Computer Based Decision-making by Farmers and Advisors

Project information
Many Australian farmers own and use computers, yet decision support software is not integral to the management of more than a fraction of Australian family farms, despite the availability and affordability of such packages. This study aimed to generate insights to help developers of decision support software avoid marketing failures associated with low adoption of these technologies. The report is targeted at developers for computer based decision support systems, and those who fund and use such systems. Many Australian farmers own and use computers, yet decision support software is not integral to the management of more than a fraction of Australian family farms, despite the availability and affordability of such packages. This study aimed to generate insights to help developers of decision support software avoid marketing failures associated with low adoption of these technologies. Who is the report targeted at? The report is targeted at developers for computer based decision support systems, and those who fund and use such systems. Background A portfolio of projects known as FARMSCAPE employed an approach that involved scientists engaged directly with groups of farmers to explore matters of tactical risk management and strategic planning in dryland cropping systems. Integral to this was the use of a computer-based cropsimulation model known as APSIM. Two key strategies have been tried to deliver the FARMSCAPE approach more widely, and in a cost-effective and commercially-sustainable manner: a) FARMSCAPE Training and Accreditation and b) Yield-Prophet® on-line. There are no guarantees that these strategies will result in widespread use of simulation, and a recent contribution to the diffusion literature (Moore, 1999) provided the stimulus for an investigation into the adoption potential of cropping systems simulation. Moore (1999) proposed two distinct markets for complex technology products, separated by a ‘chasm’ between the early adopter (also termed visionary) and early majority (pragmatist) adoption categories. The chasm refers to a breakdown in social referencing between the two markets. Social referencing is a process in which one person utilizes another person’s interpretation of the situation (or technology) to formulate his or her own interpretation of it (Feinman, 1992). This behaviour arises when there is uncertainty concerning the innovation and when one’s own intrinsic appraisal processes cannot be used. In referencing, one person serves as a base of information for another, and it is a key process in technology diffusion – i.e. the process in which an innovation is communicated through certain channels, over time, among the members of a social system (Rogers 2003). The ‘chasm’ refers only to discontinuous technologies – i.e. technologies that require the adopter to change their behaviour or modify infrastructure in order to use them. If the ‘chasm’ theory applies to the use of cropping-systems simulation, the implication is that successes with innovative farmers will not automatically result in widespread use of this technology, and there is a risk that the pragmatist market will be left behind. This exposes the possibility that cropping systems simulation, which has been highly valued by some collaborating farmers, will remain as niche products, only attractive and accessible to a very small fraction of farmers, and possibly not providing the critical market volume to allow agribusiness to viably retain this as a commercial service. Aims In the context of the two commercial delivery approaches introduced above, this study aimed to provide new knowledge about market segments and evaluate the significance of Moore’s ‘chasm’ in the diffusion of cropping systems simulation. Likewise, the ‘chasm’ was also explored in a third case study, which examined the use satellite technology designed to support pasture management decisions. The technology is branded ‘Pastures from Space’. The study also aimed to identify the critical issues for effectively implementing computer-mediated decision support among a sufficient segment of the farming community to enable a viable commercial agribusiness service.
Project results: 
Key findings Was a ‘chasm’ in social referencing evident? The test of Moore’s ‘chasm’ thesis is – are there some technology users that potential users of the technology would not reference? The findings are inconclusive. Not all pragmatists agreed that it was a prerequisite to reference other pragmatist farmers before making a decision to adopt the technologies investigated and there were cases where some self-assessed pragmatists referenced visionaries. There were, however, individual cases that provided a degree of support to the notion of chasm in social referencing between visionaries and pragmatists. Is farmer-to-farmer social referencing likely to be an effective diffusion mechanism for the technologies investigated? ‘Adoption’ by interviewees of the focus technologies depended on the sense that the ‘virtual world’ created by the technology is relevant to the physical world it represents and an experience that outcomes are significant to farm management practice – i.e. benefits sufficiently outweigh the costs (including non-monetary costs) of adopting. The findings indicated that the process of social referencing was not likely to be sufficient as a means to facilitate farmers’ appreciation of the relevance and significance of the key technologies investigated. In relation to the focus technologies, they key conditions for relevance were that the technology adequately represented the structure and behaviour of the biophysical production system and that the technologies’ output adequately relates to that experienced on the adopter’s own farm. In other words, relevance was established in the context of one’s own farm and the technology had to be credible and flexible. A personal learning experience (albeit socially facilitated in group events) also appeared to be a factor in achieving relevance. Although a social referencing process can communicate potential relevance, resulting in an attitude of openness towards the innovation, it cannot be relied on to provide the subjective appreciation that goes the next step to establish the conditions for relevance described above. This launched a second stage of enquiry for this study, which sought to identify what interventions, if necessary, could facilitate the cognitive experiences for farmers that expedite adoption of technologies. Value of cropping systems simulation in commercial use A detailed study of Yield Prophet® use in four states of Australia identified three current paths for cropping systems simulation in commercial practice: 1. A flexible simulator for systems analysis by a farmer and/or consultant, customised for a farmer’s specific production environment and management issues, to explore the consequences of tactical management decisions; 2. A flexible simulator to facilitate farmer learning and development – i.e. creation of insights into farming systems and their management; 3. A tool for meeting external regulatory demands – e.g. corporate farming reporting, accountability, dealings with finance companies. This possibility was raised infrequently, compared with the first two. These correspond with 3 of the 4 paths for model-based information systems identified by McCown (2002). In relation to Path 1, Yield Prophet’s value is the provision of a flexible tool for managing climatic uncertainty by forecasting production outcomes in relation to contemplated tactical management alternatives. To date, this has largely involved Nitrogen (N) management, and there has been little use of Yield Prophet for other management decisions (e.g. pre-season planning) – a situation largely explained by the limited promotion of the latter. While demand for tactical management support would be expected on a continuous basis, it is questionable whether Yield Prophet will generate enough value to warrant ongoing use by subscribers if it is used solely for N management. Although N is an important management decision – it is a costly but necessary input, and the only in-season management option identified by interviewed farmers for dealing with climate variability – farmers varied in the degree to which their experience and judgment was augmented by Yield Prophet’s explicit presentation of probabilities of certain crop outcomes occurring. The interviews revealed that Yield Prophet was not the only method for informing the N management decision. Not all farmers received the same value from Yield Prophet – for some, the value was a low marginal benefit, whereas other reported high value.
Project partners: 
CSIRO Sustainable Ecosystems
Contact
Contact person: 
Dr Lisa Brennan
Contact email: 
Contact organisation: 
CSIRO Sustainable Ecosystems
Funding
Funding agency: 
Rural Industries Research and Development Corporation