The Product Variety Costing Method (PVCM): A Data-Driven Approach to Resource Allocation and Cost Evaluation

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Publicado en:Machines vol. 13, no. 12 (2025), p. 1137-1160
Autor principal: Nørgaard Morten
Otros Autores: Grønvald Jakob Meinertz, Christensen Carsten Keinicke Fjord, Mortensen, Niels Henrik
Publicado:
MDPI AG
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Acceso en línea:Citation/Abstract
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Descripción
Resumen:This study introduces the Product Variety Costing Method (PVCM), a data-driven framework that addresses the limitations of existing costing approaches, which fail to accurately present the cost of product and part variety, thereby constraining cost-informed decision-making in modular product development. Traditional cost allocation methods often lack one or more of the following: a full life-cycle perspective, a lower level of granularity according to the product structure, or a combined integration of qualitative and quantitative data. The PVCM bridges these gaps by combining Time-Driven Activity-Based Costing (TDABC) with hierarchical product structures and empirical enterprise data, enabling the quantification of variety-induced resource consumption across components, subsystems, and complete products. An industrial application demonstrates that the PVCM enhances cost accuracy and transparency by linking resource use directly to specific product abstraction levels, thereby highlighting the true cost impact of product variety. In this case, results revealed deviations of up to 60% in the adjusted contribution margin ratio relative to traditional overhead-based methods, clearly indicating the influence of product variety on cost assessments. The method supports design and managerial decision-making by allowing evaluation of modularization based on detailed cost insights. While the study’s scope is limited to selected life-cycle phases and a single company case, the findings highlight the method’s future potential as a generalizable tool for evaluating economic benefits of modularization. Ultimately, the PVCM contributes to a more transparent and analytically grounded understanding of the cost of variety in complex product portfolios.
ISSN:2075-1702
DOI:10.3390/machines13121137
Fuente:Engineering Database