Risk management in the adoption of smart farming technologies by rural farmers

Abstract

Smart farming is a feasible solution to help farmers effectively and sustainably manage the potential threats and risks those traditional farmers face, such as product quality, increased production costs, the environment, climate change, natural catastrophes, pests, and inferior goods. Using a survey research design, this research examined smart farming adoption and risk management models by combining the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT). The research sampled 400 farmers who are members of community enterprises in the northeastern region of Thailand. Data was collected using a questionnaire and analyzed using a statistical package program in four steps: confirmatory factor analysis, path analysis, structural equation model analysis (SEM), and Sobel's test. The findings revealed that government support variables had the most significant influence by adopting smart farming to risk management. Based on the research results, the government can apply this model to create strategies to encourage farmers to adopt smart farming and increase the production efficiency of agricultural products. The farmer can manage the risks of smart farming, which leads to sustainable smart farming and is useful for further academic acceptance and risk management studies. Furthermore, this study contributes to the existing literature on combining TAM and IDT in model adoption and risk management. The limitations include the small sample size adopted and the limited coverage area for the study, which restricts the generalization of the findings. However, the findings offer a glimpse into the benefits of smart farming.

Promoting the Transition towards Agriculture 4.0: A Systematic Literature Review on Drivers and Barriers

“…Effective cost and resource management, along with the minimisation of unnecessary expenses, positively impacts the adoption of digital technologies [27]. Return on investment plays a significant role in the decision-making process of technology adoption.…”

“…Ka ňovská (2021) [55] argues that several factors influence the decision to adopt, including timesaving, reduced gasoline costs, and lower costs for fertilisation, irrigation, and pest control, as well as reduced personnel needs. Additionally, adopting new technologies can result in improved mobility and productivity in daily life [72], simplified life and work [45], increased production [44], and improved convenience and sustainability [27]. However, these benefits may not always be immediately visible [67].…”

“…Behavioural intention refers to an individual's cognitive disposition to be persuaded to use technology [51]. The adoption of technologies in digital agriculture has positively correlated with interest in the field [27]. However, the utilisation of these technologies on farms seems to depend solely on the perception of their benefits [49].…”

“…However, Aubert et al (2012) [38] indicate that these advantages are minor. If farmers are already interested in smart farming, they need to be stimulated, and it will be easier for them to accept smart farming [27].…”

“…Recent empirical research suggests that the decision to adopt 4.0 technologies is influenced by a multitude of key factors [12,26,27]. Despite the abundance of literature on this subject, there exists, to the best of our knowledge, a limited body of work that effectively synthesises research on the drivers and barriers to adoption [28,29].…”