Purpose: This study aims to propose a model to explain online review helpfulness grounded on both previously identified constructs (e.g. review length) and new ones, which have been analyzed in other online reviews’ contexts but not to explain helpfulness. Design/methodology/approach: A total of 112,856 reviews published in TripAdvisor about 21 Las Vegas hotels were collected and a random forest model was trained to assess if a review has received a helpful vote or not. Findings: After confirming the validity of the proposed model, each of the constructs was evaluated to assess its contribution to explaining helpfulness. Specifically, a newly proposed construct, the response lag of the manager’s replies to reviews, was among the most relevant constructs. Originality/value: The achieved results suggest that hoteliers should invest not only in responding to the most interesting reviews from the hotel’s perspective but also that they should do it quickly to increase the likeliness of the review being considered helpful to others.

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Online reviews,Helpfulness,Hospitality,Social media,TripAdvisor

• Ciências da Computação e da Informação - Ciências Naturais
• Outras Ciências Sociais - Ciências Sociais