UNDERSTANDING THE ADOPTION OF KNOWLEDGE INTENSIVE TECHNOLOGIES IN THE AUSTRALIAN SUGAR INDUSTRY--A PILOT STUDY

CROP MODELS and seasonal climate forecasts, which often form part of decision support systems (DSSs), are complex and knowledge intensive technologies. Typically, some form of learning is needed by end users to understand how these technologies can complement decision making activities. Globally, it is acknowledged that adoption levels of these technologies are limited. If industry is to benefit from information produced from knowledge intensive technologies, it is essential that researchers and industry better understand the technology development process and appropriate adoption pathways. This paper describes how researchers have been working in partnership with industry case study groups to explore opportunities and benefits associated with three knowledge intensive technologies-irrigation modelling, nitrogen modelling and climate forecasting. Data collected from observations, minutes of meetings and interviews will, as part of further research, be used to shape and refine theories that will lead to the development of a conceptual model about technology development and adoption. As well as increasing our understanding about adoption processes, this model will increase the likelihood that benefits from knowledge intensive technologies can accrue to industry.