Digital Information Loading and Sustainable Fertilizer Management in Grape Production: Evidence from a Randomized Controlled Trial

Fertilizer reduction and improved fertilization management are important approaches to achieving green and organic grape production and vineyard management. This study aims to examine whether digital agricultural extension tools can facilitate fertilizer reduction among grape growers, or whether their actual effects may be weakened by limited attention and information overload. Using data from a randomized controlled trial (RCT) involving 475 grape growers in Liaoning Province, this study employs ordinary least squares (OLS) models and propensity score matching (PSM) to test the effect of digital information loading on growers’ fertilizer-reduction behavior. Specifically, this study constructs three dimensions, including information loading breadth (comprehensiveness), loading depth (accuracy), and loading length (completeness), and employs ordered logit models and threshold regression models to explore their mechanism effects and threshold effects on fertilizer reduction. The results indicate that (1) digital information loadingsignificantly promotes fertilizer reduction behaviors among grape growers. (2) The breadth and depth of information loading facilitate fertilizer reduction by enhancing growers’ perceived usefulness, whereas this mechanism is not significant for the length dimension. (3) Information loading length has a threshold effect on fertilizer reduction behavior, which means there is an optimal time interval for single video viewing; beyond that, the limited attention triggered information overload that causes the fertilizer reduction behavior to disappear. (4) There are also long-term effects of digital information loading. These findings provide micro-level empirical evidence for promoting green and organic-oriented grape production systems, and offer policy implications for countries pursuing sustainable agricultural transition and fertilizer reduction.