運用灰色預測模型分析陸客來台觀光人數

Using Gray prediction model on the number of Chinese tourists to Taiwan

近年來在大陸當局刻意開放來台觀光下，陸客人次逐年增加，由2008年329,204人次增加至2015年4,184,102人次，但自2016年以後陸客又因政治因素，人數開始減少。在如此複雜多變的兩岸局勢中，依據過去經驗及機率推算的傳統統計分析，勢必難以預測充滿風險的未來，為求台灣觀光產業能在最短期間內，提出有效對策以因應未來的發展，在有限及不確定性的數據下，灰色預測模型有效率的推測是極具意義的。本研究利用2016年1~4月及5~8月兩組大陸來台觀光人數為樣本，使用灰色理論建構，針對不確定性環境下及資訊不完整下進行動態狀況預測，GM(1,1)與灰色Verhulst模型是較常見的選用。根據本研究以真實對照兩模式預估陸客來台觀光人數而言，GM(1,1)模式均較Verhulst模式推估更為準確，不論是各期的誤差值，還是未來各月人數估算，GM(1,1)模式都能根據當月資料做立即的反應與預判。

The Chinese mainland government deliberately opened to visit Taiwan in recent years, the number of Chinese tourists increased year by year from 329,204 in 2008 to 4,184,102 passengers in 2015, but since 2016 due to political factors, the number of Chinese tourists began to decrease. In such a complex and volatile cross-strait situation, the traditional statistical analysis based on past experience and probability will inevitably make it difficult to predict the risky future. In order to make the Taiwan tourism industry in the shortest possible time, put forward effective countermeasures, in view of the future development. The prediction of the efficiency of Gray prediction model is very meaningful under limited and uncertain data. In this study, we use the gray theory to construct the forecasting of the dynamic situation under the uncertain environment and the incomplete information, using the two groups of mainland tourists from January to April in 2016 and from May to August in 2016 as samples. GM (1,1) and Gray Verhulst model is the more common choice. According to this study to predict the actual control of two models to the number of visitors to Taiwan tourists, the GM (1,1) model is more accurate than the Gray Verhulst model in terms of the number of tourists. Whether the errors or the number of future estimates of the month, GM (1,1) model can be based on the information to do the immediate response and anticipation.