Abstract
The current research is designed to apply scoring modeling in database marketing for the hospitality industry. This research seeks to determine if previous historical data can predict future behavior patterns of individuals and groups in terms of frequency of visiting restaurants. The purpose of this study is to develop a scoring modeling to predict existing customers' future behavior using a restaurant database in a hospitality industry. The data set used for this study includes 956 customers and 11,242 restaurant transactions in a hotel from January through December. The current study builds individual models and compares those individual models to an aggregating model in terms of model assessment and prediction power.
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