Examining small farm holders’ adoption intention on artificial intelligence of things for sustainable agriculture in developing country: A structural equation modelling assessment

Artificial Intelligence of Things (AIoT) plays a crucial role in promoting sustainable farming and enhancing productivity. This emerging technology is increasingly adopted in developed countries; however, it remains under investigation in developing nations due to its novelty, contextual challenges, and support factors. Consequently, the adoption rate among farmers with small holdings is relatively low. This study addresses this research gap by developing an extended framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT), incorporating perceived gains and sustainability factors to provide a comprehensive understanding of farmers' adoption intentions. The analysis employs measurement and structural models using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicate that performance expectancy, effort expectancy, social influence, trust, and government support significantly influence the intention to adopt AIoT. Conversely, facilitating conditions and price value were found to be insignificant. Moreover, perceived gains and sustainability-related factors exert the most substantial impact on the intention to use AIoT among small farm holders, suggesting that these farmers have a positive attitude towards adopting AIoT for smart and sustainable agricultural practices, particularly in the Philippines.