Locating agricultural decision support systems in the troubled past and socio-technical complexity of 'models for management'

By R. Mccown. 2002

176 citations recorded by the source corpus.

Subfields: Environmental Chemistry, General Agricultural and Biological Sciences, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/106b8ff2b10967be893610353636d39f817f9d9e

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In Environmental Chemistry

In General Agricultural and Biological Sciences

In Management Science and Operations Research

Citations in the corpus

Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild (2019, background): “…generated identification or prediction results are founded, and the excesively high complexity of the systems (Kuhlmann and Brodersen (2001),McCown (2002)).35 In a more recent study, the missing of comprehensive techniques for rapid disease detection is still underlined on the example of…”
Changing systems for supporting farmers' decisions: problems, paradigms, and prospects (2002, methodology): “This is a return to a mode of using models to aid management that preceded the DSS, whose ‘problem of implementation’ the DSS was expected to overcome (McCown, 2002).”
Climate Services Can Support African Farmers' Context-Specific Adaptation Needs at Scale (2019, background): “But these tools proved to be more useful for fostering dialog and learning than for guiding farmers to make particular farm management adjustments in response to climate conditions (McCown, 2002; Hochman and Carberry, 2011).”
Environmental decision support systems (EDSS) development - Challenges and best practices (2011, methodology): “The analysis of agricultural DSS use by McCown (2002b) showed the same situation to be true e farmers tended to adopt DSS to learn about and understand how to adapt to changing economic, environmental or other conditions, and then discard the DSS once learning was complete.”
Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate. (2009, unknown): “As with parallel efforts around the world, the effect on farm decision making has been disappointing (McCown 2002a, 2002b; McCown et al. 2002, 2006; Hayman 2004; Stone and Hochman 2004).”
Agent-based land-use models: a review of applications (2007, background): “…fell into the third category of Parker et al. (2002) , i.e. 18 specifically designed as Decision Support Systems for direct use by end-users, but experience 19 in other more mature areas of simulation modelling suggest that at some stage they may be 20 promoted as such tools (McCown, 2002b).”
Re-inventing model-based decision support with Australian dryland farmers. 1. Changing intervention concepts during 17 years of action research (2009, methodology): “Study of the rise and demise of the DSS and of the histories of significant precursors as a source of lessons became an important part of our research on a new approach (McCown 2001b, 2002a, 2002b, 2005; McCown et al. 2002, 2006; McCown and Parton 2006).”
Knowledge management technologies and applications - literature review from 1995 to 2002 (2003, background): “…activities for collaborative decision support, information sharing, organizational learning, and organizational memory (Caraynnnis, 1999; Chen et al., 2002; Harun, 2002; Hicks, Culley, Allen, & Mullineux, 2002; McCown, 2002; Ramesh & Tiwana, 1999; Robey, Boudreau, & Rose, 2000; Yoo & Kim, 2002).”