Mitigating retail rice price volatility for sustainable supply chains: an optimization and regression-based approach [version 2; peer review: 2 approved]

Abstract

Background This study addresses the challenge of stabilizing rice retail prices in Indonesia, where rice is a critical staple food, as in many Asian countries. The government prioritizes price stability to prevent sharp increases that could trigger social unrest during shortages. Price control approaches are categorized as direct or indirect. Direct controls involve immediate interventions, such as boosting rice stocks through imports to quickly influence market prices. Indirect controls consist of longer-term measures, like enhancing domestic production capacity for gradual stabilization. This study proposes an optimization model to determine the optimal rice import volume to minimize bi-monthly retail price fluctuations. Methods A linear programming model is formulated to minimize bimonthly price changes, subject to constraints including local production capacity, import limits, rice flow balance, and demand fulfillment. The monthly retail price is modeled using a compound linear regression approach with seven explanatory variables: the rupiah exchange rate against the US dollar, GDP per capita, the price of ground dry rice (GKG) per kilogram, domestic rice procurement, rice imports, rice distribution, and government-managed rice stock aimed at ensuring domestic availability and price stability. The explanatory variable is forecasted using methods best suited to its historical pattern. Results The model was tested using data from 2020 to 2023. The results indicate that bimonthly rice prices increases can be effectively controlled, with maximum price change rates maintained between 0.75% and 1.14% and a standard deviation ranging from 0.20% to 0.34%. These values are significantly lower than the anticipated inflation rate of 2–3%. Conclusions The optimization model effectively determines the required volume of rice imports to minimize bimonthly retail price fluctuations. By regulating import volumes, excessive price increases can be prevented. Enhanced data-driven forecasting with granular historical data may further improve the accuracy of retail rice price predictions and strengthen price stabilization initiatives.

Keywords

• Rice supply chain
• Rice import
• Increasing rate of rice price
• Hybrid optimization-regression model.
• eng