Abstract

We explore the intentions of farmers’ pesticide use by using expanded versions of the theory of planned behavior (TPB). We added variables such as farmers’ knowledge about pesticides, moral norms, progressive farming approach, farm size, farming experience, and formal education of the farmers as additional predictors in the original TPB model. We interviewed 390 cotton farmers in Multan and used a hierarchical multiple regression modeling framework to run a series of multiple regression models (based on original and expanded versions of TPB) and found that the expanded TPB models with the addition of, (a) farmers’ knowledge of pesticides (R² change = 0.089, F change_{(2, 384)} = 24.8, p < 0.01), (b) farmers’ progressiveness (R² change = 0.037, F change_{(1, 383)} = 21.5, p < 0.01), and (c) socio-economic variables (R² change = 0.032, F change_{(3, 380)} = 6.4, p < 0.05) statistically significantly improved the explanatory power of the original TPB model. Farmers’ knowledge of pesticides (β = 0.316, t = 6.320, p < 0.01), and progressive farming approach (β = 2.80, t = 5.834, p < 0.01) were the most influential variables determining pesticide use intention. Pesticide use can be optimized through improved extension services, by improving pesticide knowledge and training farmers in new farming practices.

抽象的

我们通过使用计划行为理论（TPB）的扩展版本来探索农民使用农药的意图。我们在原始TPB模型中添加了变量，例如农民对农药的知识，道德规范，渐进式耕作方法，农场规模，耕作经验以及对农民的正规教育，作为其他预测因素。我们采访了穆尔坦（Multan）的390位棉农，并使用分层多元回归建模框架运行了一系列多元回归模型（基于TPB的原始版本和扩展版本），发现在扩展的TPB模型中增加了（a）棉农的农药知识（R ^2的变化= 0.089，F的变化_{（2，384）} = 24.8，p  <0.01），（b）农民的进步程度（R ²变化= 0.037，F变化_{（1，383）} = 21.5，p  <0.01），（c）社会经济变量（R ²变化= 0.032，F变化_{（3，380）} = 6.4，p  <0.05）在统计学上显着提高了原始TPB模型的解释能力。农民对农药的了解（β= 0.316，t  = 6.320，p <  0.01）和渐进耕作方式（β= 2.80，t  = 5.834，p  <0.01）是决定农药使用意图的最有影响力的变量。可以通过改善推广服务，提高农药知识和对农民进行新的耕作方法进行培训来优化农药的使用。