Startups often represent newly established business models associated with disruptive
innovation and high scalability. They are commonly regarded as powerful engines for …

We use administrative textual and non-textual data retrieved from publicly available archives
to predict the performance of Danish startups at the time of foundation. The performance …

This paper addresses the growing application of data-driven approaches within the Private
Equity (PE) industry, particularly in sourcing investment targets (ie, companies) for Venture …

Do institutional investors invest efficiently? To study this question I combine a novel dataset
of over 16,000 startups (representing over $9 billion in investments) with machine learning …

In this study, we investigate a heterogeneous set of startup ventures (different ages,
products, teams, levels of maturity, etc.) to identify the time-independent factors associated …

I conduct an investment screening performance benchmarking between 111 venture capital
(VC) investment professionals and a supervised gradient boosted tree (or “XGBoost”) …

Deal sourcing in the venture capital (VC) investment process is labour-intensive and prone
to bias. VC investors need to skim through thousands of startups every year to cherry-pick …

Venture capital investors are constantly exposed to high levels of risk in investment
scenarios. To lower that risks, various decision support tools can be exploited, such as …

Startups represent newly established business models associated with disruptive innovation
and high scalability, hence strongly propel the economic and social development …

An extensive examination of how artificial intelligence (AI) is changing the venture capital
and startup scene can be found in “Tech Unleashed: The Influential Power of Artificial …