This study focuses on optimizing supply chain decisions under two scenarios: government subsidies during disaster years and farmers with varying risk preferences. An order-agriculture supply chain model is constructed, involving three parties: farmers, distributors, and insurance companies. Farmers cultivate agricultural products with varying levels of greenness. A three-stage game model is employed to derive the optimal planting scale for farmers, the optimal wholesale price for distributors, and the optimal premium rate for insurance companies. The results indicate that government disaster year subsidies directly increase the Conditional Value-at-Risk (CVaR) of farmers, although a maximum subsidy rate exists to prevent inequity. Enhancing the greenness of agricultural products has a positive impact on agricultural production. As the probability of disaster years increases, loan guarantee insurance becomes more effective in expanding farmers' planting scales, while yield guarantee insurance demonstrates superior performance in improving farmers' CVaR. The practical value of this study lies in providing farmers with optimal decision-making frameworks and profit calculations for loan guarantee insurance and yield guarantee insurance under varying disaster-year probability scenarios. Additionally, it explores the impact of government subsidies during disaster years, the greenness level of agricultural products, and the risk of crop failure on changes in farmers' value. These findings contribute to the optimization of farmers' decision-making processes, enhancement of their economic welfare, and the promotion of sustainable agricultural development, ultimately improving the livelihoods of farmers.

As the most contributed sectors in agriculture, rice farming is facing various risks, namely uncertainty such as crop failure caused by climate change, including air temperature, weather, rainfall and others. Indonesia is categorised as an agricultural country with a tropical climate. By this season, the farmers can plant the rice. Rice farming is currently an inseparable part of most agricultural societies in Indonesia, especially in West Java. However, changes in air temperature, weather and annual rainfall, can increase the uncertainty and upward the risk of crop failure. Thus, the current study seeks to investigate the decision making for agricultural risk assessment (climate variable) through the formulation of a risk model for agricultural insurance in Indonesia. This study utilised the climate variables, which consist of air temperature, wind speed, maximum and minimum temperatures, and rainfall. For determining the magnitude of risk, we applied the Block Maxima method and Peak Over Threshold. The results of this study found that the highest risk of losses occurred in November, December, January, February and March with a value of 0.17485.