Generic algorithm for multicriteria ranking of crop technological options based on the “Technique for Order of Preference by Similarity to Ideal Solution” using ShinyApps

Many agricultural research and development programs aiming at enhancing tradeoffs related to different adoption, management and policy decisions face a methodological problem in which multi-criteria ranking is used to reach acceptable compromises between different objectives (e.g. those of farms, re...

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Vydané v:MethodsX Ročník 8; s. 101519
Hlavní autori: Frija, Aymen, Ouerghemmi, Hassen, Ismail, Firas, Gbegbelegbe, Sika, Swamikannu, Nedumaran
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.01.2021
Elsevier
Predmet:
agricultural research
algorithms
children
computer software
farm management
issues and policy
malnutrition
Method
Multicriteria assessment
poverty
Ranking of options
research and development
Rstudio
Shiny
South Asia
Sub-Saharan Africa
Tradeoffs
Sub-Saharan Africa
South Asia
Multicriteria assessment
R
Tradeoffs
Ranking of options
TOPSIS_ShinyApp
Rstudio
Shiny
ISSN:2215-0161, 2215-0161
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Shrnutí:Many agricultural research and development programs aiming at enhancing tradeoffs related to different adoption, management and policy decisions face a methodological problem in which multi-criteria ranking is used to reach acceptable compromises between different objectives (e.g. those of farms, research managers, donors or policy makers). A typical situation is where many farm management options will result in different conflicting economic, social and environmental impacts. Ranking these options and the choice of those to promote is challenging. The literature provides a set of methodological solutions that need background data organization and simulation through coding using different computing software. Here, we provide a generic solution and friendly interface, made on Shiny (an R-package) based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We apply this method for ranking different crop technological products of grain legumes and dry cereals based on their respective impacts on poverty, child malnutrition and economic benefits in more than 40 countries in eight different geographic zones across South Asia and Sub-Saharan Africa. • The developed algorithms and interface can help rank different options based on the weights (preferences) of their respective outcome indicators. • The interface allows for changing the weights (preferences) and automatically generates new ranking tables and graphs accordingly, which can serve for scenario simulations, which saves time compared to manually performing these calculations. [Display omitted]
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ISSN:2215-0161
2215-0161
DOI:10.1016/j.mex.2021.101519