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Understanding the relationships between time and cost to improve supply chain performance

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  • Whicker, L.
  • Bernon, M.
  • Templar, S.
  • Mena, C.

Abstract

In today's global competitive market, the total cost of sourcing, manufacturing and delivery of products is a major driver of competitive advantage. However, the true cost of operations in many organisations is often unclear or misleading because supply chain processes transcend both functional and company boundaries and the limitations associated with traditional cost reporting systems. Some cost-based approaches have been developed to address these issues but they tend to focus on the traditional accounting functional view of an organisation and not extend to the business processes involved. Alternative approaches to improving supply chain performance, such as time-based methods, seek to improve efficiency by identifying and eliminating areas of non-value added activity in supply chain processes. Although using time as a measure can be an effective approach to increasing value in the supply chain there is limited understanding of the relationship between time and cost across supply chains. The paper investigates, through the use of an industrial case study, how analysis of both time and cost can be combined to provide a more accurate view of supply chain performance which can lead to better informed decision making. The subsequent analysis provides an insight into the relationship between time and cost in supply chain processes and demonstrates how product costs accumulate in the supply chain.

Suggested Citation

  • Whicker, L. & Bernon, M. & Templar, S. & Mena, C., 2009. "Understanding the relationships between time and cost to improve supply chain performance," International Journal of Production Economics, Elsevier, vol. 121(2), pages 641-650, October.
  • Handle: RePEc:eee:proeco:v:121:y:2009:i:2:p:641-650
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Abraham & Luo, Hao & Huang, George Q., 2013. "A bi-objective model for supply chain design of dispersed manufacturing in China," International Journal of Production Economics, Elsevier, vol. 146(1), pages 48-58.
    3. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "Evaluating the reliability of a stochastic distribution network in terms of minimal cuts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 75-97.
    4. Cheng-Fu Huang, 2019. "Evaluation of system reliability for a stochastic delivery-flow distribution network with inventory," Annals of Operations Research, Springer, vol. 277(1), pages 33-45, June.
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    6. Niu, Yi-Feng & Zhao, Xia & Xu, Xiu-Zhen & Zhang, Shi-Yun, 2023. "Reliability assessment of a stochastic-flow distribution network with carbon emission constraint," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Askarany, Davood & Yazdifar, Hassan, 2012. "An investigation into the mixed reported adoption rates for ABC: Evidence from Australia, New Zealand and the UK," International Journal of Production Economics, Elsevier, vol. 135(1), pages 430-439.

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