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A SCOR-based model for supply chain performance measurement: application in the footwear industry

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  • Miguel Afonso Sellitto
  • Giancarlo Medeiros Pereira
  • Miriam Borchardt
  • Rosnaldo Inácio da Silva
  • Cláudia Viviane Viegas

Abstract

Supply Chain Operations Reference (SCOR) is a widely employed model for SC performance assessment, regardless its generic nature. This article presents a SCOR-based model for performance measurement in supply chains (SC) and apply it in the context of Brazilian footwear industry. The model has two dimensions: SCOR processes (source, make, deliver and return) and performance standards adapted from original SCOR (cost, quality, delivery and flexibility). This structure delivers a 4 × 4 matrix, with each component assessed under analytical hierarchy process. Using focus groups, SC’s experts weighted each component of the matrix regarding their relevance. Thereafter, SC’s managers indicated respective results. The SC’s overall performance was obtained by adding the performance of all indicators. The model application embraced one focal footwear manufacturer, four suppliers, three distribution channels and a return channel, with 85 indicators assessed. The achieved performance for the whole SC is 75.29%.The main gaps were found in deliver process (12.78 percentual points of difference between relevance and achieved proportions) and in flexibility performance (9.82). Further application is recommended in order to find consolidated results.

Suggested Citation

  • Miguel Afonso Sellitto & Giancarlo Medeiros Pereira & Miriam Borchardt & Rosnaldo Inácio da Silva & Cláudia Viviane Viegas, 2015. "A SCOR-based model for supply chain performance measurement: application in the footwear industry," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 4917-4926, August.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:16:p:4917-4926
    DOI: 10.1080/00207543.2015.1005251
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    Cited by:

    1. Miguel Afonso Sellitto & Juliane Luchese & Jéssica Mariella Bauer & Gislaine Gabrielle Saueressig & Cláudia Viviane Viegas, 2017. "Ecodesign Practices in a Furniture Industrial Cluster of Southern Brazil: From Incipient Practices to Improvement," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-25, March.
    2. Che-Wei Chang, 2022. "Supply chain movement risk in the sneaker industry: an empirical study," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1073-1092, June.
    3. NNC Pushpamali & Duzgun Agdas & Timothy M. Rose & Tan Yigitcanlar, 2021. "Stakeholder perception of reverse logistics practices on supply chain performance," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 60-70, January.
    4. Lima-Junior, Francisco Rodrigues & Carpinetti, Luiz Cesar Ribeiro, 2019. "Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks," International Journal of Production Economics, Elsevier, vol. 212(C), pages 19-38.
    5. Mohamed Rafik Noor Mohamed Qureshi, 2022. "Evaluating and Prioritizing the Enablers of Supply Chain Performance Management System (SCPMS) for Sustainability," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    6. Hald, Kim Sundtoft & Mouritsen, Jan, 2018. "The evolution of performance measurement systems in a supply chain: A longitudinal case study on the role of interorganisational factors," International Journal of Production Economics, Elsevier, vol. 205(C), pages 256-271.
    7. Miguel Afonso Sellitto & Guilherme Schreiber Pereira & Rafael Marques & Daniel Pacheco Lacerda, 2018. "Systemic Understanding of Coopetitive Behaviour in a Latin American Technological Park," Systemic Practice and Action Research, Springer, vol. 31(5), pages 479-494, October.
    8. Maestrini, Vieri & Luzzini, Davide & Maccarrone, Paolo & Caniato, Federico, 2017. "Supply chain performance measurement systems: A systematic review and research agenda," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 299-315.
    9. Giuseppe Caristi & Raffaele Boffardi & Cristina Ciliberto & Roberta Arbolino & Giuseppe Ioppolo, 2022. "Multicriteria Approach for Supplier Selection: Evidence from a Case Study in the Fashion Industry," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    10. Shahriare Mahmood & Hanna Kropsu-Vehkaperä & Pekka Kess, 2017. "A Comparative Study of the Supply Chain Key Factors Differentiated by Nearshore Manufacturing," MIC 2017: Managing the Global Economy; Proceedings of the Joint International Conference, Monastier di Treviso, Italy, 24–27 May 2017,, University of Primorska Press.
    11. Paitoon Varadejsatitwong & Ruth Banomyong & Puthipong Julagasigorn, 2022. "A Proposed Performance-Measurement System for Enabling Supply-Chain Strategies," Sustainability, MDPI, vol. 14(19), pages 1-25, September.

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