| 摘要註: |
本研究以墾丁國家公園遊客為研究對象，主要目的在瞭解墾丁國家公園遊客的旅遊動機、滿意度與旅遊後行為意向。所以本研究以便利取樣方式，共發放了466份問卷，扣除無效問卷94份後，得有效問卷為372份，有效問卷率為79.8%。本研究採用問卷調查法，所得資料以信度分析、描述性統計、集群分析、單因子變異數分析、與Pearson相關檢定分析等統計方法進行資料分析。經過資料分析後得到以下之結果：一、受訪遊客之基本資料分析：以女性遊客居多(51.3%)、年齡以20到29歲比例最高(40.9%)、婚姻狀況以未婚者居多(59.4%)、教育程度以大學最多(53.2%)、職業為學生比例最高(33.2%)、個人每月可支配所得以1萬以下最多(25.0%)，家庭每月可支配所得以1萬5千到3萬所佔比例最多(20.4%)。二、旅遊動機集群分析：以旅遊動機因子為基礎進行集群分析，識別出不同旅遊動機之遊客集群，包括積極進取型、消極參與型和均衡發展型，且不同的旅遊動機集群在滿意度、推薦意願上有顯著性差異。三、相關分析：旅遊動機與滿意度呈正相關，滿意度與推薦意願呈正相關，且滿意度與重遊意願呈正相關。 This research has its research target based on the tourists of Kenting National Park. The main objective of this research is to understand the tourist motive, satisfaction and the behavior intention after the tour for the tourists of Kenting National Park. Therefore, convenience sampling method is adopted for this research and a total of 466 copies of questionnaires are issued, after a deduction of invalid questionnaires of 94 copies, the effective questionnaires obtained are 372 copies, that is, the return rate is 79.8%. Moreover, in this research, questionnaire survey method was adopted, and the obtained data were done with reliability analysis, descriptive statistics, clustering analysis, one-way analysis of variance and Pearson’s analysis of correlation. After data analysis, the following results are obtained: 1. The basic data analysis of the tourists under interview: Female tourists have the highest percentage (51.3%), 20~ 29 years old tourists have the highest percentage (40.9%), for the marital status, the unmarried has the highest percentage (59.4%), for the educational background, those with BA degree have the highest percentage (53.2%), for the occupation, student has the highest percentage (33.2%), for the monthly disposable income of an individual, those below ten thousand NT dollars have the highest percentage (25.0%), for the family monthly disposable income, those between 15000 to 30000 NT dollars occupy the highest percentage (20.4%). 2. Tourism motive clustering analysis: Here, tourism motive factor is used as basis to perform clustering analysis so as to identify tourist clusters of different tourism motives, for example, aggressive and active type, passively participating type and uniformly developing type, moreover, different tourism motive clusters show significant difference in terms of satisfaction and willingness to recommend. 3. Correlation analysis: Positive correlation is seen between tourism motive and satisfaction, positive correlation is seen between satisfaction and willingness to recommend, and positive correlation is seen between satisfaction and willingness to re-visit. |