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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Author:Benedikt Latos, Daniela Becks, Antoine GaillardORCiD, Martin PerauORCiD, Bernd Respondek, Michael Kranz, J. Kukulies, Christian Kruse
URL:https://cgscholar.com/cg_event/events/S24en/proposal/70046
Parent Title (German):Proceedings of Twentieth International Conference on Environmental, Cultural, Economic & Social Sustainability University of Aveiro, Portugal 24-26 January 2024
Document Type:Conference Proceeding
Language:German
Date of Publication (online):2024/03/17
Date of first Publication:2024/01/14
Release Date:2024/04/23
Tag:03
AI; ESG; analytic hierarchy process; double materiality assessment; sustainability strategy
Page Number:3
Note:
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-Number:SV7847
Name of the conference:Twentieth International Conference on Environmental, Cultural, Economic & Social Sustainability
place of the conference:University of Aveiro, Portugal
Date of the conference:24.01.2024 – 26.01.2024
Institute / Department:FIR e. V. an der RWTH Aachen
Produktionsmanagement
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften