The impact of policies on the diffusion of agricultural innovations: Systematic review on evaluation approaches

• Published in: Outlook on Agriculture 2024-03, Vol.53 (1), p.3-14
• Main Authors: El Bakali, Imane, Brouziyne, Youssef, Ait El Mekki, Abdelkader, Maatala, Nassreddine, Harbouze, Rachid
• Format: Article
• Language: English
• Subjects: Agricultural policy; Change agents; Dissemination; Environmental aspects; Innovations; Mathematical programming; Policy making; Profitability; Quasi-experimental methods; Research methodology; Supply & demand; Sustainability; Systematic review
• ISSN: 0030-7270; 2043-6866
• DOI: 10.1177/00307270231215837

The demand for sustainable agricultural technologies still lags behind the supply confirming the demand articulation failure of transformational innovation change agricultural policies. To understand the reasons for demand shortcomings, the evaluation of developed policies is required. In the literature, there is little evidence on this topic, henceforth, this paper conducts a systematic review of the primary methodological approaches used to assess the influence of policies on the dissemination of agricultural innovations. The results showed that there are two clusters of evaluation; the first investigates how policies affect agricultural innovation adoption, and the second studies how policies affect yields and profitability. For the first cluster, 70% of the studies analyzed adoption decisions using the Double-hurdle, Probit, or Tobit models or captured changes in adoption levels over time using the Adoption and Diffusion Outcome Prediction Tool and discrete-time duration models. This cluster is related to the assessment of the input and output additionalities of innovation policies. In 58% of the studies related to the second cluster, the focus was the assessment of economic and environmental implications using mathematical programming models, particularly agent-based modeling. The purpose of evaluation in this cluster is more focused on behavioral additionality. There were no experimental or quasi-experimental methods among the methods utilized in this cluster. The majority of studies do not incorporate the evaluation of economic, social, and environmental aspects together; therefore, evaluation outlooks suggest increasing interest in sustainability impact. It is suggested that models from both clusters be used in combination to explore input, output, and behavioral additionalities simultaneously. Furthermore, including white-box evaluation approaches to evaluate demand-oriented innovation policy in the agricultural sector, in addition to usual black-box approaches, is a necessity.