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A conceptual framework for guiding the participatory development of agricultural decision support systems

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  • Jakku, E.
  • Thorburn, P.J.
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    Abstract

    Scientists develop decision support systems (DSSs) to make agricultural science more accessible for farmers and extension officers. Despite the growing use of participatory approaches in agricultural DSS development, reflection on this endeavour has largely focused on the 'doing' of participation or the 'problem of implementation' when DSSs have not been adopted by stakeholders. There has been little reference to relevant theoretical approaches to the social processes involved in 'participation' or 'implementation'. However, if DSS use is to reach its full potential, a more conceptually informed understanding of how stakeholders collaborate in the participatory development of DSSs is required. To contribute to this conceptualisation, we developed a framework based on three concepts drawn from the field of science and technology studies: technological frames, interpretative flexibility and boundary objects. The framework highlights the importance and value of social learning for participatory DSS development, which relies upon exploring the participating parties' different perspectives on the agricultural system represented in the DSS. Our framework provides a broad definition of success for participatory DSS development, placing greater weight on learning during the participatory process compared with subsequent use of the DSS by farmers and/or advisors. Two case studies of stakeholder collaboration to develop an irrigation scheduling DSS for sugarcane production were used to explore the relevance of the framework. The concepts in the framework were clearly displayed during the case studies. At the conclusion of the studies there were contrasting outcomes for the DSS. One group of farmers was keen to apply it in their ongoing irrigation management, while another saw little relative advantage in use of the DSS. In both instances co-learning occurred amongst case study participants, so the participatory process was clearly a success.

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    Bibliographic Info

    Article provided by Elsevier in its journal Agricultural Systems.

    Volume (Year): 103 (2010)
    Issue (Month): 9 (November)
    Pages: 675-682

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    Handle: RePEc:eee:agisys:v:103:y:2010:i:9:p:675-682

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    Web page: http://www.elsevier.com/locate/agsy

    Related research

    Keywords: Social learning Interpretative flexibility Technological frames Boundary objects Sugarcane Environmental modelling;

    References

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    1. M. Muro & P. Jeffrey, 2008. "A critical review of the theory and application of social learning in participatory natural resource management processes," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 51(3), pages 325-344.
    2. Walker, Daniel H., 2002. "Decision support, learning and rural resource management," Agricultural Systems, Elsevier, vol. 73(1), pages 113-127, July.
    3. Carberry, P. S. & Hochman, Z. & McCown, R. L. & Dalgliesh, N. P. & Foale, M. A. & Poulton, P. L. & Hargreaves, J. N. G. & Hargreaves, D. M. G. & Cawthray, S. & Hillcoat, N. & Robertson, M. J., 2002. "The FARMSCAPE approach to decision support: farmers', advisers', researchers' monitoring, simulation, communication and performance evaluation," Agricultural Systems, Elsevier, vol. 74(1), pages 141-177, October.
    4. Hearn, A. B. & Bange, M. P., 2002. "SIRATAC and CottonLOGIC: persevering with DSSs in the Australian cotton industry," Agricultural Systems, Elsevier, vol. 74(1), pages 27-56, October.
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    6. Williams, Robin & Edge, David, 1996. "The social shaping of technology," Research Policy, Elsevier, vol. 25(6), pages 865-899, September.
    7. Nelson, R. A. & Holzworth, D. P. & Hammer, G. L. & Hayman, P. T., 2002. "Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software," Agricultural Systems, Elsevier, vol. 74(3), pages 393-414, December.
    8. J Murdoch, 1995. "Actor-networks and the evolution of economic forms: combining description and explanation in theories of regulation, flexible specialization, and networks," Environment and Planning A, Pion Ltd, London, vol. 27(5), pages 731-757, May.
    9. Gibbons, James M. & Sparkes, Debbie L. & Wilson, Paul & Ramsden, Stephen J., 2005. "Modelling optimal strategies for decreasing nitrate loss with variation in weather - a farm-level approach," Agricultural Systems, Elsevier, vol. 83(2), pages 113-134, February.
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    Cited by:
    1. Kragt, Marit Ellen & Llewellyn, Rick S., 2013. "Using choice experiments to improve the design of weed decision support tools," Working Papers 147031, University of Western Australia, School of Agricultural and Resource Economics.
    2. Garb, Yaakov & Friedlander, Lonia, 2014. "From transfer to translation: Using systemic understandings of technology to understand drip irrigation uptake," Agricultural Systems, Elsevier, vol. 128(C), pages 13-24.

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