# Territorial Development as an Innovation Driver: A Complex Network Approach
## 4 Discussion  
The described approach to evaluate country performances in the StartupBlink rankings (one for each StartupBlink index) is based on community detection, an unsupervised and data-driven method that provides, in our case, stable and reasonable results, not biased by human judgment. Only objective socio-economic factors (WDIs) are used to set up the country network and determine the corresponding wealth communities. In particular, since WDIs cover multiple aspects of the social and economic performance of countries, it is not surprising that the network communities are characterized by different wealth classes but by an homogeneous wealth level therein. This result enables us to relate the wealth level of a country with the quality of its innovation ecosystem and, above all, establish which countries need specific support or can be considered as examples of best practices in the technological innovation policies. The reliability of these results also rests on the robustness of the community detection, as both Spin Glass and Leiden algorithms give the same results. We also tested classical clustering algorithms to partition the set of StartupBlink countries, finding that they are not suitable to this task for different reasons, which corroborates the need for a network model and the related tools. The use of network communities as a tool to evaluate country performances is validated by a quantitative control to confirm the existence of a relation between community membership and expected rating: the resolution ratio \(R\) quantifies the tendency of the ranked index distributions related to different network communities to be separated in a relevant way. The resolution ratio associated to the global StartupBlink index shows a good separation between communities, which allows us to compare a country's performance with the expectation based on its wealth conditions. Among the constituent indexes of StartupBlink, the only one associated with a value \(R>1\) is Business Environment, which measures the ease of conducting business in the considered territory. This result is related to the presence, among the WDIs, of indicators associated with bureaucracy, bank loans to the private sector and other aspects affecting the efficiency of firms. Instead, the quantity index, related to the number of assets in the innovation ecosystem, and the quality index, which evaluates the impact of startups, seem not to be affected in a significant way by a territorial drift effect. India and Brazil, belonging to the least-wealthly community III, exhibit relevant discrepancies between the value of these indexes and general wealth conditions: India's quantity index is larger than Canada, close to that of the United Kingdom, and larger than those of all states in Community II, indicating a very active innovation scene; Brazil, instead, in addition to a high quantity index, is also characterized by a quality index above all the ones in Community III and all but the highest 5 in Community II. The positive performance of India and Brazil with respect to the expectations is confirmed by the fact that they are labelled as top-of-the-class in both the global and the business index. Deepening the analysis of the outcomes, it can be seen that, unsurprisingly, the United States are a _benchmark_ country both from a global and an ease-of-business point of view. In fact, conditions offered by the United States startup ecosystem to both entrepreneurs and investors are excellent. The United States ecosystem mostly operates in the New York and San Francisco areas, with the technological center of the Silicon Valley representing a privileged choice to create products and initiatives that are appealing to the global market [65]. Much of the United Kingdom's strength in the global startup ecosystem comes from its startup hub, London.