Annotation data about multi criteria assessment methods used in the agri-food research: The french national institute for agricultural research (INRA) experience

Gésan-Guiziou, Geneviève; Alaphilippe, Aude; Andro, Mathieu; Aubin, Joël; Bockstaller, Christian; Botreau, Raphaëlle; Buche, Patrice; Collet, Catherine; Darmon, Nicole; Delabuis, Monique; Girard, Agnès; Grateau, Regis; Kansou, Kamal; Martinet, Vincent; Membré, Jeanne‐Marie; Sabbadin, Régis; Soler, Louis Georges; Thiollet‐Scholtus, Marie; Tonda, Alberto; Werf, Hayo M.G. van der

doi:10.1016/j.dib.2019.104204

Cited by 2 publications

(4 citation statements)

References 10 publications

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“…The articles were selected and annotated in the framework of an INRA internal project, run in 2016-2019, gathering experts covering the diversity of the disciplinary approaches and applications developed in the institute (agronomy, animal science, biological science, genetics, silviculture, environmental science, process engineering, food technology, food safety, nutrition, consumer science, risk-benefit assessment, economics, applied mathematics, applied statistics, artificial intelligence). The selection and annotation of papers were described in the related data paper (Gésan-Guiziou et al 2019).…”

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

“…Relevant articles published by INRA researchers from 2007 to mid-2017 were extracted in mid-2017 from the Web of Science using two queries as described in Gésan-Guiziou et al (2019).…”

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

“…The resulting corpus of articles ( 4920) was then manually classified as MCDA (954) or non-MCDA (3966) by domain experts using a set of positive and negative criteria that defined an "MCDA article." In order to achieve this task, these data (4920 papers) have been split into 13 Excel files corresponding to scientific domains to cover the diversity of the disciplinary approaches and applications developed in INRA (see Gésan-Guiziou et al 2019). Classification has been done in two steps.…”

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

“…Categories associated with each of those 8 criteria, listed in Gésan-Guiziou et al (2019), were used to annotate the 954 MCDA articles. The Excel files with the annotations and classifications are available in a public repository presented by Gésan-Guiziou et al (2019).…”

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

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Diversity and potentiality of multi-criteria decision analysis methods for agri-food research

Gésan-Guiziou

Alaphilippe

Aubin

et al. 2020

Agron. Sustain. Dev.

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There is a growing demand for moving towards sustainable agri-food systems which per nature covers a complex network of activities and domains; such systems will benefit from multi-criteria decision analysis (MCDA) methods. Although some reviews on MCDA in agri-food research have been published, none of them covered the whole value chain. In this article, a corpus of 954 articles published by INRA scientists from 2007 to 2017 was used to study the diversity and potentiality of MCDA techniques. For the first time, experts from more than 10 agri-food domains worked altogether to annotate the articles, carry out a multivariate analysis, and finally interpret the statistical results to identify the specificities of certain domains and the complementarities between domains and to suggest avenues for future agri-food research. One-third of the studies were based only on a list of indicators, even when their purpose was to choose, sort, or rank options. Regardless of the scientific discipline in the agri-food sector, MCDA studies rarely considered temporal dynamics, spatial scale changes, or stakeholder contributions. As the agri-food system becomes increasingly sustainable in the near future, the use of MCDA methods will accelerate. To become more effective, they will have to include ecosystem services, even outside the scope of ecological studies. Similarly, MCDA studies will need to include participatory science to involve stakeholders (i.e., public authorities, governmental agencies) and end-users (i.e., farmers, producers, industrials, consumers) in the construction of the multi-criteria evaluation but also in the resulting decisions.

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Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

“…Relevant articles published by INRA researchers from 2007 to mid-2017 were extracted in mid-2017 from the Web of Science using two queries as described in Gésan-Guiziou et al (2019).…”

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

Section: Selection and Annotation Of Scientific Articlesmentioning

confidence: 99%

See 2 more Smart Citations

Diversity and potentiality of multi-criteria decision analysis methods for agri-food research

Gésan-Guiziou

Alaphilippe

Aubin

et al. 2020

Agron. Sustain. Dev.

Self Cite

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Integrating Multi-Criteria Techniques in Life-Cycle Tools for the Circular Bioeconomy Transition of Agri-Food Waste Biomass: A Systematic Review

Romero-Perdomo

González‐Curbelo

2023

Sustainability

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Agri-food waste biomass (AWB) is consolidating as a relevant bioresource for supplying material products and energy in a circular bioeconomy. However, its recovery and sustainable processing present trade-offs that must be understood. The integration of multi-criteria decision analysis (MCDA) into life-cycle assessment (LCA) tools has emerged as a novel way to address this challenge. This paper aims to conduct a systematic literature review to critically synthesize how MCDA has been integrated into LCA in an assessment framework and how helpful it is in AWB’s circular bioeconomy transition. The literature shows that the most studied AWBs are rice husk, sugarcane bagasse, and household food waste. These are processed through the technologies of composting, anaerobic digestion, and pyrolysis for applications such as biofuels, bioenergy, and soil amendment. Environmental LCA (E-LCA) is the most widely used LCA tool, while both the analytical hierarchy process (AHP) and the technique for ordering preference by similarity to the ideal solution (TOPSIS) are the most applied techniques for MCDA. The current trend of integrating MCDA into LCA does not fully cover the LCA phases, favoring solely the impact assessment phase and indicating that the other phases are overlooked. The potential and involvement of the stakeholders are partially explored. Although there are holistic sustainability assessments, the social implications are rarely considered. The number of MCDA/LCA studies is expected to increase, assessments at the micro-, meso-, and macro-scales to become more articulated, and the impact of the results to become more aligned with government and company goals.

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Annotation data about multi criteria assessment methods used in the agri-food research: The french national institute for agricultural research (INRA) experience

Cited by 2 publications

References 10 publications

Diversity and potentiality of multi-criteria decision analysis methods for agri-food research

Diversity and potentiality of multi-criteria decision analysis methods for agri-food research

Integrating Multi-Criteria Techniques in Life-Cycle Tools for the Circular Bioeconomy Transition of Agri-Food Waste Biomass: A Systematic Review

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