Integrating generative artificial intelligence into supply chain management education using the SCOR model
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Author (Corporation)
Publication date
2024
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editor (Corporation)
Supervisor
Parent work
CAiSE 2024 International Workshops
Special issue
DOI of the original publication
Link
Series
Lecture Notes in Business Information Processing
Series number
521
Volume
Issue / Number
Pages / Duration
59-71
Patent number
Publisher / Publishing institution
Springer
Place of publication / Event location
Limassol
Edition
Version
Programming language
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Practice partner / Client
Abstract
Bridging rule-based Supply Chain Management (SCM) systems with Generative Artificial Intelligence (GenAI) presents a novel approach towards overcoming persistent SCM challenges. This study introduces a novel approach that integrates GenAl with the Supply Chain Operations Reference (SCOR) Model, a widely accepted quasi-ontology in SCM, through Retrieval-Augmented Generation (RAG). Utilizing Google's Vertex AI Search as an implementation case in an educational context, we demonstrate the practical application of resulting generative SCM (GenSCM), which seeks to combine the advantages of both symbolic and sub-symbolic AI. Our study contributes to the literature by outlining an approachable pathway for integrating GenAI in SCM, and it provides insights on a domain-specific integration of symbolic and sub-symbolic Al. While the findings illustrate the potential of GenSCM in education, future research is needed on superior SCM problem-solving and operational execution in real-life SCM settings.
Keywords
Subject (DDC)
Event
CAiSE 2024
Exhibition start date
Exhibition end date
Conference start date
03.06.2024
Conference end date
07.06.2024
Date of the last check
ISBN
978-3-031-61002-8
978-3-031-61003-5
978-3-031-61003-5
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Closed
License
Citation
Ehrenthal, J., Gachnang, P., Loran, L., Rahms, H., & Schenker, F. (2024). Integrating generative artificial intelligence into supply chain management education using the SCOR model. In J. P. A. Almeida, C. Di Ciccio, & C. Kalloniatis (Eds.), CAiSE 2024 International Workshops (pp. 59–71). Springer. https://doi.org/10.1007/978-3-031-61003-5_6