TOURISM SUSTAINABLE DEVELOPMENT THROUGH BUSINESS MODEL RECONFIGURATION: TRADITIONAL AND DATA-DRIVEN COMPUTATIONAL INTELLIGENCE EVIDENCE FROM APULIA

This study develops a computational framework based on survey data to evaluate the key characteristics of firms operating in the tourism sector. Survey responses were collected and transformed into categorical and continuous variables, followed by meaningful preprocessing to reduce dimensionality and ensure analytical robustness. The set of data was then analyzed using a combination of traditional quantitative methods—such as regression and classification—and data-driven artificial intelligence approaches, with the objective of predicting firms’ revenue growth and sustainability over a four-year period.