Jorge Calero-Sanz

About

Jorge Calero-Sanz is a leading researcher at the intersection of artificial intelligence, robotics, and the hospitality industry. His work focuses on how Industry 4.0 and 5.0 technologies—specifically service robots and machine learning—transform customer experiences and business ratings. Calero-Sanz’s major contribution lies in applying advanced text mining and AI techniques to decode User Generated Content (UGC) from platforms like TripAdvisor. His highly cited 2022 study (71 citations) pioneered the analysis of how robot implementation in hotels affects customer emotions and overall ratings, revealing a direct link between robotic interactions and guest satisfaction. A second influential paper (21 citations) developed a machine learning model to predict new hotel rating systems based on UGC, demonstrating how AI can uncover hidden consumer expectations. By bridging computational methods with tourism analytics, Calero-Sanz provides actionable insights for hoteliers adopting automation while ensuring human-centric service quality. His work is essential reading for researchers in hospitality technology, sentiment analysis, and the ethical deployment of AI in service industries.

Research Focus

Key Achievements

Top Papers

1. 1
   Does the Implementation of Robots in Hotels Influence the Overall TripAdvisor Rating? A Text Mining Analysis from the Industry 5.0 Approach

   71 citations · 2022
2. 2
   Predicting A New Hotel Rating System by Analysing UGC Content from Tripadvisor: Machine Learning Application to Analyse Service Robots Influence

   21 citations · 2022

Key Collaborators

Contact & Links