---
_id: '65105'
author:
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Haya
full_name: Halimeh, Haya
id: '87673'
last_name: Halimeh
- first_name: Philipp
full_name: Hansmeier, Philipp
id: '55603'
last_name: Hansmeier
- first_name: Christian
full_name: Vorbohle, Christian
id: '29951'
last_name: Vorbohle
- first_name: Maike
full_name: Althaus, Maike
id: '61896'
last_name: Althaus
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Dennis
full_name: Kundisch, Dennis
id: '21117'
last_name: Kundisch
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: zur Heiden P, Halimeh H, Hansmeier P, et al. Data Spaces for Heterogeneous
Data Ecosystems – Findings from a Design Study in the Cultural Sector. Communications
of the Association for Information Systems.
apa: zur Heiden, P., Halimeh, H., Hansmeier, P., Vorbohle, C., Althaus, M., Beverungen,
D., Kundisch, D., & Müller, O. (n.d.). Data Spaces for Heterogeneous Data
Ecosystems – Findings from a Design Study in the Cultural Sector. Communications
of the Association for Information Systems.
bibtex: '@article{zur Heiden_Halimeh_Hansmeier_Vorbohle_Althaus_Beverungen_Kundisch_Müller,
title={Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design
Study in the Cultural Sector}, journal={Communications of the Association for
Information Systems}, author={zur Heiden, Philipp and Halimeh, Haya and Hansmeier,
Philipp and Vorbohle, Christian and Althaus, Maike and Beverungen, Daniel and
Kundisch, Dennis and Müller, Oliver} }'
chicago: Heiden, Philipp zur, Haya Halimeh, Philipp Hansmeier, Christian Vorbohle,
Maike Althaus, Daniel Beverungen, Dennis Kundisch, and Oliver Müller. “Data Spaces
for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural
Sector.” Communications of the Association for Information Systems, n.d.
ieee: P. zur Heiden et al., “Data Spaces for Heterogeneous Data Ecosystems
– Findings from a Design Study in the Cultural Sector,” Communications of the
Association for Information Systems.
mla: zur Heiden, Philipp, et al. “Data Spaces for Heterogeneous Data Ecosystems
– Findings from a Design Study in the Cultural Sector.” Communications of the
Association for Information Systems.
short: P. zur Heiden, H. Halimeh, P. Hansmeier, C. Vorbohle, M. Althaus, D. Beverungen,
D. Kundisch, O. Müller, Communications of the Association for Information Systems
(n.d.).
date_created: 2026-03-24T13:31:24Z
date_updated: 2026-03-27T08:24:49Z
department:
- _id: '276'
- _id: '526'
- _id: '196'
language:
- iso: eng
project:
- _id: '160'
name: 'DatenraumKultur: Use Case 1 - Kulturplattformen - Datenraum Kultur'
publication: Communications of the Association for Information Systems
publication_status: accepted
status: public
title: Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study
in the Cultural Sector
type: journal_article
user_id: '16205'
year: '2026'
...
---
_id: '64870'
author:
- first_name: Marcel
full_name: Meyer, Marcel
id: '105120'
last_name: Meyer
orcid: ' 0009-0005-9136-8525'
- first_name: David Ricardo
full_name: Zapata Gonzalez, David Ricardo
id: '105506'
last_name: Zapata Gonzalez
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: Meyer M, Zapata Gonzalez DR, Kaltenpoth SB, Müller O. Benchmarking Time Series
Foundation Models for Short-Term Household Electricity Load Forecasting. IEEE
Access. 2025;13:218141-218153. doi:10.1109/access.2025.3648056
apa: Meyer, M., Zapata Gonzalez, D. R., Kaltenpoth, S. B., & Müller, O. (2025).
Benchmarking Time Series Foundation Models for Short-Term Household Electricity
Load Forecasting. IEEE Access, 13, 218141–218153. https://doi.org/10.1109/access.2025.3648056
bibtex: '@article{Meyer_Zapata Gonzalez_Kaltenpoth_Müller_2025, title={Benchmarking
Time Series Foundation Models for Short-Term Household Electricity Load Forecasting},
volume={13}, DOI={10.1109/access.2025.3648056},
journal={IEEE Access}, publisher={Institute of Electrical and Electronics Engineers
(IEEE)}, author={Meyer, Marcel and Zapata Gonzalez, David Ricardo and Kaltenpoth,
Sascha Benjamin and Müller, Oliver}, year={2025}, pages={218141–218153} }'
chicago: 'Meyer, Marcel, David Ricardo Zapata Gonzalez, Sascha Benjamin Kaltenpoth,
and Oliver Müller. “Benchmarking Time Series Foundation Models for Short-Term
Household Electricity Load Forecasting.” IEEE Access 13 (2025): 218141–53.
https://doi.org/10.1109/access.2025.3648056.'
ieee: 'M. Meyer, D. R. Zapata Gonzalez, S. B. Kaltenpoth, and O. Müller, “Benchmarking
Time Series Foundation Models for Short-Term Household Electricity Load Forecasting,”
IEEE Access, vol. 13, pp. 218141–218153, 2025, doi: 10.1109/access.2025.3648056.'
mla: Meyer, Marcel, et al. “Benchmarking Time Series Foundation Models for Short-Term
Household Electricity Load Forecasting.” IEEE Access, vol. 13, Institute
of Electrical and Electronics Engineers (IEEE), 2025, pp. 218141–53, doi:10.1109/access.2025.3648056.
short: M. Meyer, D.R. Zapata Gonzalez, S.B. Kaltenpoth, O. Müller, IEEE Access 13
(2025) 218141–218153.
date_created: 2026-03-09T16:58:28Z
date_updated: 2026-03-10T08:13:21Z
doi: 10.1109/access.2025.3648056
intvolume: ' 13'
language:
- iso: eng
page: 218141-218153
publication: IEEE Access
publication_identifier:
issn:
- 2169-3536
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Benchmarking Time Series Foundation Models for Short-Term Household Electricity
Load Forecasting
type: journal_article
user_id: '105120'
volume: 13
year: '2025'
...
---
_id: '60680'
abstract:
- lang: eng
text: "Classical machine learning techniques often struggle with overfitting and
unreliable predictions when exposed to novel conditions. Introducing causality
into the modelling process offers a promising way to mitigate these challenges
by enhancing predictive robustness. However, constructing an initial causal graph
manually using domain knowledge is time-consuming, particularly in complex time
series with numerous variables. To address this, causal discovery algorithms can
provide a preliminary causal structure that domain experts can refine. This study
investigates causal feature selection with domain knowledge using a data center
system as an example. We use simulated time-series data to compare \r\ndifferent
causal feature selection with traditional machine-learning feature selection methods.
Our results show that predictions based on causal features are more robust compared
to those derived from traditional methods. These findings underscore the potential
of combining causal discovery algorithms with human expertise to improve machine
learning applications."
author:
- first_name: David Ricardo
full_name: Zapata Gonzalez, David Ricardo
id: '105506'
last_name: Zapata Gonzalez
- first_name: Marcel
full_name: Meyer, Marcel
id: '105120'
last_name: Meyer
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Zapata Gonzalez DR, Meyer M, Müller O. Bridging the gap between data-driven
and theory-driven modelling – leveraging causal machine learning for integrative
modelling of dynamical systems. In: ; 2025.'
apa: Zapata Gonzalez, D. R., Meyer, M., & Müller, O. (2025). Bridging the
gap between data-driven and theory-driven modelling – leveraging causal machine
learning for integrative modelling of dynamical systems. European Conference
on Information Systems, Amman, Jordan.
bibtex: '@inproceedings{Zapata Gonzalez_Meyer_Müller_2025, title={Bridging the gap
between data-driven and theory-driven modelling – leveraging causal machine learning
for integrative modelling of dynamical systems}, author={Zapata Gonzalez, David
Ricardo and Meyer, Marcel and Müller, Oliver}, year={2025} }'
chicago: Zapata Gonzalez, David Ricardo, Marcel Meyer, and Oliver Müller. “Bridging
the Gap between Data-Driven and Theory-Driven Modelling – Leveraging Causal Machine
Learning for Integrative Modelling of Dynamical Systems,” 2025.
ieee: D. R. Zapata Gonzalez, M. Meyer, and O. Müller, “Bridging the gap between
data-driven and theory-driven modelling – leveraging causal machine learning for
integrative modelling of dynamical systems,” presented at the European Conference
on Information Systems, Amman, Jordan, 2025.
mla: Zapata Gonzalez, David Ricardo, et al. Bridging the Gap between Data-Driven
and Theory-Driven Modelling – Leveraging Causal Machine Learning for Integrative
Modelling of Dynamical Systems. 2025.
short: 'D.R. Zapata Gonzalez, M. Meyer, O. Müller, in: 2025.'
conference:
end_date: 18.06.2025
location: Amman, Jordan
name: European Conference on Information Systems
start_date: 16.06.2025
date_created: 2025-07-21T07:52:03Z
date_updated: 2025-07-22T06:30:37Z
department:
- _id: '196'
keyword:
- Causal Machine Learning
- Causality in Time Series
- Causal Discovery
- Human-Machine Collaboration
language:
- iso: eng
main_file_link:
- url: https://aisel.aisnet.org/ecis2025/bus_analytics/bus_analytics/2/
status: public
title: Bridging the gap between data-driven and theory-driven modelling – leveraging
causal machine learning for integrative modelling of dynamical systems
type: conference
user_id: '72849'
year: '2025'
...
---
_id: '61098'
author:
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Alexander Marcus
full_name: Skolik, Alexander Marcus
id: '92908'
last_name: Skolik
orcid: 0009-0006-2519-1765
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
citation:
ama: 'Kaltenpoth SB, Skolik AM, Müller O, Beverungen D. A Step Towards Cognitive
Automation: Integrating LLM Agents with Process Rules. In: Lecture Notes in
Computer Science. Springer Nature Switzerland; 2025. doi:10.1007/978-3-032-02867-9_19'
apa: 'Kaltenpoth, S. B., Skolik, A. M., Müller, O., & Beverungen, D. (2025).
A Step Towards Cognitive Automation: Integrating LLM Agents with Process Rules.
Lecture Notes in Computer Science. 23rd International Conference on Business
Process Management, Sevilla. https://doi.org/10.1007/978-3-032-02867-9_19'
bibtex: '@inproceedings{Kaltenpoth_Skolik_Müller_Beverungen_2025, place={Cham},
title={A Step Towards Cognitive Automation: Integrating LLM Agents with Process
Rules}, DOI={10.1007/978-3-032-02867-9_19},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Kaltenpoth, Sascha Benjamin and Skolik, Alexander Marcus and Müller, Oliver
and Beverungen, Daniel}, year={2025} }'
chicago: 'Kaltenpoth, Sascha Benjamin, Alexander Marcus Skolik, Oliver Müller, and
Daniel Beverungen. “A Step Towards Cognitive Automation: Integrating LLM Agents
with Process Rules.” In Lecture Notes in Computer Science. Cham: Springer
Nature Switzerland, 2025. https://doi.org/10.1007/978-3-032-02867-9_19.'
ieee: 'S. B. Kaltenpoth, A. M. Skolik, O. Müller, and D. Beverungen, “A Step Towards
Cognitive Automation: Integrating LLM Agents with Process Rules,” presented at
the 23rd International Conference on Business Process Management, Sevilla, 2025,
doi: 10.1007/978-3-032-02867-9_19.'
mla: 'Kaltenpoth, Sascha Benjamin, et al. “A Step Towards Cognitive Automation:
Integrating LLM Agents with Process Rules.” Lecture Notes in Computer Science,
Springer Nature Switzerland, 2025, doi:10.1007/978-3-032-02867-9_19.'
short: 'S.B. Kaltenpoth, A.M. Skolik, O. Müller, D. Beverungen, in: Lecture Notes
in Computer Science, Springer Nature Switzerland, Cham, 2025.'
conference:
end_date: 2025-09-05
location: Sevilla
name: 23rd International Conference on Business Process Management
start_date: 2025-08-31
date_created: 2025-08-30T09:43:49Z
date_updated: 2025-08-30T09:50:22Z
doi: 10.1007/978-3-032-02867-9_19
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783032028662'
- '9783032028679'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: 'A Step Towards Cognitive Automation: Integrating LLM Agents with Process Rules'
type: conference
user_id: '92908'
year: '2025'
...
---
_id: '61160'
abstract:
- lang: eng
text: As a possible solution to the demographic change and the resulting
knowledge loss due to retirements in the Energy sector, this study aimed to develop
a generic pipeline to implement and evaluate proof-of-concepts (PoCs) for LLM-based
assistance systems in new domains. Our pipeline contains an LLM-based data generation
strategy based on documents, a retrieval-augmented generation (RAG) architecture
utilizing prompting techniques on existing German LLMs, and an LLM-based automatic
evaluation strategy. We leverage our pipeline to evaluate five LLMs using data
from a German DSO. We found that the Llama3 and the Mistral model are appropriately
aligned for the task. We plan to pilot the RAG architecture in the DSO's infrastructure
for future research and continuously research improvements using the generated
human demonstrations.
article_type: original
author:
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: Kaltenpoth SB, Müller O. Don’t Touch the Power Line - A Proof-of-Concept for
Aligned LLM-Based Assistance Systems to Support the Maintenance in the Electricity
Distribution System. ACM SIGEnergy Energy Informatics Review. 2025;4(4):16-22.
doi:10.1145/3717413.3717415
apa: Kaltenpoth, S. B., & Müller, O. (2025). Don’t Touch the Power Line - A
Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support the Maintenance
in the Electricity Distribution System. ACM SIGEnergy Energy Informatics Review,
4(4), 16–22. https://doi.org/10.1145/3717413.3717415
bibtex: '@article{Kaltenpoth_Müller_2025, title={Don’t Touch the Power Line - A
Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support the Maintenance
in the Electricity Distribution System}, volume={4}, DOI={10.1145/3717413.3717415},
number={4}, journal={ACM SIGEnergy Energy Informatics Review}, publisher={Association
for Computing Machinery (ACM)}, author={Kaltenpoth, Sascha Benjamin and Müller,
Oliver}, year={2025}, pages={16–22} }'
chicago: 'Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Don’t Touch the Power
Line - A Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support
the Maintenance in the Electricity Distribution System.” ACM SIGEnergy Energy
Informatics Review 4, no. 4 (2025): 16–22. https://doi.org/10.1145/3717413.3717415.'
ieee: 'S. B. Kaltenpoth and O. Müller, “Don’t Touch the Power Line - A Proof-of-Concept
for Aligned LLM-Based Assistance Systems to Support the Maintenance in the Electricity
Distribution System,” ACM SIGEnergy Energy Informatics Review, vol. 4,
no. 4, pp. 16–22, 2025, doi: 10.1145/3717413.3717415.'
mla: Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Don’t Touch the Power Line
- A Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support the Maintenance
in the Electricity Distribution System.” ACM SIGEnergy Energy Informatics Review,
vol. 4, no. 4, Association for Computing Machinery (ACM), 2025, pp. 16–22, doi:10.1145/3717413.3717415.
short: S.B. Kaltenpoth, O. Müller, ACM SIGEnergy Energy Informatics Review 4 (2025)
16–22.
date_created: 2025-09-09T12:30:30Z
date_updated: 2025-09-09T12:31:07Z
doi: 10.1145/3717413.3717415
intvolume: ' 4'
issue: '4'
language:
- iso: eng
page: 16-22
publication: ACM SIGEnergy Energy Informatics Review
publication_identifier:
issn:
- 2770-5331
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Don't Touch the Power Line - A Proof-of-Concept for Aligned LLM-Based Assistance
Systems to Support the Maintenance in the Electricity Distribution System
type: journal_article
user_id: '50640'
volume: 4
year: '2025'
...
---
_id: '63397'
abstract:
- lang: eng
text: Decarbonizing industrial process heat is a crucial step in mitigating climate
change. While Process Mining (PM) has gained traction in sustainability research—such
as optimizing production scheduling to reduce energy use or accounting for carbon
footprints—it has largely overlooked the challenges and opportunities related
to thermal energy, accounting for 66% of total energy demand in industrial processes.
At the same time, Heat Integration (HI) is an established engineering discipline
focused on maximizing the efficiency of thermal energy systems. However, HI traditionally
relies on static or incomplete data about energy demands, limiting its effectiveness
and accuracy. In this paper, we propose a novel framework that combines PM and
HI to enable data-driven, process- and product-centric modeling of industrial
energy demands. By integrating event logs and thermal energy data, our approach
allows for a fine-grained analysis of heat demand patterns corresponding to specific
process activities and product variants. We demonstrate the applicability and
advantages of the framework by simulating a pharmaceutical manufacturing process
and evaluating energy demands and heat recovery potentials. Our findings show
that our PM-enabled HI framework provides more accurate and actionable insights
into the temporal and product-specific variation of thermal energy demands. By
capturing the causal relationships between process activities, product characteristics,
and energy consumption, our approach enables improved analysis, planning, and
optimization for heat recovery and process decarbonization. This integration of
PM and HI expands the analytical tools for both disciplines and contributes to
advancing the sustainable transformation of industrial processes.
author:
- first_name: David Ricardo
full_name: Zapata Gonzalez, David Ricardo
id: '105506'
last_name: Zapata Gonzalez
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Kay
full_name: Benkert, Kay
last_name: Benkert
- first_name: Florian
full_name: Schlosser, Florian
id: '88614'
last_name: Schlosser
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Zapata Gonzalez DR, Brennig K, Benkert K, Schlosser F, Müller O. Process Mining
for Robust Heat Integration through Process- and Product-Centric Energy Demand
Modeling. In: ACM SIGEnergy Energy Informatics Review. Vol 5. Association
for Computing Machinery (ACM); 2025:19-31. doi:10.1145/3777518.3777520'
apa: Zapata Gonzalez, D. R., Brennig, K., Benkert, K., Schlosser, F., & Müller,
O. (2025). Process Mining for Robust Heat Integration through Process- and Product-Centric
Energy Demand Modeling. ACM SIGEnergy Energy Informatics Review, 5(3),
19–31. https://doi.org/10.1145/3777518.3777520
bibtex: '@inproceedings{Zapata Gonzalez_Brennig_Benkert_Schlosser_Müller_2025, title={Process
Mining for Robust Heat Integration through Process- and Product-Centric Energy
Demand Modeling}, volume={5}, DOI={10.1145/3777518.3777520},
number={3}, booktitle={ACM SIGEnergy Energy Informatics Review}, publisher={Association
for Computing Machinery (ACM)}, author={Zapata Gonzalez, David Ricardo and Brennig,
Katharina and Benkert, Kay and Schlosser, Florian and Müller, Oliver}, year={2025},
pages={19–31} }'
chicago: Zapata Gonzalez, David Ricardo, Katharina Brennig, Kay Benkert, Florian
Schlosser, and Oliver Müller. “Process Mining for Robust Heat Integration through
Process- and Product-Centric Energy Demand Modeling.” In ACM SIGEnergy Energy
Informatics Review, 5:19–31. Association for Computing Machinery (ACM), 2025.
https://doi.org/10.1145/3777518.3777520.
ieee: 'D. R. Zapata Gonzalez, K. Brennig, K. Benkert, F. Schlosser, and O. Müller,
“Process Mining for Robust Heat Integration through Process- and Product-Centric
Energy Demand Modeling,” in ACM SIGEnergy Energy Informatics Review, 2025,
vol. 5, no. 3, pp. 19–31, doi: 10.1145/3777518.3777520.'
mla: Zapata Gonzalez, David Ricardo, et al. “Process Mining for Robust Heat Integration
through Process- and Product-Centric Energy Demand Modeling.” ACM SIGEnergy
Energy Informatics Review, vol. 5, no. 3, Association for Computing Machinery
(ACM), 2025, pp. 19–31, doi:10.1145/3777518.3777520.
short: 'D.R. Zapata Gonzalez, K. Brennig, K. Benkert, F. Schlosser, O. Müller, in:
ACM SIGEnergy Energy Informatics Review, Association for Computing Machinery (ACM),
2025, pp. 19–31.'
date_created: 2025-12-22T13:13:37Z
date_updated: 2025-12-22T13:15:08Z
doi: 10.1145/3777518.3777520
intvolume: ' 5'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/doi/abs/10.1145/3777518.3777520
oa: '1'
page: 19-31
publication: ACM SIGEnergy Energy Informatics Review
publication_identifier:
issn:
- 2770-5331
- 2770-5331
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Process Mining for Robust Heat Integration through Process- and Product-Centric
Energy Demand Modeling
type: conference
user_id: '105506'
volume: 5
year: '2025'
...
---
_id: '63400'
abstract:
- lang: eng
text: Data centers (DCs) form the backbone of our growing digital economy, but their
rising energy demands pose challenges to our environment. At the same time, reusing
waste heat from DCs also represents an opportunity, for example, for more sustainable
heating of residential buildings. Modeling and optimizing these coupled and dynamic
systems of heat generation and reuse is complex. On the one hand, physical simulations
can be used to model these systems, but they are time-consuming to develop and
run. Machine learning (ML), on the other hand, allows efficient data-driven modeling,
but conventional correlation-based approaches struggle with the prediction of
interventions and out-of-distribution generalization. Recent advances in causal
ML, which combine principles from causal inference with flexible ML methods, are
a promising approach for more robust predictions. Due to their focus on modeling
interventions and cause-and-effect relationships, it is difficult to evaluate
causal ML approaches rigorously. To address this challenge, we built a testbed
of a miniature DC with an integrated waste heat network, equipped with sensors
and actuators. This testbed allows conducting controlled experiments and automatic
collection of realistic data, which can then be used to benchmark conventional
and causal ML methods. Our experimental results highlight the strengths and weaknesses
of each modeling approach, providing valuable insights on how to appropriately
apply different types of machine learning to optimize data center operations and
enhance their sustainability.
author:
- first_name: David Ricardo
full_name: Zapata Gonzalez, David Ricardo
id: '105506'
last_name: Zapata Gonzalez
- first_name: Marcel
full_name: Meyer, Marcel
id: '105120'
last_name: Meyer
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Zapata Gonzalez DR, Meyer M, Müller O. Causal Machine Learning Approaches
for Modelling Data Center Heat Recovery: A Physical Testbed Study. In: ACM
SIGEnergy Energy Informatics Review. Vol 5. Association for Computing Machinery
(ACM); 2025:4-10. doi:10.1145/3757892.3757893'
apa: 'Zapata Gonzalez, D. R., Meyer, M., & Müller, O. (2025). Causal Machine
Learning Approaches for Modelling Data Center Heat Recovery: A Physical Testbed
Study. ACM SIGEnergy Energy Informatics Review, 5(2), 4–10. https://doi.org/10.1145/3757892.3757893'
bibtex: '@inproceedings{Zapata Gonzalez_Meyer_Müller_2025, title={Causal Machine
Learning Approaches for Modelling Data Center Heat Recovery: A Physical Testbed
Study}, volume={5}, DOI={10.1145/3757892.3757893},
number={2}, booktitle={ACM SIGEnergy Energy Informatics Review}, publisher={Association
for Computing Machinery (ACM)}, author={Zapata Gonzalez, David Ricardo and Meyer,
Marcel and Müller, Oliver}, year={2025}, pages={4–10} }'
chicago: 'Zapata Gonzalez, David Ricardo, Marcel Meyer, and Oliver Müller. “Causal
Machine Learning Approaches for Modelling Data Center Heat Recovery: A Physical
Testbed Study.” In ACM SIGEnergy Energy Informatics Review, 5:4–10. Association
for Computing Machinery (ACM), 2025. https://doi.org/10.1145/3757892.3757893.'
ieee: 'D. R. Zapata Gonzalez, M. Meyer, and O. Müller, “Causal Machine Learning
Approaches for Modelling Data Center Heat Recovery: A Physical Testbed Study,”
in ACM SIGEnergy Energy Informatics Review, 2025, vol. 5, no. 2, pp. 4–10,
doi: 10.1145/3757892.3757893.'
mla: 'Zapata Gonzalez, David Ricardo, et al. “Causal Machine Learning Approaches
for Modelling Data Center Heat Recovery: A Physical Testbed Study.” ACM SIGEnergy
Energy Informatics Review, vol. 5, no. 2, Association for Computing Machinery
(ACM), 2025, pp. 4–10, doi:10.1145/3757892.3757893.'
short: 'D.R. Zapata Gonzalez, M. Meyer, O. Müller, in: ACM SIGEnergy Energy Informatics
Review, Association for Computing Machinery (ACM), 2025, pp. 4–10.'
date_created: 2025-12-22T13:19:06Z
date_updated: 2025-12-22T13:20:02Z
doi: 10.1145/3757892.3757893
intvolume: ' 5'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/doi/abs/10.1145/3757892.3757893
oa: '1'
page: 4-10
publication: ACM SIGEnergy Energy Informatics Review
publication_identifier:
issn:
- 2770-5331
- 2770-5331
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: 'Causal Machine Learning Approaches for Modelling Data Center Heat Recovery:
A Physical Testbed Study'
type: conference
user_id: '105506'
volume: 5
year: '2025'
...
---
_id: '63525'
abstract:
- lang: eng
text: "Recommender systems (RS) can support sustainable development by steering
users toward more sustainable choices. Sustainability-aware explanations represent
one avenue for contributing to this goal by foregrounding the environmental and
social aspects of the recommended products or services. This paper advances the
line of research on sustainability-aware explanations by integrating nudging mechanisms
into their design and by evaluating their effectiveness through a randomized between-subjects
online vignette experiment across two item domains (). Our findings offer actionable
design guidelines for building RS that foster sustainability-aware decision making
and enrich the empirical foundation for impact-oriented research on explanation
in RS.\r\n"
author:
- first_name: Haya
full_name: Halimeh, Haya
id: '87673'
last_name: Halimeh
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Halimeh H, Müller O. Towards Greener Choices: Decision Information Nudging
for Sustainability-Aware Recommender Explanations. In: ; 2025. doi:10.1007/978-3-032-13342-7'
apa: 'Halimeh, H., & Müller, O. (2025). Towards Greener Choices: Decision
Information Nudging for Sustainability-Aware Recommender Explanations. The
Second International Workshop on Recommender Systems for Sustainability and Social
Good, RecSoGood 2025, Prague, Czech Republic. https://doi.org/10.1007/978-3-032-13342-7'
bibtex: '@inproceedings{Halimeh_Müller_2025, title={Towards Greener Choices: Decision
Information Nudging for Sustainability-Aware Recommender Explanations}, DOI={10.1007/978-3-032-13342-7},
author={Halimeh, Haya and Müller, Oliver}, year={2025} }'
chicago: 'Halimeh, Haya, and Oliver Müller. “Towards Greener Choices: Decision Information
Nudging for Sustainability-Aware Recommender Explanations,” 2025. https://doi.org/10.1007/978-3-032-13342-7.'
ieee: 'H. Halimeh and O. Müller, “Towards Greener Choices: Decision Information
Nudging for Sustainability-Aware Recommender Explanations,” presented at the The
Second International Workshop on Recommender Systems for Sustainability and Social
Good, RecSoGood 2025, Prague, Czech Republic, 2025, doi: 10.1007/978-3-032-13342-7.'
mla: 'Halimeh, Haya, and Oliver Müller. Towards Greener Choices: Decision Information
Nudging for Sustainability-Aware Recommender Explanations. 2025, doi:10.1007/978-3-032-13342-7.'
short: 'H. Halimeh, O. Müller, in: 2025.'
conference:
location: Prague, Czech Republic
name: ' The Second International Workshop on Recommender Systems for Sustainability
and Social Good, RecSoGood 2025'
start_date: 2025-09-26
date_created: 2026-01-07T13:40:05Z
date_updated: 2026-01-07T13:46:50Z
department:
- _id: '195'
- _id: '196'
doi: 10.1007/978-3-032-13342-7
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/book/10.1007/978-3-032-13342-7
oa: '1'
status: public
title: 'Towards Greener Choices: Decision Information Nudging for Sustainability-Aware
Recommender Explanations'
type: conference
user_id: '87673'
year: '2025'
...
---
_id: '63026'
author:
- first_name: Maike
full_name: Althaus, Maike
id: '61896'
last_name: Althaus
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Beate
full_name: Flath, Beate
id: '58896'
last_name: Flath
orcid: https://orcid.org/0000-0002-1648-0796
- first_name: Haya
full_name: Halimeh, Haya
id: '87673'
last_name: Halimeh
- first_name: Philipp
full_name: Hansmeier, Philipp
id: '55603'
last_name: Hansmeier
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Dennis
full_name: Kundisch, Dennis
id: '21117'
last_name: Kundisch
- first_name: Michelle
full_name: Müller, Michelle
id: '50286'
last_name: Müller
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Simon
full_name: Oberthür, Simon
id: '383'
last_name: Oberthür
- first_name: Christian
full_name: Vorbohle, Christian
id: '29951'
last_name: Vorbohle
- first_name: Maryam
full_name: Momen Pour Tafreshi, Maryam
last_name: Momen Pour Tafreshi
- first_name: Sebastian
full_name: Mauß, Sebastian
last_name: Mauß
- first_name: Alina
full_name: Mücke, Alina
last_name: Mücke
- first_name: Jörg
full_name: Müller, Jörg
last_name: Müller
- first_name: Malte
full_name: Peter, Malte
last_name: Peter
- first_name: Ariane
full_name: Schmitt-Chandon, Ariane
last_name: Schmitt-Chandon
- first_name: Kerstin
full_name: Sellerberg, Kerstin
last_name: Sellerberg
- first_name: Moritz
full_name: Steinhäuser, Moritz
last_name: Steinhäuser
citation:
ama: 'Althaus M, Beverungen D, Flath B, et al. Positionspapier Use Case 1: Vernetzte
Kulturplattformen.; 2025.'
apa: 'Althaus, M., Beverungen, D., Flath, B., Halimeh, H., Hansmeier, P., zur Heiden,
P., Kundisch, D., Müller, M., Müller, O., Oberthür, S., Vorbohle, C., Momen Pour
Tafreshi, M., Mauß, S., Mücke, A., Müller, J., Peter, M., Schmitt-Chandon, A.,
Sellerberg, K., & Steinhäuser, M. (2025). Positionspapier Use Case 1: Vernetzte
Kulturplattformen.'
bibtex: '@book{Althaus_Beverungen_Flath_Halimeh_Hansmeier_zur Heiden_Kundisch_Müller_Müller_Oberthür_et
al._2025, place={Universität Paderborn, SICP}, title={Positionspapier Use Case
1: Vernetzte Kulturplattformen}, author={Althaus, Maike and Beverungen, Daniel
and Flath, Beate and Halimeh, Haya and Hansmeier, Philipp and zur Heiden, Philipp
and Kundisch, Dennis and Müller, Michelle and Müller, Oliver and Oberthür, Simon
and et al.}, year={2025} }'
chicago: 'Althaus, Maike, Daniel Beverungen, Beate Flath, Haya Halimeh, Philipp
Hansmeier, Philipp zur Heiden, Dennis Kundisch, et al. Positionspapier Use
Case 1: Vernetzte Kulturplattformen. Universität Paderborn, SICP, 2025.'
ieee: 'M. Althaus et al., Positionspapier Use Case 1: Vernetzte Kulturplattformen.
Universität Paderborn, SICP, 2025.'
mla: 'Althaus, Maike, et al. Positionspapier Use Case 1: Vernetzte Kulturplattformen.
2025.'
short: 'M. Althaus, D. Beverungen, B. Flath, H. Halimeh, P. Hansmeier, P. zur Heiden,
D. Kundisch, M. Müller, O. Müller, S. Oberthür, C. Vorbohle, M. Momen Pour Tafreshi,
S. Mauß, A. Mücke, J. Müller, M. Peter, A. Schmitt-Chandon, K. Sellerberg, M.
Steinhäuser, Positionspapier Use Case 1: Vernetzte Kulturplattformen, Universität
Paderborn, SICP, 2025.'
date_created: 2025-12-10T15:50:35Z
date_updated: 2026-01-07T13:41:32Z
department:
- _id: '276'
- _id: '526'
- _id: '196'
- _id: '735'
language:
- iso: ger
place: Universität Paderborn, SICP
project:
- _id: '160'
name: 'DatenraumKultur: Use Case 1 - Kulturplattformen - Datenraum Kultur'
publication_status: published
status: public
title: 'Positionspapier Use Case 1: Vernetzte Kulturplattformen'
type: working_paper
user_id: '87673'
year: '2025'
...
---
_id: '53130'
author:
- first_name: Miriam
full_name: Stumpe, Miriam
id: '64135'
last_name: Stumpe
- first_name: Peter
full_name: Dieter, Peter
id: '88592'
last_name: Dieter
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
citation:
ama: 'Stumpe M, Dieter P, Schryen G, Müller O, Beverungen D. Designing taxi ridesharing
systems with shared pick-up and drop-off locations: Insights from a computational
study. Transportation Research Part A: Policy and Practice. Published online
2024.'
apa: 'Stumpe, M., Dieter, P., Schryen, G., Müller, O., & Beverungen, D. (2024).
Designing taxi ridesharing systems with shared pick-up and drop-off locations:
Insights from a computational study. Transportation Research Part A: Policy
and Practice.'
bibtex: '@article{Stumpe_Dieter_Schryen_Müller_Beverungen_2024, title={Designing
taxi ridesharing systems with shared pick-up and drop-off locations: Insights
from a computational study}, journal={Transportation Research Part A: Policy and
Practice}, author={Stumpe, Miriam and Dieter, Peter and Schryen, Guido and Müller,
Oliver and Beverungen, Daniel}, year={2024} }'
chicago: 'Stumpe, Miriam, Peter Dieter, Guido Schryen, Oliver Müller, and Daniel
Beverungen. “Designing Taxi Ridesharing Systems with Shared Pick-up and Drop-off
Locations: Insights from a Computational Study.” Transportation Research Part
A: Policy and Practice, 2024.'
ieee: 'M. Stumpe, P. Dieter, G. Schryen, O. Müller, and D. Beverungen, “Designing
taxi ridesharing systems with shared pick-up and drop-off locations: Insights
from a computational study,” Transportation Research Part A: Policy and Practice,
2024.'
mla: 'Stumpe, Miriam, et al. “Designing Taxi Ridesharing Systems with Shared Pick-up
and Drop-off Locations: Insights from a Computational Study.” Transportation
Research Part A: Policy and Practice, 2024.'
short: 'M. Stumpe, P. Dieter, G. Schryen, O. Müller, D. Beverungen, Transportation
Research Part A: Policy and Practice (2024).'
date_created: 2024-04-02T12:10:56Z
date_updated: 2024-04-02T12:29:47Z
ddc:
- '000'
department:
- _id: '277'
- _id: '526'
- _id: '196'
file:
- access_level: open_access
content_type: application/pdf
creator: mateskam
date_created: 2024-04-02T12:10:18Z
date_updated: 2024-04-02T12:10:18Z
file_id: '53131'
file_name: Designing_TRS-systems_Final.pdf
file_size: 835032
relation: main_file
file_date_updated: 2024-04-02T12:10:18Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
publication: 'Transportation Research Part A: Policy and Practice'
status: public
title: 'Designing taxi ridesharing systems with shared pick-up and drop-off locations:
Insights from a computational study'
type: journal_article
user_id: '51811'
year: '2024'
...
---
_id: '55096'
author:
- first_name: Kevin
full_name: Bösch, Kevin
last_name: Bösch
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Markus
full_name: Weinmann, Markus
last_name: Weinmann
citation:
ama: 'Bösch K, Müller O, Weinmann M. Not your Average Digital Nudge: Heterogeneous
Effects of Personalized Nudges with CausalML. In: Proceedings of the Symposium
on Statistical Challenges in Electronic Commerce Research. ; 2024.'
apa: 'Bösch, K., Müller, O., & Weinmann, M. (2024). Not your Average Digital
Nudge: Heterogeneous Effects of Personalized Nudges with CausalML. Proceedings
of the Symposium on Statistical Challenges in Electronic Commerce Research.'
bibtex: '@inproceedings{Bösch_Müller_Weinmann_2024, title={Not your Average Digital
Nudge: Heterogeneous Effects of Personalized Nudges with CausalML}, booktitle={Proceedings
of the Symposium on Statistical Challenges in Electronic Commerce Research}, author={Bösch,
Kevin and Müller, Oliver and Weinmann, Markus}, year={2024} }'
chicago: 'Bösch, Kevin, Oliver Müller, and Markus Weinmann. “Not Your Average Digital
Nudge: Heterogeneous Effects of Personalized Nudges with CausalML.” In Proceedings
of the Symposium on Statistical Challenges in Electronic Commerce Research,
2024.'
ieee: 'K. Bösch, O. Müller, and M. Weinmann, “Not your Average Digital Nudge: Heterogeneous
Effects of Personalized Nudges with CausalML,” 2024.'
mla: 'Bösch, Kevin, et al. “Not Your Average Digital Nudge: Heterogeneous Effects
of Personalized Nudges with CausalML.” Proceedings of the Symposium on Statistical
Challenges in Electronic Commerce Research, 2024.'
short: 'K. Bösch, O. Müller, M. Weinmann, in: Proceedings of the Symposium on Statistical
Challenges in Electronic Commerce Research, 2024.'
date_created: 2024-07-05T15:17:43Z
date_updated: 2024-07-05T15:19:28Z
department:
- _id: '196'
language:
- iso: eng
publication: Proceedings of the Symposium on Statistical Challenges in Electronic
Commerce Research
status: public
title: 'Not your Average Digital Nudge: Heterogeneous Effects of Personalized Nudges
with CausalML'
type: conference_abstract
user_id: '72849'
year: '2024'
...
---
_id: '55500'
author:
- first_name: Ralf
full_name: Gitzel, Ralf
last_name: Gitzel
- first_name: Martin
full_name: Hoffmann, Martin
last_name: Hoffmann
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Alexander Marcus
full_name: Skolik, Alexander Marcus
id: '92908'
last_name: Skolik
orcid: 0009-0006-2519-1765
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Cansu
full_name: Kanak, Cansu
last_name: Kanak
- first_name: Kajan
full_name: Kandiah, Kajan
last_name: Kandiah
- first_name: Max-Ferdinand
full_name: Stroh, Max-Ferdinand
last_name: Stroh
- first_name: Wolfgang
full_name: Boos, Wolfgang
last_name: Boos
- first_name: Maurizio
full_name: Zajadatz, Maurizio
last_name: Zajadatz
- first_name: Michael
full_name: Suriyah, Michael
last_name: Suriyah
- first_name: Thomas
full_name: Leibfried, Thomas
last_name: Leibfried
- first_name: Dhruv Suresh
full_name: Singhal, Dhruv Suresh
last_name: Singhal
- first_name: Moritz
full_name: Bürger, Moritz
last_name: Bürger
- first_name: Dennis
full_name: Hunting, Dennis
last_name: Hunting
- first_name: Alexander
full_name: Rehmer, Alexander
last_name: Rehmer
- first_name: Aydin
full_name: Boyaci, Aydin
last_name: Boyaci
citation:
ama: Gitzel R, Hoffmann M, zur Heiden P, et al. Towards Cognitive Assistance and
Prognosis Systems in Power Distribution Grids – Open Issues, Suitable Technologies,
and Implementation Concepts. IEEE Access. Published online 2024:1-1. doi:10.1109/access.2024.3437195
apa: Gitzel, R., Hoffmann, M., zur Heiden, P., Skolik, A. M., Kaltenpoth, S. B.,
Müller, O., Kanak, C., Kandiah, K., Stroh, M.-F., Boos, W., Zajadatz, M., Suriyah,
M., Leibfried, T., Singhal, D. S., Bürger, M., Hunting, D., Rehmer, A., &
Boyaci, A. (2024). Towards Cognitive Assistance and Prognosis Systems in Power
Distribution Grids – Open Issues, Suitable Technologies, and Implementation Concepts.
IEEE Access, 1–1. https://doi.org/10.1109/access.2024.3437195
bibtex: '@article{Gitzel_Hoffmann_zur Heiden_Skolik_Kaltenpoth_Müller_Kanak_Kandiah_Stroh_Boos_et
al._2024, title={Towards Cognitive Assistance and Prognosis Systems in Power Distribution
Grids – Open Issues, Suitable Technologies, and Implementation Concepts}, DOI={10.1109/access.2024.3437195},
journal={IEEE Access}, publisher={Institute of Electrical and Electronics Engineers
(IEEE)}, author={Gitzel, Ralf and Hoffmann, Martin and zur Heiden, Philipp and
Skolik, Alexander Marcus and Kaltenpoth, Sascha Benjamin and Müller, Oliver and
Kanak, Cansu and Kandiah, Kajan and Stroh, Max-Ferdinand and Boos, Wolfgang and
et al.}, year={2024}, pages={1–1} }'
chicago: Gitzel, Ralf, Martin Hoffmann, Philipp zur Heiden, Alexander Marcus Skolik,
Sascha Benjamin Kaltenpoth, Oliver Müller, Cansu Kanak, et al. “Towards Cognitive
Assistance and Prognosis Systems in Power Distribution Grids – Open Issues, Suitable
Technologies, and Implementation Concepts.” IEEE Access, 2024, 1–1. https://doi.org/10.1109/access.2024.3437195.
ieee: 'R. Gitzel et al., “Towards Cognitive Assistance and Prognosis Systems
in Power Distribution Grids – Open Issues, Suitable Technologies, and Implementation
Concepts,” IEEE Access, pp. 1–1, 2024, doi: 10.1109/access.2024.3437195.'
mla: Gitzel, Ralf, et al. “Towards Cognitive Assistance and Prognosis Systems in
Power Distribution Grids – Open Issues, Suitable Technologies, and Implementation
Concepts.” IEEE Access, Institute of Electrical and Electronics Engineers
(IEEE), 2024, pp. 1–1, doi:10.1109/access.2024.3437195.
short: R. Gitzel, M. Hoffmann, P. zur Heiden, A.M. Skolik, S.B. Kaltenpoth, O. Müller,
C. Kanak, K. Kandiah, M.-F. Stroh, W. Boos, M. Zajadatz, M. Suriyah, T. Leibfried,
D.S. Singhal, M. Bürger, D. Hunting, A. Rehmer, A. Boyaci, IEEE Access (2024)
1–1.
date_created: 2024-08-05T05:54:36Z
date_updated: 2024-08-16T11:04:56Z
doi: 10.1109/access.2024.3437195
language:
- iso: eng
page: 1-1
project:
- _id: '650'
call_identifier: 7. Energieforschungsprogramm, Förderbereich "Digitalisierung der
Energiewende"
grant_number: 03E16090E
name: 'AProSys: AProSys -KI-gestützte Assistenz- und Prognosesysteme für den nachhaltigen
Einsatz in der intelligenten Verteilnetztechnik'
publication: IEEE Access
publication_identifier:
issn:
- 2169-3536
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Towards Cognitive Assistance and Prognosis Systems in Power Distribution Grids
– Open Issues, Suitable Technologies, and Implementation Concepts
type: journal_article
user_id: '64394'
year: '2024'
...
---
_id: '56945'
abstract:
- lang: eng
text: Adopting Large language models (LLMs) in organizations potentially revolutionizes
our lives and work. However, they can generate off-topic, discriminating, or harmful
content. This AI alignment problem often stems from misspecifications during the
LLM adoption, unnoticed by the principal due to the LLM’s black-box nature. While
various research disciplines investigated AI alignment, they neither address the
information asymmetries between organizational adopters and black-box LLM agents
nor consider organizational AI adoption processes. Therefore, we propose LLM ATLAS
(LLM Agency Theory-Led Alignment Strategy) a conceptual framework grounded in
agency (contract) theory, to mitigate alignment problems during organizational
LLM adoption. We conduct a conceptual literature analysis using the organizational
LLM adoption phases and the agency theory as concepts. Our approach results in
(1) providing an extended literature analysis process specific to AI alignment
methods during organizational LLM adoption and (2) providing a first LLM alignment
problem-solutionspace.
author:
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Kaltenpoth SB, Müller O. Getting in Contract with Large Language Models -
An Agency Theory Perspective On Large Language Model Alignment. In: Wirtschaftsinformatik
2024 Proceedings. ; 2024.'
apa: Kaltenpoth, S. B., & Müller, O. (2024). Getting in Contract with Large
Language Models - An Agency Theory Perspective On Large Language Model Alignment.
Wirtschaftsinformatik 2024 Proceedings.
bibtex: '@inproceedings{Kaltenpoth_Müller_2024, title={Getting in Contract with
Large Language Models - An Agency Theory Perspective On Large Language Model Alignment},
booktitle={Wirtschaftsinformatik 2024 Proceedings}, author={Kaltenpoth, Sascha
Benjamin and Müller, Oliver}, year={2024} }'
chicago: Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Getting in Contract with
Large Language Models - An Agency Theory Perspective On Large Language Model Alignment.”
In Wirtschaftsinformatik 2024 Proceedings, 2024.
ieee: S. B. Kaltenpoth and O. Müller, “Getting in Contract with Large Language Models
- An Agency Theory Perspective On Large Language Model Alignment,” 2024.
mla: Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Getting in Contract with Large
Language Models - An Agency Theory Perspective On Large Language Model Alignment.”
Wirtschaftsinformatik 2024 Proceedings, 2024.
short: 'S.B. Kaltenpoth, O. Müller, in: Wirtschaftsinformatik 2024 Proceedings,
2024.'
conference:
end_date: 19.09.2024
start_date: 16.09.2024
date_created: 2024-11-07T16:23:23Z
date_updated: 2024-11-11T16:45:34Z
department:
- _id: '196'
language:
- iso: eng
main_file_link:
- url: https://aisel.aisnet.org/wi2024/91/
publication: Wirtschaftsinformatik 2024 Proceedings
status: public
title: Getting in Contract with Large Language Models - An Agency Theory Perspective
On Large Language Model Alignment
type: conference
user_id: '50640'
year: '2024'
...
---
_id: '37312'
abstract:
- lang: eng
text: Optimal decision making requires appropriate evaluation of advice. Recent
literature reports that algorithm aversion reduces the effectiveness of predictive
algorithms. However, it remains unclear how people recover from bad advice given
by an otherwise good advisor. Previous work has focused on algorithm aversion
at a single time point. We extend this work by examining successive decisions
in a time series forecasting task using an online between-subjects experiment
(N = 87). Our empirical results do not confirm algorithm aversion immediately
after bad advice. The estimated effect suggests an increasing algorithm appreciation
over time. Our work extends the current knowledge on algorithm aversion with insights
into how weight on advice is adjusted over consecutive tasks. Since most forecasting
tasks are not one-off decisions, this also has implications for practitioners.
author:
- first_name: Dirk
full_name: Leffrang, Dirk
id: '51271'
last_name: Leffrang
orcid: 0000-0001-9004-2391
- first_name: Kevin
full_name: Bösch, Kevin
last_name: Bösch
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Leffrang D, Bösch K, Müller O. Do People Recover from Algorithm Aversion?
An Experimental Study of Algorithm Aversion over Time. In: Hawaii International
Conference on System Sciences. ; 2023.'
apa: Leffrang, D., Bösch, K., & Müller, O. (2023). Do People Recover from Algorithm
Aversion? An Experimental Study of Algorithm Aversion over Time. Hawaii International
Conference on System Sciences. Hawaii International Conference on System Sciences.
bibtex: '@inproceedings{Leffrang_Bösch_Müller_2023, title={Do People Recover from
Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time}, booktitle={Hawaii
International Conference on System Sciences}, author={Leffrang, Dirk and Bösch,
Kevin and Müller, Oliver}, year={2023} }'
chicago: Leffrang, Dirk, Kevin Bösch, and Oliver Müller. “Do People Recover from
Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time.” In
Hawaii International Conference on System Sciences, 2023.
ieee: D. Leffrang, K. Bösch, and O. Müller, “Do People Recover from Algorithm Aversion?
An Experimental Study of Algorithm Aversion over Time,” presented at the Hawaii
International Conference on System Sciences, 2023.
mla: Leffrang, Dirk, et al. “Do People Recover from Algorithm Aversion? An Experimental
Study of Algorithm Aversion over Time.” Hawaii International Conference on
System Sciences, 2023.
short: 'D. Leffrang, K. Bösch, O. Müller, in: Hawaii International Conference on
System Sciences, 2023.'
conference:
name: Hawaii International Conference on System Sciences
date_created: 2023-01-18T10:53:51Z
date_updated: 2024-01-10T09:52:59Z
department:
- _id: '196'
keyword:
- Algorithm aversion
- Time series
- Decision making
- Advice taking
- Forecasting
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://scholarspace.manoa.hawaii.edu/items/62b58ddc-895c-48c3-8194-522a1758a26f
oa: '1'
publication: Hawaii International Conference on System Sciences
status: public
title: Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm
Aversion over Time
type: conference
user_id: '51271'
year: '2023'
...
---
_id: '50431'
abstract:
- lang: eng
text: 'Recommender systems now span the entire customer journey. Amid the multitude
of diversified experi- ences, immersing in cultural events has become a key aspect
of tourism. Cultural events, however, suffer from fleeting lifecycles, evade exact
replication, and invariably lie in the future. In addition, their low standardization
makes harnessing historical data regarding event content or past patron evaluations
intricate. The distinctive traits of events thereby compound the challenge of
the cold-start dilemma in event recommenders. Content-based recommendations stand
as a viable avenue to alleviate this issue, functioning even in scenarios where
item-user information is scarce. Still, the effectiveness of content- based recommendations
often hinges on the quality of the data representation they build upon. In this
study, we explore an array of cutting-edge uni- and multimodal vision and language
foundation models (VL-FMs) for this purpose. Next, we derive content-based recommendations
through a straightforward clustering approach that groups akin events together,
and evaluate the efficacy of the models through a series of online user experiments
across three dimensions: similarity-based evaluation, comparison-based evaluation,
and clustering assignment evaluation. Our experiments generated four major findings.
First, we found that all VL-FMs consistently outperformed a naive baseline of
recommending randomly drawn events. Second, unimodal text-based embeddings were
surprisingly on par or in some cases even superior to multimodal embeddings. Third,
multimodal embeddings yielded arguably more fine-grained and diverse clusters
in comparison to their unimodal counterparts. Finally, we could confirm that cross
event interest is indeed reliant on the perceived similarity of events, resonating
with the notion of similarity in content-based recommendations. All in all, we
believe that leveraging the potential of contemporary FMs for content-based event
recommendations would help address the cold-start problem and propel this field
of research forward in new and exciting ways.'
author:
- first_name: Haya
full_name: Halimeh, Haya
id: '87673'
last_name: Halimeh
- first_name: Florian
full_name: Freese, Florian
last_name: Freese
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Halimeh H, Freese F, Müller O. Event Recommendations through the Lens of Vision
and Language Foundation Models. In: Workshop on Recommenders in Tourism, Co-Located
with the 17th ACM Conference on Recommender Systems. ; 2023.'
apa: Halimeh, H., Freese, F., & Müller, O. (2023). Event Recommendations through
the Lens of Vision and Language Foundation Models. Workshop on Recommenders
in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems.
Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference on
Recommender Systems.
bibtex: '@inproceedings{Halimeh_Freese_Müller_2023, title={Event Recommendations
through the Lens of Vision and Language Foundation Models}, booktitle={Workshop
on Recommenders in Tourism, co-located with the 17th ACM Conference on Recommender
Systems}, author={Halimeh, Haya and Freese, Florian and Müller, Oliver}, year={2023}
}'
chicago: Halimeh, Haya, Florian Freese, and Oliver Müller. “Event Recommendations
through the Lens of Vision and Language Foundation Models.” In Workshop on
Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender
Systems, 2023.
ieee: H. Halimeh, F. Freese, and O. Müller, “Event Recommendations through the Lens
of Vision and Language Foundation Models,” presented at the Workshop on Recommenders
in Tourism, co-located with the 17th ACM Conference on Recommender Systems, 2023.
mla: Halimeh, Haya, et al. “Event Recommendations through the Lens of Vision and
Language Foundation Models.” Workshop on Recommenders in Tourism, Co-Located
with the 17th ACM Conference on Recommender Systems, 2023.
short: 'H. Halimeh, F. Freese, O. Müller, in: Workshop on Recommenders in Tourism,
Co-Located with the 17th ACM Conference on Recommender Systems, 2023.'
conference:
end_date: 2023-09-22
name: Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference
on Recommender Systems
start_date: 2023-09-18
date_created: 2024-01-10T14:20:12Z
date_updated: 2024-01-10T16:10:04Z
department:
- _id: '195'
- _id: '196'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=zBlrdP4AAAAJ&citation_for_view=zBlrdP4AAAAJ:UeHWp8X0CEIC
oa: '1'
publication: Workshop on Recommenders in Tourism, co-located with the 17th ACM Conference
on Recommender Systems
status: public
title: Event Recommendations through the Lens of Vision and Language Foundation Models
type: conference
user_id: '87673'
year: '2023'
...
---
_id: '45270'
abstract:
- lang: eng
text: Clinical depression is a serious mental disorder that poses challenges for
both personal and public health. Millions of people struggle with depression each
year, but for many, the disorder goes undiagnosed or untreated. Over the last
decade, early depression detection on social media emerged as an interdisciplinary
research field. However, there is still a gap in detecting hesitant, depression-susceptible
individuals with minimal direct depressive signals at an early stage. We, therefore,
take up this open point and leverage posts from Reddit to fill the addressed gap.
Our results demonstrate the potential of contemporary Transformer architectures
in yielding promising predictive capabilities for mental health research. Furthermore,
we investigate the model’s interpretability using a surrogate and a topic modeling
approach. Based on our findings, we consider this work as a further step towards
developing a better understanding of mental eHealth and hope that our results
can support the development of future technologies.
author:
- first_name: Haya
full_name: Halimeh, Haya
id: '87673'
last_name: Halimeh
- first_name: Matthew
full_name: Caron, Matthew
id: '60721'
last_name: Caron
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Halimeh H, Caron M, Müller O. Early Depression Detection with Transformer
Models: Analyzing the Relationship between Linguistic and Psychology-Based Features.
In: Hawaii International Conference on System Sciences. ; 2023.'
apa: 'Halimeh, H., Caron, M., & Müller, O. (2023). Early Depression Detection
with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based
Features. Hawaii International Conference on System Sciences. Hawaii International
Conference on System Sciences.'
bibtex: '@inproceedings{Halimeh_Caron_Müller_2023, title={Early Depression Detection
with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based
Features}, booktitle={Hawaii International Conference on System Sciences}, author={Halimeh,
Haya and Caron, Matthew and Müller, Oliver}, year={2023} }'
chicago: 'Halimeh, Haya, Matthew Caron, and Oliver Müller. “Early Depression Detection
with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based
Features.” In Hawaii International Conference on System Sciences, 2023.'
ieee: 'H. Halimeh, M. Caron, and O. Müller, “Early Depression Detection with Transformer
Models: Analyzing the Relationship between Linguistic and Psychology-Based Features,”
presented at the Hawaii International Conference on System Sciences, 2023.'
mla: 'Halimeh, Haya, et al. “Early Depression Detection with Transformer Models:
Analyzing the Relationship between Linguistic and Psychology-Based Features.”
Hawaii International Conference on System Sciences, 2023.'
short: 'H. Halimeh, M. Caron, O. Müller, in: Hawaii International Conference on
System Sciences, 2023.'
conference:
end_date: 2023-01-06
name: Hawaii International Conference on System Sciences
start_date: 2023-01-03
date_created: 2023-05-25T10:25:21Z
date_updated: 2024-01-10T15:16:37Z
department:
- _id: '195'
- _id: '196'
keyword:
- Social Media and Healthcare Technology
- early depression detection
- liwc
- mental health
- transfer learning
- transformer architectures
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://scholarspace.manoa.hawaii.edu/items/2ddab486-5d2f-4302-8de3-a8b24017da3d
oa: '1'
publication: Hawaii International Conference on System Sciences
publication_status: published
related_material:
link:
- relation: confirmation
url: https://hdl.handle.net/10125/103046
status: public
title: 'Early Depression Detection with Transformer Models: Analyzing the Relationship
between Linguistic and Psychology-Based Features'
type: conference
user_id: '60721'
year: '2023'
...
---
_id: '37058'
abstract:
- lang: eng
text: "Digital technologies have made the line of visibility more transparent, enabling
customers to get deeper insights into an organization’s core operations than ever
before. This creates new challenges for organizations trying to consistently deliver
high-quality customer experiences. In this paper we conduct an empirical analysis
of customers’ preferences and their willingness-to-pay for different degrees of
process transparency, using the example of digitally-enabled business-to-customer
delivery services. Applying conjoint analysis, we quantify customers’ preferences
and willingness-to-pay for different service attributes and levels. Our contributions
are two-fold: For research, we provide empirical measurements of customers’ preferences
and their willingness-to-pay for process transparency, suggesting that more is
not always better. Additionally, we provide a blueprint of how conjoint analysis
can be applied to study design decisions regarding changing an organization’s
digital line of visibility. For practice, our findings enable service managers
to make decisions about process transparency and establishing different levels
of service quality.\r\n"
author:
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Brennig K, Müller O. More Isn’t Always Better – Measuring Customers’ Preferences
for Digital Process Transparency. In: Hawaii International Conference on System
Sciences. ; 2023.'
apa: Brennig, K., & Müller, O. (2023). More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency. Hawaii International
Conference on System Sciences. 56th Hawaii International Conference on System
Sciences, Lāhainā.
bibtex: '@inproceedings{Brennig_Müller_2023, title={More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency}, booktitle={Hawaii International
Conference on System Sciences}, author={Brennig, Katharina and Müller, Oliver},
year={2023} }'
chicago: Brennig, Katharina, and Oliver Müller. “More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency.” In Hawaii International
Conference on System Sciences, 2023.
ieee: 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.
mla: Brennig, Katharina, and Oliver Müller. “More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency.” Hawaii International
Conference on System Sciences, 2023.
short: 'K. Brennig, O. Müller, in: Hawaii International Conference on System Sciences,
2023.'
conference:
end_date: '20230106'
location: Lāhainā
name: ' 56th Hawaii International Conference on System Sciences'
start_date: '20230103'
date_created: 2023-01-17T11:34:56Z
date_updated: 2024-01-11T11:21:28Z
department:
- _id: '196'
has_accepted_license: '1'
keyword:
- Digital Services
- Line of Visibility
- Process Transparency
- Customer Preferences
- Conjoint Analysis
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
publication: Hawaii International Conference on System Sciences
publication_identifier:
unknown:
- 978-0-9981331-6-4
publication_status: published
status: public
title: More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process
Transparency
type: conference
user_id: '51905'
year: '2023'
...
---
_id: '50450'
author:
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Kay
full_name: Benkert, Kay
last_name: Benkert
- first_name: Bernd
full_name: Löhr, Bernd
id: '56760'
last_name: Löhr
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Brennig K, Benkert K, Löhr B, Müller O. Text-Aware Predictive Process Monitoring
of Knowledge-Intensive Processes: Does Control Flow Matter? In: Business Process
Management Workshops. ; 2023. doi:10.1007/978-3-031-50974-2_33'
apa: 'Brennig, K., Benkert, K., Löhr, B., & Müller, O. (2023). Text-Aware Predictive
Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?
In Business Process Management Workshops. https://doi.org/10.1007/978-3-031-50974-2_33'
bibtex: '@inbook{Brennig_Benkert_Löhr_Müller_2023, title={Text-Aware Predictive
Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?},
DOI={10.1007/978-3-031-50974-2_33},
booktitle={Business Process Management Workshops}, author={Brennig, Katharina
and Benkert, Kay and Löhr, Bernd and Müller, Oliver}, year={2023} }'
chicago: 'Brennig, Katharina, Kay Benkert, Bernd Löhr, and Oliver Müller. “Text-Aware
Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow
Matter?” In Business Process Management Workshops, 2023. https://doi.org/10.1007/978-3-031-50974-2_33.'
ieee: '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.'
mla: 'Brennig, Katharina, et al. “Text-Aware Predictive Process Monitoring of Knowledge-Intensive
Processes: Does Control Flow Matter?” Business Process Management Workshops,
2023, doi:10.1007/978-3-031-50974-2_33.'
short: 'K. Brennig, K. Benkert, B. Löhr, O. Müller, in: Business Process Management
Workshops, 2023.'
date_created: 2024-01-11T09:26:05Z
date_updated: 2024-01-11T11:22:35Z
department:
- _id: '196'
doi: 10.1007/978-3-031-50974-2_33
language:
- iso: eng
publication: Business Process Management Workshops
publication_identifier:
isbn:
- '9783031509735'
- '9783031509742'
issn:
- 1865-1348
- 1865-1356
publication_status: published
status: public
title: 'Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes:
Does Control Flow Matter?'
type: book_chapter
user_id: '51905'
year: '2023'
...
---
_id: '47107'
author:
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Christiane
full_name: Lehrer, Christiane
last_name: Lehrer
- first_name: Matthias
full_name: Trier, Matthias
id: '72744'
last_name: Trier
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
- first_name: Tobias
full_name: Bradt, Tobias
last_name: Bradt
- first_name: Bettina
full_name: Distel, Bettina
last_name: Distel
- first_name: Paul
full_name: Drews, Paul
last_name: Drews
- first_name: Jan Fabian
full_name: Ehmke, Jan Fabian
last_name: Ehmke
- first_name: Hans-Georg
full_name: Fill, Hans-Georg
last_name: Fill
- first_name: Christoph M.
full_name: Flath, Christoph M.
last_name: Flath
- first_name: Gilbert
full_name: Fridgen, Gilbert
last_name: Fridgen
- first_name: Thomas
full_name: Grisold, Thomas
last_name: Grisold
- first_name: Christian
full_name: Janiesch, Christian
last_name: Janiesch
- first_name: Andreas
full_name: Janson, Andreas
last_name: Janson
- first_name: Oliver
full_name: Krancher, Oliver
last_name: Krancher
- first_name: Julia
full_name: Krönung, Julia
last_name: Krönung
- first_name: Dennis
full_name: Kundisch, Dennis
id: '21117'
last_name: Kundisch
- first_name: Attila
full_name: Márton, Attila
last_name: Márton
- first_name: Milad
full_name: Mirbabaie, Milad
id: '88691'
last_name: Mirbabaie
- first_name: Stefan
full_name: Morana, Stefan
last_name: Morana
- first_name: Benjamin
full_name: Mueller, Benjamin
last_name: Mueller
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Anna Maria
full_name: Oberländer, Anna Maria
last_name: Oberländer
- first_name: Christoph
full_name: Peters, Christoph
last_name: Peters
- first_name: Christoph
full_name: Peukert, Christoph
last_name: Peukert
- first_name: Melanie
full_name: Reuter-Oppermann, Melanie
last_name: Reuter-Oppermann
- first_name: Dennis M.
full_name: Riehle, Dennis M.
last_name: Riehle
- first_name: Susanne
full_name: Robra-Bissantz, Susanne
last_name: Robra-Bissantz
- first_name: Maximilian
full_name: Röglinger, Maximilian
last_name: Röglinger
- first_name: Kristina
full_name: Rosenthal, Kristina
last_name: Rosenthal
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Reinhard
full_name: Schütte, Reinhard
last_name: Schütte
- first_name: Susanne
full_name: Strahringer, Susanne
last_name: Strahringer
- first_name: Nils
full_name: Urbach, Nils
last_name: Urbach
- first_name: Lauri
full_name: Wessel, Lauri
last_name: Wessel
- first_name: Liudmila
full_name: Zavolokina, Liudmila
last_name: Zavolokina
- first_name: Patrick
full_name: Zschech, Patrick
last_name: Zschech
citation:
ama: 'Beverungen D, zur Heiden P, Lehrer C, et al. Implementing Digital Responsibility
through Information Systems Research: A Delphi Study of Objectives, Activities,
and Challenges in IS Research. Department of Information Systems, Paderborn
University; 2023.'
apa: 'Beverungen, D., zur Heiden, P., Lehrer, C., Trier, M., Bartelheimer, C., Bradt,
T., Distel, B., Drews, P., Ehmke, J. F., Fill, H.-G., Flath, C. M., Fridgen, G.,
Grisold, T., Janiesch, C., Janson, A., Krancher, O., Krönung, J., Kundisch, D.,
Márton, A., … Zschech, P. (2023). Implementing Digital Responsibility through
Information Systems Research: A Delphi Study of Objectives, Activities, and Challenges
in IS Research. Department of Information Systems, Paderborn University.'
bibtex: '@book{Beverungen_zur Heiden_Lehrer_Trier_Bartelheimer_Bradt_Distel_Drews_Ehmke_Fill_et
al._2023, title={Implementing Digital Responsibility through Information Systems
Research: A Delphi Study of Objectives, Activities, and Challenges in IS Research},
publisher={Department of Information Systems, Paderborn University}, author={Beverungen,
Daniel and zur Heiden, Philipp and Lehrer, Christiane and Trier, Matthias and
Bartelheimer, Christian and Bradt, Tobias and Distel, Bettina and Drews, Paul
and Ehmke, Jan Fabian and Fill, Hans-Georg and et al.}, year={2023} }'
chicago: 'Beverungen, Daniel, Philipp zur Heiden, Christiane Lehrer, Matthias Trier,
Christian Bartelheimer, Tobias Bradt, Bettina Distel, et al. Implementing Digital
Responsibility through Information Systems Research: A Delphi Study of Objectives,
Activities, and Challenges in IS Research. Department of Information Systems,
Paderborn University, 2023.'
ieee: 'D. Beverungen et al., Implementing Digital Responsibility through
Information Systems Research: A Delphi Study of Objectives, Activities, and Challenges
in IS Research. Department of Information Systems, Paderborn University, 2023.'
mla: 'Beverungen, Daniel, et al. Implementing Digital Responsibility through
Information Systems Research: A Delphi Study of Objectives, Activities, and Challenges
in IS Research. Department of Information Systems, Paderborn University, 2023.'
short: 'D. Beverungen, P. zur Heiden, C. Lehrer, M. Trier, C. Bartelheimer, T. Bradt,
B. Distel, P. Drews, J.F. Ehmke, H.-G. Fill, C.M. Flath, G. Fridgen, T. Grisold,
C. Janiesch, A. Janson, O. Krancher, J. Krönung, D. Kundisch, A. Márton, M. Mirbabaie,
S. Morana, B. Mueller, O. Müller, A.M. Oberländer, C. Peters, C. Peukert, M. Reuter-Oppermann,
D.M. Riehle, S. Robra-Bissantz, M. Röglinger, K. Rosenthal, G. Schryen, R. Schütte,
S. Strahringer, N. Urbach, L. Wessel, L. Zavolokina, P. Zschech, Implementing
Digital Responsibility through Information Systems Research: A Delphi Study of
Objectives, Activities, and Challenges in IS Research, Department of Information
Systems, Paderborn University, 2023.'
date_created: 2023-09-18T06:56:45Z
date_updated: 2023-09-18T06:56:50Z
ddc:
- '000'
department:
- _id: '195'
file:
- access_level: closed
content_type: application/pdf
creator: pzh
date_created: 2023-09-18T06:56:19Z
date_updated: 2023-09-18T06:56:19Z
file_id: '47109'
file_name: Delphi_Study_on_Digital_Responsibility.pdf
file_size: 3741688
relation: main_file
success: 1
file_date_updated: 2023-09-18T06:56:19Z
has_accepted_license: '1'
language:
- iso: eng
page: '16'
publisher: Department of Information Systems, Paderborn University
status: public
title: 'Implementing Digital Responsibility through Information Systems Research:
A Delphi Study of Objectives, Activities, and Challenges in IS Research'
type: report
user_id: '64394'
year: '2023'
...
---
_id: '45112'
article_type: letter_note
author:
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Dennis
full_name: Kundisch, Dennis
id: '21117'
last_name: Kundisch
- first_name: Milad
full_name: Mirbabaie, Milad
id: '88691'
last_name: Mirbabaie
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Simon Thanh-Nam
full_name: Trang, Simon Thanh-Nam
id: '98948'
last_name: Trang
orcid: 0000-0002-4784-4038
- first_name: Matthias
full_name: Trier, Matthias
id: '72744'
last_name: Trier
citation:
ama: Beverungen D, Kundisch D, Mirbabaie M, et al. Digital Responsibility – a Multilevel
Framework for Responsible Digitalization. Business & Information Systems
Engineering. 2023;65(4):463-474. doi:10.1007/s12599-023-00822-x
apa: Beverungen, D., Kundisch, D., Mirbabaie, M., Müller, O., Schryen, G., Trang,
S. T.-N., & Trier, M. (2023). Digital Responsibility – a Multilevel Framework
for Responsible Digitalization. Business & Information Systems Engineering,
65(4), 463–474. https://doi.org/10.1007/s12599-023-00822-x
bibtex: '@article{Beverungen_Kundisch_Mirbabaie_Müller_Schryen_Trang_Trier_2023,
title={Digital Responsibility – a Multilevel Framework for Responsible Digitalization},
volume={65}, DOI={10.1007/s12599-023-00822-x},
number={4}, journal={Business & Information Systems Engineering}, author={Beverungen,
Daniel and Kundisch, Dennis and Mirbabaie, Milad and Müller, Oliver and Schryen,
Guido and Trang, Simon Thanh-Nam and Trier, Matthias}, year={2023}, pages={463–474}
}'
chicago: 'Beverungen, Daniel, Dennis Kundisch, Milad Mirbabaie, Oliver Müller, Guido
Schryen, Simon Thanh-Nam Trang, and Matthias Trier. “Digital Responsibility –
a Multilevel Framework for Responsible Digitalization.” Business & Information
Systems Engineering 65, no. 4 (2023): 463–74. https://doi.org/10.1007/s12599-023-00822-x.'
ieee: 'D. Beverungen et al., “Digital Responsibility – a Multilevel Framework
for Responsible Digitalization,” Business & Information Systems Engineering,
vol. 65, no. 4, pp. 463–474, 2023, doi: 10.1007/s12599-023-00822-x.'
mla: Beverungen, Daniel, et al. “Digital Responsibility – a Multilevel Framework
for Responsible Digitalization.” Business & Information Systems Engineering,
vol. 65, no. 4, 2023, pp. 463–74, doi:10.1007/s12599-023-00822-x.
short: D. Beverungen, D. Kundisch, M. Mirbabaie, O. Müller, G. Schryen, S.T.-N.
Trang, M. Trier, Business & Information Systems Engineering 65 (2023) 463–474.
date_created: 2023-05-19T07:21:29Z
date_updated: 2026-03-12T13:44:38Z
ddc:
- '000'
department:
- _id: '277'
- _id: '196'
- _id: '646'
- _id: '526'
- _id: '198'
- _id: '792'
- _id: '276'
- _id: '681'
doi: 10.1007/s12599-023-00822-x
file:
- access_level: closed
content_type: application/pdf
creator: schryen
date_created: 2023-07-06T13:02:00Z
date_updated: 2023-07-06T13:02:00Z
file_id: '45871'
file_name: Digital_Responsibility- A Multilevel Framework for Responsible Digitilization-
BISE Springer VERSION.pdf
file_size: 373767
relation: main_file
success: 1
file_date_updated: 2023-07-06T13:02:00Z
has_accepted_license: '1'
intvolume: ' 65'
issue: '4'
language:
- iso: eng
page: 463 - 474
publication: Business & Information Systems Engineering
publication_status: published
status: public
title: Digital Responsibility – a Multilevel Framework for Responsible Digitalization
type: journal_article
user_id: '16205'
volume: 65
year: '2023'
...