Cognitive mapping to decode farmers' mindsets in agricultural decision-making: a systematic review

Farmers decision-making processes are critical to the implementation of technologies and climate-resilient sustainable practices. These decisions are subject to complex thinking processes, which include risk perception and belief systems. This systematic review explains the decision-making process of farmers, through cognitive mapping. Moreover, it examines mental models, perception, belief system and cause-effect relationship of farmers with particular attention given to their behavior and practices.

The research adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework. It utilized Scopus and Web of Science databases to retrieve 80 articles. The main aim was to identify research trends and gaps through bibliometric analysis and the TCCM framework by focusing on major theories, contexts, characteristics, and methodologies of agricultural cognitive-mapping research.

The major trends identified in this study are risk perception in agricultural economics, climatic change, technology adoption, conservative agricultural and sustainability. The major stakeholders considered included farmers (cattle, pig, rice, and date farmers), extension agents, policymakers, NGOs, rural households, agro-industries, technology providers, and the holders of indigenous knowledge. There are still major gaps in understanding the psychological and cognitive processes underlying the decisions of farmers: longitudinal studies are limited, the role of gender is not studied thoroughly, particularly in the conditions of climate-change effects and policy shifts.

Though, the mental model, perceptions, and belief systems have a significant impact on agricultural decision-making, there are still gaps in the comprehension of psychological and cognitive mechanisms involved since it is a persistent problem in the agricultural decision-making process. Future studies must incorporate the behavioral psychology, mixed-methods and cross-cultural research designs to develop integrated models that support agricultural sustainability and resilience.