| Summary: | 博士 === 輔仁大學 === 商學研究所博士班 === 102 === Since the starting of direct cross-strait transportation on August 2009, the number of Chinese visitors to Taiwan increased rapidly. By 2013, the number of Chinese visitors reached 2.87 million. Thus, Chinese visitors have become the most frequent visitors to Taiwan and the major source of foreign exchange earnings in tourism. This study applied three analysis model - multivariate adaptive regression splines (MARS), Artificial Neural Network (ANNs) and Support Vector Regression (SVR). Moreover, MARS combined with ANNs (MARS-ANNs) model and MARS combined with SVR (MARS-SVR) model were used to build the forecasting model for the number of Chinese visitors to Taiwan. MARS-SVR emerged as the best forecasting model and showed that the model combining with two analysis achieves better results compared to individual analysis tools.
This study used MARS-SVR predictive model to forecast the number of Chinese visitors to Taiwan in 10 months - 7 months with forecasting error smaller than 5%, 3 months with forecasting error in between 5% to 10%. The accuracy of forecasting individual month is high; therefore, the result of MARS-SVR forecasting model can provide a reference for administrative authority and tourism industry to carry out construction program of tourism industry and plans for tourism activities. Six substantial forecasting variables were selected from eight forecasting variables by applying MARS analysis, which clearly indicated the high and low seasons. Therefore, administrative authority and tourism industry should pay attention to the difference in the number of Chinese visitors to Taiwan between high and low season. Accordingly, it is needed to increase flight times of cross-strait direct flights and additional tourist hotels to increase the transportation and accommodation capacity and serve more Chinese visitors. On the other hand, China’s gross domestic product (GDP), NTD to RMB exchange rate and the world oil price influence the number of Chinese visitors to Taiwan.
|
|---|
