• PhD Information Systems, Technische Universität München
  • MSc Information Systems, Technische Universität München
  • BSc Computer Science, Technische Universität München

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.

Research & Teaching Interests

Riedl research interests are in crowdsourcing, open innovation, and network science. 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)