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Alle Publikationen der Fakultät für Wirtschaftswissenschaften

Das Research Information Systems der Universität Paderborn bietet Ihnen eine vollständige Übersicht über die Publikationen der Forscherinnen und Forscher der Fakultät für Wirtschaftswissenschaften.

Die neusten 100 Publikationen der Fakultät


Open list in Research Information System

A Renaissance of Context in Design Science Research

P. zur Heiden, D. Beverungen, in: Proceedings of the 55th Hawaii International Conference on System Sciences, 2022


Attention triggers and investors' risk-taking

M. Arnold, M. Pelster, M.G. Subrahmanyam, Journal of Financial Economics (2022), 143(2), pp. 846-875

The paper investigates the impact of individual attention on investor risk-taking. We analyze a large sample of trading records from a brokerage service that allows its customers to trade contracts-for-differences (CFD), and sends standardized push messages on recent stock performance to its client investors. The advantage of this sample is that it allows us to isolate the "push" messages as individual attention triggers, which we can directly link to the same individuals' risk-taking. A particular advantage of CFD trading is that it allows investors to make use of leverage, which provides us a pure measure of investors' willingness to take risks that is independent of the decision to purchase a particular stock. Leverage is a major catalyst of speculative trading, as it increases the scope of extreme returns, and enables investors to take larger positions than what they can afford with their own capital. We show that investors execute attention-driven trades with higher leverage, compared to their other trades, as well as those of other investors who are not alerted by attention triggers.


Context in Design Science Research: Taxonomy and Framework

A. Herwix, P. zur Heiden, in: Proceedings of the 55th Hawaii International Conference on System Sciences, 2022


Dear Guests, please pay for my license – Analyzing the heterogenous cost-pass-through of commercial and non-commercial rental suppliers in response to regulatory policies

M. Müller, J. Neumann, D. Kundisch, in: Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS), 2022


Decision Support for Disaster Relief: Coordinating Spontaneous Volunteers

M. Sperling, G. Schryen, European Journal of Operational Research (EJOR) (2022), 299(2), pp. 690 - 705


Exploring purposes of using taxonomies

T. Schoormann, F. Möller, D. Szopinski, in: Tagungsband der 17. Internationalen Tagung Wirtschaftsinformatik 2022, 2022


Feeless Micropayments and Their Impact on Business Models

M. Klein, D. Kundisch, C. Stummer, in: Handbuch Digitalisierung, Vahle, 2022


Moment or Movement – An Empirical Analysis of the Heterogeneous Impact of Media Attention on Charitable Crowdfunding Campaigns

J. Seutter, M. Müller, S.J.M. Müller, D. Kundisch, in: Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS), 2022


Rollercoaster of Emotions – A Semantic Analysis of Fundraising Campaigns over the Course of the Covid-19 Pandemic

N. Grieger, J. Seutter, D. Kundisch, in: Tagungsband der 17. Internationalen Tagung Wirtschaftsinformatik 2022, 2022


The dark triad and corporate sustainability: An empirical analysis of personality traits of middle managers

M. Pelster, S. Schaltegger, Business Ethics, the Environment & Responsibility (2022), 31(1), pp. 80-99

DOI


Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models

M. Caron, F.S. Bäumer, O. Müller, in: 55th Annual Hawaii International Conference on System Sciences (HICSS 2022), 2022

Our world is more connected than ever before. Sadly, however, this highly connected world has made it easier to bully, insult, and propagate hate speech on the cyberspace. Even though researchers and companies alike have started investigating this real-world problem, the question remains as to why users are increasingly being exposed to hate and discrimination online. In fact, the noticeable and persistent increase in harmful language on social media platforms indicates that the situation is, actually, only getting worse. Hence, in this work, we show that contemporary ML methods can help tackle this challenge in an accurate and cost-effective manner. Our experiments demonstrate that a universal approach combining transfer learning methods and state-of-the-art Transformer architectures can trigger the efficient development of toxic language detection models. Consequently, with this universal approach, we provide platform providers with a simplistic approach capable of enabling the automated moderation of user-generated content, and as a result, hope to contribute to making the web a safer place.


Using Geolocated Text to Quantify Location in Real Estate Appraisal

T. Heuwinkel, J. Kucklick, O. Müller, in: 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022

Accurate real estate appraisal is essential in decision making processes of financial institutions, governments, and trending real estate platforms like Zillow. One of the most important factors of a property’s value is its location. However, creating accurate quantifications of location remains a challenge. While traditional approaches rely on Geographical Information Systems (GIS), recently unstructured data in form of images was incorporated in the appraisal process, but text data remains an untapped reservoir. Our study shows that using text data in form of geolocated Wikipedia articles can increase predictive performance over traditional GIS-based methods by 8.2% in spatial out-of-sample validation. A framework to automatically extract geographically weighted vector representations for text is established and used alongside traditional structural housing features to make predictions and to uncover local patterns on sale price for real estate transactions between 2015 and 2020 in Allegheny County, Pennsylvania.


Utilizing Geographic Information Systems for Condition-Based Maintenance on the Energy Distribution Grid

P. zur Heiden, J. Priefer, D. Beverungen, in: Proceedings of the 55th Hawaii International Conference on System Sciences, 2022


Visual Interpretability of Image-based Real Estate Appraisal

J. Kucklick, in: 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022

Explainability for machine learning gets more and more important in high-stakes decisions like real estate appraisal. While traditional hedonic house pricing models are fed with hard information based on housing attributes, recently also soft information has been incorporated to increase the predictive performance. This soft information can be extracted from image data by complex models like Convolutional Neural Networks (CNNs). However, these are intransparent which excludes their use for high-stakes financial decisions. To overcome this limitation, we examine if a two-stage modeling approach can provide explainability. We combine visual interpretability by Regression Activation Maps (RAM) for the CNN and a linear regression for the overall prediction. Our experiments are based on 62.000 family homes in Philadelphia and the results indicate that the CNN learns aspects related to vegetation and quality aspects of the house from exterior images, improving the predictive accuracy of real estate appraisal by up to 5.4%.


”Sorry, Too Much Information” Designing Online Review Systems that Support Information Search and Processing

K. Kutzner, M. Stadtländer, J. Seutter, D. Kundisch, R. Knackstedt, in: Proceedings of the 29th European Conference on Information Systems (ECIS), 2021


"Timing is Everything" — An Empirical Analysis of the Timing of Online Review Elicitation

M. Poniatowski, J. Seutter, D. Kundisch, in: Proceedings of the 42nd International Conference on Information Systems (ICIS), 2021


“What’s the Point of the Task?” Exploring the Influence of Task Meaning on Creativity in Crowdsourcing

T. Görzen, International Journal of Innovation Management (2021), 25(1)

DOI


A Comparison of Multi-View Learning Strategies for Satellite Image-based Real Estate Appraisal

J. Kucklick, O. Müller, in: The AAAI-21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, 2021




Affordance-Experimentation: Eine Fallstudie zur Entwicklung von Virtual-Reality-Anwendungsfällen im Unternehmenskontext

J. Fromm, E. Slawinski, M. Mirbabaie, HMD Praxis der Wirtschaftsinformatik (2021)

<jats:title>Zusammenfassung</jats:title><jats:p>Durch technologische Fortschritte in den letzten Jahren ist Virtual Reality erschwinglicher und benutzerfreundlicher geworden, sodass Unternehmen die Einführung der Technologie verstärkt in Betracht ziehen. Ihren Aufschwung erlebte die Technologie jedoch durch die Unterhaltungs- und Spieleindustrie, weshalb sich für Unternehmen die Frage nach sinnvollen Anwendungsfällen stellt. Nach der Affordance-Experimentation-Actualization-Theorie ist insbesondere bei neu aufkommenden Technologien eine Experimentierphase notwendig, um Handlungsmöglichkeiten aufzudecken und daraus Anwendungsfälle zu generieren. Dieser Artikel präsentiert die Ergebnisse einer Fallstudie in einem Unternehmen, das sich während der Studie in der Experimentierphase befand. Durch Interviews mit acht Beschäftigten und einem Vertriebspartner konnten drei Handlungsmöglichkeiten für Virtual Reality im Unternehmenskontext und eine zuvor nicht bekannte Aktivität der Experimentierphase identifiziert werden. Damit erweitert die Studie bisherige Forschung zur Experimentierphase und zeigt Unterschiede im Vergleich zu anderen innovativen Technologien auf, die in vorherigen Studien untersucht wurden. Für Unternehmen bietet die Studie wertvolle Einblicke in die erfolgreiche Gestaltung der Experimentierphase als Vorbereitung auf die Implementierung.</jats:p>


Affording Technology in Crisis Situations: The Occurrence of Rumor Sense-Making Processes

M. Mirbabaie, S. Stieglitz, I. Amojo, Journal of Database Management (2021)


An update for taxonomy designers: Methodological guidance from information systems research

D. Kundisch, J. Muntermann, A.M. Oberländer, D. Rau, M. Röglinger, T. Schoormann, D. Szopinski, Business & Information Systems Engineering (2021)


Anthropogenic climate change: the impact of the global carbon budget

M. Redlin, T. Gries, Theoretical and Applied Climatology (2021)

<jats:title>Abstract</jats:title><jats:p>Using time series data for the period 1959–2015, our empirical analysis examines the simultaneous effects of the individual components of the global carbon budget on temperature. Specifically, we explore the possible effects of carbon emissions caused by fossil fuel combustion, cement production, land-use change emissions, and carbon sinks (here in terms of land sink and ocean sink) on climate change. The simultaneous inclusion of carbon emissions and carbon sinks allows us to look at the coexistent and opposing effects of the individual components of the carbon budget and thus provides a holistic perspective from which to explore the relationship between the global carbon budget and global warming. The results reveal a significant positive effect of carbon emissions on temperature for both fossil fuels emissions and emissions from land-use change, confirming previous results concerning carbon dioxide and temperature. Further, while ocean sink does not seem to have a significant effect, we identify a temperature-decreasing effect for land sink.</jats:p>


Are Risk-based Tax Audit Strategies Rewarded? An Analysis of Corporate Tax Avoidance

E. Eberhartinger, R. Safaei, C. Sureth-Sloane, Y. Wu, TRR 266 Accounting for Transparency Working Paper Series No. 60, 2021


Artificial intelligence in disease diagnostics: A critical review and classification on the current state of research guiding future direction

M. Mirbabaie, S. Stieglitz, N.R.J. Frick, Health and Technology (2021), pp. 693-731

The diagnosis of diseases is decisive for planning proper treatment and ensuring the well-being of patients. Human error hinders accurate diagnostics, as interpreting medical information is a complex and cognitively challenging task. The application of artificial intelligence (AI) can improve the level of diagnostic accuracy and efficiency. While the current literature has examined various approaches to diagnosing various diseases, an overview of fields in which AI has been applied, including their performance aiming to identify emergent digitalized healthcare services, has not yet been adequately realized in extant research. By conducting a critical review, we portray the AI landscape in diagnostics and provide a snapshot to guide future research. This paper extends academia by proposing a research agenda. Practitioners understand the extent to which AI improves diagnostics and how healthcare benefits from it. However, several issues need to be addressed before successful application of AI in disease diagnostics can be achieved.</jats:p>


Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research

M. Mirbabaie, L. Hofeditz, N.R.J. Frick, S. Stieglitz, AI & SOCIETY (2021)

<jats:title>Abstract</jats:title><jats:p>The application of artificial intelligence (AI) in hospitals yields many advantages but also confronts healthcare with ethical questions and challenges. While various disciplines have conducted specific research on the ethical considerations of AI in hospitals, the literature still requires a holistic overview. By conducting a systematic discourse approach highlighted by expert interviews with healthcare specialists, we identified the status quo of interdisciplinary research in academia on ethical considerations and dimensions of AI in hospitals. We found 15 fundamental manuscripts by constructing a citation network for the ethical discourse, and we extracted actionable principles and their relationships. We provide an agenda to guide academia, framed under the principles of biomedical ethics. We provide an understanding of the current ethical discourse of AI in clinical environments, identify where further research is pressingly needed, and discuss additional research questions that should be addressed. We also guide practitioners to acknowledge AI-related benefits in hospitals and to understand the related ethical concerns.</jats:p>


Ausgestaltungs- und Anwendungspotenziale von Virtual und Augmented Reality Technologien im Kontext von Coworking Spaces

M. Mirbabaie, L. Hofeditz, L. Schmid, HMD Praxis der Wirtschaftsinformatik (2021)

<jats:title>Zusammenfassung</jats:title><jats:p>Coworking Spaces (CSPs) sind geteilte Arbeitsplätze für Selbstständige, Freelancer*innen, Mikrounternehmen und Startups, die Isolation entgegenwirken und zum interdisziplinären Wissensaustausch anregen können. Jedoch existieren auch Barrieren, die Nutzer*innen davon abhalten, zu anderen Coworker*innen Kontakt aufzunehmen, da oft unklar ist, wann und ob jemand zum kreativen Austausch oder zum Anbieten von Hilfe bereit ist. Durch die Covid-19 Pandemie wurde die Unsicherheit bei der gegenseitigen Kontaktaufnahme noch weiter erschwert und viele CSPs mussten zeitweise schließen. Um Barrieren bei der Kontaktaufnahme zu reduzieren und die interdisziplinäre Zusammenarbeit zu fördern, können Informations- und Kommunikationstechnologien eingesetzt werden. Virtual Reality (VR) und Augmented Reality (AR) sind Technologien, die sich durch einen besonders hohen Grad an Immersion und sozialer Präsenz auszeichnen. Deshalb zeigen wir in diesem Beitrag, wie VR- und AR-Technologien gezielt eingesetzt werden können, um den interdisziplinären Wissensaustausch und Zusammenarbeit sowohl in CSPs als auch ortsunabhängig zu fördern. Dazu präsentieren wir positive Effekte, die durch den Einsatz einer der beiden Technologien im Zusammenhang mit CSPs erzielt werden können und leiten konkrete Gestaltungsempfehlungen für Anwendungsentwickler*innen, Unternehmen sowie Betreiber*innen von CSPs ab. Diese Gestaltungsempfehlungen basieren sowohl auf den neuesten Erkenntnissen aus der Fachliteratur als auch auf Interviews mit Expert*innen aus Forschung und Praxis mit Erfahrung im Bereich CSPs, VR und AR. Unsere Anwendungsszenarien können Entwickler*innen, Unternehmen und Betreiber*innen von CSPs als Grundlage dienen, vom Einsatz beider Technologien zu profitieren.</jats:p>




Banks’ tax disclosure, financial secrecy, and tax haven heterogeneity

E. Eberhartinger, R. Speitmann, C. Sureth-Sloane, WU International Taxation Research Paper Series No. #2020-01, 2021


Can Tax Rate Changes Accelerate Investment under Entry and Exit Flexibility? – Insights from an Economic Experiment

R. Fahr, E.A. Janssen, C. Sureth-Sloane, FinanzArchiv / Public Finance Analysis (2021)(Special Issue Behavioral Taxation)



Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach

J. Prester, G. Wagner, G. Schryen, N.R. Hassan, Decision Support Systems (2021), 140, pp. 113432

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.


COVID-19 reporting and willingness to pay for leisure activities

S. Warkulat, S. Krull, R. Ortmann, N. Klocke, M. Pelster, Covid Economics (2021)(83), pp. 183-205

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.


CYWARN: Strategy and Technology Development for Cross-Platform Cyber Situational Awareness and Actor-Specific Cyber Threat Communication

M. Kaufhold, T. Riebe, P. Kühn, M. Bayer, C. Reuter, M. Stöttinger, R. Möller, M. Mirbabaie, J. Fromm, A. Basyurt, S. Stieglitz, K. Eyilmez, C. Fuchß, in: Proceedings of the 8th Mensch und Computer, 2021


Dark triad managerial personality and financial reporting manipulation

M. Mutschmann, T. Hasso, M. Pelster, Journal of Business Ethics (2021)

DOI


Der Einfluss der Besteuerung auf Managementanreize und die Nutzung von Bonusbanken

D. Dyck, Junior Management Science (2021), 6(3), pp. 100-148

Diese Studie untersucht, wie Steuern und steuerlichen Regelungen die Nutzung eines Managementanreizsystems, bekannt als Bonusbank, aus Unternehmenseignersicht beeinflussen. Bonusbanken haben eine spezifische Eigenschaft: ein Teil des von einem Manager in einem Jahr verdienten Bonus wird einbehalten und nachträglich nur bei Erreichung zukünftiger Unternehmensziele ausgezahlt. Während in der bisherigen Literatur zu Bonusbanken Steuern vernachlässigt oder Manageranreize als gegeben angenommen wurden, integriere ich beide Aspekte in ein mehrperiodiges Agency-Modell mit risikoneutralem, haftungsbeschränktem Agenten. Das Modell erfasst insbesondere Ertragsteuern und Verlustverrechnungsbeschränkungen auf Unternehmensebene sowie eine proportionale, periodenabhängige Einkommensteuer beim Manager. Die Ergebnisse zeigen zweierlei: Erstens sinkt die Bonusbanknutzung gegenüber dem Fixlohnvertrag durch alle untersuchten Steuern und Regelungen mit Ausnahme der Verrechnungsbeschränkungen. Zweitens besitzt die Bonusbank einen glättenden Einkommenseffekt, der die Endvermögensreduktion aus den Verrechnungsbeschränkungen und der Einkommensteuerprogression abschwächt. Insgesamt ergänzen die Resultate das Schrifttum zur Entscheidungsrelevanz von Steuern bei der Gestaltung von Vergütungsverträgen.




Digital Facilitation Assistance for Collaborative, Creative Design Processes

E. Bittner, M. Mirbabaie, S. Morana, in: 54th Hawaii International Conference System Sciences, 2021


Digital Nudging in Social Media Disaster Communication

M. Mirbabaie, C. Ehnis, S. Stieglitz, D. Bunker, T. Rose, Information Systems Frontiers (2021)



Digitale Prozessintegration in berufs- und wirtschaftspädagogischen Studiengängen – Überlegungen zur Professionalität und professionellen Entwicklung

T. Jenert, H. Kremer, bwp@ Berufs- und Wirtschaftspädagogik – online (2021), 40, pp. 1-24


Do Smart Product Service Systems Crowd Out Interactions in Online Communities? – Empirical Evidence from a Cooking Community

J. Seutter, M. Müller, J. Neumann, D. Kundisch. Do Smart Product Service Systems Crowd Out Interactions in Online Communities? – Empirical Evidence from a Cooking Community. 2021.


Do you trust an AI-Journalist? A Credibility Analysis of News Content with AI-Authorship

L. Hofeditz, M. Mirbabaie, J. Holstein, S. Stieglitz, in: 29th European Conference on Information Systems, 2021


Drei Strategien zur Etablierung digitaler Plattformen in der Industrie

H. Lüttenberg, D. Beverungen, M. Poniatowski, D. Kundisch, N. Wünderlich, Wirtschaftsinformatik & Management (2021), 13(2), pp. 120-131


Driving Digital Transformation During a Pandemic: Study of Virtual Collaboration in a German Hospital

M. Mirbabaie, S. Stieglitz, N. Frick, H. Möllmann, Journal of Medical Internet Research Medical Informatics (2021)


Dynamics of convergence behaviour in social media crisis communication – a complexity perspective

M. Mirbabaie, S. Stieglitz, F. Brünker, Information Technology & People (2021)

DOI


Dynamics of Convergence Behaviour in Social Media Crisis Communication – A Complexity Perspective on Peoples’ Behaviour

M. Mirbabaie, S. Stieglitz, F. Brünker, Information Technology & People (2021)


Educational Assimilation of First-Generation and Second-Generation Immigrants in Germany

T. Gries, M. Redlin, M. Zehra, Journal of International Migration and Integration (2021)

<jats:title>Abstract</jats:title><jats:p>Using data from the German Socio-Economic Panel for 1984–2018, we analyze the intergenerational education mobility of immigrants in Germany by identifying the determinants of differences in educational stocks for first- and second-generation immigrants in comparison to individuals without a migration background. Our results show that on average, first-generation immigrants have fewer years of schooling than native-born Germans and have a disproportionate share of lower educational qualifications. This gap is strongly driven by age at immigration, with immigration age and education revealing a nonlinear relationship. While the gap is relatively small among individuals who migrate at a young age, integrating in the school system at secondary school age leads to large disadvantages. Examining the educational mobility of immigrants in Germany, we identify an inter-generational catch-up in education. The gap in education between immigrants and natives is reduced for the second generation. Finally, we find that country of origin differences can account for much of the education gap. While immigrants with an ethnic background closer to the German language and culture show the best education outcomes, immigrants from Turkey, Italy, and other southern European countries and especially the group of war refugees from Syria, Afghanistan, Iraq and other MENA countries, have the lowest educational attainment.</jats:p>


Eine ökonomische Einordnung des öffentlichen Country-by-Country Reporting in der EU

T. Hoppe, J. Müller, A. Weinrich, K. Wittek, IStR - internationales Steuerrecht (2021), pp. 925-932



Ethical Management of Artificial Intelligence

A. Brendel, M. Mirbabaie, T. Lembcke, L. Hofeditz, Sustainability (2021)


Exploring the Scientific Impact of Information Systems Design Science Research

G. Wagner, J. Prester, G. Schryen, Communications of the Association for Information Systems (2021), 48(1), 37


Forschung und Entwicklung: Kriterien für die Aktivierung in der Unternehmenspraxis

M. Blankenfeldt, J. Müller, A. Weinrich, in: Intangibles - Immaterielle Werte, 2nd ed., C.H.Beck, 2021


Gesellschaftliche Transformationen durch die Steigerung (popmusik)kultureller Teil-habe mittels innovativer Preiskonzepte – ein interdisziplinärer Literaturüberblick

S.J.M. Müller, D. Kundisch. Gesellschaftliche Transformationen durch die Steigerung (popmusik)kultureller Teil-habe mittels innovativer Preiskonzepte – ein interdisziplinärer Literaturüberblick. 2021.


How Does Trust Affect Concessionary Behavior in Tax Bargaining?

E. Eberhartinger, R. Speitmann, C. Sureth-Sloane, Y. Wu, FinanzArchiv / Public Finance Analysis (2021)(Special Issue Behavioral Taxation)


Hybrid Intelligence in Hospitals: Towards a Research Agenda for Collaboration and Team-Building

M. Mirbabaie, S. Stieglitz, N. Frick, Electronic Markets (2021)




Is Consistency the Panacea? Inconsistent or Consistent Tax Transfer Prices with Strategic Taxpayer and Tax Authority Behavior

M. Diller, J. Lorenz, G. Schneider, C. Sureth-Sloane, TRR 266 Accounting for Transparency Working Paper Series No. 57, 2021


Is Making Mistakes Human? On the Perception of Typing Errors in Chatbot Communication

J. Bührke, A. Brendel, S. Lichtenberg, M. Greve, M. Mirbabaie, in: 54th Hawaii International Conference System Sciences, 2021


Managerial personality traits and selective hedging

M. Pelster, A. Hofmann, N. Klocke, S. Warkulat, Journal of Business Ethics (2021)

We study the relationship between risk managers' dark triad personality traits (Machiavellianism, narcissism, and psychopathy) and their selective hedging activities. Using a primary survey of 412 professional risk managers, we find that managers with dark personality traits are more likely to engage in selective hedging than those without. This effect is particularly pronounced for older, male, and less experienced risk managers. The effect is also stronger in smaller firms, less centralized risk management departments, and family-owned firms.


Maneuvering through the stormy seas of digital transformation: the impact of empowering leadership on the AI readiness of enterprises

N.R.J. Frick, M. Mirbabaie, S. Stieglitz, J. Salomon, Journal of Decision Systems (2021), pp. 1-24

DOI



Moment or Movement – An Empirical Analysis of the Heterogeneous Impact of Media Attention on Charitable Crowdfunding Campaigns

M. Müller, J. Seutter, S.J.M. Müller, D. Kundisch, in: Proceedings of the 42nd International Conference on Information Systems (ICIS), 2021


Nudging Their Thoughts – Analyzing the Impact of Online Review Templates on Review Sentiment

M. Poniatowski, J. Neumann, D. Kundisch, in: Proceedings of the Conference on Information Systems and Technology (CIST), 2021




PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking Data

O. Müller, M. Caron, M. Döring, T. Heuwinkel, J. Baumeister, in: 8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021), 2021

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.


Projekt Art-D Grids: Nachhaltige und stabile Microgrids in Afrika - eine Plattform für Forschung und Lehre für die Entwicklung

S. Krauter, J. Boecker, C. Freitag, B. Hehenkamp, U. Hilleringmann, K. Temmen, T. Klaus, N. Rohrer, S. Lehmann, in: Tagungsband des 36. PV-Symposiums, 18.-26 Mai 2021, Conexio, 2021, pp. 305-309



Risk allocation through securitization - Evidence from non-performing loans

B. Hippert, A. Uhde, S.T. Wengerek, 2021

Employing a unique and hand-collected dataset of securitization transactions by European banks, this paper analyzes the relationship between true sale loan securitization and the issuing banks’ non-performing loans to total assets ratios (NPLRs). We provide evidence for an NPLR-reducing effect during the boom phase of securitizations suggesting that banks (partly) securitized NPLs as the most risky junior tranche. In contrast, we find the reverse effect during the crises period indicating that issuing banks demonstrated `skin in the game'. A variety of sensitivity analyses provides further important implications for the vital debate on reducing NPL exposures and regulating securitization markets.


Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall

S. Letmathe, Y. Feng, A. Uhde, 2021

In this paper new semiparametric GARCH models with long memory are in- troduced. The estimation of the nonparametric scale function is carried out by an adapted version of the SEMIFAR algorithm (Beran et al., 2002). Recurring on the revised recommendations by the Basel Committee to measure market risk in the banks' trading books (Basel Committee on Banking Supervision, 2013), the semi- parametric GARCH models are applied to obtain rolling one-step ahead forecasts for the Value at Risk (VaR) and Expected Shortfall (ES) for market risk assets. In addition, standard regulatory traffic light tests (Basel Committee on Banking Supervision, 1996) and a newly introduced traffic light test for the ES are carried out for all models. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long memory GARCH models are an attractive alternative to their conventional, parametric counterparts.


Share Price Reactions to Tariff Imposition Announcements in the Trump Era – an Event Study of the Trade Conflict

S.T. Wengerek, A. Uhde, 2021

Employing a unique sample of 2,849 tariff imposition announcements by and against the United States (U.S.) over the period from 2018 to 2019, this study analyzes the impact of recent tariff announcements on share prices from 859 U.S. companies. We provide evidence for negative (cumulative) average abnormal stock returns due to tariff announcements during a symmetric three-day event window. We suggest that stock market investors expect adverse impacts of tariff impositions, e.g. a decrease in the companies’ future cash flows and a threat of retaliation. The negative wealth effects are observed irrespective of whether the Trump administration announces safeguard tariffs to protect domestic firms or a retaliation is declared by foreign countries. Moreover, building several subsamples, we find that the adverse impact is mostly driven by announcements involving China and is associated with a variety of sector, tariff, trade and firm characteristics.



Social Media Analytics and Corporate Crises - A Case Study of Boeing's 737 Max Crashes

J. Marx, M. Mirbabaie, C. Czonstke, S. Stieglitz, in: 29th European Conference on Information Systems, 2021


Socio-legal systems and implementation of the Nash solution in Debreu–Hurwicz equilibrium

C. Haake, W. Trockel, Review of Economic Design (2021)

<jats:title>Abstract</jats:title><jats:p>In this article we combine Debreu’s (Proc Natl Acad Sci 38(10):886–893, 1952) social system with Hurwicz’s (Econ Design 1(1):1–14, 1994; Am Econ Rev 98(3):577–585, 2008) ideas of embedding a “desired” game form into a “natural” game form that includes all feasible behavior, even if it is “illegal” according to the desired form. For the resulting socio-legal system we extend Debreu’s concepts of a social system and its social equilibria to a socio-legal system with its Debreu–Hurwicz equilibria. We build on a more general version of social equilibrium due to Shafer and Sonnenschein (J Math Econ 2(3):345–348, 1975) that also generalizes the dc-mechanism of Koray and Yildiz (J Econ Theory 176:479–502, 2018) which relates implementation via mechanisms with implementation via rights structures as introduced by Sertel (Designing rights: invisible hand theorems, covering and membership. Tech. rep. Mimeo, Bogazici University, 2001). In the second part we apply and illustrate these new concepts via an application in the narrow welfarist framework of two person cooperative bargaining. There we provide in a socio-legal system based on Nash’s demand game an implementation of the Nash bargaining solution in Debreu–Hurwicz equilibrium.</jats:p>


Studierende der Berufs-und Wirtschaftspädagogik: (Un-)bekannte Wesen?

J. Grunau, T. Jenert, bwpat Spezial (2021), 18, pp. 1-6


Study on Sensitivity of Electric Bus Systems under Simultaneous Optimization of Charging Infrastructure and Vehicle Schedules

M. Stumpe, D. Rößler, G. Schryen, N. Kliewer, EURO Journal on Transportation and Logistics (2021)



Tax avoidance through securitization

A. Uhde, The Quarterly Review of Economics and Finance (2021), 79, pp. 411-421

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.


Teaching the Smart Home - User Experience in an Interactive Learning Phase

L.N. Sieger, A. Doğangün, M. Mirbabaie, in: Proceedings of the 8th Mensch und Computer, 2021


The Agony of Finding the Right Pricing Policy for Cultural Institutions: Addressing Economic Viability and Cultural Participation through Innovative Pricing

S.J.M. Müller, A. Buchholz, B. Flath, D. Kundisch, M. Momen Pour Tafreshi. The Agony of Finding the Right Pricing Policy for Cultural Institutions: Addressing Economic Viability and Cultural Participation through Innovative Pricing. 2021.


The Development of Connective Action during Social Movements on Social Media

M. Mirbabaie, F. Brünker, M. Wischnewski, J. Meinert, ACM Transactions on Social Computing (2021)


The Epidemiology of Tax Avoidance Narratives

J. Lorenz, M. Diller, C. Sureth-Sloane, TRR 266 Accounting for Transparency Working Paper Series No. 59, 2021

This study investigates the contagious nature of tax avoidance by examining how narratives affect tax avoiding behavior. We adapt the idea of narrative economics indicating that individuals' actions are stimulated by stories that spread within a society. We employ two types of infection models to theoretically investigate how tax avoidance schemes spread over time and vanish eventually consistent with patterns known from epidemiology. We find that general tax avoidance can persist even if its expected outcome is negative, while specific tax avoidance schemes might vanish even though their expected outcome is positive. We find empirical support for the predicted dissemination of narratives related to both general and specific tax avoidance schemes in google n-grams. Finally, we show that dissemination of specific tax avoidance schemes is attenuated by anti-narratives in (social) media. Our findings help to understand how tax avoidance spreads, under what conditions anti-avoidance measures can effectively curb tax avoidance and point towards the crucial role of transparency of enhanced enforcement by visible narratives.



The Power and Peril of Precise vs. Round Health Message Interventions to Increase Stair-Use

S. Krull, D.D. Loschelder, L. Boecker, Frontiers in Psychology (2021)

DOI


The relationship between talent management and individual and organizational performance

B. Krebs, M.C. Wehner, in: The Routledge companion to talent management, Routledge, 2021, pp. 539-555


The Role of Parasocial Interactions for Podcast Backchannel Response

J. Marx, M. Mirbabaie, A. Brendel, K. Zander, in: The Americas Conference on Information Systems, 2021


The Tax Complexity Index – A Survey-Based Country Measure of Tax Code and Framework Complexity

T. Hoppe, D. Schanz, S. Sturm, C. Sureth-Sloane, European Accounting Review (2021), pp. 1-35

DOI



To the Moon! Analyzing the Community of “Degenerates” Engaged in the Surge of the GME Stock

M. Caron, M. Gulenko, O. Müller, in: 42nd International Conference on Information Systems (ICIS 2021), 2021

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.


Toss a Coin to Your Host? – Why Guests Do Not Always End Up Paying for the Cost of Regulatory Policies

M. Müller, J. Neumann, D. Kundisch, in: Proceedings of the Conference on Information Systems and Technology (CIST), 2021


Toward Understanding the Complexity of Business Models – A Taxonomy of Business Model Dependencies

C. Vorbohle, D. Szopinski, D. Kundisch, in: Proceedings of the 29th European Conference on Information Systems (ECIS), 2021


Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning

J. Kirchhoff, S.C. Burmeister, C. Weskamp, G. Engels, in: Energy Informatics and Electro Mobility ICT, 2021

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.


Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems

C. Vorbohle, S. Gottschalk, in: Proceedings of the 29th European Conference on Information Systems (ECIS), AIS, 2021

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.


Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers

D. Beverungen, D. Kundisch, N. Wünderlich, Journal of Service Management (2021), 32(4), pp. 507-532


Transitioning to Condition-Based Maintenance on the Distribution Grid: Deriving Design Principles from a Qualitative Study

P. zur Heiden, J. Priefer, in: Pre-Conference 16th International Congress on Wirtschaftsinformatik at Universität Duisburg-Essen, BIS-Verlag der Carl von Ossietzky Universität Oldenburg, 2021


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