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Deciding product mix based on time-driven activity-based costing by mixed integer programming

Listed author(s):
  • Zheng-Yun Zhuang


    (Zhejiang University)

  • Shu-Chin Chang


    (Chung Yuan Christian University)

Registered author(s):

    Abstract To determine a product mix for a production process, this study proposes a mixed-integer programming (MIP) model, based on the time-driven activity-based costing (TDABC) accounting system. By using a time driver from the resource to the cost objects and simultaneously dealing with numerous resource limitations, the model obtains a global optimal decision. The model highlights the difference between supply and the use of the capacity. It avoids some possible limitations of the programming modeling approach when theory of constraints (TOC) or activity-based-costing (ABC) is used. The model is illustrated using a numerical example. In the form of a budgeted income statement, the results for the formulated MIP models that use TOC, ABC and TDABC are compared, in terms of resource-used-based profit, resource-supplied-based profit and cash flow. The proposed MIP model that uses TDABC is shown to support a product mix decision, on which studies of TDABC seldom focus. Implications for the use of this accounting system adoption to determine product-mix are detailed.

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    Article provided by Springer in its journal Journal of Intelligent Manufacturing.

    Volume (Year): 28 (2017)
    Issue (Month): 4 (April)
    Pages: 959-974

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    Handle: RePEc:spr:joinma:v:28:y:2017:i:4:d:10.1007_s10845-014-1032-2
    DOI: 10.1007/s10845-014-1032-2
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    1. Gong, Zhejun & Hu, Sun, 2008. "An economic evaluation model of product mix flexibility," Omega, Elsevier, vol. 36(5), pages 852-864, October.
    2. Michel Gervais & Yves Levant & Charles Ducrocq, 2010. "Time-Driven Activity-Based Costing (TDABC): An Initial Appraisal through a Longitudinal Case Study," Post-Print halshs-00555218, HAL.
    3. Lea, Bih-Ru & Fredendall, Lawrence D., 2002. "The impact of management accounting, product structure, product mix algorithm, and planning horizon on manufacturing performance," International Journal of Production Economics, Elsevier, vol. 79(3), pages 279-299, October.
    4. Shapiro, Jeremy F., 1999. "On the connections among activity-based costing, mathematical programming models for analyzing strategic decisions, and the resource-based view of the firm," European Journal of Operational Research, Elsevier, vol. 118(2), pages 295-314, October.
    5. Plenert, Gerhard, 1993. "Optimizing theory of constraints when multiple constrained resources exist," European Journal of Operational Research, Elsevier, vol. 70(1), pages 126-133, October.
    6. Kee, Robert, 2008. "The sufficiency of product and variable costs for production-related decisions when economies of scope are present," International Journal of Production Economics, Elsevier, vol. 114(2), pages 682-696, August.
    7. Kee, Robert & Schmidt, Charles, 2000. "A comparative analysis of utilizing activity-based costing and the theory of constraints for making product-mix decisions," International Journal of Production Economics, Elsevier, vol. 63(1), pages 1-17, January.
    8. Ratnatunga, Janek & Tse, Michael S.C. & Balachandran, Kashi R., 2012. "Cost Management in Sri Lanka: A Case Study on Volume, Activity and Time as Cost Drivers," The International Journal of Accounting, Elsevier, vol. 47(3), pages 281-301.
    9. Bakke, Nils Arne & Hellberg, Roland, 1991. "Relevance lost? A critical discussion of different cost accounting principles in connection with decision making for both short and long term production scheduling," International Journal of Production Economics, Elsevier, vol. 24(1-2), pages 1-9, November.
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