Predicting Startup Survival from Digital Traces: Towards a Procedure for Early Stage Investors

Item Type Conference or Workshop Item (Paper)
Abstract

We investigate whether digital traces can be used to predict early stage startup survival. Based on common survival factors from the entrepreneurship literature, we mined the digital footprints of 542 entrepreneurs and their ventures. Using a context-specific text mining approach, we performed a bootstrapping simulation in which we predict 5-year survival for different survival rates that range from 50% to 10%. Our results indicate that we can predict 5-year survival with an accuracy of up to 91%. With this study, we will provide an evidence-based taxonomy of digital traces for predicting early stage startup survival, identify the most important digital traces for doing so and benchmark our predictive approach against the actual investments of 339 business angels.

Authors Antretter, Torben; Blohm, Ivo & Grichnik, Dietmar
Projects Blohm, Prof. Dr. Ivo; Leimeister, Prof. Dr. Jan Marco; Haas, Philipp; Leicht, Niklas; Knop, M.A. Nicolas; Troll, Julia & Rhyn, Marcel (2013) CC Crowdsourcing [applied research project] Official URL
Language English
Subjects business studies
information management
HSG Classification contribution to scientific community
HSG Profile Area SoM - Business Innovation
Date 13 December 2018
Event Title International Conference on Information Systems (ICIS)
Event Location San Francisco, CA, USA
Event Dates 13.12.2018-16.12.2018
Depositing User Prof. Dr. Ivo Blohm
Date Deposited 26 Oct 2018 13:30
Last Modified 11 Jun 2019 12:40
URI: https://www.alexandria.unisg.ch/publications/255532

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Citation

Antretter, Torben; Blohm, Ivo & Grichnik, Dietmar: Predicting Startup Survival from Digital Traces: Towards a Procedure for Early Stage Investors. 2018. - International Conference on Information Systems (ICIS). - San Francisco, CA, USA.

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https://www.alexandria.unisg.ch/id/eprint/255532
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