Selected Publications

  • Fraiberger, S., Sinatra, R., Resch, M., Riedl, C., Barabási, A.L. (2018). “Quantifying Reputation and Success in Art,” Science, 362(6416), 825-829.
  • Riedl, C., Seidel, V. (2018). “Learning from Mixed Signals in Online Innovation Communities,” Organization Science, 29(6), 1010-1032.
  • Riedl, C., et al. (2018). “Product Diffusion Through On-Demand Information-Seeking Behavior,” Journal of the Royal Society Interface, 15(139), 20170751.
  • Foley, M., Forber, P., Smead, R., Riedl, C. (2018). “Conflict and Convention in Dynamic Networks,” Journal of the Royal Society Interface, 15(140), 2017075.
  • Riedl, C., Woolley, A.W. (2017). “Teams vs. Crowds: A Field Test of the Relative Contribution of Incentives, Member Ability, and Emergent Collaboration to Crowd-Based Problem Solving Performance,” Academy of Management Discoveries, 3(4), 382-403.
  • Boudreau, K., Guinan, E., Lakhani, K., Riedl, C. (2016). “Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance and Resource Allocation in Science,” Management Science, 62(10), 2765-2783.
  • Blohm, I., Riedl, C., Füller, J., Leimeister, J. M. (2016). “Rate or Trade? Identifying Winning Ideas in Open Idea Sourcing,” Information Systems Research, 27(1), 27-48.

Selected Presentations

  • “Strategic Behavior in Contests with Ability Heterogeneous Agents: Evidence from Field Data,” NBER Summer Institute, Cambridge, MA, July 18th, 2019.
  • “Avoiding the Bullies: How High-Ability Agents Promote Cooperation in Social Networks”, NetSci Conference, Burlington, VT, May 27-31, 2019.
  • Invited talk “Strategic Behavior in Contests with Skill Heterogeneous”, “Agents: Evidence from Field Data,” Digital Innovation Workshop 2019, Boston College, Chestnut Hill, MA, May 3, 2019.
  • “Invited talk “Quantifying Reputation and Success in Art”, Yale University, New Haven, CT, 27th March 2019.


  • Ph.D. in Information Systems, Technische Universität München
  • M.Sc. in Information Systems, Technische Universität München
  • B.Sc. in Computer Science, Technische Universität München

Research & Teaching Interests

Professor Riedl research interests are in crowdsourcing, open innovation, and network science. Professor Riedl teaches courses on Digital Business Transformation, Business Analytics, and Network Economics.

Services to the Profession

  • Member Editorial Review Board for Academy of Management Discoveries.
  • Core faculty, Network Science Institute.
  • Core faculty, Center for Digital Humanities & Computational Social Science (NUlab)
  • Visiting Fellow, Institute for Quantitative Social Science (IQSS), Harvard University

Awards & Recognition

  • Best Paper Award of the Academy of Management Discoveries, finalist (2018)
  • Best Teacher Award (D’Amore-McKim School of Business, 2018)
  • Joseph G. Riesman Professorship (D’Amore-McKim School of Business, (2016-2018)
  • Copeland Best Paper Award (2017)