Government extension, social support and farmers' response to climate-adaptive technologies: Insights from a discrete...

Climate change poses substantial challenges to agricultural production systems and rural livelihoods. Leveraging agricultural extension programs to promote climate-adaptive technologies is an important pathway to enhancing agricultural resilience and ensuring food security. However, how government extension services, social support mechanisms, and economic incentives jointly shape farmers' preferences for climate-adaptive technologies remains insufficiently understood. Based on survey data from 1,547 farm households in the main maize-producing region of Liaoning Province in China, this study employs a discrete choice experiment to examine farmers' preferences and subsidy-equivalent monetary valuations for climate-adaptive technology packages by simultaneously incorporating technological attributes, government extension services, and social support mechanisms. The results show that: (1) Farmers generally prefer technology options associated with higher perceived production benefits, indicating a significant positive preference for new crop varieties and smart water management technologies, while their preferences for agrometeorological risk mitigation technologies and improved conservation tillage are relatively weak. (2) Providing technical training has a significant negative effect on farmers' choices, whereas cooperative technical support and direct subsidies significantly increase farmers' likelihood of choosing climate-adaptive technology options. (3) The subsidy-equivalent valuation estimates show that farmers assign the highest monetary value to new crop varieties (approximately CNY 26/mu), while technical training exhibits a negative valuation (approximately CNY -31/mu), suggesting that farmers may perceive the current design of technical training as involving additional participation costs. (4) The latent class logit model further divides farmers into two groups: a relatively cautious group (13.13%) and a more technology-oriented group (86.87%). The two groups differ significantly in technology preferences, acceptance of extension modes, and reliance on social support. This paper provides empirical evidence for optimizing agricultural technology extension systems and implementing differentiated incentive policies.