Research projects and publications

Research areas and projects

Involving crowds and crowdsourcing in science

Within this research area, we explore and test the potential (benefits and costs) of involving crowds (e.g., members of the public or specific stakeholder groups such as patients in medical research) at different stages of the scientific research process and with different levels of engagement (i.e., from contributory to co-created projects). Completed and ongoing research projects relate to

  • Developing a framework for understanding the complementary contributions of crowds, scientists and artificial intelligence in the scientific knowledge production process
  • Testing the crowd’s complementary knowledge contributions to generating research questions and related facilitation mechanisms
  • Investigating the role of crowds in generating and evaluating scientific research questions and proposals
  • Investigating when, how and under which conditions co-creation between crowds of non-professional scientists and professional scientists affects productivity and impact of scientific research
  • Analyzing the drivers of continued and recurrent participation of citizens in crowd science projects
  • Investigating the role of crowdsourcing for initiating collaborations between science and industry

Organizational design for openness and collaboration in science

Within this research area, we investigate the effects of organizational design on the implementation of different open and collaborative research practices in scientific research institutions, with a view to identifying the relationships between organizational-level factors and scientists’ behavior and determining relevant contingency factors. Completed and ongoing research projects relate to

  • Conceptualizing organizational design for openness and collaboration in science
  • Exploring relevant organizational design factors that support or block the implementation of open and collaborative research practices in scientific research institutions
  • Understanding the role of autonomy vs. control in organizational design for open and collaborative knowledge production in science
  • Investigating how organizational design triggers legitimacy building towards open and collaborative research
  • Exploring the complementary role of digital infrastructures for facilitating university-industry collaborations

Micro-foundations of openness and collaboration in science

Within this research area, we study how individual-level factors influence scientists’ and non-scientists’ willingness and ability to engage in open and collaborative research, analyze how processes and outcomes of scientific knowledge production are affected by individual-level determinants and test interventions for facilitating inter- and transdisciplinary collaborations in scientific knowledge production. Completed and ongoing research projects relate to

  • Identifying individual-level determinants of effectively co-producing scientific knowledge
  • Investigating how the values of scientists affect their willingness to engage in external knowledge sourcing
  • Exploring how scientists capture value from scientific knowledge dissemination
  • Studying the preferences of innovators related to engaging with scientific knowledge
  • Understanding the role and value of building capabilities for openness and collaboration in science
  • Testing interventions for facilitating collaborations between scientists and non-scientists
  • Exploring the drivers of data reuse in science

Effects and impact of openness and collaboration in science

Within this research area, we study how different forms of openness and collaboration affect the outcome of scientific knowledge production with respect to productivity and impact and investigate new forms of assessing the impact of scientific research. Completed and ongoing research projects relate to

  • Exploring the role of artificial intelligence for measuring the impact of scientific research
  • Developing and testing a new form of measuring the societal impact of scientific research by applying artificial intelligence-based semantic processing
  • Assessing the effects of open and collaborative practices to science on outcome and impact of scientific knowledge production

Publications

Crowdsourcing research questions in science

The paper shows that involving citizens more in the early stages of research studies could be key to generating new, innovative perspectives and promoting impactful research. More specifically, on average the crowdsourced questions are less novel and scientifically relevant, but the top 20% of research questions developed by citizens outperform those of experts on all dimensions.

Beck, S., Brasseur, T.M., Poetz, M. and Sauermann, H., 2022. Crowdsourcing research questions in science. Research Policy, 51(4), p.104491.

Special Issue on Open Innovation in Science

This special issue focuses on ‘Open Innovation in Science’ (OIS) as a novel concept that provides a unifying frame to study openness and collaboration in scientific research.

Special Issue on Open Innovation in Science (Eds: Susanne Beck, Christoph Grimpe, Marion Poetz and Henry Sauermann), 2022, published in Industry and Innovation, 29(2).

Crowds, citizens, and science: a multi-dimensional framework and agenda for future research.

This paper clarifies the relation between Crowd Science and Citizen Science, proposes a framework to profile CS projects, also accommodating machines and algorithms, and outlines a research agenda anchored on important underlying organizational challenges of CS projects.

Franzoni, C., Poetz, M., & Sauermann, H. 2022. Crowds, citizens, and science: a multi-dimensional framework and agenda for future research. Industry and Innovation, 29(2), 251-284

The Open Innovation in Science Research Field: A Collaborative Conceptualisation Approach.

In this paper, 47 authors collaboratively link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. The paper highlights both tensions and commonalities between existing approaches.

Beck, S., Bergenholtz, C., Bogers, M., Brasseur, T.-M., Conradsen, M. L., Di Marco, D., Distel, A. P. Dobusch, L., Dörler, D., Effert, A., Fecher, B., Filiou, D., Frederiksen, L., Gillier, T., Grimpe, C., Gruber, M., Haeussler, C., Heigl, F., Hoisl, K., Hyslop, K., Kokshagina, O., LaFlamme, M., Lawson, C., Lifshitz-Assaf, H., Lukas, W., Nordberg, M., Norn, M. T., Poetz, M. K., Ponti, M., Pruschak, G., Pujol Priego, L., Radziwon, A., Rafner, J., Romanova, G., Ruser, A., Sauermann, H., Shah, S. K., Sherson, J. F., Suess-Reyes, J., Tucci, C. L., Tuertscher, P., Vedel, J. B., Velden,T., Verganti, R., Wareham, J., Wiggins, A., and Xu, S. M. 2022. The Open Innovation in Science Research Field: A Collaborative Conceptualisation Approach. Industry and Innovation , 29(2), 136-185.

Open Access

Experimenting with Open Innovation in Science (OIS) practices: A novel approach to co-developing research proposals.

This paper summarizes and reflects on both the process and outcome of a novel experiment to co-develop scientific research proposals in the field of Open Innovation in Science (OIS), wherein scholars engaged in the study of open and collaborative practices collaborated with the “users” of their research, i.e., scientists who apply such practices in their own research. The resulting co-developed research proposals focus on scientific collaboration, open data, and knowledge sharing and are available as an appendix.

Beck, S., Bercovitz, J., Bergenholtz, C., Brasseur, T. M., D’Este, P., Dorn, A., Doser, M., Dosi, C., Effert, A., Furtuna, R., Goodyear, M., Grimpe, C., Hans, F., Haeussler, C., Heinisch, B., Katona, N., Kleinberger-Pierer, H., Kokshagina, O., LaFlamme, M., Lawson, L., Lehner, P., Lifshitz-Assaf, H., Lukas, W., Marchini, S., Mitterhauser, M., Moscato, F., Nordberg, M., Norn, M. T., Poetz, M., Ponti, M., Pruschak, G., Rafner, J. F., Romasanta, A. K., Ruser, A., Sameed, M., Sauermann, H., Suess-Reyes, J., Tucci, C. L., Tuertscher, P., Vicente Sáez, R., Vignoli, M., and Zyontz, S. 2021. Experimenting with Open Innovation in Science (OIS) practices: A novel approach to co-developing research proposals. CERN IdeaSquare Journal of Experimental Innovation, 5(2), 28-49.

Examining Open Innovation in Science (OIS): What Open Innovation can and cannot offer the science of science.

This paper seeks to clarify and refine the meaning and ambition of OIS and gives real-world examples of how OIS approaches in Denmark and the Netherlands are helping to rebalance priorities and lay the groundwork for future breakthroughs.

Beck, S., LaFlamme, M., Bergenholtz, C., Bogers, M., Brasseur, T.-M., Conradsen, M. L., Crowston, K., Di Marco, D., Effert, A., Filiou, D., Frederiksen, L., Gillier, T., Gruber, M., Haeussler, C., Hoisl, K., Kokshagina, O., Norn, M. T., Poetz, M. K., Pruschak, G., Pujol Priego, L., Radziwon, A., Ruser, A., Sauermann, H., Shah, S. K., Suess-Reyes, J., Tucci, C. L., Tuertscher, P., Vedel, J. B., Verganti, R., Wareham, J., Xu, S. M. 2021. Examining Open Innovation in Science (OIS): What Open Innovation can and cannot offer the science of science. Innovation (2021): 1-15.

Measuring the innovation impact of scientific research: exploring the potentials of artificial intelligence.

In this paper, we explore the potential of machine learning to assess how scientific publications inform practice guidelines and as such shape actual decision-making in society.

Distel, A., Grimpe, C., Körner, S., Landhäusser, M., and Poetz, M.K. 2021. Measuring the innovation impact of scientific research: exploring the potentials of artificial intelligence. Academy of Management Best Paper Proceedings.

The value of scientific knowledge dissemination for scientists – A value capture perspective

By taking a value capture perspective, this article conceptualizes and explores how individual scientists capture value from disseminating their knowledge.

Beck, S., Mahdad, M., Beukel K., Poetz, M. 2019. The value of scientific knowledge dissemination for scientists – A value capture perspective. Publications, 7(3), 1-23.