Tourism is a rapidly growing industry in most countries in the world, including both developing and developed countries (Eijgelaar, Peeters, & Piket, 2008; Euromonitor International, 2011). Tourism as a business has grown approximately ten percent per year since the end of World War Two. (Matias, Nijkamp, & Sarmento, 2009) Much of that business is in the form of domestic tourism, but international pleasure travel does capture a significant portion of that market (Lohmann, 2004). The needs of the international tourist differ from the needs of the domestic tourist. Monitoring and forecasting the international tourism demand independently of the domestic tourism demand is vital in proper demand management.
The analysis of tourism demand is the measurement of this growth; forecasting this demand is vital in managing it and profiting from it. However, an analysis of the tourism industry across the entire world is too large and is outside the scope of this research; instead, the focus is on one example of a developing nation though with a thriving tourist industry, China, and one example of a developed nation also with a very well-established tourist industry, France. A type of tourism common to both of these nations is eco-tourism, and so eco-tourism will be used as the model to compare management strategies between the two nations.
Characteristics and Modeling of Tourism Demand
Tourism demand can be measured in a variety of ways. The most commonly used benchmark for tourism demand is the number of tourists arriving in the country or to the location Chan, Lim, & McAleer, 2005). Another method, which is generally used for economic models, is the income receipt from those tourists. A combination of these measurements is considered best to get a true picture of the demand for tourism infrastructure: if there is a situation where a large number of tourists are arriving, but their expenditure while traveling is low, it would be more sensible to focus on budget vacations than on five-star facilities, for example. The two issues at hand, the number of arrivals and the money being spent, are separate; good modeling will involve consideration of them both as individual problems and as a a combination. A wide variety of models exist for forecasting and analyzing the demand of tourism and new techniques are constantly being introduced. No single modeling technique has been found to be the most accurate overall; the best choice of modeling technique seems to depend significantly on the situation (Song & Li, 2008). For example, travel motivation theory suggest that the reasoning behind the trip is the most important in predicting the demand for tourism to a specific location (Goh, Law, & Mok, 2008). Dynamic destination image indexes (DDII) are collections of news stories about a destination that can affect a consumer's choice of vacation destination, by adding a line of reasoning about recent events to the consumer's decision-making process (Stepchenkova & Eales, 2011). Using the DDII can be more helpful to managing demand in a nation that is frequently shown on the international news, but less so in a case where fewer people are aware of current events at that location. Scenario planning is used to predict events, both positive and adverse, that could effect tourism demand. Ideally, scenario planning will also forecast the magnitude of this effect.