Evaluation of Cost Drivers with Fuzzy AHP and Fuzzy TOPSIS Methods
Abstract
Cost drivers are tools used to allocate production overheads to products or services. Although these tools vary according to the nature of the activity performed, they guide managers in determining the costs of products or services. Despite this strategic role, they are used in most businesses with intuitive approaches. This attitude causes erroneous results in cost calculations, making it difficult to manage production costs effectively.
The aim of this study is to evaluate the cost drivers used in the calculation of production costs with scientific approaches and to make suggestions to the practitioners. For this purpose, cost drivers were evaluated by using AHP and TOPSIS methods, which are multi-criteria decision making methods, with an integrated approach, and suggestions were made for practitioners to overcome these difficulties. In the evaluation process, the criteria used in determining the cost drivers were AHP, and the TOPSIS method was used in the ranking of the cost drivers To minimize the subjective effects of the data used in the research, AHP and TOPSIS methods are integrated with fuzzy set theory.
As a result of the analyzes made, it has been determined that the most effective criterion in the selection of cost drivers is the performance improvement criterion, while the other criteria, which are followed by the criteria of suitability for activity, being understandable and being related to the cost, have a very low effect. However, it has been seen that the most appropriate cost distribution key for the company is the general overhead costs.
Metrics
References
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