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Implementation of Chaid Algorithm: A Hotel Case

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  • Celal Hakan Kagnicioglu

    (AnadoluUniversity, Faculty of Economics and Administrative Sciences, Department of Business Administration, Eskisehir, 26170, Turkey)

  • Mune Mogol

    (Anadolu University, Tourism Faculty, Department of Tourism Management, Eskisehir, 26170, Turkey)

Abstract

Today, companies are planning their own activities depending on efficiency and effectiveness. In order to have plans for the future activities they need historical data coming from outside and inside of the companies. However, this data is in huge amounts to understand easily. Since, this huge amount of data creates complexity in business for many industries like hospitality industry, reliable, accurate and fast access to this data is to be one of the greatest problems. Besides, management of this data is another big problem. In order to analyze this huge amount of data, Data Mining (DM) tools, can be used effectively. In this study, after giving brief definition about fundamentals of data mining, Chi Squared Automatic Interaction Detection (CHAID) algorithm, one of the mostly used DM tool, will be introduced. By CHAID algorithm, the most used materials in room cleaning process and the relations of these materials based on in a five star hotel data are tried to be determined. At the end of the analysis, it is seen that while some variables have strong relation with the number of rooms cleaned in the hotel, the others have no or weak relation. Key Words:Data Mining, CHAID, Tourism, Hotel

Suggested Citation

  • Celal Hakan Kagnicioglu & Mune Mogol, 2014. "Implementation of Chaid Algorithm: A Hotel Case," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 3(4), pages 42-51, October.
  • Handle: RePEc:rbs:ijbrss:v:3:y:2014:i:4:p:42-51
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    References listed on IDEAS

    as
    1. Antipov, Evgeny & Pokryshevskaya, Elena, 2009. "Applying CHAID for logistic regression diagnostics and classification accuracy improvement," MPRA Paper 21499, University Library of Munich, Germany.
    2. McCarty, John A. & Hastak, Manoj, 2007. "Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression," Journal of Business Research, Elsevier, vol. 60(6), pages 656-662, June.
    3. repec:bla:jorssc:v:29:y:1980:i:2:p:119-127 is not listed on IDEAS
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