This study attempts to explore the service attributes, satisfaction, and sentiment of food tour experiences. Four food tour operators located in Taiwan were selected as the study sample, and their customer reviews on three social media platforms (i.e., TripAdvisor, Google, and Facebook) were collected. A total of 766 reviews were obtained. The data were pre-processed and the final dataset consisted of 99 pages of text with 47,450 words. The concept map produced by Leximancer reveals salient themes based on the reviews, including “tour”, “market”, “guide”, “fun” and “walking”. Other notable themes being identified include “history”, “delicious”, “interesting places”, and “experience”. These themes reflect salient service attributes that food tour participants valued. Sentiment analysis results revealed a very high proportion of “moderately positive” and “very positive” sentiments in the reviews, indicating that food tour experiences offered by the sample were perceived as positive by the participants. The results correspond with the online review ratings of these four tour operators (ranged from 4.9 to 5.0). Most of the positive sentiments identified are related to the food and the tour guide, suggesting the importance of both attributes. A number of positive sentiments revolve around the evidence of thoughtfulness or care shown in the arrangement of the food tour. Conversely, some negative sentiments were found to be related to the perceived value and deficiencies in the arrangement of the food tour. Given the lack of research in examining food tour systematically, the findings of this interpretivist study are believed to offer important theoretical and practical insights into the salient service attributes, satisfaction level and sentiment of food tour experiences. Such knowledge would be valuable for future research and conceptual elaboration in the field, as well as crucial in designing, planning and executing successful food tours.
|Effective start/end date||2019/08/01 → 2021/07/31|
- food tour
- service attributes
- text mining
- sentiment analysis
- online reviews
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