Katharina Brennig

Wirtschaftsinformatik, insb. Data Analytics
katharina.brennig@uni-paderborn.de
ID
51905

4 Publications

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[4]
2023 | Conference Paper | LibreCat-ID: 37058
K. Brennig and O. Müller, “More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process Transparency,” presented at the 56th Hawaii International Conference on System Sciences, Lāhainā, 2023.
LibreCat
 
[3]
2023 | Conference Paper | LibreCat-ID: 50459
J. Brock et al., “A Process Mining Maturity Model: Enabling Organizations to Assess and Improve their Process Mining Activities,” 2023.
LibreCat
 
[2]
2023 | Book Chapter | LibreCat-ID: 50450
K. Brennig, K. Benkert, B. Löhr, and O. Müller, “Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?,” in Business Process Management Workshops, 2023.
LibreCat | DOI
 
[1]
2022 | Conference Paper | LibreCat-ID: 36912
B. Löhr, K. Brennig, C. Bartelheimer, D. Beverungen, and O. Müller, “Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing,” 2022, doi: 10.1007/978-3-031-16103-2_18.
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4 Publications

Mark all

[4]
2023 | Conference Paper | LibreCat-ID: 37058
K. Brennig and O. Müller, “More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process Transparency,” presented at the 56th Hawaii International Conference on System Sciences, Lāhainā, 2023.
LibreCat
 
[3]
2023 | Conference Paper | LibreCat-ID: 50459
J. Brock et al., “A Process Mining Maturity Model: Enabling Organizations to Assess and Improve their Process Mining Activities,” 2023.
LibreCat
 
[2]
2023 | Book Chapter | LibreCat-ID: 50450
K. Brennig, K. Benkert, B. Löhr, and O. Müller, “Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?,” in Business Process Management Workshops, 2023.
LibreCat | DOI
 
[1]
2022 | Conference Paper | LibreCat-ID: 36912
B. Löhr, K. Brennig, C. Bartelheimer, D. Beverungen, and O. Müller, “Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing,” 2022, doi: 10.1007/978-3-031-16103-2_18.
LibreCat | DOI
 
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Citation Style: IEEE

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