Economy and Food Security

Extended Abstract
Background: The agricultural sector is considered one of the fundamental pillars of the national economy and plays a decisive role in ensuring food security, employment generation, and the sustainability of rural livelihoods. In many developing countries, including Iran, more than 80 percent of society’s food requirements are supplied through agricultural activities, which highlights the critical need to improve the performance, productivity, and sustainability of this sector at both local and national levels. Despite its strategic importance, agriculture is inherently exposed to a wide range of risks and uncertainties. These risks include production risks resulting from climatic variability, pests, and plant diseases, market and price risks arising from fluctuations in input and output prices, financial risks related to credit constraints and liquidity limitations, institutional risks caused by instability or uncertainty in government support policies, and human risks associated with farmers’ health, skills, and managerial capacity.
To mitigate the adverse effects of these risks, farmers adopt various strategies, such as crop diversification, production of crops with guaranteed prices, intercropping of complementary crops, flexibility in input procurement, and maintaining financial reserves for emergency situations. Among these strategies, agricultural crop insurance is recognized as one of the most important formal risk management tools, playing a significant role in compensating losses, reducing income volatility, and enhancing farmers’ resilience against adverse shocks. However, the level of insurance adoption and farmers’ satisfaction with insurance services is not uniform across regions and is influenced by individual characteristics, farm structure, spatial and temporal conditions, and the efficiency of the insurance system. Therefore, identifying factors affecting farmers’ satisfaction and the acceptance of agricultural crop insurance can contribute substantially to improving the design and implementation of insurance policies. This study mainly aims to identify and analyze factors influencing farmers’ satisfaction with agricultural crop insurance services using an artificial neural network modeling approach.
Methods: This study is based on primary field data, which were collected in September 2021 through a structured questionnaire. The statistical population consisted of crop farmers and orchard owners in Sari County, among whom 200 respondents were randomly selected to complete the questionnaire. The questionnaire was designed to capture information related to farmers’ personal and professional characteristics, farming experience, status of agricultural crop insurance usage, and their attitudes toward insurance services. The reliability of the research instrument was assessed by calculating Cronbach’s alpha coefficient, yielding a value of 0.82, indicating an acceptable level of reliability. The questionnaire items were measured using a nine-point Likert scale ranging from 1 (very low) to 9 (very high).
Artificial neural network (ANN) modeling was employed to analyze the data and identify the relationships among variables. ANNs are particularly suitable for analyzing farmers’ decision-making behavior under uncertainty due to their strong capability to model complex and nonlinear relationships, parallel processing capacity, and ability to learn and adapt to changing conditions. In this study, farmers’ satisfaction with agricultural crop insurance services was considered the dependent variable. The independent variables included farm size, farming experience, status of agricultural crop insurance usage during the past three years, and farmers’ intention to use crop insurance in the following year. The neural network model was trained, and its predictive performance and the relative importance of explanatory variables were evaluated.
Results: The descriptive results indicated that the average farming experience of the surveyed farmers was approximately 23 years, reflecting a relatively experienced sample. Analysis of agricultural crop insurance usage during the past 3 years revealed that 57 percent of the farmers 

insured their crops, while 43 percent did not use crop insurance. Furthermore, the results regarding farmers’ intentions to use crop insurance in the coming year showed that 58 percent of the respondents planned to insure their crops, whereas 42 percent expressed no intention to do so.

The results obtained from the ANN modeling demonstrated that all independent variables considered in the study had a statistically significant effect on farmers’ satisfaction with agricultural crop insurance services. Based on the importance coefficients, the status of crop insurance usage during the past 3 years had the greatest impact on farmers’ satisfaction. This finding suggests that farmers’ previous experiences with insurance play a crucial role in shaping their perceptions and evaluations of insurance services. Farm size was identified as the second most influential factor, indicating the importance of farm scale in farmers’ assessment of the benefits and effectiveness of insurance. Farming experience ranked third, which might reflect greater awareness among experienced farmers regarding risk management tools. Finally, farmers’ intention to use crop insurance in the following year had the lowest impact on satisfaction. Moreover, the normalized importance coefficients showed that crop insurance status during the past 3 years had the highest predictive power (100 percent), while intention to use insurance in the coming year had the lowest predictive power (73.9 percent) in explaining farmers’ satisfaction with agricultural crop insurance services.

Conclusion: The findings of this study indicate that farmers’ satisfaction with agricultural crop insurance services is significantly influenced by farm size, farming experience, previous insurance participation, and future insurance intentions. The prominent role of prior insurance experience highlights the importance of improving the quality of insurance services, enhancing transparency in loss assessment and compensation procedures, and strengthening farmers’ trust in insurance institutions to ensure sustained and expanded insurance coverage. Accordingly, it is recommended to design agricultural crop insurance premium structures in a more flexible manner and tailored to farm characteristics. In particular, providing premium discounts, exemptions, or flexible payment facilities for larger farms may contribute to higher insurance acceptance. Additionally, incorporating farmers’ insurance history into premium determination could enhance fairness and increase the overall acceptability of insurance schemes. Finally, the development and implementation of alternative insurance products, such as yield insurance and revenue insurance, can play a significant role in increasing farmers’ satisfaction and strengthening the position of agricultural crop insurance as an effective risk management instrument in the agricultural sector.