Data science in supporting hotel management: Application of predictive models to Booking.com guest evaluations

Abstract

Data science is a multidisciplinary area that gathers several branches, such as statistics, databases, and computer science and whose importance has become more substantial over the last few years. Using several techniques and algorithms from machine learning allows us to understand how certain variables are related, as well as to visualize data and make predictions. This paper aims to use data science as a strategic instrument for the hospitality industry by proposing a model that can help to predict which characteristics will be more valued by guests. By better understanding which features guests value most when evaluating a stay at a hotel, it will be easier for hotel managers to make informed decisions about which service operations management strategies should be used. It can also be helpful in terms of investment decisions, as it can indicate which aspects will be most important to value in a hotel. In this research, it was possible to conclude that guests’ ratings are related primarily to the commodities available at the hotels, followed by cleanliness, staff, location, price-quality relation, and comfort.