@phdthesis{37396,
  author       = {{Fiedler, Moritz}},
  publisher    = {{Dr. Kovac}},
  title        = {{{Development of a Strategic Controlling Concept}}},
  year         = {{2021}},
}

@techreport{37136,
  abstract     = {{This study examines the relation between voluntary audit and the cost of debt in private firms. We use a sample of 4,058 small private firms operating in the period 2006‐2017 that are not subject to mandatory audits. Firms decide for a voluntary audit of financial statements either because the economic setting in which they operate effectively forces them to do so (e.g., ownership complexity, export‐oriented supply chain, subsidiary status) or because firm fundamentals and/or financial reporting practices limit their access to financial debt, both reflected in earnings quality. We use these factors to model the decision for voluntary audit. In the outcome analyses, we find robust evidence that voluntary audits are associated with higher, rather than lower, interest rate by up to 3.0 percentage points. This effect is present regardless of the perceived audit quality (Big‐4 vs. non‐Big‐4), but is stronger for non‐Big‐4 audits where auditees have a stronger position relative to auditors. Audited firms’ earnings are less informative about future operating performance relative to unaudited counterparts. We conclude that voluntary audits facilitate access to financial debt for firms with higher risk that may otherwise have no access to this form of financing. The price paid is reflected in higher interest rates charged to firms with voluntary audits – firms with higher information and/or fundamental risk.}},
  author       = {{Ichev, Riste and Koren, Jernej and Kosi, Urska and Sitar Sustar, Katarina and Valentincic, Aljosa}},
  keywords     = {{private firms, voluntary audit, cost of debt, self‐selection bias, risk}},
  title        = {{{Cost of Debt for Private Firms Revisited: Voluntary Audits as a Reflection of Risk}}},
  year         = {{2021}},
}

@techreport{22219,
  author       = {{Leimeister, Jan Marco and Stieglitz, Stefan and Matzner, Martin and Kundisch, Dennis and Flath, Christoph and Röglinger, Maximilian}},
  pages        = {{741--749}},
  title        = {{{Quo Vadis Conferences in the Business and Information Systems Engineering (BISE) Community After Covid}}},
  volume       = {{63 (6)}},
  year         = {{2021}},
}

@misc{39351,
  author       = {{Heinze, Erik}},
  title        = {{{Kollusion durch Plattformen - der Einfluss von Tank-Apps auf den Preiswettbewerb von Tankstellen in Deutschland}}},
  year         = {{2021}},
}

@misc{39358,
  author       = {{Rayhan, Shahi}},
  title        = {{{Big Data in Digital Markets - Challenges for Competition Policy to Protect Consumer Welfare}}},
  year         = {{2021}},
}

@misc{39356,
  author       = {{Joshan, Saeid}},
  title        = {{{Network Development of Low-Cost Carriers at German Airports}}},
  year         = {{2021}},
}

@misc{39962,
  author       = {{Ajredini, Zurkani}},
  title        = {{{Plattformgestaltungen auf digitalen Märkten - eine Analyse der Wohlfahrtseffekte}}},
  year         = {{2021}},
}

@misc{40465,
  author       = {{Kanne, Niklas}},
  title        = {{{Marktmachtmissbrauch digitaler Plattformen - eine Analyse anhand der zehnten Novelle des GWB}}},
  year         = {{2021}},
}

@misc{40466,
  author       = {{Klüppel, Pascal}},
  title        = {{{Marktmachtmissbrauch von Google – Eine wettbewerbspolitische Analyse}}},
  year         = {{2021}},
}

@techreport{41197,
  author       = {{Ortmann, Regina and Warkulat, Sonja and Krull, Sebastian and Klocke, Nina and Pelster, Matthias}},
  title        = {{{COVID-19 Reporting and Willingness to Pay for Leisure Activities}}},
  volume       = {{83}},
  year         = {{2021}},
}

@techreport{41184,
  author       = {{Ortmann, Regina and Simons, Dirk and Voeller, Dennis}},
  title        = {{{Real effects of an international tax reform for MNEs}}},
  volume       = {{64}},
  year         = {{2021}},
}

@misc{40473,
  author       = {{Yigitbas , Osman}},
  title        = {{{Preisabsprachen in der Automobilindustrie - eine wettbewerbspolitische Analyse}}},
  year         = {{2021}},
}

@misc{40470,
  author       = {{Schulte, Marcel}},
  title        = {{{Facebooks digitale Währung - eine wettbewerbspolitische Analyse}}},
  year         = {{2021}},
}

@inbook{35758,
  author       = {{Meydani, Elnaz and Düsing, Christoph and Trier, Matthias}},
  booktitle    = {{Lecture Notes in Information Systems and Organisation}},
  isbn         = {{9783030867966}},
  issn         = {{2195-4968}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Towards a Trust-Aware Item Recommendation System on a Graph Autoencoder with Attention Mechanism}}},
  doi          = {{10.1007/978-3-030-86797-3_5}},
  year         = {{2021}},
}

@inproceedings{24547,
  abstract     = {{Over the last years, several approaches for the data-driven estimation of expected possession value (EPV) in basketball and association football (soccer) have been proposed. In this paper, we develop and evaluate PIVOT: the first such framework for team handball. Accounting for the fast-paced, dynamic nature and relative data scarcity of hand- ball, we propose a parsimonious end-to-end deep learning architecture that relies solely on tracking data. This efficient approach is capable of predicting the probability that a team will score within the near future given the fine-grained spatio-temporal distribution of all players and the ball over the last seconds of the game. Our experiments indicate that PIVOT is able to produce accurate and calibrated probability estimates, even when trained on a relatively small dataset. We also showcase two interactive applications of PIVOT for valuing actual and counterfactual player decisions and actions in real-time.}},
  author       = {{Müller, Oliver and Caron, Matthew and Döring, Michael and Heuwinkel, Tim and Baumeister, Jochen}},
  booktitle    = {{8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021)}},
  keywords     = {{expected possession value, handball, tracking data, time series classification, deep learning}},
  location     = {{Online}},
  title        = {{{PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking Data}}},
  year         = {{2021}},
}

@inproceedings{25029,
  abstract     = {{In early 2021, the finance world was taken by storm by the dramatic price surge of the GameStop Corp. stock. This rise is being, at least in part, attributed to a group of Redditors belonging to the now-famous r/wallstreetbets (WSB) subreddit group. In this work, we set out to address if user activity on the WSB subreddit is associated with the trading volume of the GME stock. Leveraging a unique dataset containing more than 4.9 million WSB posts and comments, we assert that user activity is associated with the trading volume of the GameStop stock. We further show that posts have a significantly higher predictive power than comments and are especially helpful for predicting unusually high trading volume. Lastly, as recent events have shown, we believe that these findings have implications for retail and institutional investors, trading platforms, and policymakers, as these can have disruptive potential.}},
  author       = {{Caron, Matthew and Gulenko, Maryna and Müller, Oliver}},
  booktitle    = {{42nd International Conference on Information Systems (ICIS 2021)}},
  keywords     = {{Retail investors, GameStop, Social Networks, Reddit, WallStreetBets}},
  location     = {{Austin, Texas}},
  title        = {{{To the Moon! Analyzing the Community of “Degenerates” Engaged in the Surge of the GME Stock}}},
  year         = {{2021}},
}

@inproceedings{44073,
  author       = {{Meydani, Elnaz and Düsing, Christoph and Trier, Matthias}},
  booktitle    = {{Innovation Through Information Systems: Volume II: A Collection of Latest Research on Technology Issues}},
  pages        = {{72–77}},
  title        = {{{Towards a Trust-Aware Item Recommendation System on a Graph Autoencoder with Attention Mechanism}}},
  year         = {{2021}},
}

@article{21289,
  author       = {{Kaimann, Daniel and Tanneberg, Ilka and Cox, Joe}},
  issn         = {{0143-6570}},
  journal      = {{Managerial and Decision Economics}},
  number       = {{1}},
  pages        = {{3--20}},
  title        = {{{“I will survive”: Online streaming and the chart survival of music tracks}}},
  doi          = {{10.1002/mde.3226}},
  volume       = {{42}},
  year         = {{2021}},
}

@misc{42317,
  author       = {{N., N.}},
  publisher    = {{Universität Paderborn}},
  title        = {{{Die Aufteilung der Barentsseegebiete mithilfe des Adjusted Winner Verfahrens bei asymmetrischen Machtverhältnissen}}},
  year         = {{2021}},
}

@misc{42315,
  author       = {{N., N.}},
  publisher    = {{Universität Paderborn}},
  title        = {{{Versionisierung von Serviceleistungen auf Videoplattformen}}},
  year         = {{2021}},
}

