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Designing a use case for supply chain resilience based on process mining
ID Sekulovska, Angela (Author), ID Morelli, Frank (Author), ID Siurdyban, Artur (Author), ID Manfreda, Anton (Author), ID Schätter, Frank (Author)

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Abstract
Amidst global disruptions, the significance of Supply Chain Resilience (SCR) has surged in scholarly and practical discourse. This paper endeavors to craft an industry-neutralconceptual dashboard, tailored for in-house consultants, to measureand oversee SCR. Drawing from the SCOR model's resilience metrics, Key Resilience Areas (KRAs), and Accenture's SCR application, this study presents a practical use case for deploying such a dashboard. Expert evaluation by process mining and supply chain specialists highlighted potential enhancements for the dashboard.

Language:English
Keywords:supply chain resilience management, process mining, SCOR model, key resilience areas, design science research
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:EF - School of Economics and Business
Publication status:Published
Publication version:Version of Record
Year:2023
Number of pages:14 str.
Numbering:Nr. 18
PID:20.500.12556/RUL-167431 This link opens in a new window
UDC:658.7
ISSN on article:2296-4592
DOI:10.26034/lu.akwi.2023.4204 This link opens in a new window
COBISS.SI-ID:180055811 This link opens in a new window
Publication date in RUL:21.02.2025
Views:870
Downloads:256
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Record is a part of a journal

Title:Anwendungen und Konzepte der Wirtschaftsinformatik
Shortened title:Anwend. Konzepte Wirtsch.inform.
Publisher:Institut für Wirtschaftsinformatik, Hochschule Luzern - Wirtschaft
ISSN:2296-4592
COBISS.SI-ID:142131203 This link opens in a new window

Licences

License:CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Link:http://creativecommons.org/licenses/by-nc/4.0/
Description:A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.

Secondary language

Language:German
Title:Mensch-Maschine-Zusammenarbeit bei der Entscheidungsfindung
Keywords:management, preskrbovalne verige, modeli

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