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$(14$ Marks

abstract provided below represents a summary of a recent study that presents a new data$-$driven framework a help investors be more effective in selecting companies with a higher probability of success.

Hacking the venture industry: An Early$-$stage Startups Investment framework for data$-$driven investors

Francesco Coraa, Giorga Bertinetii, Enrico Maria Cervallati $(2021)$

Abstract

Investing in eatly$-$stage companias is incredibly hard. especially when no data are available to support the decsion process. Venture capitaists often rely on gut feeling or heuristics to reach a decision, which is bisped and potentially harmful. This work proposes a new dala$-$driven framewark to nelo inwestors be more effective in selecting companies with a higher probability of success. We buill upon existing interdisciplirany research and augmented it wing further analysis on more than $600,000$ companies cher a $20-$year timeframe. The resulting tramewok is therefore a smart checkist of $21$ relevant features that may help investors to select the companes more ikehy to succeed.

Source: hitps iliww. sciencedirect.oamisciencelarticlelaiuS$2666827021000311$

Required tolthe entrepreneurial finanue literature?