Entrepreneurship communities can follow very different paths. The most influential actors in a network can have a significant effect on an entire industry, including which companies become successful and how success is even defined. Network analysis can be a very useful tool in understanding these patterns and how they create different outcomes in different cities and industries.
Endeavor Insight has conducted network analyses of entrepreneurial communities around the world, including regions like Puerto Rico, New York, Cape Town, and a recent comparison of Bangalore and Nairobi. The findings of these studies all illustrate key principles of network science that have important policy implications for decision-makers in entrepreneurial communities.
- The number of connections in a network does not seem to be linked to productivity.
While high levels of connectivity, mentorship, and support among entrepreneurs may seem to be an indicator of a successful entrepreneurship community, it is really the quality of these connections and the patterns of influence that affect productivity.
This means that policies and entrepreneurship support programs focusing on building connections between entrepreneurs will not necessarily improve productivity. They may even have negative effects if inexperienced founders unknowingly share bad practices through these connections.
- “Like attracts like”: Network members tend to build relationships with people who share common characteristics.
In Bangalore, for example, there is a high concentration of “boomerang” founders who studied or worked abroad then returned to India to become entrepreneurs. They are more likely to connect with other “boomerangs” and attract more of them to the community as they become more influential. In Nairobi, there is a high concentration of expat entrepreneurs, who are in turn more likely to connect with other expat entrepreneurs.
This has important implications for entrepreneurship communities where certain groups are excluded for reasons unrelated to their performance as entrepreneurs, including gender and race. This principle may also determine the types of companies that become successful, as the next point shows.
- The most influential actors signify what entrepreneurial success looks like – for better or for worse.
When a group of players becomes influential in a network, their patterns and behavior become an implicit model of what success and status look like in the ecosystem. If the most influential actors are founders of companies at scale, other entrepreneurs are likely to aspire to do the same.
In Nairobi, many of the most influential actors have no entrepreneurial leadership experience but run entrepreneurship support programs that attract large amounts of international grant funding. In turn, local founders are more likely than others to rely on grant funding from large international foundations as a means to success and status.
- Influence is relative in networks.
The ability to change the behavior of 50 people means very different things depending on the size of the network and the number of people an organization can typically influence. In entrepreneurship networks, this means that when one actor becomes more influential, it decreases the relative influence of other actors.
For example, when the founders of a company at scale become active venture capital investors in Bangalore, it reduces the relative influence of local investment firms led by non-entrepreneurs. Similarly, if a foundation in Nairobi funds a program run by someone with no entrepreneurial experience, it decreases the relative influence of entrepreneurs at scale.
This means that entrepreneurship programs can never a neutral impact. Even initiatives with short-term outputs that seem positive may have negative long-term impacts if they elevate leaders who weaken the local entrepreneurship network.
- Hubs in entrepreneurship networks are persistent.
Once an entity becomes a major influencer, or hub, in a network, it will almost always remain very influential and may even become more so as the network grows. Due to the effects of like-attracts-like, even new influencers often take on the same traits as current influencers and end up looking very similar.
This has important policy implications. When decision makers elevate specific types of actors in an entrepreneurial community, these actors can remain influential even after those decision makers and their organizations are no longer involved.
Contributed by Maha AbdelAzim.