日本來台旅客對觀光旅館住宿需求預測之研究

The Study of the Tourist Hotel Accommodation Demand Forecasting for Tourist of Japan

蔡美霞(Mei-Hsia Tsai)

《觀光與休閒管理期刊》 2卷2期 (2014/09) Pp. 226-244

https://doi.org/10.6510/JTLM.2(2).17

摘要

本研究藉由觀光資料統計結果，了解日本觀光旅客人數變動情形，使用迴歸分析之方法，建構出日本旅客來台對觀光旅館住宿需求之預測模型及其影響變數。本研究分析採用交通部觀光局、行政院主計處自1999年至2012年間公佈及提供之月資料。本文分成北、中、南、東四區採用計量經濟迴歸模型，這項研究共同探討依變數日本來台住宿與總體經濟變數觀光旅館住用數、國人住宿人數、觀光旅館客房數、觀光旅館平均房價、台灣總人口數等四區變數住宿需求影響關係。透過回顧相關文獻、目的地市場分析，建構日本來台住宿需求預測模式，再經由SPSS統計軟體分析，並採用敘述性統計、單因子變異數、相關係數、迴歸來進行處理各項檢定的檢驗，以獲得最佳預測模式。結果發現觀光旅館平均房價、觀光旅館住用數只對北區日本來台住宿人數有影響，其它三區並無任何作用，而台灣人口總數對於北、中二區皆是顯著的影響。觀光旅館客房數對於南、東二區皆是顯著的影響，那表示觀光旅館規模大小對日本來台住宿人數是有影響。整體的解釋能力，是以北區解釋變異量為40%較為上升。最後，透過本研究結果，期望提供相關業者營運管理上之參考。

關鍵字

日本觀光客 ； 觀光旅館 ； 迴歸 ； 住宿預測 ； 相關係數

並列摘要

The purpose of this study is to observe the statistical results of changes in the Japanese leisure traveling and the number of cases. The use of regression analysis method was employed to construct a predictive model of Japanese tourist hotel accommodation needs impact and variables for regression analysis in order to forecast accommodation demand of tourists from Japan to Taiwan. Accounting data is provided monthly by the Ministry of Transportation and Communications from 1999 to 2012. All input variables were collected by literature survey, market analysis and preliminary evaluation to determine the input variable and the resulting data is tested with the impact prediction model one-way ANOVA, Pearson correlation, and regression analysis processing were all utilized for the verification of the test to obtain the best predictive model. This study used econometric regression model and selected various macroeconomic variables, such as the population of Taiwan, the tourist number of Taiwan lodging, the average hotel rates and the occupancy number and the rooms in the north, south, central and east of Taiwan, to predict how accommodation needs of Japan-to-Taiwan tourism is affected. Through review of the relevant literature of the destination market analysis, construction of the Japan-to-Taiwan accommodation demand model by regression analysis (exhibiting a variance of 40%) showed that the average price and the occupancy number impact of the northern tourist hotel accommodation needs of Taiwan-to-Japan's tourism was impacted the most. In conclusion, the results of study will hopefully benefit the decision-making policies of hotel business leaders and allow a better understanding of the needs and impacts on their clientele.

並列關鍵字

Japanese Tourist ； Tourist Hotel ； Lodging Demand Forecast ； Regression Analysis ； Correlation Coefficient