Enhancing sustainable smart farming: an analysis of Thai farmers' information behavior for achieving SDGs

The transition to sustainable smart agriculture (SSA)is vital for promoting food security, reducing poverty, and enhancing resilience to climate change (CC) in developing countries. However, limited understanding of rural farmers ’ Information behavior (IB) remains a key barrier to advancing the Sustainable Development Goals (SDGs). While various IB models exist, gaps persist regarding their suitability to smart farming contexts. This study aimed to develop a conceptual framework that describes the information process of Thai farmers using a qualitative case study approach. Data were collected through in-depth interviews with 25 farmers in Satun Province, a region highly impacted by CC, characterized by unseasonal rainfall, water shortages during dry spells, and sudden floods. A focus group discussion with 13 participants was conducted to improve the model. Thematic content analysis was used to analyze the data. The research proposes an eight -stage model of Thai farmers’ IB for SSA: recognizing information needs (IN), specifying IN, information seeking, browsing and exploration, information selection and evaluation, information use, information sharing and communication, and process reflection. This model conceptualizes adaptive IB, differing from traditional linear, problem-solving paradigms by emphasizing experiential decision-making, reflective practice, and iterative, context -responsive strategies that evolve with each season and situation. Accordingly, the study expands existing theoretical knowledge and introduces a novel perspective relevant to CC adaptation in the agricultural sector of developing countries. These findings highlight the need for policy and extension strategies tailored to farmers’ real-world IB, thereby facilitating more effective adoption of SSA and contributing to broader SDG objectives.