Unlocking Shelf Performance Potential in Stationary Retail Using Artificial Intelligence: Learning from Digital Shelf Twin Data - Forschungsportal der Justus-Liebig-Universität Gießen:

Meeting Abstract

Unlocking Shelf Performance Potential in Stationary Retail Using Artificial Intelligence: Learning from Digital Shelf Twin Data

Autorenliste: Roggenkämper, Luisa; Feurer, Sven; Schuhmacher, Monika

Jahr der Veröffentlichung: 2023

URL: https://proceedings.emac-online.org/index.cfm?abstractid=A2023-114472&Unlocking%20Shelf%20Performance%20Potential%20in%20Stationar

Konferenz: EMAC annual conference 2023

Autoren/Herausgeber

- Uni.-Prof. Dr. Monika Christine Schuhmacher

Zitierstile

Harvard-Zitierstil: Roggenkämper, L., Feurer, S. and Schuhmacher, M. (2023) Unlocking Shelf Performance Potential in Stationary Retail Using Artificial Intelligence: Learning from Digital Shelf Twin Data, EMAC annual conference 2023, Odense, Denmark , May 23 - 26, 2023. https://proceedings.emac-online.org/index.cfm?abstractid=A2023-114472&Unlocking%20Shelf%20Performance%20Potential%20in%20Stationar

APA-Zitierstil: Roggenkämper, L., Feurer, S., & Schuhmacher, M. (2023, May 23 - 26, 2023). Unlocking Shelf Performance Potential in Stationary Retail Using Artificial Intelligence: Learning from Digital Shelf Twin Data. EMAC annual conference 2023, Odense, Denmark . https://proceedings.emac-online.org/index.cfm?abstractid=A2023-114472&Unlocking%20Shelf%20Performance%20Potential%20in%20Stationar