Understanding Farmers’ Intentions to Adopt Pest and Disease Green Control Techniques: Comparison and Integration Based on Multiple Models

Abstract

Green control techniques (GCT) are an important supporting technology to ensure sustainable agricultural development. To advance the adoption of GCT, it is crucial to understand the intention of farmers to adopt GCT and its related determinants. However, current research is mostly limited to using a single theoretical model to explore farmers’ intentions to adopt GCT, which is not conducive to revealing the determinants of farmers’ intentions to adopt GCT. To address this gap, this study integrates the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), the Innovation Diffusion Theory (IDT), and the Motivational Model (MM) based on research data from 362 rice farmers in Heshan District, Yiyang City, Hunan Province, and uses partial least squares structural equation modeling (PLS-SEM) to empirically test and compare the above models. The model comparison results prove that the TPB (R2 = 0.818, Q2 = 0.705), TAM (R2 = 0.649, Q2 = 0.559), IDT (R2 = 0.782, Q2 = 0.674), and MM (R2 = 0.678, Q2 = 0.584) models all have explanatory power and predictive validity in the context of green control techniques. However, the integrated model (R2 = 0.843, Q2 = 0.725) is found to be superior to these individual theoretical models because it has larger values of R2, Q2, and smaller values of Asymptotically Efficient, Asymptotically Consistent, and provides a multifaceted understanding for identifying the factors influencing adoption intentions. The results of the path analysis show that attitude, perceived behavioral control, perceived usefulness, subjective norm, and visibility significantly and positively influence adoption intentions in both the single and integrated models and are determinants of farmers’ intentions to adopt GCT.