Service attributes for sustainable rural tourism from online comments: Tourist satisfaction perspective

Abstract

While there have been many tourism studies exploring business opportunities from online comments, research in the context of sustainable rural tourism is rare. In particular, practitioners involved in rural destinations are usually transformed from farmers who are relatively new to information technology and therefore unable to understand the voices of tourists in a timely and effective manner. Aiming to expand the literature on sustainable rural tourism, this study cuts from tourist satisfaction and proposes a mixed methodology to investigate insights for sustaining rural destinations from online comments. Specifically, the KMeans clustering algorithm is first utilized to discover service attributes that visitors value; then Importance-Performance Analysis (IPA), an effective satisfaction analysis tool, is adopted to understand tourist satisfaction; to develop specific sustainable strategies, using an advanced opinion extraction technique this work identified dissatisfaction factors of visitors. 5832 online comments of two adjacent rural destinations (i.e. Hongcun and Xidi) were crawled to validate the proposed methodology. Results show that five service attributes were discovered, including Natural environment, Price, Food, Hospitality, and Culture & heritage; Hongcun's Natural environment and Price require urgent measures, and its Food and Hospitality are at a competitive disadvantage compared to Xidi; detailed factors dissatisfying visitors were identified through opinion extraction technique, based on which specific sustainable strategies are generated for authorities and practitioners. By excavating business opportunities from online reviews via big data analysis and text mining techniques, the proposed methodology advances the academic understanding of promoting rural tourism.