Abstract
This paper introduces a methodology for activity-based modelling of customer profitability analysis (CPA) in hotels. It proposes a methodology for defining and effectively addressing cost drivers in the hotel industry. This study also combines three methods (association rule mining – ARM, simulation and ABC) for the purpose of making accurate cost estimations. Activity-based costing (ABC) uses as input the corresponding output produced by the simulation of the relevant cost drivers. The presented methodology eliminates the need to estimate empirical distributions of all simulated cost drivers. This is achieved with the use of data mining techniques, particularly ARM. ARM finds dependencies between a cost driver, whose estimation is time-consuming, with another cost driver, which can easily be calculated. This dependency can lead the user to the estimation or calculation of the former. The methodology provides more accurate accounting information with regards to the various market segments in the hotel industry in a CPA context.
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