@misc{40468, author = {{Perampalam, Abirame}}, title = {{{Zum Potenzial von Kryptowährungen. Eine ökonomische Analyse zu den Chancen und Risiken digitaler Währungen}}}, year = {{2022}}, } @misc{40467, author = {{Nassar, Hamza}}, title = {{{Mergers on digital markets - An economic analysis}}}, year = {{2022}}, } @misc{35775, author = {{Sureth-Sloane, Caren}}, publisher = {{VHB}}, title = {{{Steuerreformen: Investitionsstimulus oder bloß heiße Luft? Wann steuerliche Verlustrückträge der Wirtschaft helfen können}}}, year = {{2022}}, } @misc{40469, author = {{Sarsar, Abdelmajid}}, title = {{{Monopolbildung im Zuge der Globalisierung und Digitalisierung der GAFA-Unternehmen (Google, Amazon, Facebook, Apple) - eine wettbewerbspolitische Analyse}}}, year = {{2022}}, } @misc{40474, author = {{Bas, Mikail}}, title = {{{Kartelle und technischen Absprachen zur Forschung und Entwicklung - Eine wettbewerbspolitische Analyse anhand der Automobilindustrie}}}, year = {{2022}}, } @misc{40472, author = {{Vikue, Baribuma Lucy}}, title = {{{Blockchain Technology and the Internet of Thing-Risks and Chances for Supply Chains}}}, year = {{2022}}, } @misc{40471, author = {{Taskin, Ibrahim}}, title = {{{Die Fusion von Kaiser's Tengelmann und EDEKA - eine wettbewerbspolitische Analyse}}}, year = {{2022}}, } @article{36083, author = {{Constantiou, Ioanna and Mukkamala, Alivelu and Sjöklint, Mimmi and Trier, Matthias}}, issn = {{0960-085X}}, journal = {{European Journal of Information Systems}}, keywords = {{Library and Information Sciences, Information Systems, Self-Tracking, User Behaviour, Discontinuance}}, pages = {{1--21}}, publisher = {{Informa UK Limited}}, title = {{{Engaging with self-tracking applications: how do users respond to their performance data?}}}, doi = {{10.1080/0960085x.2022.2081096}}, year = {{2022}}, } @article{36960, author = {{Constantiou, Ioanna and Mukkamala, Alivelu and Sjöklint, Mimmi and Trier, Matthias}}, issn = {{0960-085X}}, journal = {{European Journal of Information Systems}}, keywords = {{Library and Information Sciences, Information Systems}}, pages = {{1--21}}, publisher = {{Informa UK Limited}}, title = {{{Engaging with self-tracking applications: how do users respond to their performance data?}}}, doi = {{10.1080/0960085x.2022.2081096}}, year = {{2022}}, } @inproceedings{36084, author = {{Meydani, Elnaz and Düsing, Christoph and Trier, Matthias}}, booktitle = {{Wirtschaftsinformatik 2022 Proceedings}}, location = {{Erlangen Nürnberg}}, title = {{{The Black Box of Social Commerce Platforms - A Closer Look at Users’ Activities}}}, year = {{2022}}, } @techreport{41182, author = {{Ortmann, Regina and Schindler, Dirk}}, title = {{{Income Shifting and Management Incentives}}}, year = {{2022}}, } @inproceedings{41487, author = {{Sven, Weinzierl and Bartelheimer, Christian and Zilker, Sandra and Beverungen, Daniel and Matzner, Martin}}, booktitle = {{Proceedings of the 26th Pacific Asia Conference on Information Systems (PACIS)}}, title = {{{ A Method for Predicting Workarounds in Business Processes}}}, year = {{2022}}, } @inbook{21586, author = {{Klein, M. and Kundisch, Dennis and Stummer, C.}}, booktitle = {{Handbuch Digitalisierung}}, editor = {{Corsten, H. and Roth, S.}}, pages = {{799--814}}, publisher = {{Vahle}}, title = {{{Feeless Micropayments and Their Impact on Business Models}}}, year = {{2022}}, } @article{21405, abstract = {{Previous accounting research shows that taxes affect decision making by individuals and firms. Most studies assume that agents have an accurate perception regarding their tax burden. However, there is a growing body of literature analyzing whether taxes are indeed perceived correctly. We review 128 studies on the measurement of tax misperception and its behavioral implications. The review reveals that many taxpayers have substantial tax misperceptions that lead to biased decision making. We develop a Behavioral Taxpayer Response Model on the impact of provided tax information on tax perception. Besides individual traits, characteristics of the tax information and the decision environment determine the extent of tax misperception. We discuss opportunities for future research and methodological limitations. While there is much evidence on tax misperception at the individual level, we hardly find any research at the firm level. Little is known about the real effects of managers’ tax misperception and on how tax information is strategically managed to impact stakeholders. This research gap is surprising as a large part of the accounting literature analyzes decision making and disclosure of firms. We recommend a mixed-method approach combining experiments, surveys, and archival data analyses to improve the knowledge on tax misperception and its consequences.}}, author = {{Blaufus, Kay and Chirvi, Malte and Huber, Hans-Peter and Maiterth, Ralf and Sureth-Sloane, Caren}}, journal = {{European Accounting Review}}, number = {{1}}, pages = {{111--144}}, title = {{{Tax Misperception and Its Effects on Decision Making - Literature Review and Behavioral Taxpayer Response Model}}}, doi = {{10.1080/09638180.2020.1852095}}, volume = {{31}}, year = {{2022}}, } @misc{42525, author = {{Dubbert, Annika}}, title = {{{Marktmissbrauch in Online-Märkten und die Herausforderungen für die Wettbewerbsbehörden - eine wettbewerbspolitische Betrachtung}}}, year = {{2022}}, } @misc{42526, author = {{Miftari, Ardita}}, title = {{{Zur Bekämpfung von Marktmachtmissbrauch in digitalen Märkten – Wettbewerbspolitische Maßnahmen im Vergleich}}}, year = {{2022}}, } @misc{42527, author = {{Minhaj, Noor}}, title = {{{Of the efficacy of competition law in dealing with challenges of digital markets - Selected cases of Facebook}}}, year = {{2022}}, } @misc{42528, author = {{Rayhan, Md. Sashi}}, title = {{{On the Efficacy of EU Competition Policy in the Context of Big Data}}}, year = {{2022}}, } @misc{42524, author = {{Busch, Anna Lisa}}, title = {{{On the privatization of hospitals - The case of Germany}}}, year = {{2022}}, } @inproceedings{41486, abstract = {{Now accounting for more than 80% of a firm's worth, brands have become essential assets for modern organizations. However, methods and techniques for the monetary valuation of brands are still under-researched. Hence, the objective of this study is to evaluate the utility of explanatory statistical models and machine learning approaches for explaining and predicting brand value. Drawing upon the case of the most valuable English football brands during the 2016/17 to 2020/21 seasons, we demonstrate how to operationalize Aaker's (1991) theoretical brand equity framework to collect meaningful qualitative and quantitative feature sets. Our explanatory models can explain up to 77% of the variation in brand valuations across all clubs and seasons, while our predictive approach can predict out-of-sample observations with a mean absolute percentage error (MAPE) of 14%. Future research can build upon our results to develop domain-specific brand valuation methods while enabling managers to make better-informed investment decisions.}}, author = {{Caron, Matthew and Bartelheimer, Christian and Müller, Oliver}}, booktitle = {{Proceeding of the 28th Americas Conference on Information Systems (AMCIS)}}, location = {{Minneapolis, USA}}, title = {{{Towards a Reliable & Transparent Approach to Data-Driven Brand Valuation}}}, year = {{2022}}, }