@article{Kragt:147031,
      recid = {147031},
      author = {Kragt, Marit Ellen and Llewellyn, Rick S.},
      title = {Using choice experiments to improve the design of weed  decision support tools},
      address = {2013-03-29},
      number = {1784-2016-141906},
      series = {Working Paper},
      pages = {25},
      month = {Mar},
      year = {2013},
      note = {This paper has been published in a peer-reviewed journal  as:
Kragt, M.E. & Llewellyn, R. (2014) Using a Choice  experiment to improve Decision Support Tool design. Applied  Economic Perspectives and Policy, 36(2): 351-371. DOI:  10.1093/aepp/ppu001},
      abstract = {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.},
      url = {http://ageconsearch.umn.edu/record/147031},
      doi = {https://doi.org/10.22004/ag.econ.147031},
}