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Autorinnen/Autoren:
Winkel, Fabian; Geierhos, Michaela; Fink, Josef
Dokumenttyp:
Konferenzbeitrag / Conference Paper
Titel:
Evaluating Embedding Models for Retrieving ESG Information from Annual Business Reports
Titel Konferenzpublikation:
ICIS 2024 Proceedings, 23, AI in Business and Society
Konferenztitel:
International Conference on Information Systems (45., 2024, Bangkok)
Konferenztitel:
International Conference on Information Systems (ICIS) 2024 Conference
Tagungsort:
Bangkok, Thailand
Jahr der Konferenz:
2024
Datum Beginn der Konferenz:
15.12.2024
Datum Ende der Konferenz:
18.12.2024
Verlegende Institution:
Association for Information Systems (AIS)
Jahr:
2024
Seitenbereich:
2621
Sprache:
Englisch
Stichwörter:
ESG statements ; annual business reports ; retrieval systems ; language model selection
Abstract:
Development Goals (SDG) has become paramount. Companies embed their ESG achievements, plans, and commitments into their annual reports in a non-standardized textual format. We propose a retrieval system for increasing transparency and comparability in ESG reporting, enabling various stakeholders to compare sustainability statements across annual reports. We employed qualitative and quantitative evaluation methods to select the most suitable embedding model for the proposed ESG retrieval applicat...     »
Article-ID:
2621
URL zum Inhalt:
https://aisel.aisnet.org/icis2024/aiinbus/aiinbus/23
Fakultät:
Fakultät für Informatik
Institut:
INF 7 - Institut für Datensicherheit
Professorin/Professor:
Geierhos, Michaela
Forschungszentrum:
CODE
Open Access:
Ja / Yes
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