Is AI really better than conventional methods to identify the key drivers of firms’ performance? An exploratory study in the hospitality industry

ANNs are a key theme in tourism and hospitality. However, they haven't been widely employed to identify internal and external determinants of firms' performance. Based on a dataset of daily hotels' reservations, we demonstrate the capability of a specific unsupervised ANN (Auto Contractive Map - CM) to outperform other methods in assessing the hidden connections among variables and providing guidelines for hotel managers to improve competitive performance. Since AutoCM results are static, they could be enriched by dynamic simulation tools to measure the impact of the variation of key determinants of company's performance on the entire data ecosystem.