Networking For Innovation

Olav Sorenson from Yale published a new NBER working paper called “Innovation Policy in a Networked World”. The essay is quite interesting because it reviews insights we got from social network theory (no, not Facebook, although you could analyze Facebook with the same tools) and puts them into context for designing effective policy measures to stimulate innovation.

The key idea is that many valuable resources, such as money, influence or ideas, are not freely available to every individual or organization, but are instead distributed via social networks such as this one:

Source: Sorenson (2017), NBER Working Paper 23431

In this example, ideas might flow freely and efficiently between Gina, David, Emily, and Fred because they are all well-connected (these connections could be mutual friendships or business relationships). But for Chris it might be very hard to benefit from Emily’s ideas, simply because they are so far apart in the network.

Sorenson makes a good case for the importance of  networks and combining new ideas in science and technology:

“The solving of the structure of DNA contains examples of many of the ways in which social relationships shape the process of innovation. It required the combination of ideas from a range of fields, from biology to mathematics and physics. Watson gained early access to the crystallography, a crucial piece of information, because he had met Wilkens at a conference and remained in contact with him. Crick and Watson, the most central individuals involved, moreover, have received most of the credit for the discovery, despite the near simultaneous determination of the structure of DNA by others and despite the involvement of Franklin and Wilkens. Social relationships played a role in determining both who first arrived at the discovery and who received attention for it.”

You could think of Crick and Watson as being Beth and Chris in the network above. Wilkens might have been the boundary spanner, such as Alex, that connected them—more or less by chance—to a whole set of new ideas (crystallogrpahy) developed in a different scientific community.

Now, as I heard a social network scholar once say, networks and their influence on society are fascinating to study but they can be quite inefficient. In the end we might be better of if key resources were not allocated via them. Sorenson thus proposes two broad approaches for policy to mitigate network effects.

First, policy could try to steer the allocation of resources away from networks by creating more commons and open access. This would essentially reduce the importance of networks. One example from the scientific community is to require open access to research data which reduces entry barriers to certain fields for less connected researchers.

Second, policy could embrace the importance of social networks but try to increase the connectedness of members. This would be an attempt to manipulate individuals’ position within the network. One tool to achieve this goal—which is already used frequently in the EU—is to give out travel grants to researchers such that they can spend some time abroad to enlarge their network.

I enjoyed reading Sorenson’s essay a lot. He provides thought-provoking impulses for designing unconventional innovation policies with high impact. An added advantage is that these policies are often not very expensive to implement once you understand the power of social networks.

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