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Determining sourcing strategies: a decision model based on activity and cost driver information

Author

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  • Z Degraeve

    (Katholieke Universiteit Leuven)

  • F Roodhooft

    (Katholieke Universiteit Leuven)

Abstract

Determining sourcing strategies for different material groups provides a major challenge to most companies. There has been little research on the choice of the optimal number of different suppliers for a given product group and the determination of their market shares. In this paper we propose a mathematical programming model using activity based costing information to determine optimal order splitting among suppliers on the basis of the different costs associated with the purchasing decision. We argue that sourcing strategies should be based on the minimisation of the total cost of ownership resulting from external purchases. We demonstrate the model by a real life case regarding the procurement of ball bearings at Cockerill Sambre S.A., a Belgian multinational steel producer. This decision support system is currently used by the company. This case resulted in the decision by management to develop comprehensive, company wide purchasing software using our mathematical program based on the total cost of ownership concept.

Suggested Citation

  • Z Degraeve & F Roodhooft, 1998. "Determining sourcing strategies: a decision model based on activity and cost driver information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 49(8), pages 781-789, August.
    • Handle: RePEc:pal:jorsoc:v:49:y:1998:i:8:d:10.1057_palgrave.jors.2600589
    DOI: 10.1057/palgrave.jors.2600589
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    Citations

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    Cited by:

    1. Singer, Marcos & Donoso, Patricio, 2008. "Empirical validation of an activity-based optimization system," International Journal of Production Economics, Elsevier, vol. 113(1), pages 335-345, May.
    2. Yahya, Salleh & Kingsman, Brian, 2002. "Modelling a multi-objective allocation problem in a government sponsored entrepreneur development programme," European Journal of Operational Research, Elsevier, vol. 136(2), pages 430-448, January.
    3. Andrea Bacchetti & Stefano Bonetti & Marco Perona & Nicola Saccani, 2018. "Investment and Management Decisions in Aluminium Melting: A Total Cost of Ownership Model and Practical Applications," Sustainability, MDPI, vol. 10(9), pages 1-36, September.
    4. Z Degraeve & F Roodhooft & B van Doveren, 2005. "The use of total cost of ownership for strategic procurement: a company-wide management information system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(1), pages 51-59, January.
    5. Degraeve, Zeger & Labro, Eva & Roodhooft, Filip, 2000. "An evaluation of vendor selection models from a total cost of ownership perspective," European Journal of Operational Research, Elsevier, vol. 125(1), pages 34-58, August.
    6. Tanskanen, Kari & Ahola, Tuomas & Aminoff, Anna & Bragge, Johanna & Kaipia, Riikka & Kauppi, Katri, 2017. "Towards evidence-based management of external resources: Developing design propositions and future research avenues through research synthesis," Research Policy, Elsevier, vol. 46(6), pages 1087-1105.
    7. Singer, Marcos & Donoso, Patricio, 2006. "Strategic decision-making at a steel manufacturer assisted by linear programming," Journal of Business Research, Elsevier, vol. 59(3), pages 387-390, March.
    8. Moisello Anna Maria, 2012. "Cost Measurement And Cost Management In Target Costing," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 533-547, July.

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