Designing a closed-loop information flow model in bridging the market information gap among agriculture stakeholders in Sri Lanka

The stakeholders in the agriculture domain need agricultural information and relevant knowledge to make informed decisions at various stages of the crop life cycle. Coordination failures among the stakeholders in the agriculture sector result in the inability to provide accurate, timely, and actionable information. As a result, the agriculture sector faces several challenges, such as oversupply, undersupply and crop wastage. The existing digital agriculture eco-system can gather data produced by different stakeholders more frequently and accurately. However, the data collected from various stakeholders should be analyzed and forecasted to deliver the required knowledge to make more informed and appropriate decisions. This study was carried out to propose a ‘closedloop information flow model’ to provide forecasted demand and supply to create better coordination among stakeholders. Different prototypes were designed to deliver forecasted demand and supply information for major stakeholders in the agriculture sector. Initially, farmers, input suppliers, and logistic suppliers were selected in this study to expand to other stakeholders in the future. The prediction model was developed and evaluated according to stakeholder requirements by analyzing the actual and predicted data. The existing ‘Govi- Nena’ mobile-based farmer application was refined to provide supply and demand information for farmers. Separate web dashboards were designed to deliver the required information to other stakeholders such as input suppliers and logistic suppliers. Designed prototypes will be evaluated with the stakeholders for further improvements. The proposed Closedloop information flow model for forecasted demand and supply will bridge the market information gap among stakeholders. Thus, it will reduce the coordination failures in the Sri Lankan agriculture sector while increasing transparency in making informed decisions.