Table 2.

Reasons for mobilizing collective intelligence.

Issues with traditional research practice	How collective intelligence can address the issue
Research questions were becoming more complex, and the answers could not be found from a single discipline	Collective intelligence provided the opportunity to work with people with different types of expertise and integrate their skills to solve problems from different angles: Knowledge is distributed in different domains and some “wicked” questions cannot be answered within a single discipline or sector, ie, we need both different science disciplines as well as expertise from the practice and policy sector. (S75)
Current research was conducted inefficiently by “repeating efforts” (I06)	Collective intelligence allowed researchers to conduct research as collective efforts where different approaches to a research question could be collectively and thoroughly evaluated to avoid redundant efforts: In science, often we are developing solutions independently and we are kind of repeating erm…efforts, […] an alternative is to post a problem or a question to the research community and then just see what kind of solutions people come up with, and possibly combine these solutions and that you could call CI. (I06)
As research questions became more complex, conducting research required a longer time. Researchers would not have enough time to investigate different aspects. “It takes for hundreds of years…you will never [be able to] explore everything.” (I08)	With a large community contributing, researchers were able to finish work within shorter time scales: Draw on the experiences and expertise of a varied group of people to advance and implement ideas that would take a significantly longer time to solve as an individual. (S104)
It was more costly to work with experts in the field and took longer to engage them	Mobilizing contribution from a wide community was cheaper than working with experts in the field, yet the former could achieve the same outcomes: Our organization has done over 300 crowd-based challenges and has found success in 80-90% of those challenges with cost and schedule savings in the majority of them. (S49)