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  4. Publikationen School of Engineering
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-28226
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dc.contributor.authorTe, Yiea-Funk-
dc.contributor.authorWieland, Michèle-
dc.contributor.authorFrey, Martin-
dc.contributor.authorPyatigorskaya, Asya-
dc.contributor.authorSchiffer, Penny-
dc.contributor.authorGrabner, Helmut-
dc.date.accessioned2023-07-08T16:40:36Z-
dc.date.available2023-07-08T16:40:36Z-
dc.date.issued2023-
dc.identifier.issn2405-9188de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/28226-
dc.description.abstractStartups are a key force driving economic development, and the success of these high-risk ventures can bring huge profits to venture capital firms. The ability to predict the success of startups is a major advantage for investors to outperform their competitors. In this study, we explore the potential of using publicly available LinkedIn profiles as an alternative and complementary data source to Crunchbase for predicting startup success. We provide a comprehensive review of the existing literature on the factors that influence startup success to create a large set of features for predictive modeling. We train two models for predicting startup success employing light gradient boosting that use LinkedIn data as a standalone and as a complementary data source, and compare them to baseline models based on Crunchbase data. We show that using LinkedIn as a complementary data source yields the best result with a mean area under the curve (AUC) value of 84%. We also provide a thorough analysis of what types of information contribute most to modeling startup success using the Shapley value method. Our models and analysis can be used to develop a decision support system to facilitate startup screening and the due diligence process for venture capital firms.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofThe Journal of Finance and Data Sciencede_CH
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/de_CH
dc.subjectSuccess predictionde_CH
dc.subjectMachine learningde_CH
dc.subjectStartupde_CH
dc.subjectVenture capitalde_CH
dc.subjectCrunchbasede_CH
dc.subjectGradient boostingde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.subject.ddc658.1: Organisation und Finanzende_CH
dc.titleMaking it into a successful series a funding : an analysis of Crunchbase and LinkedIn datade_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.1016/j.jfds.2023.100099de_CH
dc.identifier.doi10.21256/zhaw-28226-
zhaw.funding.euNode_CH
zhaw.issue100099de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume9de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedFinTechde_CH
zhaw.funding.zhawMachine Learning-Aided Startup Investing (MALASI)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Te, Y.-F., Wieland, M., Frey, M., Pyatigorskaya, A., Schiffer, P., & Grabner, H. (2023). Making it into a successful series a funding : an analysis of Crunchbase and LinkedIn data. The Journal of Finance and Data Science, 9(100099). https://doi.org/10.1016/j.jfds.2023.100099
Te, Y.-F. et al. (2023) ‘Making it into a successful series a funding : an analysis of Crunchbase and LinkedIn data’, The Journal of Finance and Data Science, 9(100099). Available at: https://doi.org/10.1016/j.jfds.2023.100099.
Y.-F. Te, M. Wieland, M. Frey, A. Pyatigorskaya, P. Schiffer, and H. Grabner, “Making it into a successful series a funding : an analysis of Crunchbase and LinkedIn data,” The Journal of Finance and Data Science, vol. 9, no. 100099, 2023, doi: 10.1016/j.jfds.2023.100099.
TE, Yiea-Funk, Michèle WIELAND, Martin FREY, Asya PYATIGORSKAYA, Penny SCHIFFER und Helmut GRABNER, 2023. Making it into a successful series a funding : an analysis of Crunchbase and LinkedIn data. The Journal of Finance and Data Science. 2023. Bd. 9, Nr. 100099. DOI 10.1016/j.jfds.2023.100099
Te, Yiea-Funk, Michèle Wieland, Martin Frey, Asya Pyatigorskaya, Penny Schiffer, and Helmut Grabner. 2023. “Making It into a Successful Series a Funding : An Analysis of Crunchbase and LinkedIn Data.” The Journal of Finance and Data Science 9 (100099). https://doi.org/10.1016/j.jfds.2023.100099.
Te, Yiea-Funk, et al. “Making It into a Successful Series a Funding : An Analysis of Crunchbase and LinkedIn Data.” The Journal of Finance and Data Science, vol. 9, no. 100099, 2023, https://doi.org/10.1016/j.jfds.2023.100099.


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