| Issue |
E3S Web Conf.
Volume 665, 2025
6th International Conference on Agribusiness and Rural Development (IConARD 2025)
|
|
|---|---|---|
| Article Number | 01013 | |
| Number of page(s) | 11 | |
| Section | Agricultural Economic and Business | |
| DOI | https://doi.org/10.1051/e3sconf/202566501013 | |
| Published online | 19 November 2025 | |
Understanding Farmer’s Risk Behavior in Shallot Farming on the Slopes of Mount Merbabu, Magelang Regency, Central Java
Department of Agribusiness, Universitas Muhammadiyah Yogyakarta, Indonesia
* Corresponding author: sriyadi@umy.ac.id
Shallot farming is characterized by production and price uncertainties that create significant economic risks for farmers. These risks influence farmers’ decision-making regarding production and resource allocation, which are essential aspects of agricultural economics. His study aims to analyze the level of income risk, farmers’ behavior toward risk, and factors influencing such behavior in shallot farming on the slopes of Mount Merbabu, Magelang Regency. This research was conducted through interviews with farmers and other relevant stakeholders as well as observations. The findings revealed that shallot farming had a relatively high-income risk. Most farmers exhibited risk-averse toward the risks of shallot farming. Farmers are usually more reluctant to take a risk due to the larger land area, the older farmer, and more frequent failure. In contrast, farmers with higher education, longer farming experience, larger household size, and higher income tended to be more willing to take risks. Moreover, the income risk of shallot farming was greater due to variations in production. From an agricultural economics perspective, these findings highlight how various factors shape farmers’ economic decisions under uncertainty. Coordinated planting schedules are recommended to reduce production variability and stabilize farmers’ income.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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