@inproceedings{23723, author = {{Sieger, L. N. and Doğangün, A. and Mirbabaie, Milad}}, booktitle = {{Proceedings of the 8th Mensch und Computer}}, title = {{{Teaching the Smart Home - User Experience in an Interactive Learning Phase}}}, year = {{2021}}, } @inproceedings{23724, author = {{Marx, J. and Mirbabaie, Milad and Czonstke, C. and Stieglitz, S.}}, booktitle = {{29th European Conference on Information Systems}}, title = {{{Social Media Analytics and Corporate Crises - A Case Study of Boeing's 737 Max Crashes}}}, year = {{2021}}, } @inproceedings{23725, author = {{Hofeditz, L. and Mirbabaie, Milad and Holstein, J. and Stieglitz, S.}}, booktitle = {{29th European Conference on Information Systems}}, title = {{{Do you trust an AI-Journalist? A Credibility Analysis of News Content with AI-Authorship}}}, year = {{2021}}, } @inproceedings{23726, author = {{Marx, J. and Mirbabaie, Milad and Brendel, A.B. and Zander, K.}}, booktitle = {{The Americas Conference on Information Systems}}, title = {{{The Role of Parasocial Interactions for Podcast Backchannel Response}}}, year = {{2021}}, } @article{22205, abstract = {{In January 2021, the GameStop stock was the epicenter of the first case of predatory trading initiated by retail investors. We use brokerage accounts to study who participated in this GameStop frenzy and how they performed. We investigate the extent to which investors’ personal and trading characteristics differ from the general population of retail investors. GameStop traders had a history of investing in speculative instruments, including stocks with lottery-like features. They were also more likely to close their positions before the peak of the bubble. At the onset of the frenzy, numerous retail investors also shorted GameStop. Overall, our results indicate that the GameStop frenzy was not a pure digital protest against Wall Street but speculative trading by a group of retail investors, in line with their prior high-risk trading behavior.}}, author = {{Hasso, Tim and Müller, Daniel and Pelster, Matthias and Warkulat, Sonja}}, journal = {{Finance Research Letters}}, keywords = {{Predatory Trading, Retail Investors, Trading Behavior}}, title = {{{Who participated in the GameStop frenzy? Evidence from brokerage accounts}}}, doi = {{10.1016/j.frl.2021.102140}}, year = {{2021}}, } @techreport{22211, author = {{Lorenz, Johannes and Sureth-Sloane, Caren and Diller, Markus}}, title = {{{Inconsistent tax transfer prices: tax filings, audits, and double taxation}}}, doi = {{10.52569/acpj5634}}, year = {{2021}}, } @inbook{22221, author = {{Blankenfeldt, Maximilian and Müller, Jens and Weinrich, Arndt}}, booktitle = {{Intangibles - Immaterielle Werte}}, editor = {{Vögele, Alexander}}, isbn = {{978-3-406-71601-0}}, publisher = {{C.H.Beck}}, title = {{{Forschung und Entwicklung: Kriterien für die Aktivierung in der Unternehmenspraxis}}}, year = {{2021}}, } @inproceedings{22514, author = {{Kucklick, Jan-Peter and Müller, Jennifer and Beverungen, Daniel and Müller, Oliver}}, booktitle = {{European Conference on Information Systems}}, location = {{Virtual}}, title = {{{Quantifying the Impact of Location Data for Real Estate Appraisal – A GIS-based Deep Learning Approach}}}, year = {{2021}}, } @article{22523, abstract = {{The containment of COVID-19 critically hinges on individuals’ behavior. We investigate how individuals react to variations in COVID-19 reporting. Using a survey, we elicit individuals' perceived infection risk given various COVID-19 metrics (e.g., confirmed cases, reproduction rate, or case-fatality ratio). We proxy individuals' risk perception with their willingness to pay for the participation in everyday life and amusements events. We find that participants react to different COVID-19 metrics with varying sensitivity. We observe a saturation of sensitivity for several measures at critical limits used in the political discussion, making our results highly relevant for policy makers in their efforts to direct individuals to adhere to hygienic etiquette and social distancing guidelines.}}, author = {{Warkulat, Sonja and Krull, Sebastian and Ortmann, Regina and Klocke, Nina and Pelster, Matthias}}, journal = {{Covid Economics}}, keywords = {{COVID-19 reporting, willingness to pay, willingness to accept}}, number = {{83}}, pages = {{183--205}}, publisher = {{CEPR Press}}, title = {{{COVID-19 reporting and willingness to pay for leisure activities}}}, year = {{2021}}, } @article{22631, author = {{Krull, Sebastian and Loschelder, David D. and Boecker, Lea}}, journal = {{Frontiers in Psychology}}, title = {{{The Power and Peril of Precise vs. Round Health Message Interventions to Increase Stair-Use}}}, doi = {{10.3389/fpsyg.2021.624198}}, year = {{2021}}, } @inproceedings{21723, author = {{Müller, Stefanie Jutta Marianne and Buchholz, Anna and Flath, Beate and Kundisch, Dennis and Momen Pour Tafreshi, Maryam}}, location = {{Virtual Conference/Workshop}}, title = {{{The Agony of Finding the Right Pricing Policy for Cultural Institutions: Addressing Economic Viability and Cultural Participation through Innovative Pricing}}}, year = {{2021}}, } @inproceedings{21727, abstract = {{Platform-based business models underlie the success of many of today’s largest, fastest-growing, and most disruptive companies. Despite the success of prominent examples, such as Uber and Airbnb, creating a profitable platform ecosystem presents a key challenge for many companies across all industries. Although research provides knowledge about platforms’ different value drivers (e.g., network effects), companies that seek to transform their current business model into a platform-based one lack an artifact to reduce knowledge boundaries, collaborate effectively, and cope with the complexities and dynamics of platform ecosystems. We address this challenge by developing two artifacts and combining research from variability modeling, business model dependencies, and system dynamics. This paper presents a design science research approach to develop the platform ecosystem modeling language and the platform ecosystem development tool that support researcher and practitioner by visualizing and simulating platform ecosystems. }}, author = {{Vorbohle, Christian and Gottschalk, Sebastian}}, booktitle = {{Proceedings of the 29th European Conference on Information Systems (ECIS)}}, keywords = {{Platform Ecosystems, Platform Ecosystem Modeling Language, Platform Ecosystem Development Tool, Business Models, Design Science}}, location = {{Virtual Conference/Workshop}}, publisher = {{AIS}}, title = {{{Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems }}}, year = {{2021}}, } @inproceedings{21799, author = {{Kutzner, K. and Stadtländer, M. and Seutter, Janina and Kundisch, Dennis and Knackstedt, R.}}, booktitle = {{Proceedings of the 29th European Conference on Information Systems (ECIS)}}, location = {{Virtual Conference/Workshop}}, title = {{{”Sorry, Too Much Information” Designing Online Review Systems that Support Information Search and Processing}}}, year = {{2021}}, } @inproceedings{21812, author = {{Vorbohle, Christian and Szopinski, Daniel and Kundisch, Dennis}}, booktitle = {{Proceedings of the 29th European Conference on Information Systems (ECIS)}}, location = {{Virtual Conference/Workshop}}, title = {{{Toward Understanding the Complexity of Business Models – A Taxonomy of Business Model Dependencies}}}, year = {{2021}}, } @article{5163, abstract = {{Employing a unique hand-collected sample of 956 credit risk securitization transactions issued by 64 stock-listed European banks across the EU-13 plus Switzerland over the period from 1997 to 2010, this paper empirically analyzes the impact of securitization on the issuing banks’ effective tax rates. Our analysis reveals that banks may reduce their tax expense through securitization via a direct and indirect channel suggesting that tax avoidance may be a further motive for banks to engage in the securitization business. These baseline findings remain robust under various robustness checks, especially when implementing structural equation models and controlling for a reverse causality between the banks’ tax burden and their incentive to securitize. Finally, various sensitivity analyses provide further important results and implications for tax policies, banking regulation and the ongoing process of revitalizing the European securitization market.}}, author = {{Uhde, André}}, journal = {{The Quarterly Review of Economics and Finance}}, keywords = {{Securitization, Credit risk transfer, Effective tax rates, European banking}}, pages = {{411--421}}, title = {{{Tax avoidance through securitization}}}, doi = {{10.1016/j.qref.2020.07.008}}, volume = {{79}}, year = {{2021}}, } @article{15073, abstract = {{ In this paper, we analyze the effect of light conditions on road accidents and estimate the long run consequences of different time regimes for road safety. Identification is based on variation in light conditions induced by differences in sunrise and sunset times across space and time. We estimate that darkness causes annual costs of more than £500 million in Great Britain. By setting daylight saving time year-round 8 percent of these costs could be saved. Thus, focusing solely on the short run costs related to the transition itself underestimates the total costs of the current time regime. }}, author = {{Bünnings, Christian and Schiele, Valentin}}, issn = {{0034-6535}}, journal = {{The Review of Economics and Statistics}}, number = {{1}}, pages = {{165--176}}, title = {{{Spring Forward, Don't Fall Back: The Effect of Daylight Saving Time on Road Safety}}}, doi = {{10.1162/rest_a_00873}}, volume = {{103}}, year = {{2021}}, } @inproceedings{21093, abstract = {{Requirements for energy distribution networks are changing fast due to the growing share of renewable energy, increasing electrification, and novel consumer and asset technologies. Since uncertainties about future developments increase planning difficulty, flexibility potentials such as synergies between the electricity, gas, heat, and transport sector often remain unused. In this paper, we therefore present a novel module-based concept for a decision support system that helps distribution network planners to identify cross-sectoral synergies and to select optimal network assets such as transformers, cables, pipes, energy storage systems or energy conversion technology. The concept enables long-term transformation plans and supports distribution network planners in designing reliable, sustainable and cost-efficient distribution networks for future demands.}}, author = {{Kirchhoff, Jonas and Burmeister, Sascha Christian and Weskamp, Christoph and Engels, Gregor}}, booktitle = {{Energy Informatics and Electro Mobility ICT}}, editor = {{Breitner, Michael H. and Lehnhoff, Sebastian and Nieße, Astrid and Staudt, Philipp and Weinhardt, Christof and Werth, Oliver}}, title = {{{Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning}}}, year = {{2021}}, } @article{20212, abstract = {{Ideational impact refers to the uptake of a paper's ideas and concepts by subsequent research. It is defined in stark contrast to total citation impact, a measure predominantly used in research evaluation that assumes that all citations are equal. Understanding ideational impact is critical for evaluating research impact and understanding how scientific disciplines build a cumulative tradition. Research has only recently developed automated citation classification techniques to distinguish between different types of citations and generally does not emphasize the conceptual content of the citations and its ideational impact. To address this problem, we develop Deep Content-enriched Ideational Impact Classification (Deep-CENIC) as the first automated approach for ideational impact classification to support researchers' literature search practices. We evaluate Deep-CENIC on 1,256 papers citing 24 information systems review articles from the IT business value domain. We show that Deep-CENIC significantly outperforms state-of-the-art benchmark models. We contribute to information systems research by operationalizing the concept of ideational impact, designing a recommender system for academic papers based on deep learning techniques, and empirically exploring the ideational impact of the IT business value domain. }}, author = {{Prester, Julian and Wagner, Gerit and Schryen, Guido and Hassan, Nik Rushdi}}, journal = {{Decision Support Systems}}, keywords = {{Ideational impact, citation classification, academic recommender systems, natural language processing, deep learning, cumulative tradition}}, number = {{January}}, title = {{{Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach}}}, volume = {{140}}, year = {{2021}}, } @article{20844, abstract = {{Review papers are essential for knowledge development in IS. While some are cited twice a day, others accumulate single digit citations over a decade. The magnitude of these differences prompts us to analyze what distinguishes those reviews that have proven to be integral to scientific progress from those that might be considered less impactful. Our results highlight differences between reviews aimed at describing, understanding, explaining, and theory testing. Beyond the control variables, they demonstrate the importance of methodological transparency and the development of research agendas. These insights inform all stakeholders involved in the development and publication of review papers.}}, author = {{Wagner, Gerit and Prester, Julian and Roche, Maria and Schryen, Guido and Benlian, Alexander and Paré, Guy and Templier, Mathieu}}, journal = {{Information & Management}}, keywords = {{Literature review, review papers, scientometric, scientific impact, citation analysis}}, number = {{3}}, title = {{{Which Factors Affect the Scientific Impact of Review Papers in IS Research? A Scientometric Study}}}, volume = {{58}}, year = {{2021}}, } @article{23494, author = {{Stumpe, Miriam and Rößler, David and Schryen, Guido and Kliewer, Natalia}}, journal = {{EURO Journal on Transportation and Logistics}}, title = {{{Study on Sensitivity of Electric Bus Systems under Simultaneous Optimization of Charging Infrastructure and Vehicle Schedules}}}, doi = {{https://doi.org/10.1016/j.ejtl.2021.100049}}, volume = {{10}}, year = {{2021}}, }