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An intelligent decision support system modelling for improving agroindustry's supply chain performance: a case study

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  • Muhammad Asrol
  • M. Marimin
  • M. Machfud
  • Moh. Yani

Abstract

Decision-making has an important role to improve agroindustry's business process performance. This paper proposed an intelligent decision support system (IDSS) which was organised by four main performance models to improve agroindustry's competitiveness. Supply chain performance modelling was organised by using supply chain operation reference (SCOR) framework, agroindustry's risks assessment by using fuzzy house of risk, green productivity evaluation by using green productivity index (GPI) and fuzzy inference system (FIS) while agroindustry's business promising and feasibility assessment was modelled with FIS. The overall supply chain performance was developed to realise the supply chain performance. The proposed IDSS was validated at a sugarcane agroindustry and simulated the performance. The overall supply chain performance validations showed that sugarcane agroindustry's performance - as a case study -was moderate. For further research, this paper requires experienced expert verification to formulate the supply chain performance improvement strategy and verify the IDSS model to be implemented for the real world.

Suggested Citation

  • Muhammad Asrol & M. Marimin & M. Machfud & Moh. Yani, 2024. "An intelligent decision support system modelling for improving agroindustry's supply chain performance: a case study," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 16(2), pages 134-168.
    • Handle: RePEc:ids:ijidsc:v:16:y:2024:i:2:p:134-168
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