A Study Modelling of Fuzzy Activity-Based Cost Approach to Evaluate the Accuracy of Indirect Cost Allocation Under Data Uncertainty
A Study Modelling of Fuzzy Activity-Based Cost Approach to Evaluate the Accuracy of Indirect Cost Allocation Under Data Uncertainty

Summary/Abstract: Technological developments such as digital transformation and artificial intelligence have affected the way manufacturing is done and therefore the way costs are calculated; this has led to changes in the structure and dynamics of costs compared to previous methods. The traditional approach to costing has resulted in inaccurate assessments of costs, consistently distorting the costs of products and services and providing misleading data to decision makers within organizations which rely upon it. Therefore, organizations are required to develop and implement cost systems and cost management practices to maintain their competitive advantage and meet the needs of their customers. Activity-based costing is one of the most effective cost management practices available today because it provides accurate data for allocating indirect costs to products and/or services. However, activity-based costing systems require continuous and comprehensive improvements in the collection and analysis of data. As a result, there is often little value placed on the data collected from activity-based costing systems due to the variability and ambiguity inherent in all systems, especially those operating in today’s rapidly changing automated industry. To address these problems and improve the accuracy of cost estimates and increase the reliability of the results, fuzzy logic was applied as a concept and methodology that reduces the ambiguity and uncertainty associated with estimating cost drivers using activity-based costing systems so that managers receive reliable and relevant information when assessing the cost of products and/or services.

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