Using choice experiments to improve the design of weed decision support tools
The potential for computer-based decision support tools (DSTs) to better inform farm management decisions is well-recognised. However, despite considerable investment in a wide range of tools, the uptake by advisers and farmers remains low. Greater understanding of the demand and the most valued features of decision support tools has been proposed as an important step in improving the impact of DSTs. Using a choice experiment, we estimated the values that Australian farm advisers attach to specific attributes of decision support tools, in this case relating to weed and herbicide resistance management. The surveys were administered during dedicated workshops with participants who give weed management advice to grain growers. Results from various discrete choice models showed that advisers’ preferences differ between private fee-charging consultants, those attached to retail outlets for cropping inputs, and advisers from the public sector. Reliably accurate results were valued, but advisers placed a consistently high value on models with an initial input time of three hours or less, compared to models that are more time demanding. Results from latent class models revealed a large degree of personal preference heterogeneity across advisers. Although the majority of advisers attributed some value to the capacity for DST output that is specific to individual paddocks, approximately one quarter of respondents preferred generic predictions for the district rather than greater specificity. The use of a novel non-market valuation approach can help to inform development of decision support tools with attributes valued by potential users.
|Date of creation:||29 Mar 2013|
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- Ian J. Bateman & Roy Brouwer & Helen Davies & Brett H. Day & Amelie Deflandre & Salvatore Di Falco & Stavros Georgiou & David Hadley & Michael Hutchins & Andrew P. Jones & David Kay & Graham Leeks & M, 2006. "Analysing the Agricultural Costs and Non-market Benefits of Implementing the Water Framework Directive," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(2), pages 221-237, 07.
- Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132.
- Jakku, E. & Thorburn, P.J., 2010. "A conceptual framework for guiding the participatory development of agricultural decision support systems," Agricultural Systems, Elsevier, vol. 103(9), pages 675-682, November.
- Hensher, David A. & Rose, John M., 2007. "Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 428-443, June.
- Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
- David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
- Hochman, Z. & Carberry, P.S., 2011. "Emerging consensus on desirable characteristics of tools to support farmers' management of climate risk in Australia," Agricultural Systems, Elsevier, vol. 104(6), pages 441-450, July.
- Swait, Joffre & Adamowicz, Wiktor, 2001. " The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching," Journal of Consumer Research, University of Chicago Press, vol. 28(1), pages 135-48, June.
- Kragt, Marit Ellen & Bennett, Jeffrey W., 2011.
"Using choice experiments to value catchment and estuary health in Tasmania with individual preference heterogeneity,"
Australian Journal of Agricultural and Resource Economics,
Australian Agricultural and Resource Economics Society, vol. 55(2), June.
- Marit E. Kragt & J.W. Bennett, 2011. "Using choice experiments to value catchment and estuary health in Tasmania with individual preference heterogeneity," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(2), pages 159-179, 04.
- McIntosh, E. & Ryan, M., 2002. "Using discrete choice experiments to derive welfare estimates for the provision of elective surgery: Implications of discontinuous preferences," Journal of Economic Psychology, Elsevier, vol. 23(3), pages 367-382, June.
- Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, September.
- Daniel McFadden, 1986. "The Choice Theory Approach to Market Research," Marketing Science, INFORMS, vol. 5(4), pages 275-297.
- Caussade, Sebastián & Ortúzar, Juan de Dios & Rizzi, Luis I. & Hensher, David A., 2005. "Assessing the influence of design dimensions on stated choice experiment estimates," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 621-640, August.
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