DSS for Agricultural Products Supply Chain Risk Balancing using Stakeholder Dialogues and Fuzzy Non Linear Regression

The high complexity of the supply chain network and the characteristics of products made supply chain management of agricultural products were more susceptible to the risks emergence of loss. Therefore, it is required to develop a mechanism for price negotiation which distributes the risks fairly for each stakeholder in the supply chain. In addition it is necessary to identify and evaluate supply chain risks in order to avoid continuing problems that can occur at any point in the supply chain network. The objectives of this study were to describe the model of identification and evaluation for corn supply chain risk, to formulate a fair pricing mechanism for corn supply chain using risk balancing model. Risk identification was conducted using fuzzy Analytical Hierarchy Process (AHP) approach and risk evaluation was done by using fuzzy logic with data input form the opinion of several experts maize supply chain. A fairly pricing model at farmer level was developed by using stakeholder dialogue approach based on a balanced fuzzy risk utility preference that was faced by all stages of the supply chain. In addition, fuzzy risk utility optimization was used to get a consensus of the supply chain stakeholder dialogue, where basic risk utility function was derived using fuzzy regression approach. Risk mitigation for each stage of supply chain was developed using fuzzy inferences based on the risk that has been evaluated. Based on the verification results, the model could identify the level of risks for each party of the supply chain and the action that must be taken for minimizing its impacts using appropriate strategies. The model could shift the risks from the farmer to the other parties to determine the fair benefit distribution on the price negotiation.