Predicting the cleaning time of hotel rooms based on guests characteristics

Gal Oblak (2018) Predicting the cleaning time of hotel rooms based on guests characteristics. EngD thesis.

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Abstract

Data science is becoming more and more relevant due to the increasing amount of data generated every day. The aim of our Bachelor’s thesis was to assist a company that offers computer solutions to support hotel processes and collects series of data generated during these processes. Firstly, the methods that are used in predicting are presented. Then, the approach of predicting the duration of room cleaning and the construction of predictive models is defined. The goal of our thesis was to identify the profiles of guests that effect longer or shorter room cleaning time by using data analysis and producing various predictive models. Another goal was to define variables that actually affect the length of the cleaning. The results of the analysis showed that for the development of more precise forecasting models, more variables related primarily to the hotel are needed, but also having data of several different hotels is crucial. Created models were designed for individual hotel due to large differences among the time needed for room cleaning in different hotels. The results contributed to a better understanding of factors that influence the time of cleaning.

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