Finding the Next Unicorn: When Big Data Meets Venture Capital

dc.contributor.authorWeibl, Johannes
dc.contributor.authorHess, Thomas
dc.date.accessioned2019-01-02T23:48:45Z
dc.date.available2019-01-02T23:48:45Z
dc.date.issued2019-01-08
dc.description.abstractVenture capital (VC) has been growing rapidly in recent years. So far the screening and evaluation of potential startups as investment objects largely depends on the venture capitalist’s personal experience, network and qualitative evaluations. In the era of big data, the advent of new data sources and analytic techniques enables a data-driven investment process. Grounded in systems theory and the theory of complementarity, this study reports the findings from an exploratory study of 13 VC firms that synthesize and use novel data sources. Our analysis shows that the data-driven approach, in particular, impacts the deal origination and screening stages of investment. It leads to informational and transactional benefits, which lower operational costs in the short term and enlarge the potential return on investment of a VC firm in the long term. We contribute to the literature by shedding light on how various data sources complementarily lead to additional business value.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.132
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59547
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBig Data and Analytics: Pathways to Maturity
dc.subjectDecision Analytics, Mobile Services, and Service Science
dc.subjectVenture Capital, Big Data, Systems Theory, Business Value
dc.titleFinding the Next Unicorn: When Big Data Meets Venture Capital
dc.typeConference Paper
dc.type.dcmiText

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