Amoussouhoui Rico, Arouna Aminou, Ruzzante Sacha, Banout Jan
Department of Sustainable Technologies, Faculty of Tropical AgriSciences, Czech University of Life Science in Prague, Kamýcká 129, 165 00, Prague, Czech Republic.
Africa Rice Center (AfricaRice), 01 BP 2551 Bouake 01, Bouake, Cote d'Ivoire.
Heliyon. 2024 Apr 25;10(9):e30210. doi: 10.1016/j.heliyon.2024.e30210. eCollection 2024 May 15.
Various Digital Agricultural Technologies (DAT) have been developed and implemented around the world. This study aims to estimate the overall adoption rate and identify the determinant factors for a better adoption perspective after decades of innovation and dissemination. A systematic review was conducted on published studies that reported adoption rates and determinant factors using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. We used meta-regression and the partial correlation coefficient to estimate the effect size and establish the correlation between socioeconomic characteristics and the adoption of various technologies reported. Fifty-two studies with 32400 participants met the selection criteria and were included in the study. The results revealed an overall pooled adoption rate of 39 %, with the highest adoption rates in developing countries in Africa and South America. Socioeconomic factors such as age, education, gender, and income were found to be the main determinants and should be considered when designing technology for sustainable adoption. The study also found that young farmers were more susceptible to adoption. Moreover, farmers with higher income levels and educational attainment are more likely to use technology linked to agricultural production, market access, and digital advising, implying that high-income farmers with more education are more tech-savvy. However, this does not exclude low-income and low-educated farmers from adopting the technologies, as many models and strategies with socioeconomic considerations were developed. It is one of the reasons behind the underlying enthusiasm for digital agricultural adoption in low and middle-income countries.
世界各地已开发并实施了各种数字农业技术(DAT)。本研究旨在估计总体采用率,并确定在经过数十年的创新和推广之后,能带来更好采用前景的决定因素。我们按照系统评价与荟萃分析的首选报告项目(PRISMA)协议,对已发表的报告采用率和决定因素的研究进行了系统评价。我们使用元回归和偏相关系数来估计效应大小,并确定所报告的社会经济特征与各种技术采用之间的相关性。52项涉及32400名参与者的研究符合入选标准并被纳入本研究。结果显示总体汇总采用率为39%,非洲和南美洲的发展中国家采用率最高。年龄、教育程度、性别和收入等社会经济因素被发现是主要决定因素,在设计可持续采用的技术时应予以考虑。研究还发现年轻农民更容易采用。此外,收入水平和教育程度较高的农民更有可能使用与农业生产、市场准入和数字咨询相关的技术,这意味着受教育程度更高的高收入农民对技术更在行。然而,这并不排除低收入和低教育程度的农民采用这些技术,因为已经制定了许多考虑社会经济因素的模式和策略。这是中低收入国家对数字农业采用潜在热情背后的原因之一。