A5043636503- Corporate Governance and Management
- Digital Platforms and Economics
- Digital Innovation in Industries
- Business Strategy and Innovation
- Outsourcing and Supply Chain Management
- Business Process Modeling and Analysis
- Big Data and Business Intelligence
- Open Source Software Innovations
- Technology Adoption and User Behaviour
- Privacy, Security, and Data Protection
- Service-Oriented Architecture and Web Services
- Information Technology Governance and Strategy
- Digital Marketing and Social Media
- Flexible and Reconfigurable Manufacturing Systems
- ERP Systems Implementation and Impact
- Information and Cyber Security
- Innovation and Knowledge Management
- Digitalization, Law, and Regulation
- Advanced Database Systems and Queries
- Knowledge Management and Sharing
- Customer Service Quality and Loyalty
- Public Administration and Political Analysis
- Innovation, Technology, and Society
- Software Engineering Research
- Digital Rights Management and Security
Technical University of Darmstadt
2015-2024
Software (Germany)
2012-2024
University of St. Gallen
2015
University of Duisburg-Essen
2015
Augsburg University
2015
University of Augsburg
2015
University of Bayreuth
2015
Systems, Applications & Products in Data Processing (Germany)
2004-2013
Saarland University
2012
Goethe University Frankfurt
1997-2011
Research findings on how participation in social networking sites (SNSs) affects users’ subjective well-being are equivocal. Some studies suggest a positive impact of SNSs life satisfaction and mood, whereas others report undesirable consequences such as depressive symptoms anxiety. However, the factors behind effects have received significant scholarly attention, little is known about mechanisms that underlie unfavorable consequences. To fill this gap, study uses comparison theory responses...
From its earliest days, research in business and information systems engineering (BISE) has been dedicated to envisioning how technology will change the way we work live. Today, technological innovation happens at a faster pace reaches users more quickly than ever before. For example, while it took 75 years for telephone reach 100 million users, was 16 mobile phones, 7 World Wide Web, four half Facebook (Dreischmeier et al. 2015), only few weeks Pokemon GO (Moon 2016). The rapid...
With the rise of machine learning (ML), humans are no longer only ones capable and contributing to an organization’s stock knowledge. We study how organizations can coordinate human ML in order learn effectively as a whole. Based on series agent-based simulations, we find that, first, reduce demand for explorative that is aimed at uncovering new ideas; second, adjustments systems made by largely beneficial, but this effect diminish or even become harmful under certain conditions; third,...
With millions of users worldwide, online dating platforms strive to assert themselves as powerful tools find dates and form romantic relationships. However, significant differences exist in male female use this mate-matching technology with respect motivation, preferences, self-presentation, interaction outcomes. While existing research has routinely reported on gender dating, these insights remain scattered across multiple studies. To gain a systematic insight into findings, study we...
Background Recently, machine learning (ML) has been transforming our daily lives by enabling intelligent voice assistants, personalized support for purchase decisions, and efficient credit card fraud detection. In addition to its everyday applications, ML holds the potential improve medicine as well, especially with regard diagnostics in clinics. a world characterized population growth, demographic change, global COVID-19 pandemic, systems offer opportunity make more effective efficient,...
We propose a conceptual model of acceptance contact tracing apps based on the privacy calculus perspective. Moving beyond duality personal benefits and risks, we theorize that users hold social considerations (i.e., risks) underlie their decisions. To test our propositions, chose context COVID-19 conducted qualitative pre-study longitudinal quantitative main study with 589 participants from Germany Switzerland. Our findings confirm prominence individual in explaining intention to use actual...
Clinical decision support systems (CDSSs) based on machine learning (ML) hold great promise for improving medical care. Technically, such CDSSs are already feasible but physicians have been skeptical about their application. In particular, opacity is a major concern, as it may lead to overlook erroneous outputs from ML-based CDSSs, potentially causing serious consequences patients. Research explainable AI (XAI) offers methods with the potential increase explainability of black-box ML...