Identifying Segments of a Domestic Tourism Market by Means of Data Mining

Gül Gökay Emel () and Çağatan Taşkın ()
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Gül Gökay Emel: Uludağ University
Çağatan Taşkın: Uludağ University

A chapter in Operations Research Proceedings 2005, 2006, pp 653-658 from Springer

Abstract: Abstract This paper helps to analyse a typical problem seen in the marketing systems of firms in tourism industry. The problem here is the difficulty in determining the market segments for an optimal customer management. In this work, data mining is used as a decision support tool in order to extract previously unknown patterns and ultimately comprehensible information from large databases which traditional statistical tools can not extract. The research is conducted in Bursa, the fourth biggest city of Turkey. The multi-dimensional analysis of this domestic market is very important for foreign hotel investors, tour operators and travel agencies in their investment, marketing and management strategies. For this multi-dimensional analysis, visual and robust data mining software Clementine 8.1 is used for the classification task of data mining in order to determine the market segments for optimal customer management.

Keywords: Monthly Income; Market Segment; Classification Rule; Association Rule Mining; Market Segmentation (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-540-32539-0_102

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DOI: 10.1007/3-540-32539-5_102

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