Housing Demand Forecast from Different Sources : A Case Study of a Business Hotel in New Taipei City

• Main Authors: HUANG,SZU-TING, 黃思婷
• Other Authors: TSAI,CHANG-CHING
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/cxdx39

碩士 === 國立高雄科技大學 === 觀光管理系 === 107 === Whether you are on a business trip or a weekend trip, the choice of accommodation is always an important part. Taiwan's tourism strategy in the "multiple layouts and global perspective" strategy under the flexible tourism marketing method, following the breakthrough of 10 million in 2015, the total number of visitors to Taiwan in 2017 has once again surged by 10.73 million. According to the Tourism Bureau (2017), from January 2003 to January 2018, the number of general hotels in the Greater Taipei area increased from 566 to 850, and the number of rooms increased from 19,022 to 41,832 during the same period. Compared with 2003, the number of hotel rooms in the Greater Taipei area has more than doubled, and no other cities have been included. In November 2017, Hsinchu Miracle Hotel ceased business due to the reduced housing rate and the loss. In January 2018, the Kenting Resort Hotel in Pingtung Checheng City collapsed and the Luk Fook Palace officially announced its operation until the end of 2018. Such kind of market information can not help but let people think whether the supply of hotels is oversupply? Therefore, how to predict housing demand and early response to the trends has become an important issue in the future. This study takes a business hotel in New Taipei City as the research subject, and establishes moving average, exponential smoothing, and simple linear regression models for the source of accommodation for three consecutive years, quarters and months of data. Three time series models are used to predict the demand of different source accommodations. The results of the study show that the forecasting accuracy of the hotel's quarterly or monthly forecast with simple linear regression analysis is the best, and the forecasting accuracy of the annual forecast with the smooth index analysis is the best. Three time series models are available for different customer source predictions. The research results will help human resources planning and effectively improve the efficiency of procurement of goods, and can be used as a reference for the hotel's pricing strategy and marketing objectives, to understand the direction and demand of customers, to adjust the hardware design and equipment during the renovation and to increase customer satisfaction and to increases profits and earnings.