@unpublished{63783,
  author       = {{Thommes, Kirsten and Mehic, Miro}},
  publisher    = {{Elsevier BV}},
  title        = {{{Foreign Language Use, Attribution Error, and Newcomer Integration}}},
  year         = {{2025}},
}

@article{61377,
  author       = {{Schneider, Martin and Hemsen, Paul and Kundisch, Dennis}},
  journal      = {{management revue - Socio-Economic Studies, Special Issue “Digital Transformation of Work”.}},
  publisher    = {{Nomos Verlag}},
  title        = {{{Who are the Actively Participating Crowdworkers? A Qualitative Comparative Analysis of a German Text Creation PlatformSocio-Economic Studies, }}},
  year         = {{2025}},
}

@inbook{61820,
  abstract     = {{<jats:title>Abstract</jats:title>
          <jats:p>A scoring list is a sequence of simple decision models, where features are incrementally evaluated and scores of satisfied features are summed to be used for threshold-based decisions or for calculating class probabilities. In this paper, we introduce a new multi-class variant and compare it against previously introduced binary classification variants for incremental decisions, as well as multi-class variants for classical decision-making using all features. Furthermore, we introduce a new multi-class dataset to assess collaborative human-machine decision-making, which is suitable for user studies with non-expert participants. We demonstrate the usefulness of our approach by evaluating predictive performance and compared to the performance of participants without AI help.</jats:p>}},
  author       = {{Heid, Stefan and Kornowicz, Jaroslaw and Hanselle, Jonas and Thommes, Kirsten and Hüllermeier, Eyke}},
  booktitle    = {{Communications in Computer and Information Science}},
  isbn         = {{9783032083265}},
  issn         = {{1865-0929}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making}}},
  doi          = {{10.1007/978-3-032-08327-2_6}},
  year         = {{2025}},
}

@article{61819,
  author       = {{Papenkordt, Jörg and Ngonga Ngomo, Axel-Cyrille and Thommes, Kirsten}},
  issn         = {{0144-929X}},
  journal      = {{Behaviour &amp; Information Technology}},
  pages        = {{1--22}},
  publisher    = {{Informa UK Limited}},
  title        = {{{Are numerical or verbal explanations of AI the key to appropriate user reliance and error detection?}}},
  doi          = {{10.1080/0144929x.2025.2568928}},
  year         = {{2025}},
}

@inbook{61877,
  abstract     = {{<jats:title>Abstract</jats:title>
          <jats:p>Research indicates that anger is a prevalent emotion in human-technology interactions, often leading to frustration, rejection and reduced trust, significantly impacting user experience and acceptance of technology. Particularly in high-risk or uncertain situations, where AI explanations are intended to help users make more informed decisions, decision-making is influenced by emotional factors, impairing understanding and leading to suboptimal choices. While XAI research continues to evolve, greater consideration of users’ emotions and individual characteristics remains necessary. Broadening empirical studies in this area could foster a more comprehensive understanding of decision-making processes following explanations, especially in relation to the interaction between emotions and cognition. In response, this study seeks to contribute to this area by employing an experimental design to examine the effects of AI explanations and emotion regulation on user reliance and trust of emotional users. The results provide a foundation for future human-centered research in XAI, focusing on the impact of emotions and cognition in human-technology interactions.</jats:p>}},
  author       = {{Lammert, Olesja}},
  booktitle    = {{Communications in Computer and Information Science}},
  isbn         = {{9783032083326}},
  issn         = {{1865-0929}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Can AI Regulate Your Emotions? An Empirical Investigation of the Influence of AI Explanations and Emotion Regulation on Human Decision-Making Factors}}},
  doi          = {{10.1007/978-3-032-08333-3_11}},
  year         = {{2025}},
}

@article{62213,
  author       = {{Kornowicz, Jaroslaw}},
  issn         = {{1044-7318}},
  journal      = {{International Journal of Human–Computer Interaction}},
  pages        = {{1--19}},
  publisher    = {{Informa UK Limited}},
  title        = {{{An Empirical Examination of the Evaluative AI Framework}}},
  doi          = {{10.1080/10447318.2025.2581260}},
  year         = {{2025}},
}

@article{58939,
  author       = {{Kornowicz, Jaroslaw and Thommes, Kirsten}},
  journal      = {{Plos One}},
  title        = {{{Algorithm, expert, or both? Evaluating the role of feature selection methods on user preferences and reliance}}},
  doi          = {{10.1371/journal.pone.0318874}},
  year         = {{2025}},
}

@article{60280,
  author       = {{Heinovski, Julian and Ergenç, Doǧanalp and Thommes, Kirsten and Dressler, Falko}},
  issn         = {{2687-7813}},
  journal      = {{IEEE Open Journal of Intelligent Transportation Systems}},
  pages        = {{1--1}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Incentive-Based Platoon Formation: Optimizing the Personal Benefit for Drivers}}},
  doi          = {{10.1109/ojits.2025.3580464}},
  year         = {{2025}},
}

@inbook{60292,
  abstract     = {{Im Rahmen meines SoTL-Projekts habe ich mich aufgrund meiner Vorerfahrungen mit dem experimentellen Forschungsansatz für die Untersuchung der Wirksamkeit von Lernzielen mittels eines Gruppenvergleichs entschieden. In dieser Reflexion stelle ich zunächst heraus, welche Hindernisse und welche Möglichkeiten die Durchführung einer experimentellen Studie im hochschuldidaktischen Kontext mit sich bringt. Anschließend zeige ich anhand konkreter Vorgehensweisen in meinem SoTL-Projekt sowie Bezügen zur experimentellen Wirtschaftsforschung auf, wie wesentliche Punkte für ein fundiertes experimentelles Forschungsdesign in der Hochschullehre umgesetzt werden können und wie Forschende verschiedener Fachrichtungen mit einem derart gestalteten SoTL-Projekt einen Mehrwert sowohl für sich als auch für die Lehrforschung generieren können.}},
  author       = {{Auer, Thorsten Fabian}},
  booktitle    = {{Scholarship of Teaching and Learning und disziplinäre Forschung: Eine komplexe Beziehung}},
  editor       = {{Bohndick, Carla and Kordts, Robert and Leschke, Jonas and Vöing, Nerea}},
  isbn         = {{978-3-658-47907-7}},
  pages        = {{65--69}},
  publisher    = {{Springer VS}},
  title        = {{{SoTL und Forschung in den Sozialwissenschaften: Der experimentelle Ansatz in SoTL}}},
  doi          = {{10.1007/978-3-658-47908-4_11}},
  year         = {{2025}},
}

@article{61137,
  abstract     = {{Prior research shows that social norms can reduce algorithm aversion, but little is known about how such norms become established. Most accounts emphasize technological and individual determinants, yet AI adoption unfolds within organizational social contexts shaped by peers and supervisors. We ask whether the source of the norm-peers or supervisors-shapes AI usage behavior. This question is practically relevant for organizations seeking to promote effective AI adoption. We conducted an online vignette experiment, complemented by qualitative data on participants' feelings and justifications after (counter-)normative behavior. In line with the theory, counter-normative choices elicited higher regret than norm-adherent choices. On average, choosing AI increased regret compared to choosing an human. This aversion was weaker when AI use was presented as the prevailing norm, indicating a statistically significant interaction between AI use and an AI-favoring norm. Participants also attributed less blame to technology than to humans, which increased regret when AI was chosen over human expertise. Both peer and supervisor influence emerged as relevant factors, though contrary to expectations they did not significantly affect regret. Our findings suggest that regret aversion, embedded in social norms, is a central mechanism driving imitation in AI-related decision-making.}},
  author       = {{Kornowicz, Jaroslaw and Pape, Maurice and Thommes, Kirsten}},
  journal      = {{Arxiv}},
  title        = {{{Would I regret being different? The influence of social norms on attitudes toward AI usage}}},
  doi          = {{10.48550/ARXIV.2509.04241}},
  year         = {{2025}},
}

@article{63908,
  author       = {{Mir Djawadi, Behnud and Plaß, Sabrina and Loer, Sabrina}},
  issn         = {{0014-2921}},
  journal      = {{European Economic Review}},
  publisher    = {{Elsevier BV}},
  title        = {{{“I don’t believe that you believe what I believe”: an experiment on misperceptions of social norms and whistleblowing}}},
  doi          = {{10.1016/j.euroecorev.2025.105189}},
  volume       = {{180}},
  year         = {{2025}},
}

@article{63911,
  author       = {{Mir Djawadi, Behnud and Plaß, Sabrina and Loer, Sabrina}},
  journal      = {{SSRN Electronic Journal}},
  publisher    = {{Elsevier BV}},
  title        = {{{Social Information Interventions under Competing Norms: Evidence from a Whistleblowing Experiment}}},
  doi          = {{http://dx.doi.org/10.2139/ssrn.5345248}},
  year         = {{2025}},
}

@article{63912,
  author       = {{Mir Djawadi, Behnud and Wester, Lisa}},
  journal      = {{SSRN Electronic Journal}},
  publisher    = {{Elsevier BV}},
  title        = {{{Social Interaction and Feedback-Giving Behavior in the Sharing Economy - An Experimental Analysis}}},
  doi          = {{https://dx.doi.org/10.2139/ssrn.5345248}},
  year         = {{2025}},
}

@article{52202,
  author       = {{Lammert, Olesja and Richter, Birte and Schütze, Christian and Thommes, Kirsten and Wrede, Britta}},
  journal      = {{Frontiers in Behavioral Economics}},
  title        = {{{Humans in XAI: Increased Reliance in Decision-Making Under Uncertainty by Using Explanation Strategies}}},
  doi          = {{10.3389/frbhe.2024.1377075}},
  year         = {{2024}},
}

@article{53611,
  author       = {{Hoffmann, Christin and Thommes, Kirsten}},
  issn         = {{0095-0696}},
  journal      = {{Journal of Environmental Economics and Management}},
  keywords     = {{Management, Monitoring, Policy and Law, Economics and Econometrics}},
  publisher    = {{Elsevier BV}},
  title        = {{{Can leaders motivate employees’ energy-efficient behavior with thoughtful communication?}}},
  doi          = {{10.1016/j.jeem.2024.102990}},
  year         = {{2024}},
}

@article{34114,
  abstract     = {{Qualitative comparative analysis (QCA) enables researchers in international management to better understand how the impact of a single explanatory factor depends on the context of other factors. But the analytical toolbox of QCA does not include a parameter for the explanatory power of a single explanatory factor or “condition”. In this paper, we therefore reinterpret the Banzhaf power index, originally developed in cooperative game theory, to establish a goodness-of-fit parameter in QCA. The relative Banzhaf index we suggest measures the explanatory power of one condition averaged across all sufficient combinations of conditions. The paper argues that the index is especially informative in three situations that are all salient in international management and call for a context-sensitive analysis of single conditions, namely substantial limited diversity in the data, the emergence of strong INUS conditions in the analysis, and theorizing with contingency factors. The paper derives the properties of the relative Banzhaf index in QCA, demonstrates how the index can be computed easily from a rudimentary truth table, and explores its insights by revisiting selected papers in international management that apply fuzzy-set QCA. It finally suggests a three-step procedure for utilizing the relative Banzhaf index when the causal structure involves both contingency effects and configurational causation.
}},
  author       = {{Haake, Claus-Jochen and Schneider, Martin}},
  journal      = {{Journal of International Management}},
  keywords     = {{Qualitative comparative analysis, Banzhaf power index, causality, explanatory power}},
  number       = {{2}},
  publisher    = {{Elsevier}},
  title        = {{{Playing games with QCA: Measuring the explanatory power of single conditions with the Banzhaf index}}},
  volume       = {{30}},
  year         = {{2024}},
}

@inbook{54624,
  author       = {{Papenkordt, Jörg}},
  booktitle    = {{Artificial Intelligence in HCI}},
  isbn         = {{9783031606052}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Navigating Transparency: The Influence of On-demand Explanations on Non-expert User Interaction with AI}}},
  doi          = {{10.1007/978-3-031-60606-9_14}},
  year         = {{2024}},
}

@article{54910,
  author       = {{Heid, Stefan and Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}},
  issn         = {{0888-613X}},
  journal      = {{International Journal of Approximate Reasoning}},
  publisher    = {{Elsevier BV}},
  title        = {{{Learning decision catalogues for situated decision making: The case of scoring systems}}},
  doi          = {{10.1016/j.ijar.2024.109190}},
  volume       = {{171}},
  year         = {{2024}},
}

@article{54908,
  author       = {{Heid, Stefan and Hanselle, Jonas and Fürnkranz, Johannes and Hüllermeier, Eyke}},
  issn         = {{0888-613X}},
  journal      = {{International Journal of Approximate Reasoning}},
  publisher    = {{Elsevier BV}},
  title        = {{{Learning decision catalogues for situated decision making: The case of scoring systems}}},
  doi          = {{10.1016/j.ijar.2024.109190}},
  volume       = {{171}},
  year         = {{2024}},
}

@book{54972,
  editor       = {{Thommes, Kirsten and Iseke, Anja and Schneider, Martin}},
  isbn         = {{9783662688373}},
  issn         = {{2523-3637}},
  publisher    = {{Springer Berlin Heidelberg}},
  title        = {{{Digitales und prädiktives Kompetenzmanagement}}},
  doi          = {{10.1007/978-3-662-68838-0}},
  year         = {{2024}},
}