The issue of allocating human resources costs in a realistic manner to products, processes, activities and individual employees has been an issue of research and practice in the field of accounting during the last two decades. The major problem is that the cost of calculating human resources costs has proven to be very high in the vast majority of cases. Also, in the vast majority of approaches the validity of the calculation of time allocated to resource usage has been questioned putting costing estimations in doubt. Approaches like activity based costing have been enhanced by incorporating the element of Time and led to the creation of the so called Time Driven activity based costing approaches. However, even these approaches are depended on the calculations of unit costs of time usage per resource and in the majority of cases have also been questioned if unit costs have been calculated correctly and also if the time allocated to individual employees per activity are realistic. Our research presented in this paper proposes the use of a process mining approach for human resource cost estimations based on data-records captured in event logs that enhances existing Time Driven activity based costing approaches.
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