Tourism may be defined as, "The sum of the phenomena and relationships arising from the interaction of tourists, business suppliers, host governments and host communities in the process of attracting and hosting these tourists and other visitors," (McIntosh and Goeldner, 1990, p. 4).
From the above definition, it can be seen that the development of tourism in any area involves multiple players. In addition, tourism is made of up numerous activities, services, and industries that contribute to the tourists' experience. These include the provision of transportation and accommodation; eating and drinking establishments; entertainment facilities; and shops, among others (McIntosh and Goeldner, 1990). Edgell (1990, p. 12) adds that,
"The full scope of international travel and tourism, therefore, encompasses the output of segments of many industries. The travel 'industry' consumes the output of and creates a far-reaching base of wealth for feeder industries such as agriculture, fishing, food processing, brewing, construction, airports, automobiles, and furniture. In addition, tourist activities make use of the services of other industries such as insurance, credit cards, advertising, and data processing."
The tourism industry is therefore not a 'stand-alone' industry, but has relations that cut across industry, product and service lines. This is a fact that has significance when considering the impacts of tourism on a host country.
In much of the current literature, tourism development is usually linked to the activities of developing countries. However, Roche (1992, p. 566), made the observation that while the development of tourism has been viewed as a symbol of 'westernization' and progress, particularly in what are known as developing countries, its "role as both a symbol and vehicle of economic and socio-cultural change and 'modernization' is potentially just as significant for the advanced industrial countries."
2. Tourism Demand
The key challenge in measuring tourism impacts on an economy is that tourism is part of many different industries, but comprises 100% of no one industry (Global Insights, 2003). Conventionally, tourism has been measured from the demand side, reflecting the amount of expenditures made by visitors to local areas. Other economic sectors have traditionally been measured from the supply side, looking at production inputs and outputs to determine their effect on the overall economy. This has made comparison difficult.
There have been a number of attempts to bring tourism in line with other industry measurements internationally. The most common form of economic impact measurement is the input/output model (I/O), which only looks at the products and services produced by the tourist sectors and how this production impacts the regional economy. It does not take into account tourism spending patterns, only the production of commodities by industries assigned to tourism sectors. The next step was the development of the tourism satellite account (TSA), which incorporates demand in the form of tourism expenditures when assessing impacts. The final impact model approach is computable general equilibrium modeling (CGE), including tourism policy and forecasting models. Each model is a step closer in the comprehensive measurement of assessing the true impacts of tourism on local economies, and each model is based on adjustments to previous models.
Edgell reports that in 1989, there were 403 million international tourist arrivals worldwide, and that the international tourist receipts exceeded U.S. $208 billion. According to the World Tourism Organization's (WTO) Tourism Highlights 2006 Edition, the total number of worldwide international tourist arrivals in 2005 was 806 million. With the number of wars, natural disasters, terrorist activities that occurred between 1989 and 2005, this doubling of the scale of tourism is no doubt significant. The total international tourist receipts in 2005 tripled to U.S. $680 billion.
Looking at the international tourist arrivals by region in 2005, Europe took the lead with 441.5 million, followed by Asia and the Pacific, the Americas, the Middle East and Africa with 155.4 million, 133.5 million, 39.1 million, and 36.7 million respectively. The ranking of the international tourist receipts was similar to that of the arrivals with Europe receiving more than half (U.S.$348.2 billion), and Africa bringing up the rear with U.S.$21.5 billion. While these figures do not specifically detail the totals for individual countries in arrivals or revenue, it can be seen that the distribution of both is skewed among global regions.
Tourism is a very complex phenomenon which has been viewed from various perspectives and studies by disciplines, such as economics, psychology, sociology, marketing, geography, and political science (Lundberg, Krishnamoorthy, & Stavenga, 1995; Przeclawski, 1993). Consequently, each discipline has provided a partial rather than a holistic point-of-view regarding the factors that influence tourism activities including choice of destinations, and expenditure patterns (Song & Wong, 2003).
International Tourism Demand Estimation
Depending on the objectives and circumstances of the research, various functional forms have been used in empirical international tourism demand studies. Until the mid-1980s, most of the international tourism demand studies adopted a causal econometric approach that is represented by the single equation method, either in a linear or in a power equation format (Barry & O'Hagan, 1972; Gray, 1966; Stronge & Redman, 1982).
As new economic theory and econometric methods have developed, tourism researchers applied those techniques in an attempt to develop an international tourism demand model, which was expected to include the most appropriate variables in the model and provide significant estimation results. Since the introduction of the Almost Ideal Demand System (AIDS) method (Deaton & Muellbauer, 1980b), tourism researchers and applied economists adopted the AIDS method to analyze international tourism demand particularly in a region where many competing tourism destinations adjoin each other.
Over sixty percent of the previous international tourism demand studies adopted the number of international tourist visitations (or arrivals) as the measure of international tourism demand (Crouch, 1994).
Both tourist arrivals and tourism expenditure have their own limitations. Song and Witt (2000) indicated that tourist visitation data are collected via frontier counts, or registration at accommodation establishments, but this procedure does not account for day-trippers or visitors with friends and relatives especially when the data relied on the record from lodging facilities.
In general, demand theory suggests that consumers respond to a price decline by buying more of a product. In the tourism industry, the demand for tourism theoretically increases when trip costs decline (Loomis & Walsh, 1997). But the actual degree of consumer responsiveness to a price change can vary considerably depending on product or destination. Economists measure how responsive, or sensitive, consumers are to changes in the price of a product by employing the concept of price elasticity. Loomis and Walsh (1997) suggested that price elasticity of demand is a convenient way of comparing how price changes affect demand. Basically, price elasticity of demand is the ratio of two percentages: percentage of the change in the demand, and percentage of the change in price.
Based on the economic theory that luxury products have elastic price demand, one can assume that international, being luxury product has price sensitive demand. In the literature, however, one finds the results of price elasticity of international tourism demand studies to be highly varied. Tourism demand appears to be price elastic for some international destinations and inelastic for others.
In 1995, a White House Conference on travel and tourism expressed the concern in the difficulty of linking demand-side side measurements of tourism with the measurement of other economic sectors. The result was a partnership between the U.S. Department of Commerce and the travel and tourism industries through which the travel and tourism satellite account was developed. This model provided the needed consistency between U.S. national economic accounts. In 1997, the Tourism Industries Office of the International Trade Administration, the U.S. Department of Commerce and the Bureau of Economic Affairs formalized the Travel and Tourism Satellite Accounts (TTSA).
The Tourism Satellite Account (TSA) was revised by the World Tourism Association and ratified by the United Nations in 2000. Since then, numerous TSAs have been developed both nationally and globally. At this time, Alaska, Delaware, South Carolina, Virginia, Hawaii, New Jersey, Rhode Island and North Carolina have completed similar studies (Global Insights, 2005). The World Tourism Association has sanctioned numerous international studies, including TSAs for New Zealand, the United Kingdom, China, Philippians and the European Union.
Computable general equilibrium modeling (CGE) is an alternative modeling approach to assess changes in economic factors to determine the impacts on the local economy. CGEs derive their strength through tourism planning, policy analysis and forecasting. CGEs use data provided by TSAs, but provide added instruments in their flexibility, such as measuring changes in demand due to price or regulatory changes within the industry. Whereas the I/O and TSA models rely on an initial stimulus which is traced through the economic system in a deterministic way, CGE models tell how economic agents react to changes in the economy and then solve a system of equations simultaneously for all markets, production sectors and economic agents (Blake, 2004).