A5061582145- Open Source Software Innovations
- Knowledge Management and Sharing
- Research Data Management Practices
- Mobile Crowdsensing and Crowdsourcing
- Flexible and Reconfigurable Manufacturing Systems
- Digital Platforms and Economics
- Scientific Computing and Data Management
- Technology Adoption and User Behaviour
- Digital Innovation in Industries
- Digital Transformation in Industry
- Expert finding and Q&A systems
- Innovation and Knowledge Management
- Innovation, Technology, and Society
- scientometrics and bibliometrics research
Ludwig Boltzmann Gesellschaft
2019-2022
Copenhagen Business School
2019-2022
Vienna University of Economics and Business
2017
University of Vienna
2017
Scientists are increasingly crossing the boundaries of professional system by involving general public (the crowd) directly in their research. However, this crowd involvement tends to be confined empirical work and it is not clear whether how crowds can also involved conceptual stages such as formulating questions that research trying address. Drawing on five different "paradigms" crowdsourcing related mechanisms, we first discuss potential merits formulation (RQs). We then analyze data from...
Tiare-Maria Brasseur - Lecturer, Department of e-Business, University ViennaAddress: 1, Oskar-Morgenstern-Platz, Vienna, 1090, AustriaE-mail: tiare.brasseur@gmail.comAndreas Mladenow andreas.mladenow@univie.ac.atChristine Strauss Professor, christine.strauss@univie.ac.at In today’s fast-paced business environment, firms are constantly pressured to innovate in order remain competitive. Business model innovation (BMI) has recently attracted increasing attention as a promising approach achieve...
Scholars across disciplines increasingly hear calls for more open and collaborative approaches to scientific research. The concept of Open Innovation in Science (OIS) provides a framework that integrates dispersed research efforts aiming understand the antecedents, contingencies, consequences applying practices. While OIS has already been taken up by science scholars, its conceptual underpinnings require further specification. In this essay, we critically examine bring light two key aspects:...
An increasing number of research projects successfully involve the general public (the crowd) in tasks such as collecting observational data or classifying images to answer scientists’ questions. Although crowd science have generated great hopes among scientists and policy makers, it is not clear whether can also meaningfully contribute other stages process, particular identification questions that should be studied. We first develop a conceptual framework ties different aspects “good” types...