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Data Mining in Tourism
Abstract
Everyday, millions of people travel around the globe for business, vacations, sightseeing, or other reasons. An astronomical amount of money is spent on tickets, accommodations, food, transportation, and entertainment. According to World Travel and Tourism Council, travel and tourism represents approximately 11% of the worldwide gross domestic product (GDP) (Werthner & Ricci, 2004). Tourism is an information-based business where there are two types of information flow. One flow of information is from the providers to the consumers or tourists. This is information about goods that tourists consume such as tickets, hotel rooms, entertainments, and so forth. The other flow of information which follows a reverse direction consists of aggregate information about tourists to service providers. In this chapter we will discuss the second form of information flow about the behavior of tourists. When the aggregated data about the tourists is presented in the right way, analyzed by the correct algorithm, and put into the right hands, it could be translated into meaningful information for making vital decisions by tourism service providers to boost revenue and profits. Data mining can be a very useful tool for analyzing tourism-related data.
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