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Title: 台灣地區外籍觀光旅客人數預測模式之探討
Other Titles: Analysis of Population Forecasting Models of the Foreign Tourists of Taiwan
Authors: 吳柏林;賴家瑞;劉勇杉
Wu, Berlin;Lia, Jerry;Liu, Ycong-ahan
Contributors: 應數系
Keywords: 外籍觀光人口數;意願分析;匯率;消費者物價指數;數列神經網路;預測
Tourists;Motivations analysis;Seasonal ARMA model;State space model;Neural networks;Forecasing
Date: 1994-03
Issue Date: 2016-10-18 12:14:16 (UTC+8)
Abstract: 由於台灣地區國民所得大幅提高,休閒旅遊業愈來愈受到重視。加上為了配合政策上的產業轉型要求,政府積極推動素有無煙囪工業之稱的觀光事業,使得來台觀光之外籍觀光客人數有逐年增加的趨勢。但自1989年來華旅客突破二百萬人次之後,卻又呈衰退現象,觀光局及觀光旅遊業者均感重視。觀光客之多寡直接影響本地觀光業者及政府對整體觀光環境之政策與投資。不準確的評估將造成觀光資源的浪費,因此對未來之外籍觀光人口數,作一個總體的意願分析與建立一個適當的預測模型是亟其必要。本文即以歷年來外籍觀光客人數與各種主要經濟指標作一個意願分析,並應用時間數列方法與神經網路模式,建構外籍觀光客人數預測模式,並比較其結果。
During the second half of the twentieth century, tourism has become one of the largest and most rapidly growing sectors in the world economy. The policy and investment about the tourism are heavily affected by the population of tourist. Inspropriate prediction for the population of toturist will lead to wasting the source of tourism. In this paper, we first survey the motivations of tourists visiting. Then we build certain models to forecast the population of foreign tourist of Taiwan in the following years. Three approaches are used, i.e., seasonal ARMA model, state space model, and neural networks computing, in the estimating and forecasting the population of foreign tourist. Finally, we compare the forecasting performance for these models.
Relation: 國立政治大學學報, 68 part 2,267-295
Data Type: article
Appears in Collections:[第68期] 期刊論文

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