Cloud-oriented direct marketing service model: A case study on a tourist hotel

To recover from the global financial crisis in 2008 and awareness of leisure consumption and environmental protection, many countries had devoted to develop their tourism industries to enhance their GDP. Based on the global trend and increasing importance of the service sector in Taiwan (nearly 70% of GDP and 60% of the employed population), Taiwan's government identified "tourism industry" as one of the six important emerging industries which it would focus substantial resources on since 2009. To enhance the region's economy and develop the tourism industry, it is important to obtain important decision data of tourist hotels for increasing revenue. In recent years, with the progress of cloud technology, cloud-oriented service may be considered as one of the solutions for efficiently obtaining decision information. Therefore, the purpose of this research is to propose a cloud-oriented service framework for a tourist hotel to acquire new customers by formulating a strategic alliance with a virtual retailer. This research adopts data mining approaches on developing response prediction models for direct marketing of the case hotel. The result shows that the ensemble model developed by logistic regression, neural networks and CART decision trees in this case study has the best performance and could be used to help the case hotel acquire new customers efficiently.