Analysis of tourism industry economy development in Taiwan

• Main Authors: WU, CHIN-JU, 吳謹如
• Other Authors: Kao, Huey-Lien
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/62646515786487483620

碩士 === 國立屏東大學 === 資訊管理學系碩士班 === 103 === This research paper`s purpose is to understand the correlation of Taiwan passenger population to Taiwan economy and the correlation of macroeconomic factors and microeconomic factors to total Taiwan passenger population. This research paper discusses the relationship between dependent variables, the prediction ability of multiple regression analysis, and artificial neural networks. In accordance with the database from Tourism Bureau, National Development Council and Central Bank, we analyze the time series data through descriptive statistics, the relevant analysis, analysis of variance, multiple regression analysis and artificial neural networks by using SPSS statistical software. The results were shown as follows. First, the Taiwan passenger population has a very significant correlation with Taiwan economy. Second, the Taiwan passenger population, gender specific, age, occupation, and the Customer Price Index have significant correlations with total Taiwan passenger population. Third, there are statistically significant differences in the average Taiwan passenger population between certain samples of the continent, purpose, age, occupation, income and education. Fourth, the multiple regression analysis gives an excellent statistical interpretation of total Taiwan passenger population based on the previous data from microeconomic factors. Including the Taiwan passenger population of the continent, gender, purpose, age, occupation, income and macroeconomic factor of Customer Price Index. Fifth, the artificial neural networks gives a clear statistical interpretation of total Taiwan passenger population based on the distribution of macroeconomic factors. In summary, this research report shows important factors and precise rules which affect Taiwan tourism economy, the government and the enterprise in Taiwan’s future.