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Integration of Generative AI into a tool to assist participatory ESG doublemateriality assessment for SMEs

  • The research outlines a concept to conduct the double materiality assessment through the synergistic use of Generative AI and the AHP method. In the first step, we employ interactive, moderated workshops as our chosen methodology to create a tailored set of sustainability target criteria. This process is enriched by the inclusion of Generative AI. The outcome is a comprehensive set of company-specific sustainability target criteria.

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Verfasserangaben:Benedikt Latos, Daniela Becks, Antoine Gaillard, Martin PerauORCiD, Bernd Respondek, Michael Kranz, J. Kukulies, Christian Kruse
URL:https://cgscholar.com/cg_event/events/S24en/proposal/70046
Titel des übergeordneten Werkes (Deutsch):Proceedings of Twentieth International Conference on Environmental, Cultural, Economic & Social Sustainability University of Aveiro, Portugal 24-26 January 2024
Dokumentart:Konferenzveröffentlichung
Sprache:Deutsch
Datum der Veröffentlichung (online):17.03.2024
Datum der Erstveröffentlichung:14.01.2024
Datum der Freischaltung:23.04.2024
Freies Schlagwort / Tag:AI; ESG; analytic hierarchy process; double materiality assessment; sustainability strategy
Umfang:3
Bemerkung:
This work was created as part of a collaboration with associated partners in the context of the funded joint project DiCES (Digital Transformation of Circular Economy for Industrial Sustainability) with the funding code 01MN23022E, which is part of the GreenTech funding framework "Development of Digital Technologies" of the Federal Ministry for Economic Affairs and Climate Action (BMWK), Germany. The responsibility for the content of this publication lies with the authors.
FIR-Nummer:-FOLGT-
Konferenzname:Twentieth International Conference on Environmental, Cultural, Economic & Social Sustainability
Konferenzort:University of Aveiro, Portugal
Konferenzzeitraum:24.01.2024 – 26.01.2024
Institut / Bereiche des FIR:FIR e. V. an der RWTH Aachen
Produktionsmanagement
DDC-Klassifikation:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften