Resumen de Recommend or not: A comparative analysis of customer reviews to uncover factors influencing explicit online recommendation behavior in peer-to-peer accommodation
Kai Ding, Xi Yung Gong, Tao Huang, Wei Chong Choo
In the fiercely competitive landscape of the peer-to-peer accommodation platform Airbnb, understanding customers’ online recommendation behavior is essential for optimizing competitiveness and harnessing the potential of electronic word-of-mouth. This study aims to provide comprehensive insights into the factors driving customers’ issuance of positive or negative recommendations based on their experiences. Leveraging 10,101 online reviews from Airbnb users, we employ the Structural Topic Model to determine latent topics relating to customers’ recommendation intentions. This study reveals that positive recommendations are primarily influenced by hedonic values tied to the overall experience, including crucial aspects such as convenience for exploring points of interest, local authenticity, social interaction, and emotional fulfillment. These findings highlight the significance of providing memorable and enriching experiences to elicit positive reviews from customers. On the other hand, negative recommendations are closely linked to utilitarian values focused on practical concerns such as check-in procedures, cleanliness, comfortableness, and amenities. Understanding these utilitarian factors is vital for hosts and platform administrators to improve service quality and address potential issues that may lead to negative reviews. Furthermore, this study emphasizes the significant role of hosts in shaping both positive and negative recommendations. This research contributes valuable insights to the field of peer-to-peer accommodation, highlighting the significance of various factors influencing customers’ recommendation behavior.
