---
_id: '63838'
abstract:
- lang: eng
text: "Industrial electrification is increasing to reduce fossil fuel dependence,
alongside a growing share of volatile renewables.\r\nA secure and reliable energy
supply is crucial for industry, leading to a shift from centralised to decentralised
grid structures.\r\nDC microgrids becoming increasingly popular in industry, since
they enable energy recuperation from braking, reduce components and cables, and
integrate storage and local generation to manage supply interruptions or peak
loads.\r\nEVs add further synergies by serving as mobile storage units, helping
to store and redistribute locally generated renewable energy.\r\nThis paper analyses
how EV integration in droop-controlled DC grids can contribute to a more stable,
low-emission and peak-reduced load profile to the supply grid through load shifting
and bridge interruptions.\r\nA droop-controlled DC grid model has been developed,
incorporating an EV charging park based on probability functions.\r\nScalable
scenarios allow for diverse condition analysis using an energy management system
that utilises fuzzy logic and sequential MILP optimisation.\r\nIt has been shown
that a 7% improvement of coefficient represented grid-serving behaviour is possible
by load shifting.\r\nIt has also been demonstrated that an optimised EMS can reduce
the demand-based CO2 emissions by 41kg for a representative day compared to a
fuzzy logic EMS.\r\nAt the same time peak load is decreased yielding a more constant
residual load.\r\nThese results highlight the potential of a controlled bidirectional
charging infrastructure in DC grids and underscore the need to explicitly consider
charging processes to ensure a residual load as constant as possible."
article_number: '100227'
article_type: original
author:
- first_name: Henning Christoph
full_name: Rahlf, Henning Christoph
id: '56955'
last_name: Rahlf
orcid: 0009-0006-8106-2132
- first_name: Lukas
full_name: Knorr, Lukas
id: '90391'
last_name: Knorr
orcid: 0009-0005-4727-7511
- first_name: Simon
full_name: Althoff, Simon
last_name: Althoff
- first_name: Henning
full_name: Meschede, Henning
id: '86954'
last_name: Meschede
orcid: 0000-0002-1538-089X
citation:
ama: Rahlf HC, Knorr L, Althoff S, Meschede H. Analysis of bidirectional EV charging
infrastructures within industrial DC grids. Smart Energy. Published online
2026. doi:10.1016/j.segy.2026.100227
apa: Rahlf, H. C., Knorr, L., Althoff, S., & Meschede, H. (2026). Analysis of
bidirectional EV charging infrastructures within industrial DC grids. Smart
Energy, Article 100227. https://doi.org/10.1016/j.segy.2026.100227
bibtex: '@article{Rahlf_Knorr_Althoff_Meschede_2026, title={Analysis of bidirectional
EV charging infrastructures within industrial DC grids}, DOI={10.1016/j.segy.2026.100227},
number={100227}, journal={Smart Energy}, publisher={Elsevier BV}, author={Rahlf,
Henning Christoph and Knorr, Lukas and Althoff, Simon and Meschede, Henning},
year={2026} }'
chicago: Rahlf, Henning Christoph, Lukas Knorr, Simon Althoff, and Henning Meschede.
“Analysis of Bidirectional EV Charging Infrastructures within Industrial DC Grids.”
Smart Energy, 2026. https://doi.org/10.1016/j.segy.2026.100227.
ieee: 'H. C. Rahlf, L. Knorr, S. Althoff, and H. Meschede, “Analysis of bidirectional
EV charging infrastructures within industrial DC grids,” Smart Energy,
Art. no. 100227, 2026, doi: 10.1016/j.segy.2026.100227.'
mla: Rahlf, Henning Christoph, et al. “Analysis of Bidirectional EV Charging Infrastructures
within Industrial DC Grids.” Smart Energy, 100227, Elsevier BV, 2026, doi:10.1016/j.segy.2026.100227.
short: H.C. Rahlf, L. Knorr, S. Althoff, H. Meschede, Smart Energy (2026).
date_created: 2026-02-02T14:45:17Z
date_updated: 2026-02-03T12:58:44Z
department:
- _id: '644'
doi: 10.1016/j.segy.2026.100227
keyword:
- DC-grid
- Droop control
- Grid-serving behaviour
- Grid stability
- Bidirectional charging
- Sequential decision
- MILP optimisation
language:
- iso: eng
publication: Smart Energy
publication_identifier:
issn:
- 2666-9552
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: Analysis of bidirectional EV charging infrastructures within industrial DC
grids
type: journal_article
user_id: '56955'
year: '2026'
...
---
_id: '64820'
abstract:
- lang: eng
text: Political goals, emerging EU sustainability regulations, and industrial digitalization
are driving the introduction of Digital Product Passports (DPPs) to enhance transparency,
traceability, and compliance across product life cycles. However, the appropriate
granularity of DPP integration across product architectures remains ambiguous.
This paper introduces a structured, decision-oriented framework that links product
structure, regulatory relevance, and information depth to define consistent DPP
levels, supporting both industry implementation and future standardization.
author:
- first_name: Katharina
full_name: Rohde, Katharina
id: '70143'
last_name: Rohde
orcid: 0009-0000-5738-7304
- first_name: Finn Lukas
full_name: Budde, Finn Lukas
id: '74585'
last_name: Budde
- first_name: Bárbara
full_name: Patrício, Bárbara
last_name: Patrício
- first_name: Tânia
full_name: Ferreira, Tânia
last_name: Ferreira
- first_name: Ana
full_name: Gonçalves, Ana
last_name: Gonçalves
- first_name: Manuel
full_name: Ott, Manuel
id: '44204'
last_name: Ott
- first_name: Iryna
full_name: Mozgova, Iryna
id: '95903'
last_name: Mozgova
citation:
ama: 'Rohde K, Budde FL, Patrício B, et al. Digital product passports and the challenge
of product structure granularity: A decision-making framework for the level of
DPP integration. In: Proceedings of the Design Society. Vol 6.'
apa: 'Rohde, K., Budde, F. L., Patrício, B., Ferreira, T., Gonçalves, A., Ott, M.,
& Mozgova, I. (n.d.). Digital product passports and the challenge of product
structure granularity: A decision-making framework for the level of DPP integration.
Proceedings of the Design Society, 6.'
bibtex: '@inproceedings{Rohde_Budde_Patrício_Ferreira_Gonçalves_Ott_Mozgova, title={Digital
product passports and the challenge of product structure granularity: A decision-making
framework for the level of DPP integration}, volume={6}, booktitle={Proceedings
of the Design Society}, author={Rohde, Katharina and Budde, Finn Lukas and Patrício,
Bárbara and Ferreira, Tânia and Gonçalves, Ana and Ott, Manuel and Mozgova, Iryna}
}'
chicago: 'Rohde, Katharina, Finn Lukas Budde, Bárbara Patrício, Tânia Ferreira,
Ana Gonçalves, Manuel Ott, and Iryna Mozgova. “Digital Product Passports and the
Challenge of Product Structure Granularity: A Decision-Making Framework for the
Level of DPP Integration.” In Proceedings of the Design Society, Vol. 6,
n.d.'
ieee: 'K. Rohde et al., “Digital product passports and the challenge of product
structure granularity: A decision-making framework for the level of DPP integration,”
in Proceedings of the Design Society, Cavtat, Dubrovnik, Croatia, vol.
6.'
mla: 'Rohde, Katharina, et al. “Digital Product Passports and the Challenge of Product
Structure Granularity: A Decision-Making Framework for the Level of DPP Integration.”
Proceedings of the Design Society, vol. 6.'
short: 'K. Rohde, F.L. Budde, B. Patrício, T. Ferreira, A. Gonçalves, M. Ott, I.
Mozgova, in: Proceedings of the Design Society, n.d.'
conference:
end_date: 2026-05-21
location: Cavtat, Dubrovnik, Croatia
name: 19th International Design Conference - DESIGN 2026
start_date: 2026-05-18
date_created: 2026-03-03T11:26:07Z
date_updated: 2026-03-03T11:26:11Z
department:
- _id: '741'
intvolume: ' 6'
keyword:
- digital product passport
- product architecture
- circular economy
- information granularity
- decision-making framework
language:
- iso: eng
publication: Proceedings of the Design Society
publication_status: accepted
quality_controlled: '1'
status: public
title: 'Digital product passports and the challenge of product structure granularity:
A decision-making framework for the level of DPP integration'
type: conference
user_id: '70143'
volume: 6
year: '2026'
...
---
_id: '58650'
abstract:
- lang: eng
text: 'Technical systems are characterized by increasing interdisciplinarity, complexity
and networking. A product and its corresponding production systems require interdisciplinary
multi-objective optimization. Sustainability and recyclability demands increase
said complexity. The efficiency of previously established engineering methods
is reaching its limits, which can only be overcome by systematic integration of
extreme data. The aim of "hybrid decision support" is as follows: Data science
and artificial intelligence should be used to supplement human capabilities in
conjunction with existing heuristics, methods, modeling and simulation to increase
the efficiency of product creation.'
alternative_title:
- Hybride Entscheidungsunterstützung in der Produktentstehung - Mit Data Science und
Künstlicher Intelligenz die Leistungsfähigkeit erhöhen
article_type: original
author:
- first_name: Iris
full_name: Gräßler, Iris
id: '47565'
last_name: Gräßler
orcid: 0000-0001-5765-971X
- first_name: Jens
full_name: Pottebaum, Jens
id: '405'
last_name: Pottebaum
orcid: http://orcid.org/0000-0001-8778-2989
- first_name: Peter
full_name: Nyhuis, Peter
last_name: Nyhuis
- first_name: Rainer
full_name: Stark, Rainer
last_name: Stark
- first_name: Klaus-Dieter
full_name: Thoben, Klaus-Dieter
last_name: Thoben
- first_name: Petra
full_name: Wiederkehr, Petra
last_name: Wiederkehr
citation:
ama: Gräßler I, Pottebaum J, Nyhuis P, Stark R, Thoben K-D, Wiederkehr P. Hybrid
Decision Support in Product Creation - Improving performance with data science
and artificial intelligence. Industry 40 Science. 2025;2025(1). doi:10.30844/i4sd.25.1.18
apa: Gräßler, I., Pottebaum, J., Nyhuis, P., Stark, R., Thoben, K.-D., & Wiederkehr,
P. (2025). Hybrid Decision Support in Product Creation - Improving performance
with data science and artificial intelligence. Industry 4.0 Science, 2025(1).
https://doi.org/10.30844/i4sd.25.1.18
bibtex: '@article{Gräßler_Pottebaum_Nyhuis_Stark_Thoben_Wiederkehr_2025, title={Hybrid
Decision Support in Product Creation - Improving performance with data science
and artificial intelligence}, volume={2025}, DOI={10.30844/i4sd.25.1.18},
number={1}, journal={Industry 4.0 Science}, publisher={GITO mbH Verlag}, author={Gräßler,
Iris and Pottebaum, Jens and Nyhuis, Peter and Stark, Rainer and Thoben, Klaus-Dieter
and Wiederkehr, Petra}, year={2025} }'
chicago: Gräßler, Iris, Jens Pottebaum, Peter Nyhuis, Rainer Stark, Klaus-Dieter
Thoben, and Petra Wiederkehr. “Hybrid Decision Support in Product Creation - Improving
Performance with Data Science and Artificial Intelligence.” Industry 4.0 Science
2025, no. 1 (2025). https://doi.org/10.30844/i4sd.25.1.18.
ieee: 'I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, and P. Wiederkehr,
“Hybrid Decision Support in Product Creation - Improving performance with data
science and artificial intelligence,” Industry 4.0 Science, vol. 2025,
no. 1, 2025, doi: 10.30844/i4sd.25.1.18.'
mla: Gräßler, Iris, et al. “Hybrid Decision Support in Product Creation - Improving
Performance with Data Science and Artificial Intelligence.” Industry 4.0 Science,
vol. 2025, no. 1, GITO mbH Verlag, 2025, doi:10.30844/i4sd.25.1.18.
short: I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, P. Wiederkehr,
Industry 4.0 Science 2025 (2025).
date_created: 2025-02-15T09:31:30Z
date_updated: 2025-02-15T09:40:52Z
department:
- _id: '152'
doi: 10.30844/i4sd.25.1.18
intvolume: ' 2025'
issue: '1'
keyword:
- AI
- artificial intelligence
- Data Science
- decision support
- extreme data
- Künstliche Intelligenz
- product creation
- product development
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
publication: Industry 4.0 Science
publication_identifier:
issn:
- 2942-6170
publication_status: published
publisher: GITO mbH Verlag
quality_controlled: '1'
status: public
title: Hybrid Decision Support in Product Creation - Improving performance with data
science and artificial intelligence
type: journal_article
user_id: '405'
volume: 2025
year: '2025'
...
---
_id: '62701'
abstract:
- lang: eng
text: 'Learning continuous vector representations for knowledge graphs has
significantly improved state-of-the-art performances in many challenging tasks.
Yet, deep-learning-based models are only post-hoc and locally explainable. In
contrast, learning Web Ontology Language (OWL) class expressions in Description Logics (DLs) is ante-hoc and globally
explainable. However, state-of-the-art learners have two well-known lim-itations: scaling to large knowledge graphs and handling missing infor-mation. Here, we present a decision-tree-based learner (tDL) to learn
Web Ontology Languages (OWLs) class expressions over large knowl-edge
graphs, while imputing missing triples. Given positive and negative example individuals,
tDL firstly constructs unique OWL expressions in .SHOIN from concise bounded descriptions of individuals. Each OWL
class expression is used as a feature in a binary classification problem to represent
input individuals. Thereafter, tDL fits a CART decision tree to learn Boolean
decision rules distinguishing positive examples from nega-tive examples. A final
OWL expression in.SHOIN is built by traversing the built CART decision tree from the root node to leaf nodes for each
positive example. By this, tDL can learn OWL class expressions without exploration,
i.e., the number of queries to a knowledge graph is bounded by the number of input
individuals. Our empirical results show that tDL outperforms the current state-of-the-art models across
datasets. Impor-tantly, our experiments over a large knowledge graph (DBpedia
with 1.1 billion triples) show that tDL can effectively learn accurate OWL class
expressions, while the state-of-the-art models fail to return any results.
Finally, expressions learned by tDL can be seamlessly translated into
natural language explanations using a pre-trained large language model and a DL
verbalizer.'
author:
- first_name: Caglar
full_name: Demir, Caglar
last_name: Demir
- first_name: Moshood
full_name: Yekini, Moshood
last_name: Yekini
- first_name: Michael
full_name: Röder, Michael
last_name: Röder
- first_name: Yasir
full_name: Mahmood, Yasir
last_name: Mahmood
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
last_name: Ngonga Ngomo
citation:
ama: 'Demir C, Yekini M, Röder M, Mahmood Y, Ngonga Ngomo A-C. Tree-Based OWL Class
Expression Learner over Large Graphs. In: Lecture Notes in Computer Science.
Springer Nature Switzerland; 2025. doi:10.1007/978-3-032-06066-2_29'
apa: Demir, C., Yekini, M., Röder, M., Mahmood, Y., & Ngonga Ngomo, A.-C. (2025).
Tree-Based OWL Class Expression Learner over Large Graphs. In Lecture Notes
in Computer Science. European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases - ECML PKDD, Porto, Portugal.
Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-06066-2_29
bibtex: '@inbook{Demir_Yekini_Röder_Mahmood_Ngonga Ngomo_2025, place={Cham}, title={Tree-Based
OWL Class Expression Learner over Large Graphs}, DOI={10.1007/978-3-032-06066-2_29},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Demir, Caglar and Yekini, Moshood and Röder, Michael and Mahmood, Yasir
and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
chicago: 'Demir, Caglar, Moshood Yekini, Michael Röder, Yasir Mahmood, and Axel-Cyrille
Ngonga Ngomo. “Tree-Based OWL Class Expression Learner over Large Graphs.” In
Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2025.
https://doi.org/10.1007/978-3-032-06066-2_29.'
ieee: 'C. Demir, M. Yekini, M. Röder, Y. Mahmood, and A.-C. Ngonga Ngomo, “Tree-Based
OWL Class Expression Learner over Large Graphs,” in Lecture Notes in Computer
Science, Cham: Springer Nature Switzerland, 2025.'
mla: Demir, Caglar, et al. “Tree-Based OWL Class Expression Learner over Large Graphs.”
Lecture Notes in Computer Science, Springer Nature Switzerland, 2025, doi:10.1007/978-3-032-06066-2_29.
short: 'C. Demir, M. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture
Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.'
conference:
end_date: 2025-09-19
location: Porto, Portugal
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases - ECML PKDD
start_date: 2025-09-15
date_created: 2025-11-28T14:09:17Z
date_updated: 2025-11-28T14:57:39Z
department:
- _id: '34'
- _id: '574'
doi: 10.1007/978-3-032-06066-2_29
keyword:
- Decision Tree
- OWL Class Expression Learning
- Description Logic
- Knowledge Graph
- Large Language Model
- Verbalizer
language:
- iso: eng
place: Cham
project:
- _id: '285'
name: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783032060655'
- '9783032060662'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Tree-Based OWL Class Expression Learner over Large Graphs
type: book_chapter
user_id: '114533'
year: '2025'
...
---
_id: '56282'
abstract:
- lang: eng
text: "Algorithmic bias has long been recognized as a key problem affecting decision-making
processes that integrate artificial intelligence (AI) technologies. The increased
use of AI in making military decisions relevant to the use of force has sustained
such questions about biases in these technologies and in how human users programme
with and rely on data based on hierarchized socio-cultural norms, knowledges,
and modes of attention.\r\n\r\nIn this post, Dr Ingvild Bode, Professor at the
Center for War Studies, University of Southern Denmark, and Ishmael Bhila, PhD
researcher at the “Meaningful Human Control: Between Regulation and Reflexion”
project, Paderborn University, unpack the problem of algorithmic bias with reference
to AI-based decision support systems (AI DSS). They examine three categories of
algorithmic bias – preexisting bias, technical bias, and emergent bias – across
four lifecycle stages of an AI DSS, concluding that stakeholders in the ongoing
discussion about AI in the military domain should consider the impact of algorithmic
bias on AI DSS more seriously."
author:
- first_name: Ishmael
full_name: Bhila, Ishmael
id: '105772'
last_name: Bhila
- first_name: Ingvild
full_name: Bode, Ingvild
last_name: Bode
citation:
ama: Bhila I, Bode I. The Problem of Algorithmic Bias in AI-Based Military Decision
Support Systems. ICRC Humanitarian Law & Policy Blog; 2024.
apa: Bhila, I., & Bode, I. (2024). The problem of algorithmic bias in AI-based
military decision support systems. ICRC Humanitarian Law & Policy Blog.
bibtex: '@book{Bhila_Bode_2024, title={The problem of algorithmic bias in AI-based
military decision support systems}, publisher={ICRC Humanitarian Law & Policy
Blog}, author={Bhila, Ishmael and Bode, Ingvild}, year={2024} }'
chicago: Bhila, Ishmael, and Ingvild Bode. The Problem of Algorithmic Bias in
AI-Based Military Decision Support Systems. ICRC Humanitarian Law & Policy
Blog, 2024.
ieee: I. Bhila and I. Bode, The problem of algorithmic bias in AI-based military
decision support systems. ICRC Humanitarian Law & Policy Blog, 2024.
mla: Bhila, Ishmael, and Ingvild Bode. The Problem of Algorithmic Bias in AI-Based
Military Decision Support Systems. ICRC Humanitarian Law & Policy Blog,
2024.
short: I. Bhila, I. Bode, The Problem of Algorithmic Bias in AI-Based Military Decision
Support Systems, ICRC Humanitarian Law & Policy Blog, 2024.
date_created: 2024-09-30T11:44:28Z
date_updated: 2024-11-26T09:49:48Z
has_accepted_license: '1'
keyword:
- Algorithmic Bias
- AI
- Decision Support Systems
- Autonomous Weapons Systems
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://blogs.icrc.org/law-and-policy/2024/09/03/the-problem-of-algorithmic-bias-in-ai-based-military-decision-support-systems/
oa: '1'
publication_status: published
publisher: ICRC Humanitarian Law & Policy Blog
related_material:
link:
- relation: confirmation
url: https://blogs.icrc.org/law-and-policy/2024/09/03/the-problem-of-algorithmic-bias-in-ai-based-military-decision-support-systems/
status: public
title: The problem of algorithmic bias in AI-based military decision support systems
type: misc
user_id: '105772'
year: '2024'
...
---
_id: '48086'
abstract:
- lang: eng
text: 'Individuals strive to make decisions that are consistent with not only their
consumer preferences but also their psychological needs. However, they are confronted
with complex, ambiguous or even false information. Ideologies and belief systems
provide guidance when processing and evaluating information and give a coherent
and comprehensible interpretation of reality. The first question is: why is an
individual attracted to a particular ideology? Individuals choose ideologies that
resonate with their subjective psychological needs and preferences. Second, how
do individuals search for ideologies and find out which suit them best? We model
an individual’s sequential information search for the best matching ideologies
by applying Bayesian learning and utility optimization. Additional information
enhances utility by reducing uncertainty. As a search is costly, the process may
stop once an individual adopts an ideology even if the information set remains
incomplete. Third, once they have chosen a particular ideology, individuals adhere
to its rules and norms when making everyday decisions. Consumers not only physically
consume, but they also act in accordance with their psychological needs.'
author:
- first_name: Carina
full_name: Burs, Carina
id: '44010'
last_name: Burs
- first_name: Thomas
full_name: Gries, Thomas
id: '186'
last_name: Gries
- first_name: Veronika
full_name: Müller, Veronika
last_name: Müller
citation:
ama: Burs C, Gries T, Müller V. The Choice of Ideology and Everyday Decisions. Journal
of Organizational Psychology. 2023;23(1). doi:10.33423/jop.v23i1.6033
apa: Burs, C., Gries, T., & Müller, V. (2023). The Choice of Ideology and Everyday
Decisions. Journal of Organizational Psychology, 23(1). https://doi.org/10.33423/jop.v23i1.6033
bibtex: '@article{Burs_Gries_Müller_2023, title={The Choice of Ideology and Everyday
Decisions}, volume={23}, DOI={10.33423/jop.v23i1.6033},
number={1}, journal={Journal of Organizational Psychology}, publisher={North American
Business Press}, author={Burs, Carina and Gries, Thomas and Müller, Veronika},
year={2023} }'
chicago: Burs, Carina, Thomas Gries, and Veronika Müller. “The Choice of Ideology
and Everyday Decisions.” Journal of Organizational Psychology 23, no. 1
(2023). https://doi.org/10.33423/jop.v23i1.6033.
ieee: 'C. Burs, T. Gries, and V. Müller, “The Choice of Ideology and Everyday Decisions,”
Journal of Organizational Psychology, vol. 23, no. 1, 2023, doi: 10.33423/jop.v23i1.6033.'
mla: Burs, Carina, et al. “The Choice of Ideology and Everyday Decisions.” Journal
of Organizational Psychology, vol. 23, no. 1, North American Business Press,
2023, doi:10.33423/jop.v23i1.6033.
short: C. Burs, T. Gries, V. Müller, Journal of Organizational Psychology 23 (2023).
date_created: 2023-10-16T10:29:31Z
date_updated: 2023-10-16T10:43:29Z
department:
- _id: '200'
- _id: '202'
doi: 10.33423/jop.v23i1.6033
intvolume: ' 23'
issue: '1'
keyword:
- Economics
- Ideology
- Decision-making
language:
- iso: eng
publication: Journal of Organizational Psychology
publication_identifier:
issn:
- 2158-3609
publication_status: published
publisher: North American Business Press
status: public
title: The Choice of Ideology and Everyday Decisions
type: journal_article
user_id: '44010'
volume: 23
year: '2023'
...
---
_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: '50118'
abstract:
- lang: eng
text: Despite the widespread use of machine learning algorithms, their effectiveness
is limited by a phenomenon known as algorithm aversion. Recent research concluded
that unobserved variables can cause algorithm aversion. However, the impact of
an unobserved variable on algorithm aversion remains unclear. Previous studies
focused on situations where humans had more variables available than algorithms.
We extend this research by conducting an online experiment with 94 participants,
systematically varying the number of observable variables to the advisor and the
advisor type. Surprisingly, our results did not confirm that an unobserved variable
had a negative effect on advice-taking. Instead, we found a positive impact in
an algorithm appreciation scenario. This study provides new insights into the
paradoxical behavior in which people weigh advice more despite having fewer variables,
as they correct for the advisor's errors. Practitioners should consider this behavior
when designing algorithms and account for user correction behavior.
author:
- first_name: Dirk
full_name: Leffrang, Dirk
id: '51271'
last_name: Leffrang
orcid: 0000-0001-9004-2391
citation:
ama: 'Leffrang D. The Broken Leg of Algorithm Appreciation: An Experimental Study
on the Effect of Unobserved Variables on Advice Utilization. In: Wirtschaftsinformatik
Conference. ; 2023.'
apa: 'Leffrang, D. (2023). The Broken Leg of Algorithm Appreciation: An Experimental
Study on the Effect of Unobserved Variables on Advice Utilization. Wirtschaftsinformatik
Conference, 19.'
bibtex: '@inproceedings{Leffrang_2023, title={The Broken Leg of Algorithm Appreciation:
An Experimental Study on the Effect of Unobserved Variables on Advice Utilization},
number={19}, booktitle={Wirtschaftsinformatik Conference}, author={Leffrang, Dirk},
year={2023} }'
chicago: 'Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental
Study on the Effect of Unobserved Variables on Advice Utilization.” In Wirtschaftsinformatik
Conference, 2023.'
ieee: 'D. Leffrang, “The Broken Leg of Algorithm Appreciation: An Experimental Study
on the Effect of Unobserved Variables on Advice Utilization,” in Wirtschaftsinformatik
Conference, Paderborn, 2023, no. 19.'
mla: 'Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental
Study on the Effect of Unobserved Variables on Advice Utilization.” Wirtschaftsinformatik
Conference, no. 19, 2023.'
short: 'D. Leffrang, in: Wirtschaftsinformatik Conference, 2023.'
conference:
location: Paderborn
name: Wirtschaftsinformatik
date_created: 2024-01-03T09:50:06Z
date_updated: 2024-01-10T09:53:24Z
department:
- _id: '196'
issue: '19'
keyword:
- Algorithm aversion
- Data
- Decision-making
- Advice-taking
- Human-Computer Interaction
language:
- iso: eng
main_file_link:
- url: 'https://aisel.aisnet.org/wi2023/19 '
publication: Wirtschaftsinformatik Conference
status: public
title: 'The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect
of Unobserved Variables on Advice Utilization'
type: conference
user_id: '51271'
year: '2023'
...
---
_id: '53216'
author:
- first_name: Madjid
full_name: Tavana, Madjid
id: '31858'
last_name: Tavana
- first_name: Mehdi
full_name: Soltanifar, Mehdi
last_name: Soltanifar
- first_name: Francisco J.
full_name: Santos-Arteaga, Francisco J.
last_name: Santos-Arteaga
citation:
ama: 'Tavana M, Soltanifar M, Santos-Arteaga FJ. Analytical hierarchy process: revolution
and evolution. Annals of Operations Research. 2023;326(2):879-907. doi:10.1007/s10479-021-04432-2'
apa: 'Tavana, M., Soltanifar, M., & Santos-Arteaga, F. J. (2023). Analytical
hierarchy process: revolution and evolution. Annals of Operations Research,
326(2), 879–907. https://doi.org/10.1007/s10479-021-04432-2'
bibtex: '@article{Tavana_Soltanifar_Santos-Arteaga_2023, title={Analytical hierarchy
process: revolution and evolution}, volume={326}, DOI={10.1007/s10479-021-04432-2},
number={2}, journal={Annals of Operations Research}, publisher={Springer Science
and Business Media LLC}, author={Tavana, Madjid and Soltanifar, Mehdi and Santos-Arteaga,
Francisco J.}, year={2023}, pages={879–907} }'
chicago: 'Tavana, Madjid, Mehdi Soltanifar, and Francisco J. Santos-Arteaga. “Analytical
Hierarchy Process: Revolution and Evolution.” Annals of Operations Research
326, no. 2 (2023): 879–907. https://doi.org/10.1007/s10479-021-04432-2.'
ieee: 'M. Tavana, M. Soltanifar, and F. J. Santos-Arteaga, “Analytical hierarchy
process: revolution and evolution,” Annals of Operations Research, vol.
326, no. 2, pp. 879–907, 2023, doi: 10.1007/s10479-021-04432-2.'
mla: 'Tavana, Madjid, et al. “Analytical Hierarchy Process: Revolution and Evolution.”
Annals of Operations Research, vol. 326, no. 2, Springer Science and Business
Media LLC, 2023, pp. 879–907, doi:10.1007/s10479-021-04432-2.'
short: M. Tavana, M. Soltanifar, F.J. Santos-Arteaga, Annals of Operations Research
326 (2023) 879–907.
date_created: 2024-04-04T13:38:44Z
date_updated: 2024-04-15T13:07:27Z
department:
- _id: '277'
doi: 10.1007/s10479-021-04432-2
intvolume: ' 326'
issue: '2'
keyword:
- Management Science and Operations Research
- General Decision Sciences
language:
- iso: eng
page: 879-907
publication: Annals of Operations Research
publication_identifier:
issn:
- 0254-5330
- 1572-9338
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: 'Analytical hierarchy process: revolution and evolution'
type: journal_article
user_id: '51811'
volume: 326
year: '2023'
...
---
_id: '53223'
author:
- first_name: Andreas
full_name: Dellnitz, Andreas
last_name: Dellnitz
- first_name: Madjid
full_name: Tavana, Madjid
id: '31858'
last_name: Tavana
- first_name: Rajiv
full_name: Banker, Rajiv
last_name: Banker
citation:
ama: Dellnitz A, Tavana M, Banker R. A novel median-based optimization model for
eco-efficiency assessment in data envelopment analysis. Annals of Operations
Research. 2023;322(2):661-690. doi:10.1007/s10479-022-04937-4
apa: Dellnitz, A., Tavana, M., & Banker, R. (2023). A novel median-based optimization
model for eco-efficiency assessment in data envelopment analysis. Annals of
Operations Research, 322(2), 661–690. https://doi.org/10.1007/s10479-022-04937-4
bibtex: '@article{Dellnitz_Tavana_Banker_2023, title={A novel median-based optimization
model for eco-efficiency assessment in data envelopment analysis}, volume={322},
DOI={10.1007/s10479-022-04937-4},
number={2}, journal={Annals of Operations Research}, publisher={Springer Science
and Business Media LLC}, author={Dellnitz, Andreas and Tavana, Madjid and Banker,
Rajiv}, year={2023}, pages={661–690} }'
chicago: 'Dellnitz, Andreas, Madjid Tavana, and Rajiv Banker. “A Novel Median-Based
Optimization Model for Eco-Efficiency Assessment in Data Envelopment Analysis.”
Annals of Operations Research 322, no. 2 (2023): 661–90. https://doi.org/10.1007/s10479-022-04937-4.'
ieee: 'A. Dellnitz, M. Tavana, and R. Banker, “A novel median-based optimization
model for eco-efficiency assessment in data envelopment analysis,” Annals of
Operations Research, vol. 322, no. 2, pp. 661–690, 2023, doi: 10.1007/s10479-022-04937-4.'
mla: Dellnitz, Andreas, et al. “A Novel Median-Based Optimization Model for Eco-Efficiency
Assessment in Data Envelopment Analysis.” Annals of Operations Research,
vol. 322, no. 2, Springer Science and Business Media LLC, 2023, pp. 661–90, doi:10.1007/s10479-022-04937-4.
short: A. Dellnitz, M. Tavana, R. Banker, Annals of Operations Research 322 (2023)
661–690.
date_created: 2024-04-04T13:52:01Z
date_updated: 2024-04-15T13:11:41Z
department:
- _id: '277'
doi: 10.1007/s10479-022-04937-4
intvolume: ' 322'
issue: '2'
keyword:
- Management Science and Operations Research
- General Decision Sciences
language:
- iso: eng
page: 661-690
publication: Annals of Operations Research
publication_identifier:
issn:
- 0254-5330
- 1572-9338
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: A novel median-based optimization model for eco-efficiency assessment in data
envelopment analysis
type: journal_article
user_id: '51811'
volume: 322
year: '2023'
...
---
_id: '56477'
abstract:
- lang: eng
text: We describe a prototype of a Clinical Decision Support System (CDSS) that
provides (counterfactual) explanations to support accurate medical diagnosis.
The prototype is based on an inherently interpretable Bayesian network (BN). Our
research aims to investigate which explanations are most useful for medical experts
and whether co-constructing explanations can foster trust and acceptance of CDSS.
author:
- first_name: Felix
full_name: Liedeker, Felix
id: '93275'
last_name: Liedeker
- first_name: Philipp
full_name: Cimiano, Philipp
last_name: Cimiano
citation:
ama: 'Liedeker F, Cimiano P. A Prototype of an Interactive Clinical Decision Support
System with Counterfactual Explanations. In: ; 2023.'
apa: Liedeker, F., & Cimiano, P. (2023). A Prototype of an Interactive Clinical
Decision Support System with Counterfactual Explanations. xAI-2023 Late-breaking
Work, Demos and Doctoral Consortium co-located with the 1st World Conference on
eXplainable Artificial Intelligence (xAI-2023), Lissabon.
bibtex: '@inproceedings{Liedeker_Cimiano_2023, title={A Prototype of an Interactive
Clinical Decision Support System with Counterfactual Explanations}, author={Liedeker,
Felix and Cimiano, Philipp}, year={2023} }'
chicago: Liedeker, Felix, and Philipp Cimiano. “A Prototype of an Interactive Clinical
Decision Support System with Counterfactual Explanations,” 2023.
ieee: F. Liedeker and P. Cimiano, “A Prototype of an Interactive Clinical Decision
Support System with Counterfactual Explanations,” presented at the xAI-2023 Late-breaking
Work, Demos and Doctoral Consortium co-located with the 1st World Conference on
eXplainable Artificial Intelligence (xAI-2023), Lissabon, 2023.
mla: Liedeker, Felix, and Philipp Cimiano. A Prototype of an Interactive Clinical
Decision Support System with Counterfactual Explanations. 2023.
short: 'F. Liedeker, P. Cimiano, in: 2023.'
conference:
end_date: 2023-07-28
location: Lissabon
name: xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with
the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023)
start_date: 2023-07-26
date_created: 2024-10-09T14:50:09Z
date_updated: 2024-10-09T15:04:53Z
department:
- _id: '660'
keyword:
- Explainable AI
- Clinical decision support
- Bayesian network
- Counterfactual explanations
language:
- iso: eng
project:
- _id: '128'
name: 'TRR 318 - C5: TRR 318 - Subproject C5'
status: public
title: A Prototype of an Interactive Clinical Decision Support System with Counterfactual
Explanations
type: conference
user_id: '93275'
year: '2023'
...
---
_id: '29539'
abstract:
- lang: eng
text: Explainable Artificial Intelligence (XAI) is currently an important topic
for the application of Machine Learning (ML) in high-stakes decision scenarios.
Related research focuses on evaluating ML algorithms in terms of interpretability.
However, providing a human understandable explanation of an intelligent system
does not only relate to the used ML algorithm. The data and features used also
have a considerable impact on interpretability. In this paper, we develop a taxonomy
for describing XAI systems based on aspects about the algorithm and data. The
proposed taxonomy gives researchers and practitioners opportunities to describe
and evaluate current XAI systems with respect to interpretability and guides the
future development of this class of systems.
author:
- first_name: Jan-Peter
full_name: Kucklick, Jan-Peter
id: '77066'
last_name: Kucklick
citation:
ama: 'Kucklick J-P. Towards a model- and data-focused taxonomy of XAI systems. In:
Wirtschaftsinformatik 2022 Proceedings. ; 2022.'
apa: Kucklick, J.-P. (2022). Towards a model- and data-focused taxonomy of XAI systems.
Wirtschaftsinformatik 2022 Proceedings. Wirtschaftsinformatik 2022 (WI22),
Nürnberg (online).
bibtex: '@inproceedings{Kucklick_2022, title={Towards a model- and data-focused
taxonomy of XAI systems}, booktitle={Wirtschaftsinformatik 2022 Proceedings},
author={Kucklick, Jan-Peter}, year={2022} }'
chicago: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI
Systems.” In Wirtschaftsinformatik 2022 Proceedings, 2022.
ieee: J.-P. Kucklick, “Towards a model- and data-focused taxonomy of XAI systems,”
presented at the Wirtschaftsinformatik 2022 (WI22), Nürnberg (online), 2022.
mla: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.”
Wirtschaftsinformatik 2022 Proceedings, 2022.
short: 'J.-P. Kucklick, in: Wirtschaftsinformatik 2022 Proceedings, 2022.'
conference:
end_date: 2022-02-23
location: Nürnberg (online)
name: Wirtschaftsinformatik 2022 (WI22)
start_date: 2022-02-21
date_created: 2022-01-26T08:22:03Z
date_updated: 2022-01-26T08:24:30Z
department:
- _id: '195'
- _id: '196'
keyword:
- Explainable Artificial Intelligence
- XAI
- Interpretability
- Decision Support Systems
- Taxonomy
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1056&context=wi2022
oa: '1'
publication: Wirtschaftsinformatik 2022 Proceedings
status: public
title: Towards a model- and data-focused taxonomy of XAI systems
type: conference
user_id: '77066'
year: '2022'
...
---
_id: '53241'
author:
- first_name: Kaveh
full_name: Khalili-Damghani, Kaveh
last_name: Khalili-Damghani
- first_name: Madjid
full_name: Tavana, Madjid
id: '31858'
last_name: Tavana
- first_name: Peiman
full_name: Ghasemi, Peiman
last_name: Ghasemi
citation:
ama: Khalili-Damghani K, Tavana M, Ghasemi P. A stochastic bi-objective simulation–optimization
model for cascade disaster location-allocation-distribution problems. Annals
of Operations Research. 2022;309(1):103-141. doi:10.1007/s10479-021-04191-0
apa: Khalili-Damghani, K., Tavana, M., & Ghasemi, P. (2022). A stochastic bi-objective
simulation–optimization model for cascade disaster location-allocation-distribution
problems. Annals of Operations Research, 309(1), 103–141. https://doi.org/10.1007/s10479-021-04191-0
bibtex: '@article{Khalili-Damghani_Tavana_Ghasemi_2022, title={A stochastic bi-objective
simulation–optimization model for cascade disaster location-allocation-distribution
problems}, volume={309}, DOI={10.1007/s10479-021-04191-0},
number={1}, journal={Annals of Operations Research}, publisher={Springer Science
and Business Media LLC}, author={Khalili-Damghani, Kaveh and Tavana, Madjid and
Ghasemi, Peiman}, year={2022}, pages={103–141} }'
chicago: 'Khalili-Damghani, Kaveh, Madjid Tavana, and Peiman Ghasemi. “A Stochastic
Bi-Objective Simulation–Optimization Model for Cascade Disaster Location-Allocation-Distribution
Problems.” Annals of Operations Research 309, no. 1 (2022): 103–41. https://doi.org/10.1007/s10479-021-04191-0.'
ieee: 'K. Khalili-Damghani, M. Tavana, and P. Ghasemi, “A stochastic bi-objective
simulation–optimization model for cascade disaster location-allocation-distribution
problems,” Annals of Operations Research, vol. 309, no. 1, pp. 103–141,
2022, doi: 10.1007/s10479-021-04191-0.'
mla: Khalili-Damghani, Kaveh, et al. “A Stochastic Bi-Objective Simulation–Optimization
Model for Cascade Disaster Location-Allocation-Distribution Problems.” Annals
of Operations Research, vol. 309, no. 1, Springer Science and Business Media
LLC, 2022, pp. 103–41, doi:10.1007/s10479-021-04191-0.
short: K. Khalili-Damghani, M. Tavana, P. Ghasemi, Annals of Operations Research
309 (2022) 103–141.
date_created: 2024-04-04T15:52:05Z
date_updated: 2024-04-15T13:17:18Z
department:
- _id: '277'
doi: 10.1007/s10479-021-04191-0
intvolume: ' 309'
issue: '1'
keyword:
- Management Science and Operations Research
- General Decision Sciences
language:
- iso: eng
page: 103-141
publication: Annals of Operations Research
publication_identifier:
issn:
- 0254-5330
- 1572-9338
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: A stochastic bi-objective simulation–optimization model for cascade disaster
location-allocation-distribution problems
type: journal_article
user_id: '51811'
volume: 309
year: '2022'
...
---
_id: '31691'
abstract:
- lang: eng
text: Sustainable product engineering is becoming increasingly important. This includes
the development of environmentally friendly products and the design for recycling.
In this paper a holistic method for the assessment of solution alternatives is
presented, in which the stakeholder perspectives along the generic product lifecycle
are taken into account. Finally, a new visualization is presented. By visualizing
the results in the integrated sustainability triangle, decision-makers in product
development can holistically assess the sustainability of the solution alternatives.
author:
- first_name: Iris
full_name: Gräßler, Iris
id: '47565'
last_name: Gräßler
orcid: 0000-0001-5765-971X
- first_name: Philipp
full_name: Hesse, Philipp
id: '60633'
last_name: Hesse
citation:
ama: Gräßler I, Hesse P. Approach to Sustainability-Based Assessment of Solution
Alternatives in Early Stages of Product Engineering. Proceedings of the Design
Society. 2022;2:1001-1010. doi:10.1017/pds.2022.102
apa: Gräßler, I., & Hesse, P. (2022). Approach to Sustainability-Based Assessment
of Solution Alternatives in Early Stages of Product Engineering. Proceedings
of the Design Society, 2, 1001–1010. https://doi.org/10.1017/pds.2022.102
bibtex: '@article{Gräßler_Hesse_2022, title={Approach to Sustainability-Based Assessment
of Solution Alternatives in Early Stages of Product Engineering}, volume={2},
DOI={10.1017/pds.2022.102},
journal={Proceedings of the Design Society}, publisher={Cambridge University Press
(CUP)}, author={Gräßler, Iris and Hesse, Philipp}, year={2022}, pages={1001–1010}
}'
chicago: 'Gräßler, Iris, and Philipp Hesse. “Approach to Sustainability-Based Assessment
of Solution Alternatives in Early Stages of Product Engineering.” Proceedings
of the Design Society 2 (2022): 1001–10. https://doi.org/10.1017/pds.2022.102.'
ieee: 'I. Gräßler and P. Hesse, “Approach to Sustainability-Based Assessment of
Solution Alternatives in Early Stages of Product Engineering,” Proceedings
of the Design Society, vol. 2, pp. 1001–1010, 2022, doi: 10.1017/pds.2022.102.'
mla: Gräßler, Iris, and Philipp Hesse. “Approach to Sustainability-Based Assessment
of Solution Alternatives in Early Stages of Product Engineering.” Proceedings
of the Design Society, vol. 2, Cambridge University Press (CUP), 2022, pp.
1001–10, doi:10.1017/pds.2022.102.
short: I. Gräßler, P. Hesse, Proceedings of the Design Society 2 (2022) 1001–1010.
conference:
end_date: 27.05.2022
name: International Design Conference (Design 2022)
start_date: 24.05.2022
date_created: 2022-06-07T05:58:07Z
date_updated: 2023-05-10T07:25:35Z
department:
- _id: '9'
- _id: '152'
- _id: '321'
doi: 10.1017/pds.2022.102
intvolume: ' 2'
keyword:
- sustainability
- decision making
- generic product lifecycle
- design analysis
- ecodesign
language:
- iso: eng
page: 1001-1010
publication: Proceedings of the Design Society
publication_identifier:
issn:
- 2732-527X
publication_status: published
publisher: Cambridge University Press (CUP)
quality_controlled: '1'
status: public
title: Approach to Sustainability-Based Assessment of Solution Alternatives in Early
Stages of Product Engineering
type: journal_article
user_id: '60633'
volume: 2
year: '2022'
...
---
_id: '16933'
abstract:
- lang: eng
text: The continuous innovation of its business models is an important task for
a company to stay competitive. During this process, the company has to validate
various hypotheses about its business models by adapting to uncertain and changing
customer needs effectively and efficiently. This adaptation, in turn, can be supported
by the concept of Software Product Lines (SPLs). SPLs reduce the time to market
by deriving products for customers with changing requirements using a common set
of features, structured as a feature model. Analogously, we support the process
of business model adaptation by applying the engineering process of SPLs to the
structure of the Business Model Canvas (BMC). We call this concept a Business
Model Decision Line (BMDL). The BMDL matches business domain knowledge in the
form of a feature model with customer needs to derive hypotheses about the business
model together with experiments for validation. Our approach is effective by providing
a comprehensive overview of possible business model adaptations and efficient
by reusing experiments for different hypotheses. We implement our approach in
a tool and illustrate the usefulness with an example of developing business models
for a mobile application.
author:
- first_name: Sebastian
full_name: Gottschalk, Sebastian
id: '47208'
last_name: Gottschalk
- first_name: Florian
full_name: Rittmeier, Florian
id: '5281'
last_name: Rittmeier
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Gottschalk S, Rittmeier F, Engels G. Hypothesis-driven Adaptation of Business
Models based on Product Line Engineering. In: Proceedings of the 22nd IEEE
International Conference on Business Informatics. IEEE; 2020. doi:10.1109/CBI49978.2020.00022'
apa: 'Gottschalk, S., Rittmeier, F., & Engels, G. (2020). Hypothesis-driven
Adaptation of Business Models based on Product Line Engineering. In Proceedings
of the 22nd IEEE International Conference on Business Informatics. Antwerp:
IEEE. https://doi.org/10.1109/CBI49978.2020.00022'
bibtex: '@inproceedings{Gottschalk_Rittmeier_Engels_2020, title={Hypothesis-driven
Adaptation of Business Models based on Product Line Engineering}, DOI={10.1109/CBI49978.2020.00022},
booktitle={Proceedings of the 22nd IEEE International Conference on Business Informatics},
publisher={IEEE}, author={Gottschalk, Sebastian and Rittmeier, Florian and Engels,
Gregor}, year={2020} }'
chicago: Gottschalk, Sebastian, Florian Rittmeier, and Gregor Engels. “Hypothesis-Driven
Adaptation of Business Models Based on Product Line Engineering.” In Proceedings
of the 22nd IEEE International Conference on Business Informatics. IEEE, 2020.
https://doi.org/10.1109/CBI49978.2020.00022.
ieee: S. Gottschalk, F. Rittmeier, and G. Engels, “Hypothesis-driven Adaptation
of Business Models based on Product Line Engineering,” in Proceedings of the
22nd IEEE International Conference on Business Informatics, Antwerp, 2020.
mla: Gottschalk, Sebastian, et al. “Hypothesis-Driven Adaptation of Business Models
Based on Product Line Engineering.” Proceedings of the 22nd IEEE International
Conference on Business Informatics, IEEE, 2020, doi:10.1109/CBI49978.2020.00022.
short: 'S. Gottschalk, F. Rittmeier, G. Engels, in: Proceedings of the 22nd IEEE
International Conference on Business Informatics, IEEE, 2020.'
conference:
end_date: 2020-06-24
location: Antwerp
name: 22nd IEEE International Conference on Business Informatics
start_date: 2020-06-22
date_created: 2020-05-04T12:16:54Z
date_updated: 2022-01-06T06:52:59Z
ddc:
- '006'
department:
- _id: '66'
doi: 10.1109/CBI49978.2020.00022
file:
- access_level: open_access
content_type: application/pdf
creator: sego
date_created: 2020-07-14T09:33:00Z
date_updated: 2020-07-14T09:33:00Z
file_id: '17383'
file_name: CBI.pdf
file_size: 569290
relation: main_file
file_date_updated: 2020-07-14T09:33:00Z
has_accepted_license: '1'
keyword:
- Business Model Decision Line
- Business Model Adaptation
- Hypothesis-driven Adaptation
- Software Product Line
- Feature Model
language:
- iso: eng
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '17'
name: SFB 901 - Subproject C5
publication: Proceedings of the 22nd IEEE International Conference on Business Informatics
publisher: IEEE
status: public
title: Hypothesis-driven Adaptation of Business Models based on Product Line Engineering
type: conference
user_id: '47208'
year: '2020'
...
---
_id: '48845'
abstract:
- lang: eng
text: In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems
(VRPs) often imply repeated decision making on dynamic customer requests. As in
classical VRPs, tours have to be planned short while the number of serviced customers
has to be maximized at the same time resulting in a multi-objective problem. Beyond
that, however, dynamic requests lead to the need for re-planning of not yet realized
tour parts, while already realized tour parts are irreversible. In this paper
we study this type of bi-objective dynamic VRP including sequential decision making
and concurrent realization of decisions. We adopt a recently proposed Dynamic
Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend
it to the more realistic (here considered) scenario of multiple vehicles. We empirically
show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant
variant of the proposed DEMOA as well as with the dynamic single-vehicle approach
proposed earlier.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Bossek J, Grimme C, Trautmann H. Dynamic Bi-Objective Routing of Multiple
Vehicles. In: Proceedings of the Genetic and Evolutionary Computation Conference.
GECCO ’20. Association for Computing Machinery; 2020:166–174. doi:10.1145/3377930.3390146'
apa: Bossek, J., Grimme, C., & Trautmann, H. (2020). Dynamic Bi-Objective Routing
of Multiple Vehicles. Proceedings of the Genetic and Evolutionary Computation
Conference, 166–174. https://doi.org/10.1145/3377930.3390146
bibtex: '@inproceedings{Bossek_Grimme_Trautmann_2020, place={New York, NY, USA},
series={GECCO ’20}, title={Dynamic Bi-Objective Routing of Multiple Vehicles},
DOI={10.1145/3377930.3390146},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Grimme,
Christian and Trautmann, Heike}, year={2020}, pages={166–174}, collection={GECCO
’20} }'
chicago: 'Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective
Routing of Multiple Vehicles.” In Proceedings of the Genetic and Evolutionary
Computation Conference, 166–174. GECCO ’20. New York, NY, USA: Association
for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390146.'
ieee: 'J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of
Multiple Vehicles,” in Proceedings of the Genetic and Evolutionary Computation
Conference, 2020, pp. 166–174, doi: 10.1145/3377930.3390146.'
mla: Bossek, Jakob, et al. “Dynamic Bi-Objective Routing of Multiple Vehicles.”
Proceedings of the Genetic and Evolutionary Computation Conference, Association
for Computing Machinery, 2020, pp. 166–174, doi:10.1145/3377930.3390146.
short: 'J. Bossek, C. Grimme, H. Trautmann, in: Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, New York, NY, USA,
2020, pp. 166–174.'
date_created: 2023-11-14T15:58:52Z
date_updated: 2023-12-13T10:43:24Z
department:
- _id: '819'
doi: 10.1145/3377930.3390146
extern: '1'
keyword:
- decision making
- dynamic optimization
- evolutionary algorithms
- multi-objective optimization
- vehicle routing
language:
- iso: eng
page: 166–174
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-7128-5
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’20
status: public
title: Dynamic Bi-Objective Routing of Multiple Vehicles
type: conference
user_id: '102979'
year: '2020'
...
---
_id: '15367'
abstract:
- lang: eng
text: 'n this paper, I review the empirical literature in the intersection of banks
and corporate income taxation that emerged over the last two decades. To structure
the included studies, I use a stakeholder approach and outline how corporate income
taxation plays into the relation of banks and their four main stakeholders: bank
regulators, customers, investors and tax authorities. My contribution to the literature
is threefold: First, I contribute by providing, to the best of my knowledge, a
first comprehensive review on this topic. Second, I point to areas for future
research. Third, I deduce policy implications from the studies under review. In
sum, the studies show that taxes distort banks’ pricing decisions, the relative
attractiveness of debt and equity financing, the decision to report on or off
the balance sheet and banks’ investment allocations. Empirical insights on how
tax rules affect banks’ decision-making are helpful for policymakers to tailor
suitable and sustainable tax legislation directed at banks. '
author:
- first_name: Vanessa
full_name: Gawehn, Vanessa
id: '52547'
last_name: Gawehn
citation:
ama: 'Gawehn V. Banks and Corporate Income Taxation: A Review. SSRN; 2019.'
apa: 'Gawehn, V. (2019). Banks and Corporate Income Taxation: A Review. SSRN.'
bibtex: '@book{Gawehn_2019, title={Banks and Corporate Income Taxation: A Review},
publisher={SSRN}, author={Gawehn, Vanessa}, year={2019} }'
chicago: 'Gawehn, Vanessa. Banks and Corporate Income Taxation: A Review.
SSRN, 2019.'
ieee: 'V. Gawehn, Banks and Corporate Income Taxation: A Review. SSRN, 2019.'
mla: 'Gawehn, Vanessa. Banks and Corporate Income Taxation: A Review. SSRN,
2019.'
short: 'V. Gawehn, Banks and Corporate Income Taxation: A Review, SSRN, 2019.'
date_created: 2019-12-18T06:56:24Z
date_updated: 2022-01-06T06:52:21Z
department:
- _id: '186'
- _id: '189'
keyword:
- corporate income taxes
- banks
- stakeholder approach
- decision-making process
language:
- iso: eng
page: '34'
publication_status: published
publisher: SSRN
status: public
title: 'Banks and Corporate Income Taxation: A Review'
type: working_paper
user_id: '48187'
year: '2019'
...
---
_id: '5675'
abstract:
- lang: eng
text: When responding to natural disasters, professional relief units are often
supported by many volunteers which are not affiliated to humanitarian organizations.
The effective coordination of these volunteers is crucial to leverage their capabilities
and to avoid conflicts with professional relief units. In this paper, we empirically
identify key requirements that professional relief units pose on this coordination.
Based on these requirements, we suggest a decision model. We computationally solve
a real-world instance of the model and empirically validate the computed solution
in interviews with practitioners. Our results show that the suggested model allows
for solving volunteer coordination tasks of realistic size near-optimally within
short time, with the determined solution being well accepted by practitioners.
We also describe in this article how the suggested decision support model is integrated
in the volunteer coordination system which we develop in joint cooperation with
a disaster management authority and a software development company.
author:
- first_name: Gerhard
full_name: Rauchecker, Gerhard
last_name: Rauchecker
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
citation:
ama: 'Rauchecker G, Schryen G. Decision Support for the Optimal Coordination of
Spontaneous Volunteers in Disaster Relief. In: Proceedings of the 15th International
Conference on Information Systems for Crisis Response and Management. ; 2018.'
apa: Rauchecker, G., & Schryen, G. (2018). Decision Support for the Optimal
Coordination of Spontaneous Volunteers in Disaster Relief. In Proceedings of
the 15th International Conference on Information Systems for Crisis Response and
Management. Rochester, NY, USA.
bibtex: '@inproceedings{Rauchecker_Schryen_2018, title={Decision Support for the
Optimal Coordination of Spontaneous Volunteers in Disaster Relief}, booktitle={Proceedings
of the 15th International Conference on Information Systems for Crisis Response
and Management}, author={Rauchecker, Gerhard and Schryen, Guido}, year={2018}
}'
chicago: Rauchecker, Gerhard, and Guido Schryen. “Decision Support for the Optimal
Coordination of Spontaneous Volunteers in Disaster Relief.” In Proceedings
of the 15th International Conference on Information Systems for Crisis Response
and Management, 2018.
ieee: G. Rauchecker and G. Schryen, “Decision Support for the Optimal Coordination
of Spontaneous Volunteers in Disaster Relief,” in Proceedings of the 15th International
Conference on Information Systems for Crisis Response and Management, Rochester,
NY, USA, 2018.
mla: Rauchecker, Gerhard, and Guido Schryen. “Decision Support for the Optimal Coordination
of Spontaneous Volunteers in Disaster Relief.” Proceedings of the 15th International
Conference on Information Systems for Crisis Response and Management, 2018.
short: 'G. Rauchecker, G. Schryen, in: Proceedings of the 15th International Conference
on Information Systems for Crisis Response and Management, 2018.'
conference:
location: Rochester, NY, USA
name: 15th International Conference on Information Systems for Crisis Response and
Management
date_created: 2018-11-14T15:35:54Z
date_updated: 2022-01-06T07:02:28Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2018-12-07T11:25:06Z
date_updated: 2018-12-13T15:05:44Z
file_id: '6020'
file_name: 2018_ISCRAM_Conference_Proceedings - Publication Version.pdf
file_size: 488472
relation: main_file
file_date_updated: 2018-12-13T15:05:44Z
has_accepted_license: '1'
keyword:
- Coordination of spontaneous volunteers
- volunteer coordination system
- decision support
- scheduling optimization model
- linear programming
language:
- iso: eng
oa: '1'
publication: Proceedings of the 15th International Conference on Information Systems
for Crisis Response and Management
status: public
title: Decision Support for the Optimal Coordination of Spontaneous Volunteers in
Disaster Relief
type: conference
user_id: '61579'
year: '2018'
...
---
_id: '5671'
abstract:
- lang: eng
text: Multi-attribute value theory (MAVT)-based recommender systems have been proposed
for dealing with issues of existing recommender systems, such as the cold-start
problem and changing preferences. However, as we argue in this paper, existing
MAVT-based methods for measuring attribute importance weights do not fit the shopping
tasks for which recommender systems are typically used. These methods assume well-trained
decision makers who are willing to invest time and cognitive effort, and who are
familiar with the attributes describing the available alternatives and the ranges
of these attribute levels. Yet, recommender systems are most often used by consumers
who are usually not familiar with the available attributes and ranges and who
wish to save time and effort. Against this background, we develop a new method,
based on a product configuration process, which is tailored to the characteristics
of these particular decision makers. We empirically compare our method to SWING,
ranking-based conjoint analysis and TRADEOFF in a between-subjects laboratory
experiment with 153 participants. Results indicate that our proposed method performs
better than TRADEOFF and CONJOINT and at least as well as SWING in terms of recommendation
accuracy, better than SWING and TRADEOFF and at least as well as CONJOINT in terms
of cognitive load, and that participants were faster with our method than with
any other method. We conclude that our method is a promising option to help support
consumers' decision processes in e-commerce shopping tasks.
author:
- first_name: Michael
full_name: Scholz, Michael
last_name: Scholz
- first_name: Verena
full_name: Dorner, Verena
last_name: Dorner
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Alexander
full_name: Benlian, Alexander
last_name: Benlian
citation:
ama: Scholz M, Dorner V, Schryen G, Benlian A. A configuration-based recommender
system for supporting e-commerce decisions. European Journal of Operational
Research. 2017;259(1):205-215.
apa: Scholz, M., Dorner, V., Schryen, G., & Benlian, A. (2017). A configuration-based
recommender system for supporting e-commerce decisions. European Journal of
Operational Research, 259(1), 205–215.
bibtex: '@article{Scholz_Dorner_Schryen_Benlian_2017, title={A configuration-based
recommender system for supporting e-commerce decisions}, volume={259}, number={1},
journal={European Journal of Operational Research}, publisher={Elsevier}, author={Scholz,
Michael and Dorner, Verena and Schryen, Guido and Benlian, Alexander}, year={2017},
pages={205–215} }'
chicago: 'Scholz, Michael, Verena Dorner, Guido Schryen, and Alexander Benlian.
“A Configuration-Based Recommender System for Supporting e-Commerce Decisions.”
European Journal of Operational Research 259, no. 1 (2017): 205–15.'
ieee: M. Scholz, V. Dorner, G. Schryen, and A. Benlian, “A configuration-based recommender
system for supporting e-commerce decisions,” European Journal of Operational
Research, vol. 259, no. 1, pp. 205–215, 2017.
mla: Scholz, Michael, et al. “A Configuration-Based Recommender System for Supporting
e-Commerce Decisions.” European Journal of Operational Research, vol. 259,
no. 1, Elsevier, 2017, pp. 205–15.
short: M. Scholz, V. Dorner, G. Schryen, A. Benlian, European Journal of Operational
Research 259 (2017) 205–215.
date_created: 2018-11-14T15:06:18Z
date_updated: 2022-01-06T07:02:27Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2018-12-07T11:30:59Z
date_updated: 2018-12-13T15:06:56Z
file_id: '6025'
file_name: EJOR article.pdf
file_size: 762889
relation: main_file
file_date_updated: 2018-12-13T15:06:56Z
has_accepted_license: '1'
intvolume: ' 259'
issue: '1'
keyword:
- E-Commerce
- Recommender System
- Attribute Weights
- Configuration System
- Decision Support
language:
- iso: eng
oa: '1'
page: 205 - 215
publication: European Journal of Operational Research
publisher: Elsevier
status: public
title: A configuration-based recommender system for supporting e-commerce decisions
type: journal_article
user_id: '61579'
volume: 259
year: '2017'
...
---
_id: '5678'
abstract:
- lang: eng
text: Many academic disciplines - including information systems, computer science,
and operations management - face scheduling problems as important decision making
tasks. Since many scheduling problems are NP-hard in the strong sense, there is
a need for developing solution heuristics. For scheduling problems with setup
times on unrelated parallel machines, there is limited research on solution methods
and to the best of our knowledge, parallel computer architectures have not yet
been taken advantage of. We address this gap by proposing and implementing a new
solution heuristic and by testing different parallelization strategies. In our
computational experiments, we show that our heuristic calculates near-optimal
solutions even for large instances and that computing time can be reduced substantially
by our parallelization approach.
author:
- first_name: Gerhard
full_name: Rauchecker, Gerhard
last_name: Rauchecker
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
citation:
ama: 'Rauchecker G, Schryen G. High-Performance Computing for Scheduling Decision
Support: A Parallel Depth-First Search Heuristic. In: Australasian Conference
on Information Systems. ; 2015:1-13.'
apa: 'Rauchecker, G., & Schryen, G. (2015). High-Performance Computing for Scheduling
Decision Support: A Parallel Depth-First Search Heuristic. In Australasian
Conference on Information Systems (pp. 1–13).'
bibtex: '@inproceedings{Rauchecker_Schryen_2015, title={High-Performance Computing
for Scheduling Decision Support: A Parallel Depth-First Search Heuristic}, booktitle={Australasian
Conference on Information Systems}, author={Rauchecker, Gerhard and Schryen, Guido},
year={2015}, pages={1–13} }'
chicago: 'Rauchecker, Gerhard, and Guido Schryen. “High-Performance Computing for
Scheduling Decision Support: A Parallel Depth-First Search Heuristic.” In Australasian
Conference on Information Systems, 1–13, 2015.'
ieee: 'G. Rauchecker and G. Schryen, “High-Performance Computing for Scheduling
Decision Support: A Parallel Depth-First Search Heuristic,” in Australasian
Conference on Information Systems, 2015, pp. 1–13.'
mla: 'Rauchecker, Gerhard, and Guido Schryen. “High-Performance Computing for Scheduling
Decision Support: A Parallel Depth-First Search Heuristic.” Australasian Conference
on Information Systems, 2015, pp. 1–13.'
short: 'G. Rauchecker, G. Schryen, in: Australasian Conference on Information Systems,
2015, pp. 1–13.'
date_created: 2018-11-14T15:39:50Z
date_updated: 2022-01-06T07:02:30Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2018-12-07T11:40:18Z
date_updated: 2018-12-13T15:08:28Z
file_id: '6031'
file_name: ACIS_2015_paper_7.pdf
file_size: 6771871
relation: main_file
file_date_updated: 2018-12-13T15:08:28Z
has_accepted_license: '1'
keyword:
- scheduling
- decision support
- heuristic
- high performance computing
- parallel algorithms
language:
- iso: eng
oa: '1'
page: 1-13
publication: Australasian Conference on Information Systems
status: public
title: 'High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First
Search Heuristic'
type: conference
user_id: '61579'
year: '2015'
...