Managing Virtual Rapport on TripAdvisor: Discourse in Hotel Responses to Negative Online Reviews

Abstract

Digital technology has immensely transformed communication, and social media facilitates online feedback mechanisms, empowering consumers' voices via online reviews. This has led to the pervasively growing influence of electronic word of mouth (eWOM) on customers' purchase intentions, as negative online reviews can be detrimental to business performance. Therefore, digital business engagement on online platforms is essential to ensure customer satisfaction and manage online reputation. Building on Spencer-Oatey's (2008) Rapport Management Model (RMM), this qualitative study explores the rapport management strategies used by eighteen Malaysian five-, four-and threestar hotels to respond to negative online reviews, from the perspective of the RMM discourse domain. The hotel responses were collected from TripAdvisor, using purposeful sampling and analysed with Computer-Mediated Discourse Analysis. The findings show that the five-and four-star hotels employed higher frequencies of moves in their responses to complaints in negative reviews. Some four-and three-star hotels took a more confrontational approach by using the sub-move 'denying problems'. In terms of RMM rapport orientation, this sub-move can be rapport-challenging in customer relationships. This study highlights that managing negative reviews more efficiently for service recovery on online platforms is essential to maintain customer relationships and establish a positive online corporate reputation. More generally, the findings provide insights on cultural rapport management strategies used in one Southeast Asian country-Malaysia.

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“…Previous studies have concluded that consumers generally trust information shared by other consumers more than information from the official sites of the brands themselves (Dabholkar & Sheng, 2012;Dellarocas et al, 2007). Different types of eWOM and their influence on consumer purchase intention and decision have been studied (Taw et al, 2022). Online ratings, either by score or by stars; reviews on e-commerce sites; external blogs; YouTube channels; and other social networks are the most extensively investigated types of user-generated content (Rentería-García et al, 2020;Prantl & Mičík, 2019).…”