@inproceedings{61106,
  author       = {{Liszt-Rohlf, Verena and Büker, Ronja and Kamsker, Susanne}},
  booktitle    = {{21th Biennial EARLI Conference}},
  location     = {{Graz}},
  title        = {{{Entrepreneurship Education at All Levels of Education: A Systematic Literature Review}}},
  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{60949,
  author       = {{Giese, Henning and Holtmann, Svea and Koch, Reinald and Langenmayr, Dominika}},
  journal      = {{ifo Schnelldienst}},
  number       = {{8}},
  pages        = {{34--40}},
  title        = {{{Steuerliches Investitionssofortprogramm: Ausreichender Schritt zur Stärkung des Wirtschaftsstandorts Deutschland?}}},
  volume       = {{78}},
  year         = {{2025}},
}

@inproceedings{61309,
  abstract     = {{Service ecosystems reshape service innovation by enabling value co-creation among diverse actors. However, small and medium-sized enterprises and public organizations face significant challenges navigating and leveraging these ecosystems due to resource constraints, knowledge gaps, and partnership difficulties. While digital innovation hubs have been introduced as potential intermediaries to foster innovation, existing models primarily focus on individual solutions and networking rather than orchestrating service innovation. This study investigates the design of a digital service innovation hub as an orchestrating entity that facilitates service innovation within ecosystems. Under the design science research paradigm, we analyze the challenges faced by small and medium-sized enterprises and public organizations and derive design requirements for these hubs. Based on 17 expert interviews and focus group validations, we define the problem
space and provide a requirements catalog for designing digital service innovation hubs as a step towards providing holistic support for service innovation initiatives.}},
  author       = {{Schäfer, Jannika Marie and Liebschner, Jonas and Rajko, Polina and Cohnen, Henrik and Lugmair, Nina and Heinz, Daniel}},
  booktitle    = {{Proceedings of the 20th International Conference on Wirtschaftsinformatik (WI 2025)}},
  keywords     = {{service innovation, ecosystem, innovation hubs, SMEs, public sector}},
  location     = {{Münster, Germany}},
  publisher    = {{Association for Information Systems (AIS)}},
  title        = {{{Designing Digital Service Innovation Hubs: An Ecosystem Perspective on the Challenges and Requirements of SMEs and the Public Sector}}},
  year         = {{2025}},
}

@inproceedings{61368,
  author       = {{Stumpe, Miriam and Speckenmeyer, Philipp and Schryen, Guido and Kleinjohann, Lisa and Weskamp, Christoph}},
  booktitle    = {{Proceedings of the Thirty-first Americas Conference on Information Systems (AMCIS 2025)}},
  title        = {{{Planning a Swarm-Based Mobility System with Autonomous Vehicles for Sustainable and Flexible Transportation in Rural Areas}}},
  year         = {{2025}},
}

@inproceedings{61370,
  author       = {{Göbel, J. and Betke, H. and Boldt, J. and Tran, M. L. and Schryen, Guido}},
  booktitle    = {{Proceedings of the Thirty-first Americas Conference on Information Systems (AMCIS 2025)}},
  title        = {{{The Impact of Chatbot Familiarity and Frequency of Use on Human-Likeness}}},
  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}},
}

@inproceedings{61381,
  author       = {{Grieger, Nicole and Okumus, Hasan and Burdorf, Sven and Kundisch, Dennis}},
  booktitle    = {{Proceedings of the MCIS 2025}},
  title        = {{{Traffic Scenario Detection – A Comparison of CNN-RNN and Transformer-based Architectures in the Context of Autonomous Driving}}},
  year         = {{2025}},
}

@inproceedings{61380,
  author       = {{Althaus, Maike}},
  booktitle    = {{Proceedings of the MCIS 2025}},
  title        = {{{Tech, Trash and Theft – Exploring the Impact of Food Waste Apps on Local Shoplifting in Grocery Stores and Supermarkets}}},
  year         = {{2025}},
}

@article{61366,
  author       = {{Paré, Guy and Wagner, Gerit and Tate, Mary and Schryen, Guido and Templier, Mathieu}},
  issn         = {{0960-085X}},
  journal      = {{European Journal of Information Systems}},
  pages        = {{1--25}},
  publisher    = {{Informa UK Limited}},
  title        = {{{Theorising Forward: Positioning Deductive Elaboration in the Information Systems Research Repertoire}}},
  doi          = {{10.1080/0960085x.2025.2550403}},
  year         = {{2025}},
}

@techreport{61491,
  abstract     = {{We examine behavioral frictions in entrepreneurs’ tax planning when choosing between corporate and partnership taxation under a check-the-box rule. Using German tax return data, we show that only a small fraction of entrepreneurs opt for corporate taxation, despite substantial potential tax savings. A pre registered incentivized online experiment demonstrates that complexity aversion, status quo bias, and misperception about the corporate tax burden—arising from the interaction of corporate and deferred dividend taxation—help explain the preference for partnership taxation. We further find that these behavioral frictions heighten liquidity risk under the corporate system, particularly in the face of unexpected cash flow needs. Finally, a survey of German tax advisors indicates that tax advice only partially mitigates these frictions. Some advisors misperceive the benefits of corporate taxation, while others anticipate client biases and therefore refrain from recommending the corporate tax system.}},
  author       = {{Blaufus, Kay and Maiterth, Ralf and Milde, Michael and Sureth-Sloane, Caren}},
  keywords     = {{Check-the-box, Legal Form, Tax Complexity, Tax Misperception, Behavioral Taxation, Tax Advice}},
  pages        = {{107}},
  title        = {{{Choosing the Wrong Box? Behavioral Frictions and Limits of Tax Advice in Tax Regime Choice }}},
  doi          = {{10.2139/ssrn.5378466}},
  year         = {{2025}},
}

@techreport{61490,
  abstract     = {{This study examines the effect of tax complexity on the market value of publicly traded firms. Using firm-level measures of tax complexity, we find that a one standard deviation increase in tax complexity—comparable in magnitude to the rise following the U.S. Tax Cuts and Jobs Act—is associated with a 2.6% decline in Tobin’s Q. The effect is particularly pronounced for complexity arising from anti-avoidance regulations and post-filing procedures. The negative valuation effect is more substantial for firms with limited opportunities for international profit shifting, weak governance, or low internal information quality. Further analyses reveal that tax system complexity is associated with a reduced growth potential of firms and less R&D and thus negative real responses that go beyond negative investment effects. Overall, our findings provide novel evidence of the economic costs of tax complexity and contribute to the debate on the design of efficient and equitable tax systems.}},
  author       = {{Braun, Anna-Sophie and Koch, Reinald and Sureth-Sloane, Caren}},
  pages        = {{48}},
  title        = {{{Tax Complexity and Firm Value}}},
  doi          = {{10.2139/ssrn.5378221}},
  year         = {{2025}},
}

@techreport{61508,
  abstract     = {{We investigate how tax authorities use joint tax audits as a coordinated enforcement tool in cross-border transactions of a multinational firm. Joint tax audits aim to resolve potential tax disputes early, before such disputes escalate into costly and time-consuming resolution procedures that may not fully eliminate double taxation. Employing a game-theoretic model, we identify settings in which we expect joint audits to occur and investigate their effect on the firm's expected tax payments and tax audit efficiency. We find that the occurrence of joint audits critically depends on the double taxation risk in the absence of joint audits. Unless tax rules are consistently applied, joint audits can occur more often when this risk is higher. The reason is that the firm changes its income-shifting strategy to reduce its expected tax payments, and thereby also enables tax authorities to better target tax disputes via joint audits that would otherwise escalate. However, we identify conditions under which joint audits are then detrimental to tax audit efficiency, particularly when the firm prefers them most. Our results imply that cost-sharing arrangements for joint audits should be tailored to the level of double taxation risk, with firm involvement having the potential to improve efficiency when this risk is high.}},
  author       = {{Dyck, Daniel and Kourouxous, Thomas and Lorenz, Johannes}},
  keywords     = {{joint tax audits, double taxation, dispute prevention, income shifting}},
  pages        = {{57}},
  title        = {{{An Economic Analysis of Joint Tax Audits}}},
  doi          = {{10.2139/ssrn.5398645}},
  year         = {{2025}},
}

@techreport{61502,
  abstract     = {{This study introduces sloppiness---the inaccurate preparation of supporting information during tax disputes---as a neglected but critical factor influencing taxpayer noncompliance. We conceptualize sloppiness as arising both from imperfections in the internal information environment, exacerbated by structural uncertainty over litigation outcomes (factual dimension), and from strategic aversion to compliance effort (strategic dimension). We examine whether and to what extent improved documentation and engaging an internal monitoring expert can mitigate sloppiness and prevent litigation. Using a game-theoretic model, we derive equilibrium strategies for a tax manager's compliance effort, a monitoring expert's dispute resolution effort, and a tax authority's litigation decision. Absent a monitoring expert, we find that improved documentation consistently reduces the litigation probability. However, when a monitoring expert is present, we surprisingly find that improved documentation crowds out compliance effort and can increase the litigation probability. Overall, our results suggest that sloppiness can be overcome either through strong documentation alone or by engaging a monitoring expert when documentation is weak, with the latter approach becoming more attractive as the dispute resolution costs decline.}},
  author       = {{Dyck, Daniel and Lorenz, Johannes and Sureth-Sloane, Caren}},
  title        = {{{Sloppiness in Tax Disputes: How to Prevent Litigation?}}},
  year         = {{2025}},
}

@article{61533,
  author       = {{Balsmeier, B. and Lück, Sonja and Fleming, L.}},
  issn         = {{0048-7333}},
  journal      = {{Research Policy}},
  number       = {{10}},
  publisher    = {{Elsevier BV}},
  title        = {{{Science knowledge localizes}}},
  doi          = {{10.1016/j.respol.2025.105333}},
  volume       = {{54}},
  year         = {{2025}},
}

@inbook{61769,
  author       = {{Kiepe, Karina and Schlömer, Tobias}},
  booktitle    = {{berufsbildung. Zeitschrift für Theorie-Praxis-Dialog}},
  pages        = {{9--12}},
  title        = {{{Vom Muster in die Struktur: Ein Verfahrenskonzept der Wissenschaftskommunikation für die BBNE}}},
  volume       = {{3}},
  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}},
}

@inproceedings{61375,
  author       = {{Reineke, Malte Fabian and Löhr, Bernd and Aßbrock, Agnes and Bartelheimer, Christian and Beverungen, Daniel}},
  booktitle    = {{International Conference on Business Process Management 2025}},
  isbn         = {{9783032028662}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{From Temporary Fixes to Informed Decisions—Design Echelons for Evaluating Workarounds}}},
  doi          = {{10.1007/978-3-032-02867-9_32}},
  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}},
}