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Academic Conferences and Collaboration

Evidence that academic conferences facilitate subsequent collaborations between attendees

Published onJul 16, 2021
Academic Conferences and Collaboration
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As academic conferences were being cancelled (along with everything else) during the onset of the 2020 covid-19 pandemic, a common question on twitter was whether in-person conferences were really needed at all in the era of zoom and skype. People say there is more to conferences than simply the presentation of information; but is there? Let’s look at some recent studies on whether conferences facilitate academic collaboration.

Freeman, Ganguli, and Murciano-Goroff (2015) survey scientists in particle and field physics, nanoscience and nanotechnology, and biotechnology and applied microbiology, and ask how they met their collaborators. Among collaborators who do not live in the same city, about 15% say they met at conferences; the rest met as colleagues (most common answer), as advisor/advisees, or as visitors (or not at all, in some cases!).

From Freeman, Ganguli, and Murciano-Goroff (2015)

Alternatively, Chai and Freeman (2019) study 1,254 participants in Gordon Research conferences in the early 1990s. Participants in the conferences are matched to a set of “control” scientists who do not attend the conference. Compared to the controls, attendees with no prior collaboration produce about 9% more joint publications after attending the conference. These biology conferences are ideally designed to foster new relationships: they consist of small groups (80-150) working on the same topic, who spend a week together at a remote location engaging in both research and informal social activities. However, studies of more recent conferences have found a larger impact for more transient meetings.

Campos, Leon, and McQuillen (2018) look at the impact of the abrupt cancellation of the 2012 American Political Science Association annual meeting due to Hurricane Isaac. By comparing the extent of new collaboration among those scheduled but unable to attend to actual attendees of the conference in previous years and un-cancelled political science conventions in the same year, they can estimate the effect of cancellation on new collaboration. They estimate cancelling the conference reduced the probability potential attendees collaborate by 16%, with the effect strongest for potential collaborators who are not colocated.

Instead of comparing people who attend a conference to those that do not, you can also look within a conference and see if attendees who interact more often during the conference are more likely to collaborate on new projects. Two papers find that is also the case.

Zajdela et al. (2022) examine four recent conferences (around 60 attendees), that mixed large topic discussions of around 10 people with small group discussions of 3-4 people. Zajdela and coauthors estimate how much time people spent interacting at the conferences based on their joint assignment to different sessions (they assume you might have interacted more if the session was longer or if the number of attendees was smaller). At the end of the conference they can see if people spontaneously teamed up to submit a proposal for research funding. Do people who spent more time in the same sessions team up at a greater rate? Yes!

But that doesn’t tell us much unless we know how these groups were formed. Maybe the conference organizers tried to match people up who they thought were most likely to want to work together; and maybe these people would have identified each other no matter what, in a conference with just 60 attendees. In that case, time spent in sessions together doesn’t matter - these people would always have collaborated.

Fortunately, Zajdela and coauthors also know the algorithm which was used to assign people to small and large group sessions. The conferences tried to optimally place people together according to some seemingly desirable, but possibly conflicting, rules.1 Because this group assignment problem is very complex, the algorithm doesn’t exactly solve for the “best” outcome by these criteria. Instead, it just tries to get as close as it can, and there is a bit of randomness in where it ends up. Zajdela and coauthors re-run this algorithm a bunch of time to come up alternative conference schedules, each of which might well have been the actual schedule but for a bit of algorithmic luck. Then they look to see if collaboration is highly correlated with the actual time spent interacting, rather than the potential time interacting under alternative plausible conference schedules. And it is: among people who did not previously know each other, collaboration was about 9x more likely for pairs that actually attended a small group session together, as compared to pairs who did not attend a small group session together in the real world but would have in alternative possible conference schedules.

Finally, Boudreau et al. (2017) actually conduct an explicit field experiment with attendees of a research symposium to study the impact of very short in-person interactions on collaboration. To access a grant opportunity, Harvard Medical School researchers were required to attend a research symposium, where they learned about relevant research and participated in a 90-minute brainstorming session with other participants. These sessions occurred in physically separated rooms, and attendees were randomized into different rooms. Being in the same (randomly assigned) room increased the probability any two attendees submitted a joint grant proposal by 75% (from a very low base-rate). The intervention suggests very short in-person meetings can have a big impact on collaboration.

This group also tracked the attendees of this experimental conference for another six years to see the long-run fallout from these short randomized meetings. As discussed in more detail in this post, the long-run results vary according to the intellectual proximity of those who meet. For those whose work is very unrelated, meeting had essentially no impact on the probability of future collaboration; for those whose work is very similar, meeting actually had a negative impact on the probability of collaboration! But for those in the middle - those who plausibly had complementary knowledge - those who met in randomly assigned meetings were more likely to collaborate than those who did not.

So let’s go back to that original question: in the era of zoom and skype, are conferences really necessary? Well, it seems that people were right to insist there are more to conferences than the presentations: conferences do perform a useful networking role. As Campos, Leon, and McQuillen point out, they are particularly important for forming relationships with scientists who are not geographically close. That finding also gets some support from Freeman, Ganguli, and Murciano-Goroff, who find non-colocated authors met at conference 15% of the time, compared to 1% of the time for colocated ones.

That said - I don’t think these papers have shown its impossible to get these benefits with a virtual conference, so long as it permits networking. On the one hand, most agree that there’s something intangible about being there that really makes a difference in solidifying relationships. On the other hand, if a short 90 minute brainstorming session suffices to get people collaborating, maybe we’re overestimating the scale of the challenge. I imagine we’ll start to know more in the years ahead.

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Articles cited

Freeman, Richard B., Ina Ganguli, Raviv Murciano-Goroff. 2015. Why and Wherefore of Increased Scientific Collaboration. In The Changing Frontier: Rethinking Science and Innovation Policy, eds. Adam B. Jaffe and Benjamin F. Jones, pgs. 17-48. http://www.nber.org/chapters/c13040

Chai, Sen, Richard B. Freeman. 2019. Temporary colocation and collaborative discovery: Who confers at conferences. Strategic Management Journal 40(13): 2138-2164. https://doi.org/10.1002/smj.3062

Campos, Raquel, Fernanda Leon, Ben McQuillin. 2018. Lost in the Storm: The Academic Collaborations That Went Missing in Hurrican Issac. The Economic Journal 128(610): 995-1018. https://doi.org/10.1111/ecoj.12566

Zajdela, Emma R., Kimberly Huynh, Andy T. Wen, Andrew L. Feig, Richard J. Wiener, and Daniel M. Abrams. 2022. Catalyzing collaborations: Prescribed interactions at conferences determine team formation. arXiv 2112.08468. https://doi.org/10.48550/arXiv.2112.08468

Boudrea, Kevin J. Tom Brady, Ina Ganguli, Patrick Gaule, Eva Guinan, Anthony Hollenberg, and Karim R. Lakhani. 2017. A Field Experiment on Search Costs and the Formation of Scientific Collaborations. The Review of Economics and Statistics 99(4): 565-576. https://doi.org/10.1162/REST_a_00676

Lane, Jacqueline N., Ina Ganguli, Patrick Gaule, Eva Guinan, and Karim R. Lakhani. 2020. Engineering Serendipity: When does knowledge sharing lead to knowledge production? Strategic Management Journal: https://doi.org/10.1002/smj.3256

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