Predicting success in the worldwide start-up network

@article{Bonaventura2020PredictingSI,
  title={Predicting success in the worldwide start-up network},
  author={Moreno Bonaventura and Valerio Ciotti and Pietro Panzarasa and Silvia Liverani and Lucas Lacasa and Vito Latora},
  journal={Scientific Reports},
  year={2020},
  volume={10}
}
By drawing on large-scale online data we are able to construct and analyze the time-varying worldwide network of professional relationships among start-ups. The nodes of this network represent companies, while the links model the flow of employees and the associated transfer of know-how across companies. We use network centrality measures to assess, at an early stage, the likelihood of the long-term positive economic performance of a start-up. We find that the start-up network has predictive… 
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References

SHOWING 1-10 OF 44 REFERENCES
Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences1
A recursive analysis of network and institutional evolution is offered to account for the decentralized structure of the commercial field of the life sciences. Four alternative logics of
The role of venture capital firms in Silicon Valley's complex innovation network
Abstract We still poorly understand why Silicon Valley has originated so many breakthrough innovations and large companies. The durability of Silicon Valley's innovative competence over the last
Embeddedness in the making of financial capital : How social relations and networks benefit firms seeking financing
I investigate how social embeddedness affects an organization’s acquisition and cost of financial capital in middle-market banking—a lucrative but understudied financial sector. Using existing theory
Liquidity Events and the Geographic Distribution of Entrepreneurial Activity
In this paper, we examine the ecological consequences of initial public offerings (IPOs) and acquisitions, specifically how the spatial distribution of these events influences the location-specific
Anatomy of funded research in science
TLDR
It is found that the leading universities form a cohesive clique among themselves and occupy brokerage positions between otherwise disconnected entities, and as the inequality in the distribution of funding grows over time, so does the degree of brokerage.
Quantifying and predicting success in show business
TLDR
The authors study the careers of actors and identify a "rich-get-richer" mechanism with respect to productivity, the emergence of hot streaks and the presence of gender bias, and are able to predict whether the most productive year of an actor is yet to come.
R&D Alliances and Firm Performance: The Impact of Technological Diversity and Alliance Organization on Innovation
In response to competitive pressures, firms increasingly use R&D alliances to complement in-house R&D efforts. However, empirical evidence to date provides little guidance on how firms can use this
On the Predictability of Future Impact in Science
TLDR
By applying a future impact model to 762 careers drawn from three disciplines: physics, biology, and mathematics, this work identifies a number of subtle, but critical, flaws in current models.
Quantifying reputation and success in art
TLDR
An extensive record of exhibition and auction data is used to study and model the career trajectory of individual artists relative to a network of galleries and museums, finding a lock-in effect among highly reputed artists who started their career in high-prestige institutions and a long struggle for access to elite institutions among those who start their career at the network periphery.
...
...