全球來台旅客預測模式之模式建構

The Construct Predictive Models for Pattern of Global Visitors to Taiwan

謝茵如(Yin-Ru Hsieh) ； 陳俊言(Chun-Yen Chen)

《多國籍企業管理評論》 9卷1期 (2015/03) Pp. 27-61

https://doi.org/10.3966/199553922015030901002

摘要

根據世界觀光組織（World Tourism Organization, WTO）分析報告指出，在全球各國的外匯收入中約有超過百分之八來自觀光收益高居第一，儼然已成為許多國家賺取外匯的重要來源之一。本研究主要是利用時間數列分析與預測模式等多變量分析方法，並配合SAS等統計軟體加以建立來台旅客預測之建構模式、預測及檢定，並據以推論其結果、關係及影響，依據中華民國交通部觀光局來華人數統計1997年1月至2005年9月的觀光資料統計之結果了解來華觀光旅客變動情形，我們由研究結果可看出實際和預測來台旅客人數發展趨勢，發現干預模型比ARIMA有更好的預測效果。藉由掌握來華觀光旅客旅遊趨勢及型態，建立來華觀光旅客人數需求。希研究結果提供政府相關機關或地方民間企業之相關規劃部門，做為對未來我國觀光需求政策方針的擬定規劃之參考。

關鍵字

預測模式 ； 旅客

並列摘要

In twenty-first Century tourism industry has become one the most important economic indicators of the industry. According to the World Tourism Organization (WTO) report it pointed out that about more than eight percent from tourism which is the highest income in the global foreign exchange earnings for the country, just like it (tourism revenue) has become the primary source of many countries to earn profit from the foreign exchange. This study is the use of multivariate analysis, time series analysis and forecasting methods, and with SAS statistical software, such as the establishment of Taiwan visitors to construct predictive model to predict and test. In addition, according to the statistics the number of tourist statistics from January 1997 to September 2005 to Taiwan visitors provided by Tourism Bureau, Republic of China Ministry of Transportation. From the inference result, relationship and influence, understand the visitor changes in the situation from time to time, and get to travel trends and patterns of travel to Taiwan visitors. We figure out the actual and forecast trends, the intervention model for better prediction of the number of Taiwan ARIMA. We hope the results can provide the relevant government authorities or the relevant planning department of the local private sector, create to Taiwan visitor number of demands and as demand for the future of tourism policy guidelines of reference drawn planning.

並列關鍵字

Predictive Model ； Visitor ； ARIMA

參考文獻

Box, G. E.,Jenkins, G. M.,Reinsel, G. C.(2013).Time series analysis: forecasting and control.John Wiley & Sons.

(Blume, M., Lazarus, M. A., Peranich, L. S., Vernhes, F., Caid, W. R., Dunning, T. E., & Sitze, K. L. (2005). U.S. Patent No. 6,839,682. Washington, DC: U.S. Patent and Trademark Office).

Bohnert, F.,Zukerman, I.,Berkovsky, S.,Baldwin, T.,Sonenberg, L.(2008).Using interest and transition models to predict visitor locations in museums.AI Communications.21(2),195-202.

De Cannière, M. H.,De Pelsmacker, P.,Geuens, M.(2009).Relationship quality and the theory of planned behavior models of behavioral intentions and purchase behavior.Journal of Business Research.62(1),82-92.

Gross, M. J.,Brown, G.(2008).An empirical structural model of tourists and places: Progressing involvement and place attachment into tourism.Tourism Management.29(6),1141-1151.