近幾年來,國際旅遊市場已成為全球最具發展潛力的產業,亦是台灣政府積極推動的產業之一。2003年受到「SARS」疫情的影響,台灣觀光市場遭受重大衝擊,導致來台遊客數量與產值普遍下降。因此,台灣觀光局便致力於發展相關旅遊事業,不僅開放了大陸人士來台觀光,同時亦舉辦了許多觀光活動與計劃,以吸引國際旅客來台旅遊。 根據過去的研究指出,有效地維護舊有的顧客,並且讓顧客對於公司產生高度的忠誠度,遠比不斷地開發新顧客,還來得重要許多。而且透過既有顧客間的口耳相傳,不但可節省許多廣告成本,亦可讓新顧客加速產生高度信任。 旅遊動機是人們引發旅遊活動的起因,擁有高度的滿意度可與遊客建立良好且長期的關係,進而達到旅客願意再次重遊。本研究目的為分析旅客之旅遊動機、滿意度、重遊意願及其間之關係,以提供相關旅遊業者做為未來經營管理與規劃活動之參考。換言之,基於所提出的研究架構,期望去建立一個重複性旅客的預測模式,來幫助預測旅客重遊的意願,並找到旅客願意重遊的主要因素。 研究結果顯示,旅客來台最主要的動機為「現代化與基礎建設」、「氣候與環境」、「台灣特有風俗民情」、「夜市和娛樂」、「增長知識」、「放鬆與逃避壓力」、「刺激」及「團聚」。而依據不同的社經特性,旅客的旅遊動機、滿意度與重遊意願亦有顯著的差別。在確立研究假設成立後,運用二元邏輯迴歸、支援向量機與CLC進行重遊旅客的預測,結果發現三種方法皆擁有相當好的預測能力。
Global tourism has become one of the most potent industries in the world in recent years. Simiarly, tourism has been gaining popularity in past years in Taiwan. After the effect of Severe Acute Respiratory Syndrome (SARS), the Taiwan government started to open the door of Taiwan tourism to the people from mainland China and held many activities to attract tourists. After the review of literature, it is costly to capture new customers from competitors because a greater degree of service improvement is needed to convince customers to switch from competitors. Hence, methods that can forecast repeat visitation accurately are greatly needed. The purposes of this study are to build predictive models and find the main factors for repeat visitation. In addition this study mainly investigates the relationship amng travel motivation, tourist satisfaction and intention of repeat visitation. A total of 307 questionaires were found valid and the findings of this study are summarized as follows. First of all, the results indicated that the main motivations of traveling in Taiwna are “Modernity and infrastructure,” “Climate and surroundings,” “Differebt cultures,” “Nightlife and entertainment,” “Education and knowledge,” “Relaxation and escaping,” Exciting” and “Togetherness.” In addition, some siginificant differences were foumd between demographic characteristics of tourists and the three construct, travel motivations, tourist satisfaction, and repeat visitation. Moreover, the positive relationship among travel motivation, tourist satisfaction and repeat visitation was identified. That explained travel motivations drive people to travel. With travel experience, tourists have some levels of satisfaction, which can directly lead to the intention of repeat visitation. Finally, three predictive models were constructed by Binary Logistic Regression, Support Vector Machines and Clustering-Launched Clssification. The three models possessed good predictive ability.
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