A Sustainability-Based KPI Framework for Distribution Performance Assessment and Supply Chain Improvement in Soybean Processing SMEs

Authors

  • Khoerun Nisa Safitri Universitas Ibnu Sina
  • Nurul 'Aini Universitas Ibnu Sina
  • Khairunnisa Sulistiawati Universitas Ibnu Sina
  • Nayla Uriatul Ulfa Universitas Ibnu Sina

DOI:

https://doi.org/10.56882/jisem.v5i1.77

Keywords:

Sustainability KPI, Distribution Performance, Supply Chain Management, Delphi-AHP, Soybean-Processing SMEs

Abstract

The sustainability of distribution activities has become increasingly important for improving supply chain performance in soybean-processing SMEs. However, many SMEs still lack a structured performance measurement system that integrates economic, environmental, and social aspects. This study aimed to develop a sustainability-based Key Performance Indicator (KPI) framework to assess distribution performance and improve supply chains for soybean-processing SMEs in Batam City, Indonesia. A quantitative case study approach was employed, using the Triple Bottom Line (TBL) concept, the Delphi method, and the Analytic Hierarchy Process (AHP). The results identified and validated 18 KPIs, comprising 6 economic, 6 environmental, and 6 social indicators. AHP analysis revealed that the Economic dimension received the highest weight (0.52), followed by the Environmental (0.29) and Social (0.19) dimensions. At the indicator level, Order Fulfillment Rate (0.109) and Delivery Reliability (0.109) achieved the highest global weights, followed by On-Time Delivery (0.104) and Carbon Emission (0.087). The consistency test yielded a CR value of 0.062, indicating reliable expert judgments. The proposed framework provides a practical tool for evaluating distribution performance, identifying improvement priorities, and supporting sustainable supply chain development in soybean-processing SMEs.

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Published

2026-06-30

How to Cite

[1]
K. N. Safitri, N. ’Aini, K. Sulistiawati, and N. U. Ulfa, “A Sustainability-Based KPI Framework for Distribution Performance Assessment and Supply Chain Improvement in Soybean Processing SMEs”, JISEM, vol. 5, no. 1, pp. 21–31, Jun. 2026.