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A SCOR-based Performance Measurement of Indonesia’s Kayumas Specialty Coffe Supply Chain

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  • Aisya Risanda Rahmadyahningrum

    (Department of Socio-Economics, Faculty of Agriculture, University of Brawijaya, Malang, Indonesia)

  • Abdul Wahib Muhaimin

    (Department of Socio-Economics, Faculty of Agriculture, University of Brawijaya, Malang, Indonesia)

  • Silvana Maulidah

    (Department of Socio-Economics, Faculty of Agriculture, University of Brawijaya, Malang, Indonesia)

Abstract

Performance evaluation is essential in defining supply chain strategies because by taking measurements, companies can find out how the business processes in the supply chain are running and formulate strategic policies to improve supply chain performance. Specialty coffee is a premium coffee with a unique aroma and flavour originating from a specific region, and it is easy to trace its origin from the farm to the consumer. This study aims to evaluate the performance of the Kayumas specialty coffee supply chain using the SCOR-ANP method and determine performance improvement strategies using ANP analysis. The research results can be concluded that (1) Kayumas specialty coffee supply chain consists of farmers, farmer groups, distributors/resellers, and consumers. (2) The performance position of Kayumas specialty coffee is inferior (3) The performance improvement strategy needed to improve product quality is a partnership between supply chain members to reach a price agreement.

Suggested Citation

  • Aisya Risanda Rahmadyahningrum & Abdul Wahib Muhaimin & Silvana Maulidah, 2024. "A SCOR-based Performance Measurement of Indonesia’s Kayumas Specialty Coffe Supply Chain," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3), pages 887-892, March.
    • Handle: RePEc:bcp:journl:v:8:y:2024:i:3:p:887-892
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    References listed on IDEAS

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    1. 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.
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