This paper seeks to demonstrate an application of a methodology, which is based on the integration of three techniques, with the purpose of modelling activity‐based costing (ABC) in restaurants. The proposed methodology serves as a tool for effectively computing values of cost drivers in the restaurant industry, as well as making accurate cost estimations.
The methodology is based on the integration of three techniques: simulation modelling, association rule mining (ARM) and ABC. Simulation modelling is used to model process variability and produce a range of cost values, instead of a point estimate of the cost, by generating a range of values for the simulated cost drivers. The advantage of the proposed methodology lies on the effective utilization of ARM in the ABC model; it extracts dependencies between a cost driver, whose estimation is time‐consuming, with another cost driver, which can easily be calculated. These associations can assist the estimation of the empirical distributions of those cost drivers, which were difficult to calculate.
The extracted associations verify the hypothetical relations between the cost drivers. The output produced is more precise values of the cost drivers that are included in an ABC model and were difficult to estimate. More accurate cost estimate means better pricing decisions for the restaurant managers.
The proposed methodology is an innovative technique that provides more accurate accounting information in the restaurant industry.
