線上消費者的評分和評論，在引導潛在消費者做出購買決策的過程中扮演著越趨重要的角色。然而令人感到疑惑的是，許多時候評分星等和評論敘述有不一致的情形，例如有評論充斥著負面詞彙卻獲得滿分星等。本研究旨在檢驗日本旅客的評分和評論是否會對台灣旅館中的實際來客造成影響，以及評分和評論情緒之間是否有不一致之處。本文研究2012至2019年間日籍旅客入住旅館後在TripAdvisor留下之評論，結合各家旅館日籍旅客的真實入住人次，希望找到過去八年間影響日籍旅客入住台灣旅館的重要口碑因素，進而吸引疫後日本旅客人潮回流，加速台灣觀光旅遊產業之復甦。
在研究中，首先運用固定效果模型分析口碑變數對日籍來客數的長期影響，為值對值關聯的分析。為了檢視口碑變數的變動和日籍來客數變動的關聯，又延伸出以一階差分法運用追蹤資料的設計。結果顯示日文評分和評論情緒並不一致。在固定效果的長期觀察下，評論數量多或評論情緒正面皆會使得旅館的日籍來客數增加。然而在一階差分的短期變動下，前一個月的評論數增加，將導致下一個月的來客數減少。

Online consumer ratings and textual comments are playing an increasingly important role in guiding potential consumers to make purchasing decisions. However, it is puzzling to find that the star ratings and review texts are inconsistent in many cases—such as a review full of negative words, but with a full star rating. This research is aimed to examine whether ratings or reviews by Japanese travelers have an impact on the actual number of visitors in the hotel industry of Taiwan, and whether there is any inconsistency between ratings and sentiment of reviews. This paper studies the reviews left by Japanese on TripAdvisor from 2012 to 2019, combined with the actual number of Japanese guests in each hotel, in order to identify the important factors that have influenced Japanese tourists’ choice of hotels in Taiwan over the past eight years. These findings can help to encourage the return of Japanese visitors after the pandemic, and accelerate the Taiwanese tourism industry’s recovery.
In this study, the fixed-effects model is used to analyze the long-term effects of the eWOM variables on the number of Japanese visitors, which is the analysis of value-to-value correlations. In order to examine the correlation between the change of the eWOM variables and the change of the number of Japanese visitors, the first-difference estimator is extended so as to use the design of panel data. The results show that ratings and sentiment of reviews are inconsistent in Japanese reviews. Under the long-term observation of the fixed-effects estimator, the review volume and sentiment positively affect the number of Japanese tourists. However, under the short-term change of the first-difference estimator, an increase in the review volume in the previous month leads to a decrease in the number of Japanese visitors in the next month.

Thesis Validation Letter i
Abstract (Chinese) ii
Abstract (English) iii
Table of Contents iv
Table of Figures v
Table of Tables vi
1 Introduction 1
1.1 Research Motivation 1
1.2 Research Background 2
1.3 Research Questions 4
2 Literature Review 6
2.1 Electronic Word of Mouth 6
2.2 Sentiment Analysis 7
2.3 Model 10
3 Methodology 12
3.1 Data Collection 12
3.2 Data Processing 15
3.3 Data Variables 18
3.4 Empirical Method 19
4 Result 24
4.1 Descriptive Statistics 24
4.2 Analysis of Customer Sentiment and Ratings 28
4.3 Analysis of eWOM variables and Japanese visitors 30
5 Conclusion 34
5.1 Research Conclusion 34
5.2 Limitations and Recommendations 36
References 38

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