網際網路的興盛，使電子口碑成為影響消費者決策的重要原因。隨著觀光旅遊業的快速發展，遊客愈來愈在意旅遊品質，使其對無偏誤的旅遊資訊需求提高。而觀光工廠是台灣近年興起的旅遊景點，因此本研究針對觀光工廠的線上評論進行分析。
本研究運用大數據分析技術，先透過詞頻分析，建構目的地意象詞彙分群表，歸納出遊客的關注面向。再分別對各目的地意象下的文字評論進行情感分析，本研究將針對較負面情緒的意象進行評論回顧以揭示遊客失望之因。研究結果顯示，遊客的負面情緒主因為CP值低的感知，且遊客的情緒感受與滿意度呈正相關。故建議業者，應掌握遊客的需求，如：效益與收費的考量取捨或於停車場明顯處設置收費告示牌。最後，據本研究結果建議業者應在掌握遊客需求下，以改善及加強核心的經營重點之參考，並對後續相關學術研究者做參考之建議。

The growth of the Internet has led to a vast increase in online user reviews of business and a variety of different purchases, making electronic word of mouth (eWOM) an important factor in consumer decisions. As people start to focus more on the quality of the tourist experiences, the demand for unbiased travel information has increased particularly for the tourism industry. Recently, many local factories are becoming tourist destinations in Taiwan. For this reason, we chose tourism factories as our subject of study.
We first extracted the key dimensions by obtaining the relevant data of the tourism factories from Google Map combined with word frequency analysis and clusters of terms based on destination image. Then we applied sentiment analysis to analyze tourists’ online reviews corresponding to each destination image. We chose relatively negative categories for post-hoc analysis to reveal why tourists felt unpleasant. Furthermore, we used boxplot to examine the relationship between the tourists’ feeling and satisfaction. The findings provide useful insights for practice and future research in management.

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