Globally, the tourism industry is recognised as one of the fastest growing industries, generating high revenues and creating a vast number of job opportunities. In South Africa, this is no different and, in recent years, the tourism industry has outshone the country's gold exports therefore claiming its position as the fourth highest earner of foreign exchange to date. Yet the industry is still to receive the attention it deserves from conventional economics. This research aimed to fill this gap in South Africa by providing an understanding on the determinants of international tourism demand for South Africa. The first objective of the study was to provide a broad overview of the tourism industry of South Africa. The discussion focused on the supply and demand sides of tourism which, in turn, are divided into the domestic and international tourism markets. There has been a high growth, especially in the international market since 1994 and, while domestic and international markets continue to grow, seasonality remains an issue. Tourism has a significant impact on economic activity, employment, and the balance of payments and therefore the industry has great potential. The second objective was to create a theoretical understanding on the different factors that could determine the international demand for the tourism product. From this discussion it was found that there are various economic and non-economic factors that are believed to have an influence on tourism demand. Income, prices, transport cost, and the exchange rate are amongst the favourite economic variables with travel time, population, marketing expenditure, climate, and capacity being the more popular noneconomic factors. Among these, certain threats were also identified that could have harmful impacts on tourism growth. The third objective and main aim of the study was to determine which of the factors identified earlier determine the demand for international tourism to South Africa. This was done through an empirical investigation. Data from all the continents were used to attain an international perspective on tourist arrivals (tourism demand). The results indicated that capacity and climate factors determine tourism demand in the short term with income and transport cost influencing South Africa as a tourism destination in the long term. The last objective was to determine whether certain events or disasters that take place globally have a negative influence on tourism demand to South Africa. The event that was looked as was the terror attacks on the United States in September 2001. It was found that although the overall tourism activity of the world became stagnant during this period, the effect was not that considerable in South Africa's tourism arrivals. Tourism in countries such as the United Sates, on the other hand, has still not recovered fully after this event. / Thesis (M.Com. (International Commerce))--North-West University, Potchefstroom Campus, 2007.

Globally, the tourism industry is recognised as one of the fastest growing industries, generating high revenues and creating a vast number of job opportunities. In South Africa, this is no different and, in recent years, the tourism industry has outshone the country's gold exports therefore claiming its position as the fourth highest earner of foreign exchange to date. Yet the industry is still to receive the attention it deserves from conventional economics. This research aimed to fill this gap in South Africa by providing an understanding on the determinants of international tourism demand for South Africa. The first objective of the study was to provide a broad overview of the tourism industry of South Africa. The discussion focused on the supply and demand sides of tourism which, in turn, are divided into the domestic and international tourism markets. There has been a high growth, especially in the international market since 1994 and, while domestic and international markets continue to grow, seasonality remains an issue. Tourism has a significant impact on economic activity, employment, and the balance of payments and therefore the industry has great potential. The second objective was to create a theoretical understanding on the different factors that could determine the international demand for the tourism product. From this discussion it was found that there are various economic and non-economic factors that are believed to have an influence on tourism demand. Income, prices, transport cost, and the exchange rate are amongst the favourite economic variables with travel time, population, marketing expenditure, climate, and capacity being the more popular noneconomic factors. Among these, certain threats were also identified that could have harmful impacts on tourism growth. The third objective and main aim of the study was to determine which of the factors identified earlier determine the demand for international tourism to South Africa. This was done through an empirical investigation. Data from all the continents were used to attain an international perspective on tourist arrivals (tourism demand). The results indicated that capacity and climate factors determine tourism demand in the short term with income and transport cost influencing South Africa as a tourism destination in the long term. The last objective was to determine whether certain events or disasters that take place globally have a negative influence on tourism demand to South Africa. The event that was looked as was the terror attacks on the United States in September 2001. It was found that although the overall tourism activity of the world became stagnant during this period, the effect was not that considerable in South Africa's tourism arrivals. Tourism in countries such as the United Sates, on the other hand, has still not recovered fully after this event. / Thesis (M.Com. (International Commerce))--North-West University, Potchefstroom Campus, 2007.

This thesis is a study on the liberalization of trade in tourism services that has taken place between the European Union and Organisation of Eastern Caribbean States (OECS) under the Caribbean Forum (CARIFORUM) -European Union (EU) Economic Partnership Agreement (EPA). It focuses on Antigua and Barbuda, Dominica, Grenada, St. Kitts and Nevis, St. Lucia and St. Vincent and the Grenadines. They are all members of the OECS, the Caribbean Community and Common Market (CARICOM) and CARIFORUM and they are EPA signatories. Using Panel Auto Regressive Distributed Lag modelling, the study is the first to empirically test the effect of liberalizing trade in tourism services (proxied by the EPA) on inflows of tourism related foreign direct investment and European tourism demand regarding the aforementioned countries. It focuses on the period 1997 – 2013. The results indicate that Gross Domestic Product Per Capita (GDPPC) is a statistically significant determinant of tourism related foreign direct investment. This supports the established hypothesis that market size measured by GDP per capita is a key determinant of FDI. Inflation rate (IR) and trade openness (OPEN) are also significant determinants of tourism related foreign direct investment whilst the EPA is not. Regarding European tourism demand income, prices, prices in a substitute destination and room supply are statistically significant determinants in the long run. Barbados is viewed as a complementary destination to the OECS EPA signatories. However, in the short run the EPA is not a statistically significant determinant of European tourism demand which it negatively affects.

The objective of this study is to estimate advertising effects on international tourismdemand for the leading Swedish winter destination, Åre. The increasing share of foreigninbound tourists in this destination region creates a strong interest by shareholders toidentify the factors responsible for this trend. According to traditional micro-economictheory, economic factors, such as income and price, are considered as main determinantsfor tourism demand (Song and Witt 2000). However, according to advertising theories(Comanor and Wilson, 1974) and previous tourism research (Bhagwat and Debruine, 2008;Divisekera and Kulendran, 2006), this study additionally focuses on the brand awarenessof Åre as perceived by international tourists. More concretely, advertising theoriesdistinguish between the brand and the information function of advertising (Nelson, 1974).The former function follows the idea that advertising increases the level of productdifferentiation to build up a base of loyal customers. By contrast, the information functionimplies that advertising primarily provides information about products in order to increasethe market transparency. Accordingly, in order to estimate the impact of advertisingexpenditures for off- and online channels as well as promotional activities, furtherexplanatory variables, e.g. mega events, are considered in this study (Salman, 2003; Songet al., 2010). By applying ordinary least square (OLS) methods, demand elasticitycoefficients are estimated for each of the sending countries Norway, Finland, Russia,Denmark and the UK. Results show that advertising is the main significant driver oftourism demand from the UK, Russia and Finland, while a comparably weak advertisingleverage can be shown for Denmark and Norway. Interestingly, in contrast to microeconomictheories tested in previous research, income and tourism price levels reveal asbeing less significant drivers for demand in all analysed tourism markets. In turn, theresults provide evidence that the increased usage of online channels most significantlyaffects consumers’ buying behaviour. Finally, with respect to brand image perception,results reveal that the destination of Åre is perceived as a brand by tourists from Denmark.Moreover, for customers from the countries Norway and Finland, Åre indicates a weakbrand perception, while tourists from Russia and the UK don’t perceive Åre as a brand atall. The results gained by this research conducted at the level of the tourism destinationprovide useful hints about the factors influencing travel behaviour of tourists from maininternational markets. The study supports destination managers to appropriately adjustmarketing campaigns according to the predominant level of brand perception in respectivesending countries. / KK-Foundation project ‘Engineering the Knowledge Destination’ (no. 20100260; Stockholm, Sweden).

This paper investigates what factors affect the destination choice for Jordanian to 8 countries (Oman, Saudi Arabia, Syria, Tunisia, Yemen, Egypt, Lebanon and Bahrain) using panel data analysis. Number of outbound tourists is represented as dependent variable, which is regressed over five explanatory variables using fixed effect model. The finding of this paper is that tourists from Jordan have weak demand for outbound tourism; Jordanian decision of traveling abroad is determined by the cost of traveling to different places and choosing the cheapest alternative.

This paper examines the development of income in the tourist generating coun-tries, the relative prices controlled for the exchange rate, and the distance in kilo-meters between the capital in the origin countries and Athens as determinants of international tourism demand for Greece. By the deployment of an OLS log-linear regression model coupled with annual cross-section data for the period between 1998 and 2007, the desired effects could be captured. The results from this study indicates that after 2004, both the importance of income in the tourist generating countries and distance between the countries of origin and Athens have expe-rienced a quantum drop in importance as determinants of international tourism demand for Greece. Furthermore, the elasticities of these factors remained at the new level throughout the remaining period studied. This suggests that the respec-tive elasticities have reached a new plateau after 2004 where the impact on inter-national tourism demand is less sensitive to changes in these specific factors. Final-ly, the investments made in infrastructure supporting the Olympic Games have the possibility to benefit the T&T sector in Greece for an extended period of time going forward.

Tourism is one of the fastest growing industries in the world, employing approximately 220 million people and generating over 9.4% of the world's GDP. The growing contribution of tourism is accompanied by an increased interest in understanding the major factors which influence visitation levels to those countries. Therefore, finding the right variables to understand and estimate tourism demand becomes very important and challenging in policy formulations. The purpose of this study is to introduce Economic Sentiment Indicator (ESI) to the field of tourism demand studies. Using ESI in demand analysis, this study will assist in the ability to tap into individuals' hopes and/or worries for the present and future. The study developed a demand model in which the number of tourist arrivals to Turkey from select EU countries is used as the dependent variable. ESI along with more traditional variables such as Interest Rate, Relative Price, and Relative Exchange Rate were brought into the model as the independent demand determinants. The study utilized such econometric models as ARIMA for seasonality adjustment and ARDL Bound test approach to cointegration for the long and short-run elasticities. ESI was statistically significant in 8 countries out of 13, three of those countries had a negative coefficient and five had a positive sign as proposed by the study. The study posits that ESI is a good indicator to gauge and monitor tourism demand and adding the visitors' state of mind into the demand equation could reduce errors and increase variance in arrivals. Policy makers should monitor ESI as it fluctuates over time. Since we do not have direct influence on travelers' demand for tourism, it is imperative that we use indirect approaches such as price adjustment and creating new packages or promotional expenditures in order to influence or induce demand. Using this information generated from the study, government officials and tourism suppliers could adjust their promotional activities and expenditures in origin countries accordingly. / Master of Science

[ES] Los avances tecnológicos de los últimos años han permitido la aparición de nuevas fuentes de datos y con ello, el almacenamiento de grandes cantidades de datos o `Big Data' se ha cobrado cada vez mayor importancia. Cada vez más y más estudios científicos utilizan estas fuentes de `Big Data' para tratar de mejorar el entendimiento en diversos campos científicos. En la economía del turismo ya se han utilizado muchas de estas fuentes para predecir el comportamiento de variables reales. En turismo, la utilidad de estas nuevas fuentes de datos reside en que pueden ayudar a entender el comportamiento de los turistas, desde sus patrones espaciotemporales hasta qué atracciones y actividades son las más populares en el destino, y por tanto, pueden ayudar en la toma de decisiones de los agentes económicos. Por tanto, esta tesis intenta entender mejor cuáles son las fuentes de Big Data que resultan más útiles a la hora de lidiar con variables turísticas y además proponer mejoras metodológicas para que dichas fuentes se puedan aplicar al campo del turismo rural, y más concretamente, a la predicción de turistas. En esta tesis se presentan varios avances en este aspecto: Primero, una clasificación de fuentes de datos que genera todo turista durante su proceso turístico y que componen su huella digital. Después, respecto a esta clasificación, se escoge Google Trends como la fuente más adecuada para ayudar a predecir la demanda turística, pero se encuentran problemas de precisión, que son demostrados y ejemplificados. Más adelante, se demuestra cómo se genera este error de precisión a través del proceso de muestreo de GT y se proponen soluciones para aliviar este error, a saber, obteniendo más extracciones y utilizando su media. Finalmente, este método se pone a prueba para la predicción de pernoctaciones mensuales en alojamientos de turismo rural en España. En resumen, la contribución que esta tesis pretende hacer es aportar una mayor comprensión de las fuentes de Big Data y ayudar a generar buenas prácticas en el uso de las mismas para que se puedan aplicar a la predicción de variables reales en el turismo rural, de forma que agilice y mejore la toma de decisiones de los agentes económicos. / [CA] Els avanços tecnològics dels últims anys han permés l'aparició de noves fonts de dades i amb això, l'emmagatzematge de grans quantitats de dades o `Big Data' s'ha cobrat cada vegada major importància. Cada vegada més i més estudis científics utilitzen aquestes fonts de `Big Data' per a tractar de millorar l'enteniment en diversos camps científics. En l'economia del turisme ja s'han utilitzat moltes d'aquestes fonts per a predir el comportament de variables reals. En turisme, la utilitat d'aquestes noves fonts de dades resideix en què poden ajudar a entendre el comportament dels turistes, des dels seus patrons espaciotemporals fins a quines atraccions i activitats són les més populars en el destí, i per tant, poden ajudar en la presa de decisions dels agents econòmics. Per tant, aquesta tesi intenta entendre millor quines són les fonts de Big Data que resulten més útils a l'hora de bregar amb variables turístiques i a més proposar millores metodològiques perquè aquestes fonts es puguen aplicar al camp del turisme rural, i més concretament, a la predicció de turistes. En aquesta tesi es presenten diversos avanços en aquest aspecte: Primer, una classificació de fonts de dades que genera tot turista durant el seu procés turístic i que componen la seua empremta digital. Després, respecte a aquesta classificació, es tria Google Trends com la font més adequada per a ajudar a predir la demanda turística, però es troben problemes de precisió, que són demostrats i exemplificats. Més endavant, es demostra com es genera aquest error de precisió a través del procés de mostreig de GT i es proposen solucions per a alleujar aquest error, a saber, obtenint més extraccions i utilitzant la seua mitjana. Finalment, aquest mètode es posa a prova per a la predicció de pernoctacions mensuals en allotjaments de turisme rural a Espanya. En resum, la contribució que aquesta tesi pretén fer, és aportar una major comprensió de les fonts de Big Data i ajudar a generar bones pràctiques en l'ús de les mateixes perquè es puguen aplicar a la predicció de variables reals en el turisme rural, de manera que agilitze i millore la presa de decisions dels agents econòmics. / [EN] Technological advances in recent years have enabled the emergence of new data sources and with it, the storage of large amounts of data or 'Big Data' has become increasingly important. More and more scientific studies are using these Big Data sources to try to improve understanding in various scientific fields. In tourism economics, many of these sources have already been used to predict the behavior of real variables. In tourism, the usefulness of these new data sources lies in the fact that they can help to understand the behavior of tourists, from their spatial-temporal patterns to which attractions and activities are the most popular in the destination, and therefore, they can help in the decision making of economic agents. Therefore, this thesis tries to better understand which Big Data sources are the most useful when dealing with tourism variables and also to propose methodological improvements so that these sources can be applied to the field of rural tourism, and more specifically, to the prediction of tourists. In this thesis several advances in this aspect are presented: First, a classification of data sources that every tourist generates during his tourist process and that compose his Digital Footprint. Then, with respect to this classification, Google Trends is chosen as the most appropriate source to help predict tourist demand, but accuracy problems are found, which are demonstrated and exemplified. Further on, it is demonstrated how this accuracy error is generated through the GT sampling process and solutions are proposed to alleviate this error, namely by obtaining more extractions and using their mean. Finally, this method is tested for the prediction of monthly overnight stays in rural tourism accommodations in Spain. In summary, the contribution that this thesis aims to make is to provide a better understanding of Big Data sources and help to generate good practices in the use of them so that they can be applied to the prediction of real variables in rural tourism, in a way that streamlines and improves the decision making of economic agents. / Cebrián Cerdá, E. (2024). Big Data Sources Applied to Rural Tourism [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/206090

The natural environment is a key attraction for Australia???s tourism industry. In order to prevent the deterioration of the environment, environmental management measures have been adopted by the tourism industry. Some of these measures are related to environmental regulations imposed on tourism operators by governments. However, given the dependence of the nature-based tourism industry on the environment, voluntary environmental management measures have also been instituted. The objective of this thesis is to investigate the effect of environmental management on the competitiveness of a nature-based tourism destination. For that purpose, Tropical North Queensland, a major Australian nature-based destination, is selected as a case study. Competitiveness is measured by the aggregate profitability of the tourism industry in the destination region. The investigation incorporates an assessment of the simultaneous effects of environmental management on the destination???s tourism demand and on business costs to tourism operators at the destination. The conceptual background to the investigations is discussed in the first part of the thesis. It includes the rationale for choosing a nature-based destination region as the unit of analysis. The conceptual framework is a departure from the conventional analysis of the relationship between the environment and international competitiveness in which the effect of regulatory compliance costs is emphasised. In this thesis, the potential demand benefits and the associated voluntary environmental management are added to the conventional analytical framework. The primary data for the analysis are derived from two separate investigations. The first comprises an analysis of the tourism industry in Tropical North Queensland. The second investigation involves a discrete choice modelling analysis of destination choices by prospective visitors to Tropical North Queensland. The empirical results show that it is justified to treat the nature-based tourism destination region, Tropical North Queensland, as an aggregate entity in the analysis. The destination competes as a collective unit with other destinations. This is done, predominantly, on the basis of the region???s high-quality natural attractions. The empirical analyses show that tourism businesses??? costs due to environmental management are small in comparison with the positive demand effects. The cost and demand effects are assessed in a quantitative fashion in an economic model. That analysis shows that environmental management makes a positive contribution to Tropical North Queensland???s competitiveness as a nature-based tourism destination.

Indigenous tourism is an expansive sector in the growing tourism industry. The Sami people living in Sápmi in northern Europe have started to engage in tourism, particularly in view of the rationalised and modernised methods of reindeer herding. Sami tourism offers job opportunities and enables the spreading of information. On the other hand, Sami tourism may jeopardise the indigenous culture and harm the sensitive environment in which the Sami live. The aim of this thesis is to analyse the supply and demand of Sami tourism in northern Sweden. This is presented in four articles. The first article analyses the potential of the emerging Sami tourism in Sweden, with special emphasis on the access to Sami tourism products. The study shows that there is a growing supply of tourism activities related to the Swedish Sami. The development of tourism is, however, restricted by factors such as the peripheral location and the lack of traditions of entrepreneurship. The second article analyse which factors influence tourists when they make their decisions about Sami tourism. In the article the respondents are requested to answer a number of hypothetical questions, ranking their preferences regarding supply, price and access. The study indicates that tourism related to the Sami and Sami culture has a considerable future potential, but also that there is a gap between supply and demand. In the third article the analysis shows that the festival in Jokkmokk, thanks to continuously added attractions, has been able to retain a rather high level of popularity, despite its peripheral location. Finally, the fourth article analyses to what extent the winter festival in Jokkmokk is a genuinely indigenous event, and to what extent it is staged. It is argued that the indigenous culture presented at the festival and in media is highly staged, although backstage experiences are available for the Sami and for the tourists who show a special interest.