@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}}, } @misc{42321, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Kindergarten Allocation through Matching Mechanisms}}}, year = {{2021}}, } @misc{42309, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Faire Profitverteilung in Energienetzwerken - eine spieltheoretische Analyse von Microgrids}}}, year = {{2021}}, } @misc{42311, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{"First-Party-Content" auf zweiseitigen Märkten}}}, year = {{2021}}, } @misc{42314, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Stability in many-to-many matchings with contracts}}}, year = {{2021}}, } @misc{42313, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Preissetzungsstrategien für Neuprodukte}}}, year = {{2021}}, } @misc{42310, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Co-opetition in Two-Sided Markets}}}, year = {{2021}}, } @misc{42312, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Matching mit Minderheiten}}}, year = {{2021}}, } @misc{42316, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Piracy and Visioning}}}, year = {{2021}}, } @misc{42303, author = {{N., N.}}, publisher = {{Universität Paderborn}}, title = {{{Revenue Sharing Contracts: Horizontale Koordination in der E-Commerce-Logistik}}}, year = {{2021}}, }