and Dickinger 2015 ; Zhang et al. 2015 ; Mohamed et al. 2019 ), picture analysis (Negri and Vigolo 2015 ; Hunter 2016 ) or text analysis, be it from blogs (Akehurst 2009 ; Çakmak and Isaac 2012 ; Tseng et al. 2015 ) or from Tripadvisor (Kladou and Mavragani 2015 ; Chiu and Leng 2017 ; Garay Tamajón and Cànoves Valiente 2017 ; Wong and Qi 2017 ). Due to its speed and dynamism, Twitter has been studied as a communication tool, such as when catastrophes affect destinations (Barbe et al. 2018 ; Oliveira and Huertas 2019 ). The use of Facebook has been more varied and has served multiple purposes, compare Park et al. ( 2016 ) studying the communication of tourism policies, to Jadhav et al. ( 2018 ) investigating tourists’ behavior. The fact that online UGC content has been available for some years now means that longitudinal studies can start emerging (Wong and Qi 2017 ; Gálvez-Rodríguez et al. 2020 ). In a similar vein, the ‘traditional’ vs the ‘digital’ word-of-mouth are compared by Tan and Lin ( 2021 ).

However, most studies use a single type of UGC when studying destinations, and only a few research projects have combined more than one type of source. Table 1 gives a short overview of some of these publications. Until 2016, most research relied on Flickr and Panoramio to make comparative studies. The former has lost its significance and the latter was retired in 2016, so these sources are no longer available (or interesting) to today’s researchers.

Thus, studies bringing together congruence and evolutionary theories with the analysis of multiple UGC sources are scarce, and hence a research gap that this article covers.

As for the selected theoretical frameworks, the first thing to notice is that the presented empirical evidence is from the city of Cartagena de Indias on the Colombian Caribbean coast, chosen because it is a multi-asset destination with several main attractions and so a suitable case study. Thus, this work is ultimately framed within Case Research Theory (Yin 1984 ; Stake 1995 ) as it discusses a concrete case from an empirical point of view with the aim of verifying (or modifying, as might be the case) existing theories (Eisenhardt 1989 ). Accordingly, in this work, empirical findings from a context are studied in-depth to confirm theories and propose modifications. Within Case Research Theory, different types of cases are posited: exceptional cases, regular cases, comparative cases, etc. This paper assumes the framework outlined by Neape et al. ( 2006 ) as the discussed case is representative. In fact, Cartagena is an adequate proxy for significant samples of Latin American destinations, boasting historical attractions as well as beaches, allowing the results to be generalized to other destinations in the region. This study can also be underscored as one of the first of its kind conducted in a South American city, a geographical area that has been underexamined.

Another important framework for this research is ‘congruence’. This concept appears to play a crucial role in the frictionless consumption process at different touchpoints, be it in the choices made by consumers or in the organizations’ communication directed towards them. Van Rompay et al. ( 2010 ) state that, in multimedia messages, congruence favors “processing efficiency”, which in turn accounts for favorable attitudes from the consumers’ perspective. According to these authors, there must be a “consistency among meanings associated with [different] elements within an (online) environment” (p. 23) to create congruence. In our study, searching for congruence means researching whether the UGC by visitors to Cartagena displays similar content across different social media channels, i.e., whether the perceived image for the tourist who post photos, videos, and/or text are congruent with each other or not. While Van Rompay et al. ( 2010 )’s field work is based only on pictures and text, we extend our quest for congruence by adding video sources to our study.

Thus, our field work researches into the level of congruence among three types of UGC. For instance, a high level of congruence would mean that tourists perceive the destination in the same way, irrespective of the media they use, which can indicate an overall high congruence in the perception of the place—and favorable attitudes toward it. Correspondingly, a high level of congruence across different media outlets also means a correct strategy and use of these communication channels on behalf of the local DMO.

A potential threat to image congruence is the fact that attractions in destinations and the destination’s image are intrinsically dynamic factors. This is explained, among others, by Richards ( 2018 ), when he specifically asserts that destinations’ attractions evolve over time going from basic attractions (for example sun and sand), to tangible cultural attractions (built military heritage in the case of Cartagena), and finally to intangible attractions. This is a value-catching process and is pushed by both supply and demand. The data in this paper spans a wide timeframe; this allows for longitudinal reflections on the evolution of attractions, the place’s projected image and the destination’s perceived image.

3 Context: Cartagena de Indias, Colombia: from a growing to a Covid-plagued destination

Located on the Colombian Caribbean coast, Cartagena is one of the country’s well-established destinations, receiving around 3 million visitors annually, approximately 10% to 12% of them foreigners. Founded in the 1530 s by the Spanish conquerors, Cartagena soon became a key point in the colonization process of Hispanic America, leading to the construction of a consistent urban defense system with walls and fortresses (Bassols and Soutto-Colón 2020 ). Today, these ancient military structures, along with the historic and picturesque city center, play an iconic role in the city’s tourist landscape, landing a classification as a UNESCO-marked heritage in 1984. Thanks to its beaches, it was promoted as a sun and sand destination until around 2010. From then, it has been increasingly sold by the local tourist board as a ‘heritage destination’. This has allegedly turned Cartagena into a ‘multifaceted’ destination, i.e., a tourist space where different attraction typologies geared towards different visitor segments coexist.

This ‘multifaceted’ or ‘multi-asset’ character of the destination raises important questions about branding and management strategies (Bassols and Leicht 2020 ). It also raises questions about how the city is perceived by its visitors, in terms of what they think the destination stands for (i.e., beach or culture or other attractions). Therefore, a close study of the UGC by the tourists might provide essential clues to guide future developments of multifaceted destinations.

One study on visitors to Cartagena worth mentioning is by Pinillos Castillo and Hernández Vargas ( 2017 ), concerning the motivations of tourists from different markets of origin (Table 2 ). The study, conducted among 320 tourists visiting Cartagena in 2016, found that a majority (55%) were mainly interested in ‘culture’, whereas the remaining 45% were primarily interested in beaches and leisure. North Americans, and especially Europeans, showed a much wider gap (57% for culture versus 43% for beaches), whereas Latin Americans -with the exception of Brazilians-narrowed this gap (53% versus 47%). Thus, Table 2 shows that ‘cultural motivations’ are at the fore.

The general figures from the last decade show that Cartagena is a growing destination, or at least it was until March 2020 when the COVID-19 pandemic stroke. The fact that flights were called off for 5 months in Colombia (April to August 2020) as a cautionary measure towards the pandemic caused foreign tourism to completely collapse. The reaction from the national government in supporting the tourism industry has been relatively slow, according to several interviewed stakeholders. This situation has caused -nationwide- around one-third less turnover for hotels and restaurants, and about two thirds for the transportation industry. The impact on the largest tourist destinations in Colombia has been huge in terms of employment losses, however, the stakeholders see that Cartagena’s position as a well-established destination is not endangered in the mid- to long term. Companies were able to react to adapt to the new situation. Since September 2020, the beaches and the historic centre have reopened at a slow pace, with ‘biosecurity’ as an important argument. Meanwhile, the city has found its way back to its main vocation in past decades: being the largest national holiday destination. In fact, businesses were relatively happy with occupancies and expenditure levels in the Easter holiday 2021. Although international tourism has been at a low, some local companies say that events or incentive trips are being delayed but not canceled. Short-term predictions are difficult to make as the situation remains changeable as COVID-related travel warnings may appear (or disappear) within a few weeks. In fact, as stated by several stakeholders, short-term planning remains a challenge in the city for both the public and the private sectors.

4 Methodology and field work

4.1 establishing the attractions’ typologies.

A list of attraction types for photos and videos corresponding to Cartagena’s main attractions was set up according to FONTUR and Mincit ( 2014 ), after Richards ( 2018 ) typological division. These were the following 8 categories: Civil Architecture, Religious Architecture, Public Spaces, (standalone) Monuments, Hotels (and their different ambiances), Beaches, and People (this one split into ‘Locals’ and ‘Foreigners’). Figure  1 shows the process of establishing these typologies for pictures and videos (how these categories were matched to the text categories, see next subsection). Out of the 8 established typologies, 5 come from the classifications put forth by the literature and the local official sources, and the three categories of ‘Hotels’, ‘Locals’ and ‘Foreigners’ were created after examining the video and pictures results to further refine the retrieved data. In the case of ‘People’, due to the large numbers of pictures and videos containing people, this category is an intermediate one that is finally divided into two final categories: ‘Locals’ and ‘Foreigners’. This differentiation allows for a better understanding of this category, particularly the qualitative difference of having a visitor engaging with locals and their culture or with other tourists, possibly from his/her own traveling group (see the final sections for this discussion). With the category ‘Hotels’, the aim is to better understand the engagement of visitors with their lodgings, in an innovative view seldom taken before. Therefore, 5 categories come from the literature and 3 from the need to refine and understand the data further (Fig.  1 ).

Grounding the eight categories of attractions according to sources

4.2 Data collection

The authors of this paper intend to quantitatively analyse large swaths of data collected using web-scraping methods. Images for analysis were downloaded from Facebook, Flickr, Instagram, and the extinct Panoramio, and videos were taken from the sites Vimeo and YouTube. Texts were taken from Twitter and Instagram with the software developed by Mabrian Technologies. Purposely, different social picture and video networks were chosen to research any possible gaps or incongruences among these. Data were collected over several years from a broad time spectrum—from 2006 to 2018. Two intensive collection moments were 2016 for video and 2018 for text. This broad span of 12 years enriches the discussion, as it allows for some longitudinal considerations.

4.3 Data collection for photos

Concerning the pictures, the following seven social networks were considered from the outset: Facebook, Flickr, Instagram, the extinct Panoramio, Pinterest, TripAdvisor and Twitter. These sites were trawled for pictures of Cartagena using relevant keywords, randomly collecting the output produced by each social network’s algorithm in response to highly relevant keywords (‘Cartagena’, ‘Cartagena de Indias’, ‘Cartagena, Colombia’, etc.). The field work was carried out over 6 semesters, from 2015 to 2018, by volunteer tourism undergraduate students at the Universidad Autónoma del Caribe in Barranquilla, Colombia. A total of 15 students were involved in the project at different times. Each student was trained carefully before starting tagging, so that the tagging criteria would be consistently upheld for the duration of the whole project. The final result was 10,089 pictures with 28,219 tags. In terms of dates, the pictures cover a timeframe from 2006 to 2018, with the majority of them taken between 2010 and 2016.

However, some limitations imposed on the collected data meant some of the mentioned social networks were rejected. First, we did not want single pictures on the database, but rather pictures taken while the users were en route in the city, thus conveying an attitude of in-depth exploration. For this reason, only sets of a minimum of 4 pictures taken on the same day were entered into the database. In some instances, 3 pictures were accepted. This meant the pictures from Pinterest, TripAdvisor and Twitter were taken off the final list, as their users seldom uploaded more than one or two pictures on a given day. Additionally, there was much less quantitative material to collect in these three social networks, Pinterest being the least rich of the three sources, so the final result consisted of 9213 pictures (Table 3 ). The pictures from each source were not established beforehand, and instead reflect the best efforts of the data collectors and the ease with which pictures could be found and tagged.

In the aforementioned database, each photo was entered with its basic data (URL, date of access, etc.) and subsequently the main motive(s) in the picture were tagged.

4.4 Data collection for videos

As for videos, a total of 74 videos were taken from Vimeo and YouTube. In order to make them comparable to the pictures, it was assumed that a 1-s video is equal to 1 picture. The videos were taken in 2015 and 2016, again by volunteer students. Therefore, the video processing was identical to that described above for photos. The most popular video social networks, YouTube and Vimeo were chosen, though the former provided more material than the latter. The length of the tagged videos and other figures regarding the processed video data can be seen in Table 4 .

As said further above, in order to ensure comparability, the same eight categories (Civil Architecture, Religious Architecture, Public Spaces, Monuments, Hotels, Beaches, Locals and Foreigners) were created for both video and pictures.

4.5 Data collection for text

The third type of collected data are text. Texts were extracted from the social network sites Twitter and Instagram using Mabrian Technologies software, which output a total number of 359,350 textual mentions for Cartagena. Due to a software limitation, only the mentions included in the time span from June 2017 to June 2018 could be collected, i.e., a full year. The software did not output figures corresponding to customer keywords, and instead performed a text analysis with its own keywords (see Table 7 ) as well as a semantic analysis, in order to assign a tourism typology to each mention, dividing the resulting output into 9 categories.

In order to have comparable results among images and text, the 9 categories output by the text software were grouped into 2 overarching classes: General Tourism and Niche Tourism, and so were the 8 image categories. These two overarching typologies are recognized by many authors as perhaps the most primary tourism dichotomy (Novelli 2005 ; Butcher 2019 ). Thus, the 9 categories output by the text analysis system could be matched to the 8 categories created for photos and videos. To do so, the following categories of text tags and image tags were grouped into overarching categories in the following way:

Overarching categories for text tags:

General Tourism: ‘Sun and Sand’, ‘Night Leisure’, ‘Shopping’, and ‘Families’.

Niche Tourism: ‘Cultural Tourism’, ‘Active Tourism’, ‘Food Tourism’, ‘Wellness’, and ‘Nature Tourism’.

Overarching categories for image tags:

General Tourism: ‘Hotels’, ‘Beaches’, ‘Public Spaces’, and ‘Foreigners’.

Niche Tourism: ‘Monuments’ ‘Civil Architecture’, ‘Religious Architecture’, and ‘Locals’.

4.6 Data analysis methods: exploring congruence

In order to analyze the results, the authors used several quantitative analysis methods. For the analysis of the photo tag categories and the social networks sites, bivariate statistics such as cross-tables and chi-square tests were put to use. In order to determine the level of congruence between photos and videos, these were analyzed by applying Spearman's rank correlation on the rankings of the represented types of attractions for both types of data (Tables 5 and 6 ). Another cross-table was also set up to compare the number of text mentions belonging to the ‘general’ and ‘niche’ overarching typologies (Table 7 ).

This section presents the results of processing the photos, videos and text, each separately. In the case of photos and videos, the tables are similar due to the fact that, as said above, the same 8 categories were applied to both photos (Table 5 ) and videos (Table 6 ), thus allowing for better comparisons between them and setting the text results slightly apart.

In Table 5 , the columns display the 8 attraction categories. The rows correspond to the four researched social network sites. A chi-square test was performed ( χ 2  = 4919.7, df = 21, p value < 0.001) therefore differences among some of the social network sites were found.

The table shows the most and least tagged categories for each given social network. The category ‘Civil Architecture’ appears as the most favored category, mainly because Panoramio (37.22%) and Flickr (26.68%) display this category far above the other ones. ‘Monuments’ (16.10%) comes second because of their high share in Facebook (23.22%) and Flickr (17.14%). The categories ‘Hotels’ and ‘Religious Architecture’ are the least favored categories in each of the four networks, save for Panoramio which, significantly, shows ‘Foreigners’ as the least relevant category. Flickr is the most ‘balanced’ network, i.e., the one displaying more percentage averages. Finally, the authors observe how Facebook’s and Instagram’s most favored category is by far ‘Foreigners’, at almost 40% in the former and 30% in the latter. These two networks also display the lowest percentage of ‘Locals’ pictured.

The video results, similar to the pictures’ analysis, were collated and the mentions per type of attractions were counted. As mentioned above, the same 8 categories were created to tag the videos. The results of the video tagging in Table 6 show that ‘People’ (i.e., the combined categories of ‘Locals’ and ‘Foreigners’) is clearly the most favored motive, with almost 44% of the tags (25.61% for ‘Foreigners’ plus 18.21% for ‘Locals’), followed by ‘Civil Architecture’ (15.47%). ‘Religious Architecture’ is the least favored, with 4.46% of the tags.

The rankings of the listed types of attractions for photos (Table 5 ) and videos (Table 6 ) are correlated but only up to a certain point: Spearman's rank correlation coefficient = 0.691, showing thus a significant (though not overwhelming) level of congruence across these information sources. Comparisons between videos and photos also show that the results for certain categories are quite disparate: for the case of videos, the overarching category ‘People’ obtains almost 44% of the video tags whereas for the photo tags this category merely represents 25.81%. ‘Civil Architecture’ comes second but far behind with 15.47% of video tags. ‘Religious architecture’ is the least tagged category for both photos and videos, receiving 4.46% of video tags and 5.32% of the photo tags. In short, video accentuates differences in some instances.

Finally, Table 7 shows the results for text analysis. Here we see that ‘Cultural’ motivations are at the very fore (31%), followed from a distance by ‘Sun and Sand’ (13%). As stated in the previous section, the output types of tourism categories were grouped into the overarching ‘niche’ and ‘general’ to make it possible to conduct a comparison with the photos and videos. The table presents the identified types of tourism in Cartagena, alongside their mentions on social media and their classification into ‘general’ or ‘niche’.

6 Discussion and implications

This section discusses the data in an incremental way, i.e., pitching first the pictures of the four different networks against each other, followed by a discussion of stills vs video, and finally it discusses image vs text.

6.1 Cross-comparing the pictures: a longitudinal view

The authors use longitudinal methodology to make comparisons between different social media platforms, rendered possible by the large time span of the collected data. First, it is interesting to see that for users of the extinct Panoramio, ‘Civil Architecture’ is by far the winning category (37.22%) plus a very high share of ‘Beaches’, the highest among the four social networks (15.43%). Panoramio has the oldest set of pictures on average and became extinct some years ago, so it shows the typical behavior of tourists visiting the city in the first half of the 2010s, as built heritage was by far the largest tourist-puller to the destination, complemented by sun and sand. Flickr, with pictures from a larger time span, follows this trend but in a more nuanced way, balancing tangibles and intangibles: ‘Civil Architecture’ 26.68% closely followed by the overarching category ‘People’ (25.62%) which includes the sets of ‘Locals’ (13.13%) and ‘Foreigners’ (12.49%) in quite even numbers—in fact, this is the best balanced relationship among ‘Locals’ and ‘Foreigners’ in the four social networks, the other three showing very disparate values either in favor of ‘Locals’ (Panoramio) or ‘Foreigners’ (Instagram, Facebook). The most recent sets of pictures on Facebook and Instagram specifically show ‘Foreigners’ as the dominant category, and thus come closer to the results of the video data set for this category (Facebook 39.87%, Instagram 30.15%, Video 25.61%), demonstrating how, in the course of the last decade, tourist motivations and habits have substantially shifted. Interestingly, on Flickr, Facebook and Instagram, ‘Civil Architecture’ comes before ‘Beaches’, so the current photo rankings of attractions in Cartagena is (1) ‘Civil Architecture’ (27.34%) closely followed by (2) ‘People’ (25.81%) and ‘Beaches’ come third (12.2%).

In sum, for picture shooters, Cartagena is perceived as a ‘dual’ destination with two main attractions: ‘Civil Architecture’ and the overarching category ‘People’. These findings present interesting managerial conclusions, discussed in the next Section.

6.2 Pictures vs. video

These two types of UGC are the most easily compared of the three, as the tags and categories were created for both by the authors following Fig.  1 . However, pictures and video show a different pattern for their categories: in video, ‘People’ is the dominating category, specifically ‘Foreigners’ (25.61%), followed by ‘Locals’ (18.21%) and ‘Civil Architecture’ (15.47%). As seen above, the photo sets display quite a different pattern altogether, with ‘Civil Architecture’ and the overall category ‘People’ quite even. An explanation here might be that videographers interact much more with ‘moving’ motives like people, than with static motives.

‘Religious Tourism’ is the loser in both pictures and videos. The category of ‘Religious Tourism’ was used in the tables because, some years ago, the local DMO started promoting this type of tourism and we wanted to check on its progression. This introduction was a bit of a contradictory move, taking into account the large share of visitors interested in picturing people and even beaches before religious motives (Table 3 ). The present research confirms that the strong cultural and sun and sand image of this destination cannot be changed easily by just ‘adding’ yet another product: if this product is not adequate to the destination, it will fail, as has happened with religious tourism in Cartagena. This finding is in line with the widely accepted literature indicating that the overall image of a destination evolves very slowly, rendering short-term changes difficult (Berrozpe et al. 2017 ).

In both sets, another losing category is ‘Hotels’, which means that, notwithstanding the high standard of some of the city’s accommodation facilities, visitors give much more importance to the destination’s attractions than to the superstructure of the place, regardless of how nice or well-built it is. This is a finding full of implications in terms of place management and business strategy.

As for ‘Beaches’, this is the most consistent category between the photo set and the video set. This category has an intermediate position in both rankings, showing a consensus that, for the whole studied period, this is a complementary product, and not the main attraction in the destination. This has also been communicated this way in recent years by the DMO, so we see here congruence between supply and demand.

6.3 Image vs. text

Comparing both pictures and videos with text is more difficult as the latter data categorization differs from the other two data sets (see above). Also, the data set is much larger (359 K text mentions) than picture tags (23 K) or video tags (36 K). As explained above, the 9 categories output by the text analysis system were matched to the 8 categories created for photos and videos by generating the two overarching categories ‘general tourism’ and ‘niche tourism’ (see Sect. 4.2 ).

Grouped in this way, the text data set comes to 59% of the mentions in the ‘niche’ typology, whereas 41% belong to ‘general tourism’. If we replicate this with the other two data sets, pictures show a 59% of ‘niche’ preferences vs 41% of ‘general’ preferences, a full coincidence with the text data set. As for the video tags, 52% are ‘general’ and 48% are ‘niche’, interestingly inverting the trend. We see that, for the first two groups, Cartagena is nowadays attractive mainly because of both its tangible and intangible cultural resources rather than its basic attractions (‘Beaches’ and ‘Public Spaces’). Videographers show almost split preferences here, but with a slight predilection for the ‘general’ attractions.

7 Conclusions, limitations and further research

This research finds several gaps and differences in congruence among the three different types of UGC studied and within the four sets of pictures examined as well. Photographers at the destination still appreciate the many edifices and monuments Cartagena has to offer, with the exceptions of instagramers and facebookers, for whom picturing ‘Foreigners’ is, by far, the most exciting activity (i.e., interacting with other travelers, possibly form their traveling group). These differences are also partly explained by the characteristics of each picture network and their users: Flickr and Panoramio are used by mainly prosumers, whereas Instagram, Facebook and the video networks are used by regular consumers.

Text writers, for their part, seem much more interested in the cultural aspects of the place and the same goes for Panoramio and Flickr, which are networks for people interested in the big architecture and monuments the destination offers. These three groups display similar behavior and preferences, contrasting with the other three groups: videographers, facebookers and instagrammers. So, we see here the first general incongruences and specific congruences.

As for the coincidence in the overarching categories ‘general’ and ‘niche, in the last paragraph of Sect.  6 , we have we established the congruence of text and pictures, showing a high degree of congruence share between ‘general’ and ‘niche’ tourism types (59% vs 41%). Videos show a different pattern here (48% vs 52% for ‘general’) so when looking at the data from these two overarching categories, we also find incongruences.

If we now observe the above results in a longitudinal way, it must be said that the DMO pushed beaches as Cartagena’s main product in the 2000s. In the 2010s, the DMO sold built, tangible heritage as the main product, and it mainly continues to do so. Therefore, while a significant section of visitors sees their tastes catered for, another, growing section of them, are not served adequately: those wanting to deeply engage with the locals and their culture (revealed under the category ‘Locals’) and those seeing Cartagena as just a relax place, revealed in the category ‘Foreigners’ in stills and video—this trend seems to have grown in recent years, as exposed by the ‘youngest’ photo social networks, i.e., Facebook and Instagram as well as the video networks.

Pitching these results against Richard’s theory, we must say the destination seems completely stuck on its ‘tangible heritage’ phase. The city seems to forever cling to its material heritage without showing any big signs of evolution. Even the preference for picturing or recording ‘Foreigners’ (to the detriment of cultural motives) in the most recent data sets may point to a backwards trend towards the 2000s when the city was just promoted (and perceived) as a sun and sand destination. At the moment, it is not clear how the destination is evolving as, for the DMO and most visitors, the city’s tangible assets are its main ones. As a matter of fact, the growing category of ‘Locals’, i.e., visitors engaging with local culture and residents, seems to go unnoticed and uncatered for and, according to Richards, this is the segment with the biggest potential in places like Cartagena. As a general remark here, we may see the power the DMO has on the destination image: most visitors’ content reflects the current DMO’s image strategy, hence showing congruence.

The results also claim for a broader concept of ‘congruence’. Van Rompay et al. ( 2010 ) use this concept in a static way, i.e., as the possibility of studying ‘one moment in time’ in a communication setting. However, things become less clear in the case of longitudinal congruence studies. Particularly when focusing on the destinations’ evolution and shifts, congruence may be there at some point in time (as in the first half of the 2010’s in Cartagena) but then at other times congruence may lessen, as in recent years. Therefore, congruence also becomes determined by the ‘time’ factor; it is not a static, it is evolving within a given communication setting. Also, the more features or UGC types introduced in a study, the more exact the findings, but also the higher the likelihood of a low-congruent result. If the reader tries to unify ‘Locals’ and ‘Foreigners’ above into a single category of ‘People’—as we did in a previous version of this article—the final results show a higher degree of congruence. Therefore, ‘congruence’ as such depends on the number of features considered as well as the number or UGC sources taken: Van Rompay et al. ( 2010 ) took pictures and text; we have added video and this supplementary source brings incongruence to the final results. We therefore hypothesize that, adding a fourth source (say, audio) may still produce more incongruence—but adding more UGC sources to such research remains also a possibility for further study.

There are several limitations to the present work, notably the different dates among the three different types of data collected, as stated above. The fact that video and text never overlap in dates might pose a limitation. Another issue is the origins of the visitors producing UGC: Cartagena’s foreign arrivals are some 10% to 12% of the total arrivals at the destination, so the vast majority of its visitors are nationals. Even the most optimistic estimates based on the recent years of the tourism boom in the city do not estimate the foreign visitors’ share above 15%. However, this is compensated by a far much larger engagement of foreigners with social networks: for instance, in the case of text mentions, 60% were collected from nationals, while around 40% are from foreigners. Also, in the photo and video datasets, the presence of foreigners is much more significant than their share of arrivals at the destination. Apart from the fact that foreigners engage much more with social media than nationals, it also seems plausible that foreigners look for more “added-value” products than beaches, whereas nationals use Cartagena more as a relaxation destination. These facts might have introduced some biases into the data. However, notice that our goal in this paper is not to study segments or sub-segments of visitors to the destination but to research into the overall congruence of the place’s image. Combining this with the study of segments of visitors would have made for a very cumbersome paper, so this is a possible future research avenue more focused on consumer behavior rather than destination image. The same goes for other side issues such as cross-posting: our massive-data approach disregards them but future works based on qualitative methodologies (netnography, etc.) might take these matters into account and provide further insights.

As for the field work, it is worth noticing that, in recent years, social media providers have revealed the trend towards hiding relevant picture information (geolocation, date, hour…) and closing their APIs (Application Programming Interfaces). Users’ demographics information is more and more difficult to come by, thus making segmented studies almost impossible. As providers seem more and more reluctant to share their information, working with social media in the future will be more cumbersome and harder than it was for this study.

In any case, the usefulness of cross-studies like this one is confirmed, as is the usefulness of longitudinal studies regarding these issues. Looking into multiple-source UGC may yield interesting visions of the destination, which can benefit all the stakeholders. Of course, another way of having good insights into the goals of the present research is by studying other destinations (possibly similar ones) using the frameworks and methodologies we have applied here. According to Case Research Theory, such studies would be a source of enrichment to the conclusions put forth by this paper—or moderate them, as the case might be. This is a future research avenue.

And finally, given the current pandemic context affecting tourism worldwide, a thought-provoking research work to do in the future would be to check whether the post-COVID-19 UGC is similar or differs from the pre-COVID-19 UGC. This would be a highly interesting contribution towards the current discussion on COVID-19 and its impact on tourism, specifically on destination image. However, this will be possible only in the mid-term once international tourism has resumed in Cartagena.

Data availability

Does not apply.

Code availability

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Acknowledgements

The authors would like to thank Manuel Leguizamón Tiusabá in Bogota, Colombia, for his comments on the draft version of this paper. We also thank the group of students at the Universidad Autónoma del Caribe in Barranquilla, Colombia, who devoted their time and energy to capture the photo and video data, an essential part of this project.

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Bassols-Gardella, N., Coromina, L. The perceived image of multi-asset tourist destinations: investigating congruence across different content types. Serv Bus 16 , 57–75 (2022). https://doi.org/10.1007/s11628-021-00472-7

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Received : 01 May 2021

Accepted : 17 November 2021

Published : 30 November 2021

Issue Date : March 2022

DOI : https://doi.org/10.1007/s11628-021-00472-7

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