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The agriculture landscape is changing. The past five decades have seen a global shift in the field of agriculture from resource-driven growth to productivity-driven growth (Fuglie et al., 2019). Previously, farms have improved agricultural output through the expansion of land, use of pesticides, more fertilisers and other inputs. Now, most farms prioritise the improvement of resource and labour efficiency alongside good agricultural practices (GAP) and technology (Fuglie et al., 2019). Agricultural productivity has been lower in economically developing countries compared to advanced economics, impeding their convergence. Whilst much of the world has embraced technology with open arms, agriculture has adopted it more gradually (Fuglie et al., 2019). Technology and innovation are crucial to accelerate improvements in the sector and embody state-of-the-art practice (Fuglie et al., 2019). The knowledge capital contained within software and hardware can transform farm owners’ businesses through improved connection to customers, streamlined supply chains and enhanced yields (Fuglie et al., 2019).
DSSs, a type of software solution designed to aid users make better decisions (Dicks et al., 2014), have shown success in both private and public sectors such as healthcare, banking and engineering (Papathanasiou et al., 2016). They have the potential to benefit farmers by presenting the likelihood of various outcomes from different options (Dicks et al., 2014; Rose et al., 2016) and can guide users through decision stages by providing expert advice that automatically corresponds to the user’s inputs and recorded data for analysis (Been et al., 2009). The analysis conducted by such tools provide data-driven insights which may have otherwise been inaccessible or prone to human error. Despite a wide variety of DSSs for agriculture, studies indicate a disappointingly low uptake (Parker & Campion, 1997; Rose et al., 2016; Rossi et al., 2014) which is amplified in developing countries due to reasons such as technology and software being considered ‘risky’ by farmers (Fuglie et al., 2019). DSSs have barely contributed to practical agriculture due to this ‘problem of implementation’ which has been ascribed to technical limitations of software and farmers attitudes towards DSSs (Rossi et al., 2014). There are numerous detailed analyses on reasons for failure and non-adoption (Parker & Campion, 1997; Rose et al., 2016; Rossi et al., 2014) that will be examined more closely in the related works section.