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Handiyanto, Teguh Tri
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Economics, Econometrics & Finance

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Journal : Jurnal Perspektif Pembiayaan dan Pembangunan Daerah

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Digital-based performance model for the Arabica Coffee supply chain: A case study of the Koerintji Barokah Bersama Cooperative in Kerinci, Indonesia Handiyanto, Teguh Tri; Suandi, Suandi; Muchlis, Fuad
Jurnal Perspektif Pembiayaan dan Pembangunan Daerah Vol. 12 No. 4 (2024): Jurnal Perspektif Pembiayaan dan Pembangunan Daerah
Publisher : Program Magister Ilmu Ekonomi Pascasarjana Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/ppd.v12i4.34483

Abstract

This study examines the performance model of the Arabica coffee supply chain managed by the Koerintji Barokah Bersama Cooperative, emphasizing the integration of supply chain management (SCM), social capital (SC), and information technology (IT) to enhance efficiency, transparency, and competitiveness. Using a mixed-methods approach involving descriptive analysis and Structural Equation Modeling (SEM), the study explores the current state of SCM, SC, and IT, evaluates supply chain performance, and develops a comprehensive performance model. The findings indicate that SCM, SC, and IT significantly influence supply chain performance, with IT and SC playing crucial mediating roles. The cooperative demonstrated strengths in reliability, flexibility, and utility, though cost management requires further improvement. The proposed model validates that a collaborative and digital approach can improve operational efficiency, stakeholder coordination, and market adaptability. The study highlights the need for stronger SCM coordination, enhanced SC through trust and collaboration, and greater IT adoption for real-time monitoring and data-driven decision-making. Despite its robust methodology, limitations include a localized focus and exclusion of broader external factors like global market trends and climate change. Future research should explore advanced technologies such as IoT, AI, and Big Data Analytics and assess long-term performance across diverse regions and market contexts to ensure sustainability and global competitiveness.
Co-Authors Fuad Muchlis Suandi Suandi