Improving activity-based costing heuristics by higher-level cost drivers
Activity-based costing (ABC) tries to allocate overhead costs to cost objects more accurately than traditional cost systems. However, since ABC proportionalizes overhead costs it is a heuristic. The paper uses simulations and mixed-integer programming to analyze the extent of the sub-optimality incurred by ABC-heuristics. While previous research has focused on ABC systems with a simple set of cost drivers, thereby restricting the potential of ABC as a heuristic, the paper analyzes the effects of establishing a cost driver corresponding to a higher cost level. Specifically, a portfolio-based cost driver captures the demand heterogeneity triggered by the portfolio. This heterogeneity driver is then used to proportionalize all costs due to inflexible overhead resources. One of the main findings is that such a heterogeneity driver improves the quality of ABC-heuristics significantly.
activity-based costing heuristics simulation mixed-integer programming