From a strategy perspective, the growth of social media accelerates the need for tourism organisations to constantly re-appraise their competitive strategies. This study contributes theoretically to the tourism performance literature by validating a new approach to examining the determinants of hotel performance. Drawing from and extending prior hotel determinants studies, this study uses artificial neural network model with ten input variables to investigate the relationships among user generated online reviews, hotel characteristics, and Revpar. The sample includes 235 Swiss hotels for the period 2008-2010, with 59,688 positive reviews from 69 online sources. The empirical findings reveal four hidden nodes that have a significant impact on RevPar. Three of these have negative impacts: room quality, positive regional review, hotel regional reputation, and regional room star rating has a positive impact. Further, the findings imply that there may be boundaries to reputational benefits for Swiss hotels.