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The performance evaluation of SCOR sourcing process--The case study of Taiwan's TFT-LCD industry

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  • Hwang, Yeong-Dong
  • Lin, Yi-Ching
  • Lyu Jr., Jung

Abstract

The supply chain operations reference (SCOR) model, proposed by the supply chain council (SCC), is a standard for supply chain performance evaluation model, which has been widely embraced by many modern organizations. The SCOR model enables enterprises to analyse their supply chain performance in a systematic way, to enhance communication among the members in the supply chain, and to design a better supply chain network. To further improve the performance of the sourcing process, which is critical to many industries, this research investigates the sourcing processes and their accompanied performance metrics in the SCOR model version 7.0. The supply chain of thin film transistor-liquid crystal display (TFT-LCD) industry in Taiwan is the subject. Using the questionnaire survey to collect empirical information, the regression model was applied to examine the sourcing process of SCOR at level 2 and its performance metrics. The results obtained were further extended for discussion on the sourcing process of level 3. In addition, this article also elaborates the institutionalization of the SCOR model and justifies the project planning system based on the SCOR model. It is illustrated that the proposed approach is feasible and valuable to supply chain managers in decision-making on various industries.

Suggested Citation

  • Hwang, Yeong-Dong & Lin, Yi-Ching & Lyu Jr., Jung, 2008. "The performance evaluation of SCOR sourcing process--The case study of Taiwan's TFT-LCD industry," International Journal of Production Economics, Elsevier, vol. 115(2), pages 411-423, October.
    • Handle: RePEc:eee:proeco:v:115:y:2008:i:2:p:411-423
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    References listed on IDEAS

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    1. Scott Stephens, 2001. "Supply Chain Operations Reference Model Version 5.0: A New Tool to Improve Supply Chain Efficiency and Achieve Best Practice," Information Systems Frontiers, Springer, vol. 3(4), pages 471-476, December.
    2. Wang, Ge & Huang, Samuel H. & Dismukes, John P., 2004. "Product-driven supply chain selection using integrated multi-criteria decision-making methodology," International Journal of Production Economics, Elsevier, vol. 91(1), pages 1-15, September.
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    5. Kamble, Sachin S. & Gunasekaran, Angappa & Gawankar, Shradha A., 2020. "Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 219(C), pages 179-194.
    6. Ntabe, E.N. & LeBel, L. & Munson, A.D. & Santa-Eulalia, L.A., 2015. "A systematic literature review of the supply chain operations reference (SCOR) model application with special attention to environmental issues," International Journal of Production Economics, Elsevier, vol. 169(C), pages 310-332.
    7. Lo, Chris K.Y. & Yeung, Andy C.L. & Cheng, T.C.E., 2009. "ISO 9000 and supply chain efficiency: Empirical evidence on inventory and account receivable days," International Journal of Production Economics, Elsevier, vol. 118(2), pages 367-374, April.
    8. Yuan, Xue-Ming & Low, Joyce M.W. & Ching Tang, Loon, 2010. "Roles of the airport and logistics services on the economic outcomes of an air cargo supply chain," International Journal of Production Economics, Elsevier, vol. 127(2), pages 215-225, October.

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