The Signalling Attributes of Hotel Managerial Responses: An Analysis of Response Content through Text Mining on TripAdvisor
(A2025-126309)

AUTHORS

Badr-Eddine Lahsini, Africa Business School — University Mohammed VI Polytechnic; Ravi Ranjan, Africa Business School

ABSTRACT

In the competitive hospitality industry, online reviews are vital for customers to share experiences and assess service providers. For hotels, these reviews offer opportunities to engage with customers, manage reputation, and showcase a commitment to service improvement through strategic responses. Despite growing interest in how managerial responses influence customer satisfaction, ratings, and repeat visits, there is limited understanding of how specific response attributes differentiate high-quality from low-quality hotels. Using signalling theory, this study applies text mining and natural language processing to analyse how hotels utilise managerial responses to signal their commitment to service excellence. It focuses on the impact of response personalisation, Linguistic Style Matching (LSM), and standardisation on subsequent sentiment of problematic issues, offering insights into how these attributes convey quality.