Data Mining in Tourism Sector

Abstract

Technological developments are increasing by multiplying data production. Internet use, social media interactions of people and internet-connected devices are factors that increase data production. In the digital world where the data is stored with the stack, these data stacks are stored or flowed instantaneously. The series of transactions made to extract potential information from these data stacks is called Data Mining. Data mining is used effectively in every field today. One of the areas where Data Mining is used is tourism. There are many data regarding personal data, consumer habits, tourist mobility by months, duration of stay and regularity in tourism. Data stacks can be used for a number of basic functions such as customer profile determination, developing marketing strategies, choosing e-commerce options, process management, logistics management, increasing customer satisfaction, determining travel routes, improving service quality by processing with the Data Mining process. In this research, data mining studies in the tourism sector between 2015-2019 have been examined. These studies were examined according to years, countries, models used, journals, data sources, and study topics. According to the results of this study, most articles were published in 2019. It can be said that studies of DM on Tourism have increased in the last two years. It is seen that the most researched country is China. The proportion of predictive and descriptive models in application studies is close to each other. The most studied topics are tourist satisfaction and regularity, determining tourist travel behaviors, decisions, and touring, touring and suggestions for tourists.