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Article

Tourism Competitiveness in Eastern Africa: RCA and TTCI

by
Zsuzsanna Bacsi
1,
Abdi Shukri Yasin
2,3 and
Gabriella Bánhegyi
1,*
1
Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary
2
Doctoral School of Economics and Regional Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary
3
Department of Natural Resources Management, Kebri Dehar University, Kebri Dehar 250, Ethiopia
*
Author to whom correspondence should be addressed.
Heritage 2023, 6(9), 5997-6015; https://doi.org/10.3390/heritage6090316
Submission received: 2 August 2023 / Revised: 21 August 2023 / Accepted: 22 August 2023 / Published: 23 August 2023
(This article belongs to the Special Issue Sustainable Heritage, Tourism and Communication: Theory and Practice)

Abstract

:
Eastern Africa is home to strikingly beautiful landscapes, unique wildlife and exotic cultural heritage that create outstanding tourism appeal. Unfortunately, these attractive features do not always translate to high tourism revenues. This paper focuses on analyzing the relationships between tourism performance indicators—arrivals, revenues and the revenue-based revealed comparative advantage (RCA)—and compare them to the components of destination facilities and endowments measured by the Tourism and Travel Competitiveness Index (TTCI). The analysis concentrates on Ethiopia, Kenya, Uganda and Tanzania, using secondary data from 2005 to 2017. The methodology applies correlation analysis and panel regression. As the results show, the TTCI and RCA are negatively correlated, but the components of the TTCI have different relationships to the RCA. Natural heritage positively influences the RCA, while cultural resources do not. The higher RCA values are also enhanced by better tourism services and better ground travel infrastructure. Similar analyses have been performed for Europe and some Asian countries, but not for Eastern Africa. The novelty of the present research is the fact that natural heritage resources can contribute considerably to tourism revenues, while cultural resources are not utilized to their full potential in terms of tourism success.

1. Introduction

Tourism is one of the most important industries in the world, and tourism in Africa is growing much faster than in most parts of the world. Its contribution was 8.5% of the continent’s gross domestic product (GDP) in 2018 [1,2]. Tourism supported 9.1 million direct jobs [1] and 24.3 million jobs including induced impacts [3] in Africa, and the continent received around 5% of the estimated 1.4 billion international tourist arrivals in 2018. Even though tourism is firmly established in many developed economies, Africa is only beginning to realize its full potential, accounting for only 1% of the USD 1.7 trillion global tourism revenue [3], and only 5% of all tourists arriving globally in 2018 [4]. Recent years have shown the vulnerability of tourism to events restricting mobility, such as the COVID pandemic in 2020–2021 and terrorist attacks, leading to a decrease in tourism spending and contraction of the economy in the short term and long term [5,6]. Although the countries of the African continent have experienced exponential growth in tourism since the 1970s, this growth in arrivals has not been reflected in economic, social or environmental benefits for host communities [2].
The countries of East Africa view tourism development not only as a key component of national economic development but also as a mechanism to alleviate poverty, generate foreign revenue for the government and contribute to wildlife conservation [7]. East Africa is one of the major tourism destinations in Africa, and natural resources are among its most important tourism appeals [1]; for its geography, see Figure 1. However, local communities in the most attractive nature-based destinations rarely benefit that much from tourism, despite their crucial role in the sustainable management of these areas. Several case studies have explored the benefits of tourism, such as those by Tekalign et al. [8] about Ethiopia, Iacopino et al. [9] about Uganda, Juma and Khademi-Vidra [2] about Kenya and Melubo et al. [10] about Tanzania. In South Africa, farmers have benefited by converting their agricultural farms to private game farms [11] for tourism purposes. The results from Tanzania [10,12] and Kenya [13] are more mixed. Several studies [14,15,16] have attempted to quantify the economic benefits of tourism-related activities in rural communities, but data are scarce with results relating to specific communities instead of nationwide analyses [17].
In Africa, tourism attractions are mainly based on natural endowments (scenic landscapes, wildlife, coastal beaches, etc.), history, arts, crafts, dance and a myriad of cultural attributes. Wildlife may offer opportunities for supplementary—or even main—income generation for the rural population and may provide an alternative to livestock production. Eastern and Southern African rangelands are famous for giving home to a great variety and abundance of wildlife, including large mammals, such as elephants, rhinos, zebras, lions, giraffes and many other species. After sharp declines in wildlife between 1970 and 1990 across Africa, several countries introduced incentives for sport hunting and ecotourism. National parks and protected areas play crucial roles in maintaining African wildlife populations, and their numbers and areas have also increased significantly over the past 50 years [18].
Although sustainability principles apply to all types of tourism activities, their significance is outstanding for the various forms of nature-based tourism. Nature tourism means travelling to unspoiled places to experience and enjoy nature. It involves moderate and safe forms of exercise such as hiking, biking, sailing and camping. Wildlife tourism is a form of nature tourism, where the main attraction is to watch animals, birds and fish in their native habitats [19]. This type of tourism has shown sharp growth in recent years, and the tourism industry often uses the term “wildlife tourism” rather than wildlife-watching tourism, although wildlife tourism is sometimes also used to include hunting or fishing tourism. Wildlife watching overlaps with ecotourism [20], responsible travel to natural areas, that conserves the environment and sustains the well-being of local people [21].
Wildlife watching is a major attraction for international tourists globally and in Africa. In 2018, wildlife tourism directly contributed USD 120 billion to the world GDP, while its total contribution was three times this value (USD 343.6 billion), i.e., 3.9% of the tourism-generated GDP. However, in Africa, the respective figures are outstanding, with USD 29.3 billion generated directly by wildlife tourism, producing more than one-third (36.3%) of the continent’s travel and tourism GDP, while the total wildlife-tourism-generated GDP reached USD 70.6 billion USD—including international and domestic tourism too. Kenya’s protected areas were visited by 2.9 m people in 2018, of which about 700 thousand were international tourists, i.e., half of the foreign visitors experienced some wildlife tourism activity. Wildlife tourism is estimated to provide about 70% of tourism earnings and more than 10% of total employment in the country. In Tanzania, roughly 1.9 million ecotourism visitors were recorded in 2018, and about 46% of all international tourists—i.e., more than 600 thousand people—experienced some wildlife activity [22].
Wildlife-watching tourism generates income from payments for entrance and permit fees by tourists to visit wildlife-watching sites, and to the guides, drivers and other staff who may accompany them. Tourists also pay for accommodation and other services to travel to and stay at wildlife-watching sites, and these visits also allow them to visit other areas of the country to see other attractions such as a country’s heritage and culture [20]. The key features of the analyzed countries are shown in Table 1.
Natural and cultural heritage sites are major tourism attractions worldwide. Many studies have established that natural and cultural heritage sites are core tourism attractions, leading to increased visitor numbers and tourism receipts [26,27]. Cultural heritage includes first of all tangible heritage, including buildings, architecture and art, and objects, and intangible heritage such as gastronomy or traditional food and drink [28], as well as intangible historical resources [29], and many other attractions. Both cultural and natural resources can contribute to enhanced visitor numbers and spending, though countries differ widely in this respect. European, Latin-American and Caribbean countries tend to mainly benefit from their cultural world heritage, while African and North American countries benefit more from their natural resources [30]. The African continent is particularly rich in unique cultural and natural resources, many of which are listed as World Heritage Sites [10,14]. In 1972, UNESCO defined cultural heritage, for the purpose of the Convention concerning the Protection of the World Cultural and Natural Heritage, as three groups of (a) monuments: architectural works, works of monumental sculpture and painting, elements or structures of an archaeological nature, inscriptions, cave dwellings and combinations of features, which are of outstanding universal value from the point of view of history, art or science; (b) groups of buildings: groups of separate or connected buildings, which, because of their architecture, their homogeneity or their place in the landscape, are of outstanding universal value from the point of view of history, art or science; and (c) sites: works of man or the combined works of nature and of man, and areas including archaeological sites that are of outstanding universal value from historical, aesthetic, ethnological or anthropological points of view [31]. According to Brumann, cultural heritage includes the sites, things and practices a society regards as old, important and worthy of conservation [32]. Historically, the concept of cultural heritage developed from the interest in and attributed values given to monuments, artifacts, works of art, landscapes and other tangible elements, along with the intangible components, together representing identities in terms of culture and natural surroundings [33]. This change is well reflected in the current UNESCO definition [34]. In 2012 UNESCO adopted the text of the Convention for the Safeguarding of the Intangible Cultural Heritage and defined the intangible elements as oral traditions, performing arts, social practices, rituals, festive events, knowledge and practices concerning nature and the universe or traditional craftsmanship [35]. Tangible and intangible cultural heritage not only coexist but are often inseparable [36] (Figure 2).
The intangible attributes together with the physical artifacts characterize and identify the distinctiveness of a society [38]. According to the report of the Congress of Local and Regional Authorities of the Council of Europe, cultural heritage goes beyond the tangible and intangible aspects to also include natural and cultural heritage, as it is difficult to justify the construction of categories that are too rigid [39].
Several stakeholders can be identified in cultural heritage management, preservation and utilization. Museums play an important role in preserving objects while making it possible for the public to learn about their importance in society, history and tradition. Monuments, group of buildings often require direct government intervention to ensure their long-term survival [40], and which might need significant funding. Because of their unique and often irreplaceable nature, and their attributed importance, they raise some economic questions [41], such as the worth of cultural heritage artifacts, objects, etc., how to finance their preservation and how they can be utilized? If cultural heritage can be considered as an asset, then it has the attributes of goods and services [42]. In this sense, archaeological heritage combined with labor and other inputs can contribute to the spending of visitors at sites [38].
UNWTO and UNESCO have singled out cultural heritage tourism as one of the most suitable forms of community development for developing countries, but attention should be paid to sustainability requirements. Historic and cultural sites are appealing to many tourists, and sustainable tourism promotes socio-cultural authenticity while ensuring the optimal use of natural and environmental resources [43].
Although tourism performance has been widely researched in the way of arrivals, receipts and its contribution to GDP, the relationship of tourism performance to tourism endowments, resources or facilities has not been widely analyzed. Empirical analysis is especially missing in relation to the African continent. The present study aims at bridging this research gap, focusing on the relationship between international tourism revenues and the facilitating factors of the tourism sector in four Eastern African countries. The following research questions are raised:
Q1:
Do the natural and cultural endowments of the analyzed countries contribute significantly to the performance of tourism in the analyzed countries?
Q2:
Do the transport and tourism services enhance tourism receipts and arrivals?
Q3:
Does the revealed comparative advantage of the tourism sector (RCA) reveal the same tendencies as the facilities of the tourism industry (TTCI)?
The motivation for Q2 and Q3 is that RCA (described later in detail) describes the actual performance of the sector, whereas the TTCI reflects the sector’s development possibilities. Our opinion is that although Eastern Africa is rich in cultural and natural attractions, countries in this region cannot fully utilize their endowments, which is partly due to their low level of transport and tourism services, which may make it difficult for international tourists to access the best heritage destinations. Therefore, even if the heritage sites are attractive and highly valued themselves, they cannot be utilized to their capacities and cannot draw as large volumes of international arrivals and receipts to these countries, compared to more developed countries with similar endowments, which is reflected in the relatively moderate RCA values in Eastern Africa.
The structure of this paper is as follows: Section 2 describes the methodology and the database used for the analysis. Section 3 presents the results of the statistical analysis, while Section 4 discusses and explains our findings, reflecting on our research questions. Finally, Section 5 draws conclusions and explains the limitations and possible further research directions.

2. Materials and Methods

2.1. Methodology

This paper analyzes the competitiveness of the tourism sector in 4 Eastern African countries. To measure competitiveness, two approaches were used. The first one is the concept of destination competitiveness as measured by the Travel and Tourism Competitiveness Index (TTCI) [44] that measures the factors that contribute to the success of the tourism sector in a country. The second approach measures the competitiveness as revealed in the tourism revenues of the country, measured by the index of revealed comparative advantage (RCA) [45], explained in more detail below.
The TTCI measures the tourism development potential of a destination. The success of countries in the travel and tourism sector differs widely depending on their tourist appeal, endowments, infra- and superstructure and many other aspects of the society and economy [46]. This differentiation is reflected in the concept of tourism competitiveness, defined in the following way by OECD: “Tourism competitiveness for a destination is about the ability of place to optimise its attractiveness for residents and non-residents, to deliver quality, innovative, and attractive tourism services to consumers and to gain market shares on the domestic and global marketplaces, while ensuring that the available resources supporting tourism are used efficiently and in a sustainable way.” ([44] p. 7). The concept has been quantified by the Travel and Tourism Competitiveness Index (TTCI), based on 14 pillars of the country’s tourism assets, visitor accommodation, transport to, from and within the country, infrastructure components, the receptiveness of local populations to tourists, the skills of the range of officials and employees in the tourism sector, and the safety and security of the destinations ([45] p. 5). Data on the TTCI index and its components (pillars) were collected from [23]. As these reports are published only every second year, our data time series contain 7 years altogether (2005–2017), as the 2019 database (i.e., the report published in 2021, containing data until 2019) does not contain the relevant data for Ethiopia. Therefore, to use a full 4-country dynamic analysis, we had to restrict the time span for the mentioned period, so that Ethiopia, being the largest country in the Eastern African area, could be analyzed together with the other 3 countries. The TTCI approach has been widely used to measure destination competitiveness, and to assess its contribution to economic development in general. Krstic et al. [47] used the TTCI and its pillars to assess the global economic competitiveness of sub-Saharan countries and identify the relationship between the pillars of TTCI and the overall economic competitiveness of these countries. They found that only natural resources were significant contributors to economic development. González-Rodríguez et al. [48] analyzed 137 countries to identify the relationship between tourism competitiveness measured by international tourism arrivals and the comparative advantages of destinations measured by TTCI and revealed that countries with a major comparative advantage do not necessarily achieve high competitiveness.
One of the most commonly used competitiveness measures is the revealed comparative advantage (RCA) introduced by Balassa in 1965 [49], although it has been extensively modified and adjusted for problems related to its relative order [50]. For this reason, the normalized revealed comparative advantage (NRCA) was introduced by Yu et al. in 2009 [50]. However, RCA is still widely used for comparing countries, and we applied this measure to assess the comparative advantage of tourism in Eastern Africa.
Regarding competitiveness in the travel and tourism sector, relatively few analyses have been carried out with RCA or similar measures [51,52], especially for the African continent. Some of the most recent empirical studies about Africa and Asia are [53,54,55,56,57].
The computation of RCA is as follows [49,50]:
RCAiT = (EiT/Ei)/(EwT/Ew) = (EiT/EwT)/(Ei/Ew)
where
  • EiT: the export value of the tourism sector in country “i”;
  • Ei: the export value of all products and services in country “i”;
  • EwT: the export value of the tourism sector in the world (sum of all countries);
  • Ew: the total world export value of all products and services (sum of all countries).
Thus, a country is competitive in the tourism sector if its RCA value is higher than 1. According to Jackman et al. ([52] p. 4), countries can be classified by their RCA values, such as:
  • Countries with 0 < RCA ≤ 1 are without comparative advantage;
  • Countries with 1 < RCA ≤ 2 are of slight comparative advantage;
  • Countries with 2 < RCA ≤ 4 are of average comparative advantage;
  • Countries with RCA > 4 are of strong comparative advantage.
Our analysis is focused on identifying the relationship between the factors of destination competitiveness as measured by the pillars of TTCI, and the sector’s economic competitiveness measured by its export-based RCA indicator, for the period from 2005 to 2017, for the 4 Eastern African countries. The reason of this analysis is that although these countries are rich in natural and cultural attractions with tourist appeal, the utilization of these resources in the global tourism market is thought to be well below their capacity [2,3]. The components of TTCI evaluate the destination’s endowments of natural and cultural heritage. As the success of tourism also depends on the basic tourism services—i.e., food and accommodation—and transport infrastructure, these factors were also incorporated into the analysis. The analysis is expected to reveal how this could be enhanced, and how to improve tourism performance and its contribution to the region’s overall economic development. To our best knowledge, this kind of comparison has rarely been made. Recently, similar analyses were conducted about Lithuania and the Baltic states [58], the post-Soviet states [59] and the ASEAN countries [60].
For this purpose, the following analyses were carried out: correlation analysis between RCA and the components of TTCI, and panel regression with RCA as the dependent variable, and TTCI or its main components as predictors (fixed factors) with time used as a random factor. The correlation analysis served to identify relationships between the indicators of tourism performance (international arrivals, receipts and RCA) and indicators of natural and cultural heritage of the Eastern African countries, and their transport and tourism services. These analyses answered our first and second research questions. The computation of the RCA index time series and the application of panel regression were aimed at answering the third research question, and revealing how the mentioned components of TTCI contribute to the RCA-measured competitiveness of the analyzed countries in the global tourism marketplace. Three panel models were set up, with RCA as the dependent variable. The predictor variables of fixed effects were: TTCI in the first model, the natural and cultural heritage components of TTCI together with tourism infrastructure in the second model, and natural and cultural heritage components together with tourism infrastructure and ground transport infrastructure in the third model. The year was used as the random factor in each model structure.
The analysis was carried out using MS-EXCEL and IBM-SPSS v.27. Figure 3 gives a summary of the applied methodology.

2.2. Data

The dataset was collected from the relevant reports published by WTTC.
The World Travel and Tourism Reports [23] give the values of international tourist arrivals, international tourism receipts and tourism total economic contribution to GDP from Tourism Satellite accounts, as well as the components of the TTCI indicator [23].
The TTCI components are grouped as below (referring to the category used after 2013)—with values ranging from 1 (worst level) to 7 (best level). The actual detailed content of these index values is available in [23]:
  • P1_BusEnv: Business environment
  • P2_SafSec: Safety and security
  • P3_Health: Health and hygiene
  • P4_HumRes: Human resources
  • P5_ICT: ICT infrastructure /ICT readiness
  • P6_PriTu: Prioritisation of travel and tourism
  • P7_Open: International openness
  • P8_PriceC: Price competitiveness
  • P9_EnvSus: Environmental sustainability
  • P10_AirInf: Air travel infrastructure
  • P11_GrouInf: Ground travel infrastructure
  • P12_TourInf: Tourism services infrastructure
  • P13_NatRes: Natural resources
  • P14_CultRes: Cultural resources
As well as the above pillars, two component indicators were also considered, from P13 and from P14, respectively:
  • NatWHS—the number of natural World Heritage Sites, a component of P13
  • CultWHS—the number of cultural (built) World Heritage Sites, a component of P14.
The data about arrivals and receipts are also presented in the same reports and were included in our analysis as:
  • Arriv: International tourism, number of arrivals
  • Receipt: International tourism, receipts (current USD)
  • RecPct: International tourism, receipts % GDP
Finally, the value of the revealed comparative advantage of tourism is computed as the total share of tourism receipts in the export of the country divided by the same share in the world, i.e.,
  • RCA: the revealed comparative advantage of tourism.

3. Results

3.1. The Study Area

Ethiopia, Kenya, Tanzania and Uganda are the four largest countries in Eastern Africa according to population numbers. Together they make up more than 61% of the total population of Eastern Africa, with Ethiopia having 26.3%, Tanzania 13.7%, Kenya 11.8% and Uganda 9.8% in 2018 [61]. They are also major tourism destinations, altogether making up 70% of all international tourist arrivals to Eastern Africa in 2018, and 78% in 2019 [24,25].
Tanzania is the largest country in East Africa, lying close to the equator on the east coast. It is one of the best safari destinations, is the home of the highest mountain in Africa, Mount Kilimanjaro, and has 21 national parks. Tanzania is exceptionally endowed with cultural heritage resources, thus offering a genuine cultural mosaic and diversity that appeal to many tourists [62]. As well as nature-based and wildlife tourism, beach tourism is also a popular tourist product [63]. The country possesses several World Heritage Sites, three of which are significant cultural heritage sites (Kondoa Rock-Art Sites, Ruins of Kilwa Kisiwani and Ruins of Songo Mnara, and the Stone Town of Zanzibar) [64]. Cultural tourism relies both on tangible and intangible cultural heritage [65], and contributes significantly to improving the livelihoods of people in Tanzania [65,66]. Cultural tourism and community-based tourism (CBT) are significant in rural livelihoods [65,66,67], and the role of CBT should be strengthened [67]. Cultural tourism can have negative impacts if the economic benefits create a social distance between the generations of the local community [68].
Uganda is a landlocked country in Eastern Africa. Its size is 241,037 km2 of which 27% is occupied by lakes, rivers and swamps, and 11% is covered by wildlife protected areas. Variations in rainfall, temperature and extreme events pose a threat to the survival of both humans and biodiversity. Its main tourism attractions are nature-based activities, such as wildlife watching and adventure tourism [62,63]. Uganda’s cultural heritage is significant, including tangible and intangible heritage. The UNESCO list contains three World Heritage Sites, among them the famous cultural heritage of the Tombs of Buganda Kings at Kasubi (on the list of World Heritage in Danger), and six intangible heritages, including dance, music, oral tradition, barkcloth making, the cleansing ceremony and traditions [69]. The conservation of cultural heritage contributes to income gained from tourism activities, which in turn can contribute to the safeguarding of cultural heritage. It is also important to find ways for improved and increased community involvement [70]. The local community’s attitude toward tourism and tourists has a direct impact on the success of a viable cultural tourism development [71].
Ethiopia has a rugged and mountainous topography with altitudes ranging from 4620 m (the highest peak) to lowlands at 110 m below sea level. The country’s economy mainly depends on agriculture that contributed 37.6% to the national GDP in 2021 [72]. In total, 40% of its huge population has placed a great burden on the sustainability of almost all types of natural resources, leading to the serious degradation of land, water, forest, rangeland and wildlife resources [73]. Ethiopia is well endowed with tourism attractions, including national parks, rich wildlife, and cultural and historic sites [63,74]. Of the four analyzed countries, Ethiopia has the most World Heritage Sites with significant cultural value (Aksum, Harar Jugol, Tiya, Rock-Hewn Churches, Konso Cultural Landscape, etc.), and several more properties can be found on the tentative list [75]. Heritage sites are major assets of tourism [76] and culture is a motivating factor for visitation; however, to sustain a healthy cultural tourism, a sustainable cultural tourism policy is essential [76]. By improving destination competitiveness to increase tourism’s contribution to the local economy, more income and more employment opportunities could be achieved [27].
Kenya has a total area of about 582,650 km2 of which about 2.3% is covered by water. About 80% of the country lies in the semi-arid to very arid zones, mainly inhabited by pastoralists and agro-pastoralists. These areas also host a significant proportion of the country’s wildlife, and 90% of the national parks, sanctuaries and game reserves [77]. Kenya has a rich wildlife and ecosystems of forests, vast savannah woodlands, mountain peaks down to the bottom of the Great Rift Valley, and many protected areas, national parks, national reserves or forest reserves, which are the basis for the growing wildlife tourism of the country [22]. As well as nature-based tourism, the country is a popular beach tourism destination [63]. Kenya’s agriculture is also a significant part of the national economy with a 22% contribution to the GDP in 2021 [72]. Kenya’s World Heritage properties include four of cultural significance (Forst Jesus, Mombasa; Lamu Old Town; Sacred Mijikenda Forests; and Thimlich Ohinga Archaeological Site) [78]. The development of cultural tourism should contribute to socio-economic development among the indigenous people, who, quite often, are unable to take part in the decision-making process concerning cultural tourism projects, as was observed in the case of the Maasai people [79]. In recent research, the inadequate development of the cultural product was established as a major weakness in Kenya’s tourism plan, and the authors suggested that the cultural heritage tourism product would ease the overdependence on beach and wildlife tourism for sustainability and leverage [80].
The economies of the four countries depend on tourism to a significant extent, but despite their rich natural and cultural endowments, tourism is not fully utilized to its capacity. These countries have experienced steady increases in tourist numbers and tourism revenues from foreign tourism, but the share of tourism in GDP has actually decreased somewhat from 2004 to 2018, indicating underutilized tourism resources in the area, as was shown formerly in Table 1. Although Kenya and Tanzania are both beach tourism destinations too, the main interests of tourists coming to the region are around wildlife-related activities and cultural tourism.
As the descriptive statistics in Table 2 reveal, the analyzed countries have only medium level TTCI values (3.02 to 3.90 during the analyzed years), and the tourism infrastructure and transport facilities are at a low to medium level. The natural and cultural resources are somewhat better evaluated, having 6.1 and 5.1 maximum values, respectively, but the average values indicate that the endowments are underutilized. The RCA values range from 2.11 to 5.97, pointing to an average or strong revealed comparative advantage of these countries, which is reflected in the rather high values of arrivals, above 1 million per year on average by country.
To facilitate statistical analyses the variables were tested for normality (Table 3). Only the normality of RCA and P14_CultREs were rejected by the Shapiro–Wilk test, but the Kolmogorov–Smirnov test accepted their normality.
In Ethiopia, the majority of tourists arrived from Africa and Europe, up to 2019, with a modest share of the Americas and the Asian and Pacific region. In Kenya, up to 2017, the European market provided most of the arrivals; however, since then, the share of the African continent has been growing steadily, while the share of Europe has been shrinking. In Tanzania, African and European tourists dominate the field, and their shares are quite steady, while in Uganda, African tourists are in the overwhelming majority, and the moderate share of Europeans is slowly decreasing. The latter two countries have a rather low proportion of tourists coming from the Americas and from the East Asian and Pacific region (Figure 4).

3.2. RCA Analysis of International Tourism Receipts

The RCA was computed for tourism for the selected four countries, with the following results (Table 4 and Figure 5): the four Eastern African countries have a very strong comparative advantage in tourism, as the RCA values vary between 6.6155 (Ethiopia, 2018) and 2.065 (Kenya, 2016). While Ethiopia shows a slightly increasing trend, Kenya’s values slowly decrease, and Tanzania and Uganda fluctuate in a rather stable range between 3 and 4.

3.3. Relationship between RCA and TTCI and Components

As Table 5 shows, the TTCI value significantly correlates with GDP per capita (positive), with the RCA (negative), with ground transport infrastructure (positive) and with natural resources (positive). The RCA significantly correlates with GDP per capita (negative), with the share of tourism receipts in GDP (positive), with the TTCI (negative) and with tourism infrastructure (negative). The negative correlation between the TTCI and the RCA indicates that the revealed competitive advantage achieved by tourism receipts does not coincide with high tourism destination competitiveness. Thus, tourism endowments and facilitating factors do not translate to high levels of tourism receipts in comparison to the rest of the world, but rather, the opposite seems to be valid. Another interesting feature is that more affluent countries (of higher per capita GDP) seem to be less successful in terms of the RCA, while they are associated with better TTCI values, as well as with ground transport infrastructure and tourism infrastructure. Finally, it is worth noting that higher numbers of international arrivals do not lead to higher shares of tourism receipts, nor to higher RCA, just the opposite—i.e., arrivals do not necessarily generate higher spending in the destination areas. As country-wise correlations show, there is no significant relationship between the TTCI and the RCA per country, but the negative correlation is revealed only with the pooled dataset.
The panel regression provides a deeper insight into the relationship between the RCA and the TTCI—or its heritage-related components (Table 6). The simplest panel regression (Model 1) revealed a significant negative impact of the TTCI as a predictor of a fixed effect, and the year as a random predictor did not have any significant effect.
Model 2 included the components of the TTCI, i.e., natural and cultural heritage components and tourism infrastructure, as predictors. In this model, cultural resources did not have any significant impact on the RCA, but natural resources showed a considerable positive impact, as well as tourism infrastructure, though the negative significant impact of their interaction somewhat dampened their independent positive effect on the RCA.
Model 3 added ground transport infrastructure to the analysis. In this model structure, cultural resources had a significant negative impact on the RCA, and natural resources showed a considerable positive impact, as well as ground transport infrastructure. The interactions of natural resources and of cultural resources with the transport infrastructure factor were significant, with their signs being just opposite to the independent effects, i.e., negative for natural resources and positive for cultural resources. In this context, the tourism service infrastructure showed no effect.
There were no significant random effects of either the year or the country in any of the models.

4. Discussion

The Tourism and Travel Competitiveness Index (TTCI) measures the factors that make a country attractive for tourism development—i.e., the endowments, infrastructure and institutional system that can generate a successful tourism industry in a country. However, this does not mean that tourism industry is very successful at present but rather points at its potential for development. Ultimately, however, as tourism is one of the fastest developing industries in the world, a high TTCI should sooner or later lead to a profitable and successful tourism sector. The success of an industry in the international market is measured by the revealed comparative advantage (RCA) index; therefore, it is reasonable to expect that a developed tourism sector may be reflected in a high RCA and a high TTCI.
Our analysis addressed three particular research questions.
The first focused on revealing the impact of natural and cultural endowments on tourism performance. The correlations of the indicators of such resources with international arrivals, receipts or with the RCA are inconclusive; therefore, these resources do not imply a successful tourism industry. This is somewhat against general expectations.
The second question, namely, the impact of transport and tourism infrastructure on tourism performance, partly explains these strange results, as they are supposed to be important components of the accessibility of destinations for tourists. The correlation analysis showed a strong positive relationship between tourism infrastructure and international arrivals, and panel regressions showed the positive impacts of tourism and transport infrastructures on the RCA, which reflects international tourism revenues. In Africa, and particularly in Eastern Africa, some of the most important endowments are the natural and cultural heritage, i.e., the landscape, wildlife, cultural traditions and built attractions. These are included in the TTCI, together with the quality of the general and transport infrastructure, tourism superstructure, and health and education service, and the development of the tourism-related business sector as described in [23]. Previous studies [81] have indicated the priority of tourism infra- and superstructure over natural and cultural appeal in the TTCI, but this may vary by destination. In Africa, these factors are not particularly strong; therefore, with targeted development, natural and cultural attractions may play a more important role. As former studies [48] showed, relying on the TTCI results of 137 in 2019, the average score of natural resources was 3.15, much smaller than in our case, and of cultural resources was 2.23, which is slightly larger than in our case. Tourism service infrastructure and ground transport infrastructure also scored at least 1 point higher on average than in our case. As [62] indicates, the overall TTCI was considerably lower in sub-Saharan countries than in our countries. Our correlation analysis showed a strong positive correlation between the TTCI and ground transport infrastructure, and between the TTCI and the natural resources of the analyzed countries. Tourism infrastructure and cultural resources, however, were unrelated to the TTCI—indicating that the tourism potential of Eastern Africa mainly depends on its rich natural endowments, and on the accessibility of the major attractions by ground transport facilities. The panel regression models reveal that the natural and cultural resources of the analyzed countries have different impacts on the RCA. The natural resources have a positive significant impact, i.e., better natural endowments contribute to a higher RCA in both Model 2 and Model 3. Cultural endowments have a more complicated impact. When the impact of tourism infrastructure was taken into the model without transport infrastructure (Model 2), cultural endowments were found to be irrelevant for the RCA. On the other hand, when ground transport infrastructure was also included as a predictor (Model 3), cultural resources showed a strong negative impact. Tourism infrastructure was shown to have a positive effect only when it was analyzed without ground transport infrastructure, but in Model 3, it became insignificant when transport was also considered with significant positive impacts on the RCA. This indicates that tourism services are less important than transport facilities, which is reasonable when the major attractions are in remote areas, as is the case with natural heritage. The interaction of ground transport infrastructure with natural resources showed a negative effect, diminishing somewhat the independent positive impacts of these two factors. Ground transport infrastructure interacted with cultural resources, adding a significant positive impact on the RCA, which means that cultural resources can have a positive effect on the RCA only if the transport infrastructure is good. Our results show somewhat similar findings to those of [47], in which natural resources were also found to be a significant positive factor in general economic competitiveness in sub-Saharan Africa, together with tourism infrastructure, while cultural resources were insignificant. As [56] mentions, natural resources are the main driving factors for Chinese tourists travelling to South-East Asia, revealed in RCA values too. As both Model 2 and Model 3 underline, natural resources considerably enhance the RCA values of competitive advantage measured by the share of tourism receipts, and the availability of tourism services and transport facilities are also positive factors. The impact of cultural resources is, at the same time, more controversial, as their utilization in income generation may depend on convenience factors, such as transport, food and accommodation services.
Our third research question aimed at revealing whether the RCA and TTCI show the same pattern, i.e., whether success in the tourism market parallels the facilities of the destinations. Considering previous results in this context, Le [60] also assessed the RCA and the TTCI and its components for selected Asian countries, and they concluded that tourism exports are driven by different factors for different countries, with natural and cultural resources being the leading ones for some, while infrastructure is the leading factor for others. However, the authors assessed the TTCI and the RCA separately, without making any attempts to assess their connections. Our analysis showed that the four analyzed countries have very high RCA values based on tourism revenues. Other studies [59,60] showed that similarly high values are rather rare in Asia and occur mostly with outstanding rich natural resources. The tourism potential, however, does not readily translate into higher visitor numbers, higher revenues and higher revealed comparative advantages. In our research, the TTCI does not correlate with the number of international visitors, and its correlation with the RCA—based on tourism receipts—is not significant when analyzed countrywide, with it being significantly negative when data are pooled. This means that relatively fewer tourism revenues are collected in destinations where there are better tourism opportunities. This is also reflected in the first panel regression with the TTCI being the predictor and the RCA the dependent variable. The impact of the TTCI was found to be negative on the RCA, meaning that a smaller TTCI leads to a higher RCA and vice versa. This result is rather confusing, and the explanation may be found in the complex structure of the TTCI, with it being the weighted average of many components. However, [58] also found differences in the ranking of Baltic states by RCA and by the TTCI between 2002 and 2011. Recently, [48] also underlined that the TTCI as an indicator of tourism potential does not coincide with the efficiency of tourism performance, as many countries fail to exploit their endowments. Their results were based only on 2019, and our analysis reveals similar results in a 13-year-long time scale.
As a summary, we can say that the TTCI may not capture all the factors that make a less developed African country appealing to the global tourism market. As the breakdown of the TTCI to its components reveals, the appeal of cultural heritage, in particular, seems to be undervalued. The core attraction of these countries is nature-based tourism, with exotic wildlife flourishing in wild, nomadic environments, and this can considerably contribute to tourism receipts and the revealed competitive advantage. However, as far as cultural heritage is concerned, the transport and tourism infrastructure may be of more relevance in utilizing these resources. However these convenience elements of the developed tourism industry are simply not available to easily access the most attractive cultural sites in Eastern Africa [82]. The importance of natural and cultural heritage in Eastern Africa deserves a serious reconsideration as the examples of other countries in developing regions show [83,84], especially in view of sustainable tourism development.
Currently, as former studies also underline [48,60], a considerable gap exists between the tourism capacities (components of the TTCI) and the reality of tourism performance (as measured by the RCA), which should be bridged, and the present study is a step in this direction.

5. Conclusions

The relationship between tourism and national income generation is quite complex. It is dependent on many factors, including tourism service facilities and transport infrastructure, as well as natural and cultural attractions. The natural and cultural heritage of a country is the foundation for attracting tourists, but without accessibility and food and accommodation services, the tourist numbers and tourism receipts remain moderate. Governments usually make great efforts to advertise their attractions and service facilities to make their country competitive in the global tourism market. Arrivals may often be motivated by promotions about the landscape, wildlife and local unique culture, but the generated visitor numbers may not directly result in competitive tourism revenues.
The tourism endowments of the assessed countries, measured by the natural and cultural heritage components of the TTCI, indicate that natural resources are important enough to be reflected in a higher revealed comparative advantage, i.e., competitive tourism revenues, while cultural heritage cannot be utilized in the same way. Tourists coming for natural attractions such as wildlife watching, or to enjoy the outstanding, exotic landscape, are often prepared for rough transport and accommodation services, usually viewing these as part of the adventure. However, tourists coming with the motivation of cultural heritage visits, tend to associate cultural heritage sites with more developed, civilized environments, located in the vicinity of urban areas, and generally better serviced by transport, accommodation and food provisions. Therefore, the lack of these may influence cultural tourists negatively, driving them toward cultural destinations elsewhere that are better serviced.
Tourism services and transport facilities also positively influence international tourism receipts leading to competitive advantage. Better infrastructure often initiates longer stays and a willingness to pay more for the higher quality service provisions. Higher tourism spending in the destination leads to higher direct financial benefits for the local tourism industry, and contribute to higher tax payments from international tourism chains operating in the destination. Induced tourism revenues for non-tourism industries are also enhanced. Therefore, to become competitive in the cultural tourism market, the tourism industry has to provide better services than what is necessary for the destinations relying on natural attractions, although natural heritage destinations also benefit from infrastructural developments. These facts have important policy implications: first, that natural resources should be managed in a sustainable way to preserve the natural heritage in the long run. Second, that transport and tourism service facilities are important factors for international tourist flows; therefore, their maintenance and development cannot be neglected even in the remote, distant regions of exquisite natural attractions. Third, cultural resources of the region do not currently contribute as much to tourism revenues as they should, and further research is needed to identify the reasons for this fact, and the methods to fully utilize its potential. Africa in general, and Eastern Africa in particular, is rich in natural and cultural heritage, and the exploitation of these resources has been viewed as the main way out of poverty. The quality of the basic tourism-related services should thus be a crucial element in making these countries more competitive in the global tourism market, and this requires investment in physical infrastructure, as well as in human resource development and in the international promotion of the major destinations of the region.
The limitations of the present study include the relatively short time series of 7 years per country, due to the availability of TTCI data series. Another weakness may be the limited set of predictor variables—mainly the variables describing the natural and cultural heritages of the countries. A further possible development may be the analysis at not only national level but at the level of sub-national regions, although data availability makes this difficult at the moment. Finally, the analysis could be further refined by adding control variables to the models that incorporate the general economic and social conditions of the countries separately.

Author Contributions

Conceptualization, Z.B., A.S.Y. and G.B.; methodology, Z.B., A.S.Y. and G.B.; software, Z.B.; validation, A.S.Y. and G.B.; formal analysis, Z.B.; investigation, Z.B., A.S.Y. and G.B.; resources Z.B., A.S.Y. and G.B.; data curation, Z.B. and A.S.Y.; writing—original draft preparation, Z.B., A.S.Y. and G.B.; writing—review and editing, Z.B. and G.B.; visualization, Z.B.; supervision, Z.B. and G.B.; project administration, Z.B. and G.B.; funding acquisition, no funding received. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data were taken from publicly accessible secondary databases, as referred to in the text.

Acknowledgments

The publication of the research was supported by the Doctoral School of Economics and Regional Sciences of the Hungarian University of Agriculture and Life Sciences, Gödöllő, Hungary.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The study area. Source: https://en.wikivoyage.org/wiki/East_Africa (accessed on 17 August 2023).
Figure 1. The study area. Source: https://en.wikivoyage.org/wiki/East_Africa (accessed on 17 August 2023).
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Figure 2. The natural and cultural heritage bond. Source: Authors own construction based on [37].
Figure 2. The natural and cultural heritage bond. Source: Authors own construction based on [37].
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Figure 3. Graphical scheme of the methodology. Source: Authors’ own construction.
Figure 3. Graphical scheme of the methodology. Source: Authors’ own construction.
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Figure 4. Average share of regions in international arrivals, 2001–2020. Source: Authors’ own computation based on data from World Development Indicators, World Bank Databank, https://databank.worldbank.org/source/world-development-indicators#, accessed on 31 July 2023).
Figure 4. Average share of regions in international arrivals, 2001–2020. Source: Authors’ own computation based on data from World Development Indicators, World Bank Databank, https://databank.worldbank.org/source/world-development-indicators#, accessed on 31 July 2023).
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Figure 5. The dynamics of the RCA by country, 2000–2029. Source: authors’ own computation.
Figure 5. The dynamics of the RCA by country, 2000–2029. Source: authors’ own computation.
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Table 1. Economic and tourism indicators for Ethiopia, Kenya, Uganda and Tanzania, 2005 and 2017.
Table 1. Economic and tourism indicators for Ethiopia, Kenya, Uganda and Tanzania, 2005 and 2017.
EthiopiaKenyaUgandaTanzania
Year20052017200520172005201720052017
GDP, billion USD48.9215.178.3211.141.885.460.8134.2
Total population million77.5108.235.848.927.940.139.456.3
Area, thousand km211291129569569200200886886
International arrivals, million0.2270.9331.4791.4490.4681.4020.6131.327
Int’l tourism receipts, billion USD0.5332.5000.9691.5600.3820.9540.8352.270
Tourism receipts as % of GDP1.091.161.240.740.911.121.371.69
Tourism value-added as % of GDP6.786.3012.208.809.205.909.7010.60
TTCI (score on 1–7 scale)3.33.023.623.633.563.193.863.43
Natural resources (score on 1–7 scale)4.23.014.54.455.13.76.14.75
Number of cultural WHS67141123
Number of natural WHS11232233
Protected areas, as % of total land area11.0611.0611.4011.4048.2048.2017.8017.80
Source: Authors’ own computation based on data from World Development Indicators, World Bank Databank. https://databank.worldbank.org/source/world-development-indicators# (accessed on 30 July 2023). and [23,24,25].
Table 2. Descriptive statistics of the main variables (source: authors’ own computation).
Table 2. Descriptive statistics of the main variables (source: authors’ own computation).
NMinimumMaximumMeanStd. Dev.
GDP per capita (USD)28305.981550.20868.29346.47
Arriv, (persons)28227,0001,823,0001,008,036440,436
Receipt (USD), million25562.1462525.1871616.440618.108
RecPct (%)251.915.783.761.018
RCA282.115.9703.7801.117
TTCI283.0203.9003.402860.219981
P13_NatRes282.996.104.5660.8562
P14_CultRes281.255.001.9631.009
P12_TourInf281.303.302.1510.5950
P11_GrouInf282.103.402.7790.3352
Table 3. Normality tests for the main variables (source: authors’ own computation).
Table 3. Normality tests for the main variables (source: authors’ own computation).
Kolmogorov–SmirnovShapiro–Wilk
StatisticdfSig.StatisticdfSig.
P11_GrouInf0.151220.2000.952220.352
P12_TourInf0.132220.2000.953220.357
P13_NatRes0.178220.0680.943220.230
P14_CultRes0.166220.1190.895220.024
TTCI0.165220.1230.939220.191
Arriv0.115220.2000.961220.501
RCA0.173220.0850.898220.027
Table 4. Revealed comparative advantage (RCA) of tourism receipts, 2000–2019 (source: authors’ own computation).
Table 4. Revealed comparative advantage (RCA) of tourism receipts, 2000–2019 (source: authors’ own computation).
Tourism RCAEthiopiaKenyaTanzaniaUganda
20002.93772.56153.9806
20013.18462.53685.05043.8958
20023.53732.30044.85033.9801
20034.14672.66254.68263.4442
20044.30352.95184.60973.7447
20054.30142.82444.37533.8574
20064.84853.31344.77353.3579
20075.02523.61294.99182.7907
20085.94772.96084.07043.0961
20095.03852.35053.57273.1452
20105.12592.99383.33323.8390
20115.95923.21763.25143.9532
20125.67353.07223.47304.0267
20135.97462.72283.74593.1813
20145.18012.43663.75593.1493
20155.42402.15103.33863.1716
20165.03562.06543.52773.2153
20175.31172.10683.82132.6352
20186.61552.19314.21833.6489
20196.30802.08343.68573.0768
Table 5. Correlations between variables (source: authors’ own computation).
Table 5. Correlations between variables (source: authors’ own computation).
Spearman’s RhoArrivGDP per CapReceiptRecPctRCATTCIP11_GrouInfP12_TourInfP13_NatRes
Arriv1.0
GDP per Cap0.917 **1.0
Receipt0.2190.1081.0
RecPct−0.277−0.3150.506 **1.0
RCA−0.639 **−0.764 **0.3900.593 **1.0
TTCI0.3610.542 **−0.0240.150−0.422 *1.0
P11_GrouInf0.3680.466 *0.063−0.119−0.3600.607 **1.0
P12_TourInf0.685 **0.744 **0.093 *−0.326−0.581 **0.2340.3441.0
P13_NatRes−0.0380.197−0.2140.315−0.1370.722 **0.276−0.0811.0
P14_CultRes−0.447 *−0.393 *0.1270.2230.2700.020−0.052−0.2470.066
by countyEthiopiaKenyaTanzaniaUganda
TTCI vs. RCA −0.3560.2520.3570.334
**. Correlation is significant at the 0.01 level, *. Correlation is significant at the 0.05 level (2-tailed).
Table 6. Panel regression results with RCA as dependent variable (source: authors’ own computation).
Table 6. Panel regression results with RCA as dependent variable (source: authors’ own computation).
Information CriteriaModel 1Model 2Model 3
Akaike’s (AIC) 90.060 66.175 63.732
Schwarz’s Bayesian (BIC) 92.652 75.501 65.914
Fixed effectsEstimateStd. ErrSig.EstimateStd. ErrSig.EstimateStd. ErrSig.
TTCI−2.017470.849160.025
P13_NatRes 1.260940.209350.0002.44090.62760.001
P14_CultRes −0.684770.412630.109−2.458370.907360.013
P12_TourInf 1.955400.499160.001−0.334330.274620.236
P12_TourInf × P13_NatRes −0.650430.150300.000
P12_TourInf × P14_CultRes 0.354840.195360.082
P11_GrouInf 1.578540.612090.018
P11_GrouInf × P13_NatRes −0.863080.220570.001
P11_GrouInf × P14_CultRes 0.876990.314630.011
Residual1.036850.287570.0000.239780.070250.0010.261320.085390.002
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Bacsi, Z.; Yasin, A.S.; Bánhegyi, G. Tourism Competitiveness in Eastern Africa: RCA and TTCI. Heritage 2023, 6, 5997-6015. https://doi.org/10.3390/heritage6090316

AMA Style

Bacsi Z, Yasin AS, Bánhegyi G. Tourism Competitiveness in Eastern Africa: RCA and TTCI. Heritage. 2023; 6(9):5997-6015. https://doi.org/10.3390/heritage6090316

Chicago/Turabian Style

Bacsi, Zsuzsanna, Abdi Shukri Yasin, and Gabriella Bánhegyi. 2023. "Tourism Competitiveness in Eastern Africa: RCA and TTCI" Heritage 6, no. 9: 5997-6015. https://doi.org/10.3390/heritage6090316

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