doi: 10.18178/joebm.2020.8.1.607
Combining the Cost Drivers Based on the Singular Value Decomposition of Matrix
Xudanyang Li 1
,
Buxi Li 2
- 1 Business School, University of Newcastle, Newcastle, CO 2308 Australia.
- 2 School of Economics and Management, Shanxi University, Taiyuan, CO 030006 China.
Abstract
Reducing the complexity of activity-based costing system is one of the key factor when successfully implement the activity-based costing system. Based on dimensionality reduction of the singular value decomposition (SVD) of the matrix, this paper proposes and researches the method of SVD-based combination of cost drivers under activity-based costing. Through singular value’s decomposition for coefficient matrix in the costing model under activity-based costing, this paper classifies the cost drivers based on singular values and eigenvectors in the right singular matrix. On this basis, using integer programming, representative cost drivers are selected for combination to simplify the activity-based costing model. Numerical examples indicate that the method of SVD-based combination of cost drivers reduces the complexity of activity-based costing system and significantly improves the accuracy of the combined product cost. The result shows, whether reducing model complexity or ensuring product cost accuracy, the method of SVD-based combination of cost drivers is superior to the existing other methods, such as integer programming method, clustering method, etc.
Keywords
- Activity-based costing
- product costing model
- combination of cost drivers
- SVD of matrix
How to Cite
Xudanyang Li and Buxi Li, "Combining the Cost Drivers Based on the Singular Value Decomposition of Matrix," Journal of Economics, Business and Management, vol. 8, no. 1, pp. 23-29, 2020. https://doi.org/10.18178/joebm.2020.8.1.607
Copyright & License
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).