來臺觀光客之分析及來臺日本遊客需求預測

An Analysis of Taiwan’s Inbound Tourist and the Demand Forecasting of Japanese Tourist

余書芸(Shu-Yun Yu)

指導教授 ： 何瓊芳

中原大學/商學院/國際經營與貿易研究所/碩士(2012年)

https://doi.org/10.6840/cycu201200912

摘要

觀光產業在近二十年內發展迅速蓬勃。許多國家視觀光事業為具有競爭力的產業，因為觀光產業為賺取外匯重要穩定之來源。觀光產業可直接或間接的影響帶動不同的產業，目前其產值不僅占全球經濟產出之11.7%，更提供世界各地8%以上的工作職務。觀光事業的成長也同時加速相關禮品、航空、旅館、食品及交通運輸等產業的發展。因國外遊客的人數增加勢必為本國前述產業和經濟帶來成長。因此，準確地預測出來台觀光旅客的人數和相關市場需求是必要的。本研究的主要目的是利用迴歸之最小平方法做為預測日本遊客來台觀光人數需求，以探索觀光產業之前景。

關鍵字

遊客需求預測 ； 最小平方法 ； 來臺觀光

並列摘要

International tourism has grown rapidly over the last two decades. Because it is the fastest-growing economic sector in terms of foreign exchange earnings, countries throughout the world see tourism as a very competitive business. The tourism industry, which comprises 11.7% of total global economic output and supplies 8% of total number of job opportunities worldwide, is directly or indirectly related to wide range of business. Moreover, the growth in tourism industry accelerates other related industries. The growth in international visits brings enormous benefits to the nation’s industries including gift, hotel, transportation, food and etc. Thus, an accurate forecast of tourism demand is important. The main purpose of this paper is to design a forecasting model to accurately forecast the incoming tourist with a special emphasis on Japanese tourists. The method of OLS was employed in order to estimate the demand forecast for Japanese arrivals.

並列關鍵字

Ordinary Least Squares ； Taiwan’s Inbound Tourist ； Tourist Demand Forecast

參考文獻

Hsu, L. C., & Wang, C. H. (2008). Applied multivariate forecasting model to tourism industry. Tourism, 56( 2), 159-172.

Ahmed, Z. U. & Krohn, F. B. (1992). Understanding the unique consumer behavior of Japanese tourists. Journal of Travel and Tourism Research, 1(3), 73-86.

Andrew, W. P., Crange, D. A., & Lee, C. K. (1990). Forecasting hotel occupancy rates with time series models: An empirical analysis. Hospitality Research Journal, 14(2), 173-181.

Burger , C.J.S.C., Dohnal, M., Kathrada, M. &Law, R. (2001). A practitioners guide to time-series methods for tourism demand forecasting－case study of Durban, South Africa. Tourism Management 22 (2001) 403-409

Chang, Yu-Wei, & Liao, Meng-Yuan (2010). A Seasonal ARIMA Model of Tourism Forecasting: The Case of Taiwan. Asia Pacific Journal of Tourism Research,15( 2), 215-211