Unlocking Uniqueness: Analyzing Online Reviews of Airbnb Experiences Using BERT-based Models

Abstract

As the tourism industry navigates post-pandemic recovery, understanding customer perceptions of uniqueness in tourism experiences is critical. It enables businesses to tailor offerings that stand out and attract travelers seeking novel and distinct experiences after a period of limited travel opportunities. The current study bridges this knowledge gap by employing the Bidirectional Encoder Representations from Transformers (BERT) model to analyze online reviews of Airbnb Experiences. BERT, a tool for contextual and sentiment analysis, aids us in identifying and categorizing experiences that contribute to value creation for tourists. We propose four dimensions of uniqueness, grounded in the service-dominant (S-D) logic framework. Our research enriches academic discourse surrounding the role of uniqueness in value creation and provides organizations with strategic insights into enhancing the distinctiveness of their offerings.