The Impact of Travel and Tourism Sustainability on a Country’s Image and as the Most Important Factor in the Global Competitive Index: Building Brands Based on Fogel, Schultz, and Schumpeter

Abstract

Two economic metrics demonstrate the actual, practical judgment of a country: on the one hand, the number of arriving tourists and overnight stays and their share within the GDP; on the other hand, the increase in FDI arriving in the country. The impact of macroenvironmental elements is becoming more and more intense in the life of each country. How a country deals with the issue of sustainability greatly influences the perception of a given destination among travelers. In other words, sustainability has become a serious element of a country’s image. Impressions of a country formulated by others build on the image the country authentically reflects about itself. This image, if successful, boosts countries’ competitiveness in all sectors. This study focuses on the liaison between tourism and a country’s brand. Researchers examined the body of networks and the interactions thereof. For this reason, the authors established a model to explain the relationship and coaction of a country’s brand and tourism. To build up research models, the authors used data from publicly available international public databases. The researchers detected areas where the improvement achieved increases the value of the country’s brand in addition to its competitiveness in tourism.

1. Introduction

In June 2023, the Copenhagen Post reported on its website that Denmark topped the Institute for Management Development (IMD)’s competitiveness ranking for the second time [1]. The globally recognized competitiveness report places great emphasis on sustainability policies and measures in its evaluation of countries. Denmark’s result is primarily due to this. Although the priority importance of sustainability in the IMD methodology is considered a novelty, nowadays, more and more people are talking about the topic. One of the most important milestones in global development occurred in the year 2015 when the United Nations adopted a sustainability agenda from then until 2030 [2] along with the Sustainable Development Goals (SDGs). According to the United Nations World Tourism Organization (UNWTO), tourism plays an important role, directly or indirectly, in all of the goals of the Agenda.

The goals 8, 12, and 14, however, are more in focus from the perspective of tourism. They are as follows:

Goal 8: decent work and economic growth. Tourism highly contributes to global economic growth by providing 1 in 11 jobs worldwide. The sector’s contribution to job creation is recognized in Target 8.9: “By 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and products” [2] (p. 24).

Goal 11: Sustainable Cities and Communities focuses on the safety and resilient factors of a destinations from the point of view of sustainability. A city or country is sustainable, if the safety regulations are kept, and the government can react fast for the macroenvironmental changes of a destination, like a pandemic (COVID19) with creative solutions to keep the jobs in the tourism industry, or a crisis in the ecosystem with finding alternative energy resources, etc. It means that the application of these goals in our everyday life can create a safe and resilient destination, which has a potential to flourish the country’s economy. Tourism and the role of the Government also appear int he Anholt Hexagon Matrix, which is the basis for developing the country brand strategy. So, there is a connection between the goals of SDG’s and the country brand image, which take us directly to our research, where we can see clearly, that one of the key pillars of the WEF-Travel and Tourism Development Index is Travel and Tourism Sustainability, which includes Environmental sustainability, Socioeconomic Resilience and Conditions, Travel and Tourism Demand Pressure and Impact. This pillar goes hand in hand with the Sustainable Development Goals of the UNWTO.

Goal 12: responsible consumption and production. The tourism industry embraces sustainable consumption and production (SCP) practices, which stimulate global change towards sustainability.

Goal 14: Life below water. Tourism development must be the crucial area of integrated coastal zone management to be able to support and preserve the marine ecosystem and promote the blue economy (UNWTO tourism in 2030 agenda). Apart from the Sustainable Development Goals, the impact of negative macroenvironmental elements, such as global warming, shows itself with increasing intensity on the tourism market among travelers. As a result, tourists and business travelers also pay more attention to the principles of sustainability because they consciously strive to reduce their carbon footprint even during their vacations. So, sustainability became one of the most important issues in a country’s image. Additionally, the question is this: How does a country increase its international recognition and reputation? Additionally, why does sustainability matter in country branding?

A country’s brand is a very important competitiveness factor. If it is attractive, there are a number of political benefits to be enjoyed. In the age of sustainability, the brand can be maintained with a lot of measures without exhausting the available material and energy resources. Among the sectors in the national economy, the total time spent by guests in the tourism and hospitality sector continuously increased since 2015. This trend continued until the general decline in 2020 due to the pandemic. Currently, the trend is increasing again, but the time spent by foreigners in Hungary has not yet reached the 2015 length [3].

Sustainable tourism is an important state program. For this purpose, the Hungarian Tourist Agency, the government organization of the tourism sector, was established in 2016. Its most important endeavor is to make more effective use of the opportunities for tourism in Hungary and to accelerate its development. In addition to planning and strategic activities, it is also responsible for the development of the country’s tourism brand and its communication, as well as the development of not only the touristic image but also the overall image of Hungary.

The aim of this research is to determine which are the areas where performance improvement improves the country brand. Among the possible areas, this study focuses on tourist traffic and tourism. The authors examine the role of the state, the available natural and cultural resources, their use, and the background factors (infrastructure, public safety) that are the basic conditions for the effective operation of tourism.

2. Literature Review

By the 20th century, national branding had become a busy business activity. However, it existed before. Erik Torvaldsson, for example, named the discovered ice island Greenland (green land) and conducted a real campaign among the Icelanders, hoping to attract settlers here. With the slogan “What happens here, stays here” of R&R Partners, Las Vegas (“Sin City”) tempts followers of sinful desires [4]. Even today, every nation-state tries to develop and introduce its own identity to the world. Think Donald Trump’s “Make America Great Again!” (MAGA) slogan, which he also put under patent protection [5] and with which he won the presidential election in 2016 [6]. However, the slogan is only one element of modern branding.

Important issues like sustainability are always in focus, talking about the elements of tourism marketing, which is the essence of country branding. It is necessary to deal with the identity crisis caused by globalization, to which the national idea was strengthened and popularized as a reaction. In the global world, countries are like market stalls: there is fierce competition for money and influence. The goal has also changed. Today, it is no longer necessary to connect to the world but to attract the world. Simon Anholt, the first pioneer in the field, has worked with more than 50 governments over the past 25 years. The academic journal he founded, Place Branding and Public Diplomacy, is now 18 years old. He developed the foundations of the first brand measurement [7] and the brand index [8]. In an early interview, he highlighted the importance of using marketing methods in country branding [9]. Nowadays, his interest has turned more towards the good state concept [10,11]. However, the marketing approach still works today [12,13], either by combining it with the concept of a learning organization [14]. In this study, the authors investigated the question from this direction, using the data and methods of economic statistics.

Examining the economic aspect of competitiveness, [15] already drew attention half a century ago to the fact that once a certain level of economic growth is reached, capital investment injected into production will no longer be the engine of further development but the human factor, human capital. This makes it possible to start economic development even without having marketable resources. Intellectual capital can endow the given brand and country with added value [16]. Although the country brand is not only based on economic aspects but also linked to economic theory with many threads [17]. Such is the importance of human capital, but also most of the branding methods, which are adopted by country image specialists from the field of product management [18,19].

The basis for developing the country brand strategy is the Anholt hexagon, which you can find in Figure 1.

One of the key elements of the hexagon is the government; it is the element that can be least influenced; moreover, it can have a significant impact on the other five areas. The second element is tourism, which shows the real appeal of the brand in practice, together with the less spectacular pillar of investment and immigration. Exports have the same attraction beyond the country’s borders. Classic and contemporary culture is the core capital of the country brand. The population of the country (citizens) is involved in the shaping of the brand, its practical implementation, and the enjoyment of its results—but the capacities inherent in the human factor must also be used. Just as in the formation of the country brand, the government plays the most important role in some of its pillars, which manages and coordinates the related activities and creates their basic conditions.

The development of the elements of the Anholt hexagon is the foundation of a country’s good reputation. However, everywhere, the principle that bad opinions have a stronger effect than good news is also true in the field of the country’s image. This relationship is described by Bloom Consulting’s B0 metric [20]. This shows how many positive statements can be used to neutralize a negative opinion in the case of a given brand. Due to COVID-19, the current general B0 value is 1.8, i.e., two positive reviews are practically necessary to neutralize a negative opinion, and only the third positive news increases the impact of the brand. B0 is a value calculated using a statistical method, which can be assigned not only to actual but also to planned events, so it can be used in strategic decision-making.

However, in contrast to, for example, economic competitiveness, which can change significantly from one year to the next, the perception of the country brand is stable and requires either a very long time or an event of outstanding importance for it to change significantly [8]. The image of the country brand, therefore, does not always reflect reality; it is often years or decades behind it. The sources of the country brand are partly external: politics, geographical features, and cultural characteristics attract guests and investors. However, for the success of the country brand, internal resources must also be mobilized [21,22,23]. A 20–25-year program setting credible and relevant goals must be defined, in which there is consensus and whose implementation is consistently carried out by all stakeholders [24,25]. Persistence is, therefore, an important skill in brand building. Continuous, hard work is needed, which should focus on quality and not quantity in order to create a positive image.

The basis for brand development is the country’s competitive intangible assets [26,27]. This includes the human factor, the established vision, the distinctive and stable image of the country, as well as the promises made to the market. However, these intangible assets alone do not improve a country brand. Their role will only be there if the country uses these assets productively and in a coordinated manner. Without a distinctive, unique, different brand, the country cannot compete for tourists, investors, or consumers, nor for the attention of other countries. Uniqueness and attractiveness are the two qualities that can increase market share and provide a sustainable competitive advantage. In addition, good performance, reliability, and quality do not play a decisive role when products and services are comparable. In such cases, the consumer’s choice is determined by the brand [28].

Whatever happens, happens, and each and every event builds the country’s image.

The coronavirus epidemic that broke out in the Chinese city of Wuhan in December 2019 had spread into a pandemic by the spring of 2020. The consequence of the necessary countermeasures was the shutdown of the economy [29], primarily in those sectors where it was not possible to move to the online space. Tourism and hospitality were among the most affected sectors [30,31]. In Hungarian tourism, according to the [32] data, the annual number of guest nights decreased by 56 percent compared to the previous year—with this data, Hungary could record a worse result compared to neighboring countries. First of all, the number of foreign arrivals fell significantly, which was somewhat compensated by the significantly increased domestic tourism in the summer. In addition to traffic, the number of commercial accommodations also decreased significantly by 77,000 beds. The number of people employed in the sector also decreased, where the rate of decline was 8.5%. Statistical data clearly show that the pandemic and the accompanying restrictions have changed all areas of life.

The consequences not only affected the tourism sector but also fundamentally changed the perception of the countries. This necessitated a significant rethinking and transformation of the strategies related to the country’s image and country brand. Health safety has become an important aspect, for example, due to the fear of infection. This is well illustrated by the example of Montenegro [33]. In May 2020, the country lured tourists wishing to vacation in a safe place with the slogan “Corona-free Montenegro”. (In the second wave, the country was no longer so lucky.)

Although health safety itself is not included in the Anholt hexagon, it has become at least as important in the perception of the country as tourism itself. Perhaps it is the closest to the tourism category, as indicated by published announcements and reports [34,35]. The complexity of the situation and the tasks of brand building is indicated by the fact that the pandemic had not yet really ended when the Russian-Ukrainian war broke out in February 2022. This has not yet caused a global economic crisis, but due to its effects on supply chains, the long-term consequences cannot yet be assessed. The international political environment has also changed significantly, which also necessitated a rethinking of the brand strategy.

Sustainability is one of the most important aspects of our time. This is also true for tourism. Sustainability is also one of the pillars of the Travel and Tourism Development Report [36], the regular annual report of the World Economic Forum (WEF) that publishes the composite index used in this study. At WEF, this primarily means environmental sustainability: the protection and preservation of the natural and built environment and participation in international environmental cooperation. The metrics used for the pillar calculation show the extent to which the country is exposed to the consequences of climate change and how it can manage them. Policies and factors that enhance environmental sustainability are an important aspect in ensuring the country’s future attractiveness as a destination.

3. Research Method and Hypotheses

Since the goal of this study is to determine how to improve Hungary’s brand, i.e., how to attract more tourists and investors to the country, the first question to be answered is “compared to whom”. Of course, it would be most optimal to appear on the lists as the owner of the best country brand in the world, but the measure of success should not be maximized within the framework of excessive expectations but within the framework of realistic possibilities. Therefore, the country must stand out in terms of attractiveness, primarily among its neighbors, the countries of the East-Central Europe region. The Czech Republic, Slovakia, and Poland can be classified here. Thinking from a broader perspective, Austria, Slovenia, and Croatia have geographical features (coast) that are more advantageous in many respects compared to us.

The next question to be answered is “who should we message?” in order to promote the brand. Of course, reaching a wider circle, based on the law of large numbers, the country should expect more guests and investors. However, what we communicate matters. So, how do we introduce the country? The basic tenet of marketing communication: if they do not know the brand, why it is great, and why it is better than the competition, they will not even look for it. In communication, it is primarily necessary to say how the brand differs from the others. Developing the message is perhaps the part of building the country brand that carries the most responsibility. This is the main prerequisite for success. It is important to send messages about the country that can be understood and processed by the target group. The so-called Pioneer plaques [37] contain the Earth’s message in a form that can be understood by extraterrestrial civilizations. A country should follow the same path. The inhabitants of distant countries know little about Hungarians. In countless cases, politicians and journalists confuse Bucharest with Budapest [38]. That is why it is important to be clearly identifiable, to define attributes that are unmistakably characteristics.

The authors chose a focused area as a research goal. They investigated which elements of tourism performance can be improved to increase the effectiveness of the country brand. One of the most important goals of the country brand is to stimulate the economy and increase people’s well-being. Achieving these goals requires capital. In all cases, capital also means capital from abroad. This can come in two forms. On the one hand, it is spent by arriving foreigners during their stay here (tourist traffic). On the other hand, foreign investors bring it to the country for business purposes (FDI). Therefore, it is definitely worth developing the country brand in these two areas. From now on, the authors only deal with tourism; the relationship between investors and the brand is a possible subject of another study.

After reviewing the literature, the most important experience for the authors is that the state is the main coordinator of the country brand. The result of government measures and legal-political decisions is the provision of infrastructure and resources (tenders, discounts, tax system), but also the creation of public safety. The municipal government of the destinations also plays an important role in these tasks. Based on this line of thought, the authors formulated the first hypothesis.

H1: 

The state and its local representatives play a significant role in shaping the tourism brand of the country.

Tourism is primarily drawn by attractions and cultural programs, including natural values, events, festivals, and gastronomic experiences. Therefore, the second hypothesis states that:

H2: 

The construction of the country brand from a tourism point of view is based on the effective and successful use of the natural and cultural assets available to the country.

Of course, not only these two factors shape tourism and the country brand, but the authors of this study assume their dominant role.

4. Data and Methods

4.1. Data Used

In this article, the authors focused on the relationship and connections between the country brand and tourism, the relationship between the country image and foreign investors can be the topic of a separate research. The authors used internationally accepted and used indices for the study. The image of the country was modeled with the data of the Best Countries Index (BCI), regularly published by USNews. The index was developed at the University of Pennsylvania by Professor David Reibstein. It is a composite index made up of ten pillars. It contains both hard (statistical) and soft (based on a questionnaire poll of 17,000 people) data. It ranks based on a total of 76 variables that can potentially stimulate trade, travel, and investment, or directly affect the national economy. The 76 attributes form ten pillars, the scores of which are aggregated to form the ranking of the best countries: Adventure (adventure—tourist attraction), Cultural Influence (cultural factors and attraction), Entrepreneurship (role of businesses), Heritage (heritage—natural and cultural), Movers (development), Open for Business (business openness), Power (power—the role of the state) and Quality of Life (quality of life). In addition to these factors, Agility (ability to react) and Social Purpose (social goals, social flexibility) were added as new indicators as a result of the coronavirus pandemic. The former Citizenship pillar was also transferred to the latter pillar. Scoring was done based on a questionnaire survey. The analyzed countries were selected from countries with a high GDP and significant tourism income by the creators of the index. In each country studied, three groups of citizens were asked: the upper middle class, business decision-makers, and ordinary people. The scores for each pillar were calculated from their answers. The averages calculated in the individual pillars were aggregated by weighting the two pillars by the creators of the index. The weights are based on the year before the index year and the GDP value estimated by the International Monetary Fund (IMF) for 2027. After the aggregation, the countries were ranked based on the total score, and the score of the best country was considered 100, which is how the score achieved in the ranking was formed.

The BCI databases have been available since 2016, but only the rank numbers are included in them, which significantly impairs their statistical usability—nevertheless, researchers included these data in the possible analyses. Only in the results of surveys with an index structure published in 2021 and partially renewed due to the pandemic will the achieved scores appear for the first time in addition to the place occupied in the ranking. Therefore, researchers included this last report with a significantly expanded field of use in this study.

The authors used the World Economic Forum’s Travel and Competitiveness Development (formerly known as Travel and Tourism Competitiveness) Index (WEF_TT) for tourism performance. It is also a composite index. The WEF_TT examines 112 countries in its reports, and the authors used 19 metrics per country in the database compiled based on the reports. The WEF partially conducts its own questionnaire survey (Executive Opinion Survey) and uses data from other organizations (universities, business agencies, consulting organizations of the examined countries, Transparency International) to prepare its composite index.

The reports were published for the first time by the WEF in 2015, and new results are published every two years. WEF_TT also characterizes and ranks each examined country with a single score value. Every year, the WEF report includes the rank and score values broken down into pillars and sub-pillars, thus enabling a detailed statistical analysis of this composite index. In the beginning, there were 14 pillars in 4 sub-indexes, and after 2019, 17 pillars in 5 sub-indexes in the annual reports. The total number of variables is nearly 90. The reports were published for the first time by the WEF in 2015, and new results are published every two years. WEF_TT also characterizes and ranks each examined country with a single score value. Every year, the WEF report includes the rank and score values broken down into pillars and sub-pillars, thus enabling a detailed statistical analysis of this composite index. The creators of the indexes prepare detailed rankings, not only based on the aggregate score but also the rankings achieved in individual pillars and sub-pillars.

Both indexes consist of time series going back several years, which the authors used to answer the research question. In the examination of the relations and correlations between the indices, the authors included those countries that are included in the BCI and the WEF_TT. On the other hand, when examining the relationships of the index creators within each index and their effects on each other, the authors included all countries included in the given index in the research. The authors made this decision because the statistical processing of the larger sample results in a more accurate picture. As a method, the authors chose the statistical analysis of the data obtained from the time series and the construction of a model based on the results.

4.2. Definitions

Before presenting the results, the authors consider it necessary to define the conceptual framework in order to clarify the interpretation of the terms used later.

4.2.1. Best Countries Index (BCI)

The meaning and content of the individual pillars are also clear based on their names, but in other cases, they need to be clarified. Such is the case with Movers. This is a metric developed by BAV (BrandAsset Valuator Group—New York, NY, USA) for its brand-building model, which predicts the future growth of the country in terms of gross domestic product at purchasing power parity until 2024. USNews has associated the following attributes with this index: different, distinctive, dynamic, and unique. This association is not entirely clear, hence the difficulties it caused during the interpretation—the authors will discuss these in more detail in the appropriate place. Another problematic definition is Agility, which actually measures countries’ crisis management and response capabilities. It consists of components such as adaptive, dynamic, modern, progressive, and sensitive. Additionally, Social Purpose is an indicator of social consensus, goals typically supported by society (e.g., human rights, environmental protection, religious freedom), measured by USNews with a total of 11 attributes.

4.2.2. WEF-Travel and Tourism Development Index (WEF_TT)

The WEF used the following pillar system in 2021 (

Table 1. Pillar structure of WEF_TT in 2021.

Enabling Environment	Travel and Tourism Policy and Enabling Conditions	Infrastructure	Travel and Tourism Demand Drivers	Travel and Tourism Sustainability
Business Environment	Prioritization of Travel and Tourism	Air Transport Infrastructure	Natural Resources	Environmental Sustainability
Safety and Security	International Openness	Ground and Port Infrastructure	Cultural Resources	Socioeconomic Resilience and Conditions
Health and Hygiene	Price Competitiveness	Tourist Service Infrastructure	Non-Leisure Resources	Travel and Tourism Demand Pressure and Impact
Human Resources and Labour Market
ICT Readiness

).

Based on the table, the authors consider it necessary to briefly review the individual sub-indexes and the definitions of their pillars so that they can clearly use the concepts in the rest of the study. Therefore, the favorable environmental conditions (Enabling Environment) are classified by the WEF as a sub-index.

• the appropriate business environment (Business Environment)—this includes transparent and properly functioning legal regulations, respect and protection of property, the presence of foreign investors (FDI), the tax system, and the indicators necessary for starting a new business show time and costs (Pillar 1)
• safety and security (hereafter referred to as safety)—among its indicators, the authors highlight the frequency of occurrence of violent crimes (especially homicides) and terrorism and the costs of defense (Pillar 2)
• health and hygiene conditions—public infrastructure, number of doctors and hospital beds; the WEF also lists here the AIDS prevalence and malaria incidence values that were also used in the Global Competitiveness Reports before 2017—these received significant criticism there as well, and Klaus Schwab and his research team removed them from the 4.0 indices (Pillar 3)
• the human factor (Human Resources and Labor Market)—the old, much-criticized, and since-changed structure of the GCI returns here: the proportion of people enrolled in primary and secondary education, employee training, hiring and firing rates and costs, salaries, and the ratio of female workers (Pillar 4), furthermore
• IT knowledge and provision (ICT Readiness)—in this component, the provision of mobile and fixed broadband, as well as their use for private and business purposes (Pillar 5)

The policy sub-index (Travel and Tourism Enabling Conditions) shows it

6.

tourism priorities (Prioritization of Travel and Tourism)—related government measures, budget resources, statistical data, and the evaluation of the country brand strategy (Pillar 6)

7.

international openness (International Openness)—this includes the visa policy, the rate of participation in bilateral and regional agreements (Pillar 7)

8.

competitive prices (Price Competitiveness)—purchasing power of money, fuel prices, accommodation prices, airport costs (Pillar 8)

Infrastructure belongs to the subindex (Infrastructure).

9.

aviation—airports, flights, number of air journeys, airlines (Pillar 9)

10.

land—quality of roads, asphalted kilometers, railway lines, and ports (Pillar 10), also as a separate item

11.

the infrastructural background of tourism services—availability of accommodation, companies operating in the sector, ATMs (Pillar 11)

The fourth sub-index summarizes natural features and cultural resources (until 2019 Natural and Cultural Resources, from 2020 Travel and Tourism Demand Drivers)

12.

natural resources (Pillar 12)—world heritage sites, native species, protected areas, nature walks (Pillar 12) and

13.

cultural resources (Cultural Resources)—world heritage cultural sites, sports facilities, international association meetings, festivals (Pillar 13)

14.

as of 2020, this includes non-leisure resources (Non-Leisure Resources)—business and other non-leisure trips, conferences, and professional meetings, from which a significant part of the sector’s income is derived (Pillar 14)

From 2020 onward, the WEF introduced a fifth sub-index (Travel and Tourism Sustainability). Among the indices previously discussed in the political sub-index, he was reclassified here

15.

sustainable environment (Environmental Sustainability) pillar—this includes environmental protection indicators: environmental legal regulations and contracts, forest, game and fish management, water protection, biodiversity (Pillar 15), and two new indexes:

16.

social sensitivity (Socioeconomic Resilience and Conditions—Pillar 16) and

17.

the impact of travel and tourism demand (Travel and Tourism Demand Pressure and Impact—Pillar 17)

In addition to these, the former Natural and Cultural Resources subindex was also supplemented with a Non-leisure resources element and given a new name: Travel and Tourism Demand Drivers.

The last available report was published in 2022 [36]. During the investigation, if the authors did not analyze the time series itself, they worked with this report. In the case of three countries, one piece of data was missing; these were replaced by the average of the data taken from the previous two surveys.

Descriptive statistics of the overall performance (overall score) in 2021 are included in

Table 2. Descriptive statistics of the WEF_TT sample.

Descriptives
WEF_Travel_and_Tourism_Competitiveness_Index
N	112
Missing	0
Mean	3.64
Median	3.67
Standard deviation	0.981
Minimum	1.61
Maximum	6.45

. This year, 112 countries were included in the WEF report. The data set was complete; there were no missing data. The combined tourism performance of the countries is above the theoretical average (3.5). The value of the theoretical average was established based on the seven-point Likert scale of the answers to the questions. The closeness of the mean and median values indicates a symmetrical normal distribution. This is supported by the skewness value of 0.005. The next question was the normality of the sample. Given that the number of countries is over 100, the normality of the sample can be assumed by applying the theorem of the central limit distribution. Therefore, the authors have the opportunity to perform statistically more powerful parametric tests.

4.3. The Model

This research examines how the areas of tourism competitiveness are related to the performance of the country brand and what effect they have on it. After describing the descriptive statistics, the authors looked for correlations using the SPSS Statistics program, and based on these, the authors created path models (Structural Equation Model—SEM) to explore the interactions of the individual factors with the SmartPLS software 4.0. 9.6 (released 1 September 2023). SEM is an extremely broad and flexible data analysis framework. It can be seen as a family of related methods rather than a single technique. Its origins can be traced back to psychologist Charles Spearman. Perhaps it is not an oversimplification to say that SEM actually combines factor analysis and regression. At the same time, it offers much more flexibility to the modeler than these two mentioned techniques alone. It is not about running a factor analysis and then entering the factor scores into a multiple regression. The structural equality model is a widely used multivariate analysis method that is used in many disciplines, be it economics, sociology, or psychology. With the help of the method, the authors try to estimate unmeasurable concepts. These are latent or directly unmeasurable variables. The basis of the method is the review of the causal relationship between the factors. In essence, SEM examines regression equations that are separate but interrelated. The model has two main parts: the structural model, which reveals the dependency relationships between the latent constructs, and the measurement model, which, among other things, provides an estimate of the reliability of the constructs [39]. Similarly to the Granger test, SEM is suitable for causality analysis, but here, a long continuous time series is not a requirement. In contrast to the Granger test, the use of SEM for this purpose is limited from the point of view that (since it is based on correlations) the direction of the causal relationship is determined by the author’s somewhat subjective decision based on the literature, scientific experience, and logic. In fact, he elaborates on this critical remark in detail in his paper [40], giving a detailed overview of the literature dealing with the issue. However, it can be mentioned as an advantage of SEM that when there is a case of multicollinearity, SEM is a useful tool. Multicollinearity refers to highly correlated independent variables, for example, in the WEF pillars of competitiveness. The part of path analysis analogous to factor analysis is the already mentioned measurement model, and the elements that connect the measurement model to one or more dependent variables or to each other are called structural models. It happens that the variables are combined on an empirical or theoretical basis before the analysis, in which case the measurement model does not play a role.

It is also possible to ignore the measurement error and use only the observed raw variables. When there is no measurement model, only structural, the term path analysis is more appropriate than SEM, but many people use the term SEM in such cases as well. The procedure can be used with any type of data—ratio, interval, ordinal, nominal—and can model curvilinear relationships between variables, as well as interactions. The method does not require a complete set of data, but missing data must be handled with care. It works well for hierarchical, mixed, and longitudinal modeling or segmentation. It can accommodate multiple dependent variables and can be used to accommodate individual response styles in questionnaire surveys.

Fit indices are used to check the adequacy of the model. The Comparative Fit Index (CFI) and the Root Mean Square Error of Approximation (RMSEA) are perhaps the most common. The more familiar R square is sometimes also informative. At the same time, based on my experience, whether the model is appropriate ultimately depends on common sense, relevant theory, and its possible useful application in decision-making. Summarizing the details of the modeling procedure that are relevant for us now, the main point is the following. SEM can be considered a pseudo-causal model. It includes cause and effect, but the researchers themselves establish their relationship based on literature data and their own scientific experience. In true causality tests, such as the Granger test, causality is objectively proven by the test. The SEM shows the direct, indirect, and total effect of the variables included in the study on the explained, also known as the outcome variable. Some of the explanatory variables are purely explanatory; other variables appear in the model as both cause and effect.

The authors made several models. In the first model, among the WEF_TT variables, based on the results of the correlation tests, they selected which ones should be included in the model. By aggregating these, the authors created their own indexes and then examined their relationship with BCI’s country brand performance. Since WEF_TT is a composite index, its pillars are not independent of each other. This means that it is not possible to select a specific pillar for development without causing changes in the other pillars. Therefore, not only the impact of the individual pillars on tourism competitiveness and the development of the country brand but also the relationship between these pillars should be examined. For this purpose, the authors created a new model in which they selected their own variables based on the significant correlations between the variables of the WEF_TT. The authors placed them in the model according to the original index structure of WEF_TT. Since the results were not clear in all cases, the authors created a third model. This model has become simpler and better explained, as it outlines a different system of relationships than its version built on the basis of the original index structure. The study included the countries that appear in both rankings. The goal was to find the factors that can be improved to significantly increase the effectiveness of the country brand. The authors wanted to create the basis of a practical guide that can help professionals to strengthen the country brand.

5. Reviewing Results

First, the authors examined whether they could find a connection between the place occupied in the BCI ranking and the position occupied in the WEF_TT. They did not expect a trend-like relationship. The reason for this was that tourism is not the only factor in the development of the country brand. In addition, tourism data are indicators rather than determinants of the strength of the country brand. The diagram shown in Figure 2 was obtained.

The results confirmed the expectations. A higher score in one index does not necessarily mean an improvement in the other index. Hungary, for example, ranks 45th out of 70 countries in the BCI, while in the WEF_TT, examining the same 70 countries, it ranks 12th overall. That is, Hungary is one of the attractive tourist destination countries, although it does not rank high among the examined countries in terms of brand.

WEF_TT and Country Brand

Based on the index structure, the country brand and WEF_TT cannot be directly compared. The country brand is part of the WEF_TT (Pillar 6). Therefore, the authors have to compare the performance in the BCI with the dimension of the WEF_TT country brand strategy (Country Brand Strategy Rating—CBSR). Although the reports and downloadable databases published by the WEF themselves do not contain CBSR 2021 scores, the WEF has published them online. The authors examined the 68 countries that appear in both indexes. Given the element numbers below 100, the normality of both samples is an important question.

Table 3. WEF_TT Country Brand (CBSR) index constituent and descriptive statistics of performance in BCI.

Descriptives
	CBSR Values 2021	BCI 2021 Overall Score
N	68	68
Missing	0	0
Mean	4.32	40.5
Median	4.27	27.2
Standard deviation	0.476	32.7
Minimum	3.34	1.40
Maximum	5.25	100
Shapiro–Wilk W	0.975	0.869
Shapiro–Wilk p	0.187	<0.001

contains this and the descriptive statistics of the samples.

The essential information in the table is the result of the normality test (Shapiro–Wilk test). Since the value of p for the BCI is below 0.05, the condition of normality was not met in this sample. Therefore, it would use the non-parametric Spearman correlation to search for relationships.

However, the authors did not do so when they examined the correlations between the WEF_TT and the original BCI-Overall Score. Since the ordinal variable (seven-point Likert scale) was converted into a metric variable by aggregation, the authors were able to use the statistically more powerful Pearson correlation here (

Table 4. The relationship of the BCI general score with the sub-indexes of the WEF_TT.

Correlations of BCI’s Overall Score	Pearson’s r	p-Value
Adventure_TT	−0.385 **	0.001
Agility_TT	0.166	0.171
Cultural Influence_TT	0.617 ***	<0.001
Entrepreneurship_TT	0.768 ***	<0.001
Heritage_TT	0.660 ***	<0.001
Movers_TT	−0.236 *	0.049
Open for Business_TT	0.632 ***	<0.001
Power_TT	0.549 ***	<0.001
Quality of Life_TT	0.670 ***	<0.001
Social Purpose_TT	0.05	0.68

*** p < 0.001, ** p < 0.05, * p < 0.1.

).

Table 4 shows two negative correlations: the effectiveness of the country brand deteriorates in parallel with the better performance achieved in the Adventure_TT and Movers_TT pillars. Why? In the case of Movers_TT, the answer is simpler. This sub-index is somewhat confusingly defined by the BCI methodology (US News, 2021), as the authors have already highlighted in the section on concepts. On the one hand, he evaluates the future possibilities of the country’s economy, but on the other hand, he claims that this pillar is “different, distinctive, dynamic, unique”. It could not accurately interpret these characteristics as attributes of economic growth). Explaining the negative effect of Adventure_TT is more difficult. According to the mentioned methodology, the pillar shows how friendly and attractive the given country is to tourists. One possible explanation is that the creators of the index weighted the individual pillars in the creation of the final score and assigned the smallest weight factor (3.79%) to this particular pillar, compared to the weight factor of the other pillars, which is typically over 10%.

However, Table 4 also clearly illustrates that the human factor, i.e., the people, plays the main role in the formation of the country brand. The name of the Entrepreneurship pillar is, therefore, somewhat misleading. According to the definition of the methodology, this pillar primarily includes education, an innovative approach, and a good infrastructural background. These are indeed important conditions for a well-functioning enterprise, just like the openness of business life (Open for Business_TT). Perceived the operation of the country as a joint enterprise of its inhabitants, the index immediately “comes to life”, and its effect on the country’s image immediately becomes meaningful, the strength of which surpasses all its pillars. The role played by culture (Cultural Influence_TT), national heritage (Heritage_TT), and quality of life (Quality of Life_TT) in the country’s image is clearly explained by the significant correlation in the result. The authors found a medium correlation between the country brand and the role of the state (Power_TT), which clearly shows that the state has significant tasks in shaping the country’s image, but a “good state” is not the most important criterion in the assessment of the country abroad. The role of social purposes (Social Purpose_TT) is small compared to the other factors. This can also be explained by the fact that the rule of law, social justice and solidarity, and striving to preserve a sustainable environment are very important for a well-functioning country but less interesting for tourists coming to the country. Because, using a business analogy, they are mostly only interested in the “showcase” and not the “warehouse”. This statement is well supported by the Berlin Olympics of 1936, where Hitler’s Germany received many positive opinions as the host [41].

The authors created the SEM model based on the correlations (Figure 3). In the diagram, the names and explanations of the variables are shown in rectangles (in brackets at the bottom right). The so-called latent variables (presented in the form “e1”–”e5” in the figure) represent the other causes that give a complete explanation. These are factors not included in the model. The arrows indicate the strength of the direct effects. The residual variance (e1–e5) is the variance that is not explained by all exogenous predictors in the model.

Table 5. Full and (direct + indirect) effects of the SEM model.

	Cultural Infl.	Entrepreneurship	Heritage	Open for Busin.	Power	Quality of Life	Score
Cultural Infl.							0.183 (0.183 + 0)
Entrepre-neurship							0.395 (0.395 + 0)
Heritage	0.843 (0.843 + 0)						0.475 (0.321 + 0.154)
Open for Busin		0.629 (0.335 + 0.295)				0.427 (0.427 + 0)	0.264 (−0.047 + 0.311)
Power	0.003 (0.003 + 0)	0.753 (−0.052 + 0.806)		0.670 (0.670 + 0)		0.843 (0.557 + 0.286)	0.513 (0.124 + 0.389)
Quality of Life		0.689 (0.689 + 0)					0.418 (0.145 + 0.273)

contains the direct, indirect, and total effects. The importance of indirect effects is indicated by the fact that they strengthen the direct effect in all cases. The variables of own model explain 76 percent of the performance in the development of the country’s image, and the explanation of the other variables is over 60 percent (except for business openness—Open for Business_TT -, which is explained by 44.9%). Among the fit tests, the value of the NFI (Normed Fit Index) is 0.923, i.e., adequate, and the value of the SRMR (Standardized Root Mean Square Residual) is 0.121, which shows a somewhat weaker fit than the reference value (SRMR < 0.1). However, given the high explanations (R2), the model was considered usable for further analysis.

The state (Power_TT) and the cultural-national heritage (Heritage_TT) appear as purely explanatory variables in the development of the country brand performance (Overall Score). Perhaps the most important is the influence of the state (Power_TT) on the development of the country brand. Directly, this occurs only less (0.124), but in terms of the total effect, it is the strongest (0.513). This is followed by the other explanatory variable, the national-cultural heritage (Heritage_TT) (0.475) and the quality of life (Quality of Life_TT) (0.418). In other words, the state—although it has little direct influence—has a dominant role in shaping the country brand via its institutional system. These latter effects are primarily realized through openness (Open for Business_TT) and the evolution of the quality of life (Quality of Life_TT). At the same time, it seems that market freedom (Entrepreneurship_TT) (−0.052) decreases as a result of stronger state regulation (Power_TT), but this negative effect is amply compensated by measures to improve the quality of life (Quality of Life_TT) (0.557).

In addition to improving citizens’ well-being, these also have a stronger positive effect on entrepreneurship (Entrepreneurship_TT) (0.689) than the negative effect of direct state regulation, so in the end, the proper functioning of the state significantly helps businesses to thrive.

The second model was created to examine the extent to which each WEF_TT sub-index determines tourism competitiveness. Since the relationship system of sub-indexes, pillars and variables is complex, it is not necessary to review all the relationships, so the authors only focused on the significant ones. Due to significant multicollinearity, these were selected on the basis of correlations (

Table 6. Value and significance of correlations between sub-indexes of WEF_TT.

	Enabling Environment	TT Policy	Infrastructure	TT Demand Drivers	TT Sustainability
Enabl. Env.ment	----
TT Policy	0.513 ***	----
Infrastructure	0.619 ***	0.534 ***	----
TT Demand drivers	0.189 *	0.485 ***	0.588 ***	----
TT Sustainability	0.740 ***	0.635 ***	0.640 ***	0.402 ***	-----

Note: * p < 0.05 *** p < 0.001.

).

Strong and significant correlations dominate, so the authors have to expect significant multicollinearity between the individual pillars. Based on the correlation results, they included all sub-indexes and pillars in the model, which was first developed by us in accordance with the index structure established by the WEF. Figure 4 shows this model. The e1–e6 in the model are the residuals. The residual variance is the variance that is not explained by all exogenous predictors in the model.

The explanations of the symbols used are the same as those described for the model in Figure 2. The fit statistics of the model (SRMR: 0.043, NFI: 0.9) indicate a good fit.

Table 7. Full (direct + indirect) effects of the SEM model of the WEF_TT index.

	Overall Score	Enabl Envir	TT Policy	Infrastr	TT Demand Drivers	TT Sustain
Overall Score	------
Human Resources	0.187 (0.000 + 0.187)	0.155 (0.155 + 0.000)
ICT-Readiness	0.383 (0.000 + 0.383)	0.318 (0.318 + 0.000)
Prioritisation	−0.167 (0.000 − 0.167)		0.682 (0.682 + 0.000)
Internat. Openness	−0.100 (0.000 − 0.100)		0.409 (0.409 + 0.000)
Price Competness	−0.098 (0.000 − 0.098)		0.399 (0.399 + 0.000)
Air Infrastr	−0.139 (0.000 − 0.139)			0.500 (0.500 + 0.000)
Ground and Port Infrastr	−0.081 (0.000 − 0.081)			0.292 (0.292 + 0.000)
Tourist Serv. Infrastr.	−0.082 (0.000 − 0.082)			0.296 (0.296 + 0.000)
Envir. Sust.	−0.011 (0.000 − 0.011)					0.034 (0.034 + 0.000)
TT Demand Pressure	−0.127 (0.000 − 0.127)					0.401 (0.401 + 0.000)
Enabl Envir	1.204 (1.204 + 0.000)
Social Resil.	−0.317 (0.000 − 0.317)					1.005 (1.005 + 0.000)
Natural Res.	0.279 (0.000 + 0.279)				0.685 (0.685 + 0.000)
Cultur. Res.	0.039 (0.000 + 0.039)				0.095 (0.095 + 0.000)
Non-Leisure Res.	0.114 (0.000 + 0.114)				0.280 (0.280 + 0.000)
TT Policy	−0.245 (−0.245 + 0.000)
Infrastr.	−0.278 (−0.278 + 0.000)
TT Dem. drs	0.407 (0.407 + 0.000)
TT Sustain.	−0.315 (−0.315 + 0.000)
Busin Envir	0.411 (0.000 + 0.411)
Safety	0.303 (0.000 + 0.303)
Health	0.268 (0.000 + 0.268)

summarizes the strength of direct, indirect and total effects.

Many direct effects have a negative sign, i.e., the cause weakens the effect. This is not surprising, as it can be seen when examining the correlations (Table 7) that there is significant multicollinearity between the pillars of the index. The effect of state involvement (Enabling Environment), which is also the strongest effect, is clearly positive. Tourism competitiveness is at a higher level even if the country has significant geographical and cultural resources. These appear as demand boosters in the tourism sector, increasing the attractiveness of the country. The human factor (Human Resources) also enhances tourism competitiveness, all elements of which—health, digital skills (ICT Readiness)—also have a positive effect. The influence of the human factor increases tourism performance indirectly, primarily via political measures. The latter statement, although it is derived from the model, is not quite interpretable. The index structure of the WEF_TT was primarily compiled by the authors of the report on the basis of measurability and the internal consistency of the variables. This structure is perfect for this purpose. However, due to the significant interactions between the individual components, the impact of the individual pillars and their components on tourism performance is not always positive. For example, half of the total effects are also negative. In addition to the index pillars, other factors also play a role. The five sub-indices explain 69.4% of the total performance in this structural arrangement, the additional 30.6% required for complete explanation is related to other factors—these are collectively indicated by the element labeled “e6” shown in Figure 4.

Due to the multicollinear nature of the index, there are many negative and difficult-to-interpret correlations in the model built on the basis of the structure used by the index creators. Therefore, the authors decided to try to create a simpler but better-explained model using the pillars used by the WEF. In order to do this, the authors reviewed the original structure of WEF_TT and connected the index creators they selected to a different logical scheme from the creators. As a result, the authors got the model shown in Figure 5. The e1–e2 in the model are the residuals.

The fit statistics of the model are adequate (SRMR 0.085, NFI 0.891). The value of Cronbach’s alpha is 0.919, which indicates good internal consistency. The most important difference between the own model and the one based on the structure of WEF_TT is the higher explanation of the overall performance of the own model. Natural and cultural resources not only increase the demand for tourism, but also increase tourism competitiveness with a direct effect. Another positive of the model is that only one negative effect appears in it, the effect of infrastructure on the development of tourism competitiveness. A possible explanation for this is the locational nature of the infrastructure and the fact that the WEF_TT measures competitiveness at the national level. However, visitors do not choose a country, but a smaller territorial unit as the aim of their trip. Therefore, for example, a world-class capital airport or port is almost indifferent if the sights are located at the other end of the country. At the same time, infrastructure development always requires significant resources and capital. These, among other things, must be taken away from the development of local destinations. This may be the explanation for the negative impact of the infrastructure (

Table 8. Authors’ own model complete (direct + indirect effects).

	Enabling Environment	Infrastructure	Overall Score	TT-Sustainability	TT-Demand Drivers
Air Infrastr.		0.597 (0.597 + 0.000)	−0.266 (0.000 − 0.266)
Cultural Resources	−0.005 (0.000 − 0.005)	−0.001	0.409 (0.413 − 0.004)	−0.019 (0.000 − 0.019)	0.257 (0.257 + 0.000)
Enabling Environment		0.177 (0.177 + 0.000)	0.826 (0.905 − 0.079)
Ground and Port Infrastr		0.266 (0.266 + 0.000)	−0.118 (0.000 − 0.118)
Human Resource	0.132 (0.000 + 0.132)	0.023	0.109 (0.000 + 0.109)	0.531 (0.531 + 0.000)
Infrastructure			−0.446 (−0.046 + 0.000)
Natural Resources	−0.013 (0.000 − 0.013)	−0.002 (0.000 − 0.002)	0.108 (0.119 − 0.011)	−0.052 (0.000 − 0.052)	0.705 (0.705 + 0.000)
Overall Score
Social Resilience	0.536 (0.536 + 0.000)	0.095 (0.000 + 0.095)	0.442 (0.000 − 0.442)
TT-Sustainability	0.248 (0.248 + 0.000)	0.044 (0.000 + 0.044)	0.205 (0.000 + 0.205)
TT-Demand Drivers	−0.018 (0.000 − 0.018)	−0.003 (0.000 − 0.003)	−0.015 (0.000 − 0.015)	−0.073 (−0.073 + 0.000)
TT Policy	−0.030 (0.000 − 0.030)	−0.001 (0.000 − 0.001)	−0.002 (0.000 − 0.002)	−0.011 (0.000 − 0.011)	0.157 (0.157 + 0.000)
Tourist Services Infrastr.	0.090 (0.000 + 0.090)	0.016 (0.000 + 0.016)	0.074 (0.000 + 0.074)	0.362 (0.369 − 0.007)	0.098 (0.098 + 0.000)

). In the authors’ own model, it can also be seen that the role of the state has the strongest effect on tourism competitiveness. Surprisingly, however, the impact of tourism and transport policy is only exerted indirectly: if this area functions properly, it contributes to the driving forces of need in addition to natural and cultural resources.

Social sensitivity and flexibility do not have a direct impact on tourism competitiveness, but in terms of their overall effect, they influence it significantly (0.442). So, the so-called “good state” role of the state is nevertheless an important factor in the perception of the country by foreigners. The model is also characterized by the relatively “clean” nature of the effects, i.e., mostly one factor exerts its effect either exclusively directly or only indirectly. An exception to this is the impact of cultural and natural resources and a well-functioning institutional system on competitiveness, as well as the impact of tourism infrastructure on the sustainability of tourism. In these cases, the indirect effects always weaken the direct effect of the factor.

6. Conclusions

Country brand and economic competitiveness are overlapping and mutually complementary concepts. A more competitive country has a better chance of gaining a good reputation, while the reputation of a recognized country improves competitiveness. The country brand cannot therefore be discussed without economic aspects. The main result is the income from tourism and the foreign investments coming to the country, as well as the increase in exports. These are fundamental sources of economic growth. Therefore, it is important to learn about the economic factors, the improvement of which will strengthen the effect of the country brand. The results show the decisive role of the proper functioning of the state in building the country brand. In the statement, it was established that human resources and entrepreneurial approach are of great importance in the relationship between the factors of tourism competitiveness and the role of the state. The authors were able to explain the ways the development of which factors improve the value of the country brand. The degree of improvement that can be predicted on the basis of variables created using WEF_TT, with im-provements implemented in individual factors was determined.

The purpose of the research was to investigate which factors can be improved to enhance the country brand. In this regard, the own results contributed to the answer with more information. In determining the value of the BCI score, based on authors’ own model created from WEF_TT’s index constituents, it can be said that the role of the state (power) and the role of natural and cultural assets (heritage) are primarily based on indirect effects. The state primarily influences the performance of the tourism country brand by supporting the entrepreneurship sector, creating business openness, and ensuring quality of life. The state also plays a significant role in creating the background of tourist attraction, and public safety can be mentioned here as a basic condition for a peaceful stay of guests coming to the country. Cultural heritage affects not in itself, but, as the authors formulated in the H2 hypothesis, if it is used properly, it primarily affects the performance of the country. Based on this, the authors verified both of their hypotheses with some modifications.

The other aim of this research was to support the Sustainable Development Goals of the UNWTO. The research has a direct connection of support Goal 8: economic growth and Goal 11, sustainable cities and communities, where the role of the country brand play a crucial role.

The present study is the beginning of a research series. Therefore, the results can only be interpreted in a limited way. One limitation is the data used. The BCI index database used as a source examines the most economically developed countries, therefore it does not provide information on the factors affecting the brands of less developed countries. Another limitation is the method used. The path model does not show actual causal relationships, it only serves to check possible relationships. The limitation of the sample can be handled by expanding the group of countries included in the research, and the limitation of the method can be eliminated by having longer time series available. Since this study presents the results of the first investigation of a research series, the authors hope to eliminate the current limitations in the future. Having assessed the effectiveness of the applied methods, the aim will be to create the foundations of a more differentiated and usable brand-building strategy by using newer databases and methods.