Department of Veterinary Medical Sciences, University of Bologna, 40064 Ozzano dell'Emilia (Bo), Italy.
Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy.
Int J Environ Res Public Health. 2020 Jan 30;17(3):869. doi: 10.3390/ijerph17030869.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify "bottlenecks" in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual's decisions. Preliminary results found high levels of adoption among younger farmers, those that had a high level of education, those with high intensity of information, with large farm sizes, and high labor intensity. A logit model was used to understand the role played by labor intensity and perceived in the adoption process. In light of the Common Agricultural Policy Reform post 2020, the findings suggest relevant policy implications, such as the need to increase awareness of PF tools and foster dissemination of information aimed at reducing the degree of perceived complexity.
采用创新的过程,特别是在精准农业(PF)方面,本质上是复杂和社会性的,并受到生产者、变革推动者、社会规范和组织压力的影响。本研究对意大利农民进行了实证分析,以衡量农业创新采用的驱动力,并澄清“瓶颈”。本研究的目的是分析影响创新采用概率的社会结构和复杂性因素,以及驱动个人决策的决定因素。初步结果发现,年轻农民、教育程度高、信息强度高、农场规模大、劳动强度高的农民采用率较高。使用逻辑回归模型来理解劳动强度和感知在采用过程中所扮演的角色。鉴于 2020 年后的共同农业政策改革,研究结果表明有必要出台相关政策,例如提高对 PF 工具的认识,促进信息传播,以降低感知复杂性的程度。