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Multi-criteria Decision Making #23
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Sounds good - raw values and discussing trade-offs with decision-makers will be useful. There may be a bit of precedence here that we can use as a jumping-off place. In a paper on banana production, for example, we show relative farm-level effects on climate change adaptation and mitigation, ecology and production costs, change in yield and risks: In a paper on homegardens, we show the EVPI calculations for the sensitivity of the system preference to uncertainty in model parameters: annual nutrient contributions in 10,000 Monte Carlo model runs Those Papers: Whitney, Cory, John R.S. Tabuti, Oliver Hensel, Ching-hua Yeh, Jens Gebauer, and Eike Luedeling. “Homegardens and the Future of Food and Nutrition Security in Southwest Uganda.” Agricultural Systems 154 (2017): 133–44. https://doi.org/10.1016/j.agsy.2017.03.009. |
So far, as far as I know, all the different possible decision criteria/objectives are combined into one number (usually NPV) to be able to come up with decision suggestions and calculate EVPI and so on.
It would be nice, to be able to report on the "raw" decision outcomes (might be CO2, money, a nutrition metric, ...), be explicit about trade-offs and then weight them in the very last step (possibly consulting decision-makers / stakeholders again). "Option A is more slightly climate-friendly, but option B is a lot more profitable, ... We decided for option X because of ..."
The HoliDA package will be built to support this kind of workflow. Maybe already conceptualize it this way in the course/book/paper?
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