Alle Publikationen der Fakultät für Wirtschaftswissenschaften

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.

Unternehmen investieren zunehmend in Angebote Betrieblicher Gesundheitsförderung (BGF). Dabei stellt sich die Frage nach dem Kosten-Nutzen-Verhältnis jenseits des individuellen Nutzens durch die Förderung der Mitarbeitergesundheit. Deshalb wurden im Rahmen einer Sekundäranalyse Effekte der BGF auf den Unternehmenserfolg berechnet. Die Ergebnisse lassen vermuten, dass sich eine verhaltensorientierte BGF kaum positiv auf die Arbeitsproduktivität und Kommunikationsstruktur in Unternehmen auswirkt.

This study investigates the conditions under which tax rate changes accelerate risky investments. While tax rate increases are often expected to harm investment, analytical studies find tax rate increases may foster investment under flexibility.We design a theorybased experimentwith a binomial random walk and entry–exit flexibility.We find accelerated investment upon tax rate increases irrespective of an exit option, but no corresponding response to tax cuts. This asymmetry may be due to tax salience and mechanisms from irreversible choice under uncertainty. Given this evidence of unexpected tax-reform effects, tax policymakers should carefully consider behavioral aspects.

<jats:title>Abstract</jats:title><jats:p>Non-pharmaceutical interventions are an effective strategy to prevent and control COVID-19 transmission in the community. However, the timing and stringency to which these measures have been implemented varied between countries and regions. The differences in stringency can only to a limited extent be explained by the number of infections and the prevailing vaccination strategies. Our study aims to shed more light on the lockdown strategies and to identify the determinants underlying the differences between countries on regional, economic, institutional, and political level. Based on daily panel data for 173 countries and the period from January 2020 to October 2021 we find significant regional differences in lockdown strategies. Further, more prosperous countries implemented milder restrictions but responded more quickly, while poorer countries introduced more stringent measures but had a longer response time. Finally, democratic regimes and stronger manifested institutions alleviated and slowed down the introduction of lockdown measures.</jats:p>

We study the bargaining behavior between auditor and auditee in a tax setting and scrutinize the effect of interpersonal trust and trust in government on both parties’ concessions. We find evidence that both kinds of trust affect the concessionary behavior, albeit in different ways. While trust in government affects concessionary behavior in line with intuitive predictions, we find that interpersonal trust only affects tax auditors. For high interpersonal trust, the alleviating effect of high trust in government on tax auditors’ concessions is less pronounced. Our findings help tax authorities to shape programs to enhance compliance in an atmosphere of trust.

<jats:title>Abstract</jats:title><jats:p>We provide a partial equilibrium model wherein AI provides abilities combined with human skills to provide an aggregate intermediate service good. We use the model to find that the extent of automation through AI will be greater if (a) the economy is relatively abundant in sophisticated programs and machine abilities compared to human skills; (b) the economy hosts a relatively large number of AI-providing firms and experts; and (c) the task-specific productivity of AI services is relatively high compared to the task-specific productivity of general labor and labor skills. We also illustrate that the contribution of AI to aggregate productive labor service depends not only on the amount of AI services available but on the endogenous number of automated tasks, the relative productivity of standard and IT-related labor, and the substitutability of tasks. These determinants also affect the income distribution between the two kinds of labor. We derive several empirical implications and identify possible future extensions.</jats:p>

Employing a unique and hand-collected sample of 648 true sale loan securitization transactions issued by 57 stock-listed banks across the EU-12 plus Switzerland over the period from 1997 to 2010, this paper empirically analyzes the relationship between true sale loan securitization and the issuing banks’ non-performing loans to total assets ratios. Overall, we provide evidence for a negative impact of securitization on NPL exposures suggesting that banks predominantly used securitization as an instrument of credit risk transfer and diversification. In addition, the analysis at hand reveals a time-sensitive relationship between securitization and NPL exposures. While we observe an even stronger NPL-reducing effect through securitization during the non-crisis periods, the effect reverses during and after the global financial crisis suggesting that banks were forced to provide credit enhancement and employ securitization as a funding management tool. Along with the results from a variety of sensitivity analyses our study provides important implications for the recent debate on reducing NPL exposures of European banks by revitalizing the European securitization market.

Regulations to prevent ethnic discrimination in accessing the labor market are implemented most thoroughly in the public sector. However, it remains to be assessed if these regulations are internalized. We conducted a field experiment to examine ethnic discrimination when applying for internships in German municipalities by unsolicited inquiries. We compared responses in German cities to Turkish, Italian, and German applicants in two periods, and find consistent disadvantages for the Turkish and Italian applicants as well as differences related to gender. Thus, the likelihood for ethnic discrimination rises when applying for positions in public institutions that are not subject to regulations.

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.

We analyse the two-dimensional Nash bargaining solution (NBS) by deploying the standard labour market negotiations model of McDonald and Solow (1981). We show that the two-dimensional bargaining problem can be decomposed into two one-dimensional problems, such that the two solutions together replicate the solution of the two-dimensional problem if the NBS is applied. The axiom of Independence of Irrelevant Alternatives is shown to be crucial for this type of decomposability. This result has significant implications for actual negotiations because it allows for the decomposition of a multi-dimensional bargaining problem into one-dimensional problems---and thus helps to facilitate real-world negotiations.

<jats:title>Abstract</jats:title> <jats:p>An individual’s relation to time may be an important driver of pro-environmental behaviour. We studied whether young individual’s gender and time-orientation are associated with pro-environmental behaviour. In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time-orientation. In this consequential behavioural setting, we find that males who scored higher on <jats:italic>future-negative</jats:italic> orientation showed significantly more pro-environmental behaviour compared to females who scored higher on <jats:italic>future-negative</jats:italic> orientation and males who scored lower on <jats:italic>future-negative</jats:italic> orientation. Interestingly, our results are completely reversed when it comes to <jats:italic>past-positive</jats:italic> orientation. These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.</jats:p>

<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>

<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>

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>

<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>

<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>

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.

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.

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.

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.

<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>