Decision support tools for agriculture: Towards effective design and delivery

By D. Rose, W. J. Sutherland, C. Parker, M. Lobley, Michael Winter, C. Morris, S. Twining, C. Ffoulkes, Tatsuya Amano, L. Dicks. 2016

474 citations recorded by the source corpus.

Decision support tools, usually considered to be software-based, may be an important part of the quest for evidence-based decision-making in agriculture to improve productivity and environmental outputs. These tools can lead users through clear steps and suggest optimal decision paths or may act more as information sources to improve the evidence base for decisions. Yet, despite their availability in a wide range of formats, studies in several countries have shown uptake to be disappointingly low. This paper uses a mixed methods approach to investigate the factors affecting the uptake and use of decision support tools by farmers and advisers in the UK. Through a combination of qualitative interviews and quantitative surveys, we found that fifteen factors are influential in convincing farmers and advisers to use decision support tools, which include usability, cost-effectiveness, performance, relevance to user, and compatibility with compliance demands. This study finds a plethora of agricultural decision support tools in operation in the UK, yet, like other studies, shows that their uptake is low. A better understanding of the fifteen factors identified should lead to more effective design and delivery of tools in the future.

Subfields: Environmental Chemistry, General Agricultural and Biological Sciences, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/1bc4dbfdbefa7c46d9517981d83af7ce38cf0d45

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Agricultural and Biological Sciences

1. Francisco Rovira-Más
2. Verónica Sáiz-Rubio
3. D. Rose

Citations in the corpus

• High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture (2019, background): “Apart from that, farmer’s acceptance and uptake of DSS is still low [85].”
• Perceptions of the Fourth Agricultural Revolution: What’s In, What’s Out, and What Consequences are Anticipated? (2020, background): “Farmers in this sector and region tend to use technology more than others, for example in the upland or lowland livestock sector (excluding dairy) (Rose et al. 2016).”
• Dealing with the game-changing technologies of Agriculture 4.0: How do we manage diversity and responsibility in food system transition pathways? (2020, unknown): “Research in a number of different contexts, including decision support tool use (Rose et al., 2018; Rose et al., 2016), has shown that there are a number of barriers”
• From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management (2020, background): “[90] conducted a survey on DSS and arrived to the conclusion that 15 factors were influential in convincing UK growers and advisers to use DSS, including usability, cost-effectiveness, performance, relevance to user, and compatibility with compliance demands.”
• Integrated farm management for sustainable agriculture: Lessons for knowledge exchange and policy (2019, methodology): “This could be due to a number of reasons; firstly, our wider research from this project suggested that many farmers were not regularly using paid professional advice, and it is advisors that are often influential in bringing knowledge of new ideas (see Rose et al., 2016).”