In order to promote the development of start-up ecosystems in Central Eurasia, we study the best practices of world industry leaders and follow the research carried out by leading centres. Startup Genome prepared the Global Startup Ecosystem Report (2018) to determine which factors affect the operation of startup ecosystems. One such indicator is startup density. Below we offer a brief of the article about startup density.
«One of the factors that we consider when creating our Global Startup Ecosystem Report is connectedness. Why does it matter how connected a startup ecosystem is? Because, as we have detailed, when founders have meaningful relationships with their peers, it is associated with greater levels of global market reach, startup growth, and overall ecosystem performance. Local Connectedness — especially relationships with other founders — is strongly associated with higher startup performance. Just as importantly, not being locally connected is strongly associated with lower startup performance.
Using Survey Data to Determine Local Connectedness
To create the Local Connectedness metric, we have historically gathered qualitative insights from over 10,000 founders and startup executives through direct surveys. We ask how many times they have met with founders in their ecosystem in the last two weeks, and use this data to create a score for Local Connectedness.
However, we were curious whether we could make a proxy for this metric using secondary data sources. Could Local Connectedness as we calculate it from survey data be correlated with how startup clusters are connected? Could the physical density of startup clusters reveal parallels?
To evaluate density, we took the registered addresses of startups in a selected group of cities. We mapped them using Google location API to determine the latitude and longitude, and then used closeness centrality to calculate a number for the closeness of points. A measure of centrality in a network, closeness centrality calculated as the average of the shortest path length from the node to every other node in the network. The more central a node is, the closer it is to all other nodes. Our thinking was that this number would show how closely connected the startup clusters are to one another. We did this experiment using cities that we have established relationships with from our years of data gathering. As such, we were confident that we could accurately measure the correlation between the new metric and our primary data.
Can Density Be Used as a Proxy for Local Connectedness?
So what was the outcome? There is a considerable correlation between the two metrics. Cities with high startup cluster density also show a high level of Local Connectedness based on survey data. We see that Singapore, Seoul, and Kuala Lumpur match the trend as highly connected startup ecosystems. However, an example that doesn’t correlate is Seoul, which shows a higher level of connectedness from our survey than from density calculation. In this case, our density calculation is higher. This is because human relations do not solely rely on how close the clusters are interconnected. Our model can be improved by adding things such as the openness and infrastructure. In conclusion, although we won't be able to replace our Local Connectedness with the density calculation, this is an additional insight into how startup ecosystems work».
Source: Startup Density as a Measure for Connectedness, Startup Genome Blog. Farshad Fahimi, on January 06, 2022