Concepedia

Publication | Open Access

Decision support tools for agriculture: Towards effective design and delivery

489

Citations

15

References

2016

Year

TLDR

Decision support tools are software-based aids that can guide users toward optimal agricultural decisions, yet despite their availability, uptake remains disappointingly low worldwide. The study investigates factors influencing uptake and use of decision support tools by UK farmers and advisers. The authors combined qualitative interviews and quantitative surveys to identify fifteen factors—usability, cost‑effectiveness, performance, relevance, and compliance compatibility—that influence tool adoption. The study confirms widespread availability of decision support tools in the UK but low uptake, and suggests that understanding the fifteen identified factors can improve future tool design and delivery.

Abstract

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.

References

YearCitations

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