Analysing the potential of open hotel review databases for IEQ assessment: a text mining approach

Indoor Environmental Quality (IEQ) significantly affects occupants’ well-being and comfort. Assessing IEQ typically involves post-occupancy evaluation (POE), a method that can be time-consuming and particularly challenging in hotel settings, where guests may be disrupted by frequent requests for feedback. Hence, this paper investigates the capability of text mining to extract valuable information for IEQ assessment, such as identifying the main causes of IEQ dissatisfaction, detecting combined occurrences of IEQ aspects, and exploring the relationship between IEQ dissatisfaction and hotel attractiveness. To this aim, the study analysed 1494 five-star hotels in Europe, comprising 515,738 reviews. Among them, 13.1% contained references to keywords related to IEQ aspects. The major cause of dissatisfaction in hotels is acoustic (42.7% of the reviews), followed by thermal (35.7%), visual (11.1%) comfort, and IAQ (10.5%). Additionally, 9580 reviews demonstrated the co-occurrence of multiple IEQ aspects, highlighting the interplay between different aspects. Furthermore, the reviewer score, reflecting the hotel’s attractiveness, showed an inverse relationship with the percentage of dissatisfied guests regarding IEQ, highlighting the impact of the indoor environment on the hotel rating. Overall, text mining is effective in supporting IEQ assessment and the study underscores the effect of addressing IEQ aspects on a facility's overall appeal.