Australian farmers left behind in the digital economy – Insights from the Australian Digital Inclusion Index
Introduction
As the post-industrial world has moved online, access to digital communication technologies has become increasingly important for rural communities. Broadband access is now considered a core public utility (Edwards, 2009) and has been promoted as a human right (Economist Intelligence Unit, 2018, p. 2). Mere access to digital technologies, however, does not mean that people or communities are able to participate fully in the digital economy. The current scholarship on digital inclusion addresses a range of issues, from deficiencies in network infrastructure to the roles of income and education in influencing internet use. Ragnedda and Mutsvairo (2018, pviii) observe that “a growing body of empirical and theoretical research has investigated digital inclusion without coming to a common definition”. In this paper we use the term to denote the ability of people to access, afford and use online technologies effectively (Thomas et al., 2019). We analyse digital inclusion among Australian farmers, a geographically dispersed rural population facing significant technological, environmental and market challenges.
Digital inclusion is underpinned by many factors, including the existence, nature and quality of connections; options and value for money of telecommunications and internet services, hardware and software; digital literacy to use technologies for a range of social, cultural and economic purposes; and other contextual factors promoting and limiting effective digital technology use. Our approach aligns with scholarship seeking more nuanced ways to measure and understand digital inclusion and related phenomena (Wilson et al., 2019). Further, by focussing on the ways people use digital technologies to respond to their specific needs in the places they live (Collin et al., 2018), we emphasise the entanglement of digital and social participation in Australian farming communities.
Digital inclusion is important because it is closely linked with social and economic circumstances and outcomes for individuals and groups (Broadbent and Papadopoulos, 2011). Some 12 years ago Helsper (2008, p. 8) argued that “technology is so tightly woven into the fabric of society today that ICT deprivation can rightly be considered alongside, and strongly linked to, more traditional twentieth century social deprivations, such as low income, unemployment, poor education, ill health and social isolation.” This is even truer today. Internationally, researchers have investigated digital inclusion in relation to socially and economically disadvantaged populations such as seniors (Charmarkah, 2017), children (Livingstone and Helsper, 2007), people with disabilities (Seale et al., 2010), and Indigenous communities in Australia (Rennie, 2019; Ewing, anonymous) and abroad (Dyson, 2011; McMahon, 2014). Combinations of social disadvantage such as poor skills, low employment, poor health, lack of education and low income tend to be associated with low levels of digital inclusion, and digital exclusion and other forms of social disadvantage may be mutually reinforcing (Helsper, 2008).
The geographic aspects of digital inclusion have also been investigated internationally. For example, Correa and Pavez (2016) explore challenges to digital inclusion faced by remote villagers in Chile, citing geographic isolation, an aging population, and the manual nature of work available in remote areas. Galloway, Sanders and Deakins' (2011) UK-based study illustrates the discrepancy between small rural companies’ embeddedness in local supply chains compared to global opportunities afforded by the internet that are more often taken up by city counterparts. Salemik, Strijker and Bosworth (2017, p. 360) observe that in developed countries, “rural communities are the most in need of improved digital connectivity to compensate for remoteness, but they are the least connected and included.” In Australia, a third of the population live outside cities (Australian Bureau of Statistics [ABS], 2016) and many of the above-identified digital inclusion challenges are echoed in these regional and remote areas,1 including in agricultural communities.
The gross value of Australian farm production (agriculture, fisheries and forestry) in 2018-19 was AUS $69 billion, and Australian agriculture accounts for 2.2% of value added GDP (Jackson et al., 2020). The sector directly employs over 300,000 people (2.6% of national employment) and produced 11% of the nation's goods and services exports in 2018–19 (Jackson et al., 2020). The implications of digital non-participation for Australia's farming sector are profound in an era of global communications, new agricultural technologies (‘AgTech’), and the internet of things (IoT). Automation, big data, and the use of autonomous vehicles for farm management are changing rural economies (Tzounis et al., 2017; Wolfert et al., 2017). The sophistication and application of AgTech ranges from the everyday use of GPS apps and cloud-based systems, through to blockchain technology, big data techniques and precision agriculture (Dufty and Jackson, 2018). AgTech is big business globally. Worldwide investment in AgTech was $3.2 billion in 2016 and $4.6 billion in 2015 (AgFunder, 2016). In Australia, the National Farmers' Federation (2018, p. 8) claims “agriculture is currently only reaching 75% of the potential it could reach if it was enabled to fully participate in the digital economy”. If Australia's farming sector is to attract global AgTech investment, access to affordable internet and the ability to implement digital solutions in business and on farms is essential to drive innovation.
Our account of the extent and nature of digital inclusion of Australian farmers is based on our analysis of primary data from the Australian Digital Inclusion Index (ADII). The ADII dataset is extracted from the Roy Morgan Single Survey – an ongoing face-to-face and written survey of 50,000 Australian households. ADII calculations are based on a sub-sample of approximately 16,000 responses in each 12-month period. Our research drew on a custom ADII dataset to consider whether Australian farmers are more or less digitally included than other populations, and what factors may help explain the result. We isolated and interrogated the ADII data on Access, Affordability and Digital Ability for farmers, whom we define as those self-reporting their occupation as ‘farmer or farm manager’. The analysis produced a perplexing and previously unrecognised result: farmers score poorly on the Index when compared to Australians living in similar circumstances but who are not employed in the farming sector. These findings, together with our suggestions about the underlying social and economic factors contributing to this outcome, are discussed in the broader context of digital inclusion in Australia. Our results have theoretical and practical implications for the ways industry leaders, researchers and farmers may address the specific needs of agricultural communities. Before turning to a review of digital inclusion in rural and farming communities, we look at the origins of the concept of digital inclusion internationally and how it has evolved in the Australian context.
Section snippets
From the digital divide to digital inclusion
‘Digital inclusion’ first appeared in academic literature around 2003 (Warschuaer, 2003), stemming from existing work on the ‘digital divide’, a term coined in the mid-1990s (Foster & Burkowski, 2007 in Walton et al., 2013). Early conceptions of the digital divide in the US were framed as exclusion from information owing to lack of access to the internet (Compaine, 2001). In the late 1990s, digital divide policy centred on ensuring that no one was left behind in the age of digital opportunity (
Methodology
The following case study of Australian farmers’ levels of digital inclusion draws on primary data extracted from the Australian Digital Inclusion Index (ADII) dataset. The Index, which measures digital inclusion along three indices – Access, Affordably and Digital Ability – is informed by progressive conceptions of digital inclusion that ground the research in real world circumstances and therefore informs meaningful research, policy, funding and programs. Under this conceptualisation “Digital
Australian farmers’ digital inclusion scores
The Index data suggest that the farming sector in Australia is facing significant digital inclusion challenges. The data for farmers across Australia shows an overall score of 45.4 which is significantly lower than the national score for rural Australia (52.8) and the overall Australian score (59.2) (See Fig. 3).
Farmers score 42.6 for Affordability, 14.1 points lower than the national score of 56.7. The ADII dataset reveals that the Affordability issue for farmers has two components. First,
Discussion
Although we expected farmers’ digital inclusion scores to be lower than those of other Australians due to a historic lack of access to telecommunications infrastructure, and traditionally lower levels of educational attainment than the rest of the population, we were surprised at the disparity between farmers and other rural Australian residents. This was apparent across all three dimensions of the digital inclusion Index, but particularly the Affordability and Digital Ability sub-indices. We
Conclusion
In this paper we investigated the extent to which Australian farmers are digitally included and explored some of the possible factors underpinning the current state of affairs. We have presented previously undisclosed ADII data that revealed a perplexing scenario in which farmers score lower on all sub-indices – Access, Affordability and Digital Ability — than others in similar circumstances. Specifically, while overall Digital Inclusion is improving over time, farmers’ Digital Ability scores
Funding
Funding for the research reported in this article was provided as part of the Australian Digital Inclusion Index, a collaborative research project between RMIT University, Centre for Social Impact at Swinburne University of Technology, Telstra and Roy Morgan Research. A. Marshall, M. Dezuanni and J. Burgess acknowledge continued support from the Queensland University of Technology (QUT) through the Digital Media Research Centre. J. Thomas acknowledges continued support from RMIT University
CRediT authorship contribution statement
Amber Marshall: Investigation, Formal analysis, Writing - original draft, Project administration. Michael Dezuanni: Funding acquisition, Conceptualization, Formal analysis, Writing - original draft, Writing - review & editing, Supervision. Jean Burgess: Funding acquisition, Formal analysis, Writing - review & editing. Julian Thomas: Methodology, Resources, Writing - review & editing. Chris K. Wilson: Methodology, Resources, Data curation, Formal analysis, Writing - review & editing.
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