The value of big data for analyzing growth dynamics of technology-based new ventures

Maksim Malyy, Zeljko Tekic and Tatiana Podladchikova

Technological Forecasting and Social Change, 2021, vol. 169, issue C

Abstract: This study demonstrates that web-search traffic information, in particular, Google Trends data, is a credible novel source of high-quality and easy-to-access data for analyzing technology-based new ventures (TBNVs) growth trajectories. Utilizing the diverse sample of 241 US-based TBNVs, we comparatively analyze the relationship between companies’ evolution curves represented by search activity on the one hand and by valuations achieved through rounds of venture investments on another. The results suggest that TBNV's growth dynamics are positively and strongly correlated with its web search traffic across the sample. This correlation is more robust when a company is a) more successful (in terms of valuation achieved) – especially if it is a “unicorn”; b) consumer-oriented (i.e., b2c); and 3) develops products in the form of a digital platform. Further analysis based on fuzzy-set Qualitative Comparative Analysis (fsQCA) shows that for the most successful companies (“unicorns”) and consumer-oriented digital platforms (i.e., b2c digital platform companies) proposed approach may be extremely reliable, while for other high-growth TBNVs it is useful for analyzing their growth dynamics, albeit to a more limited degree. The proposed methodological approach opens a wide range of possibilities for analyzing, researching and predicting the growth of recently formed growth-oriented companies, in practice and academia.

Keywords: New venture; Startup; Google Trends; Unicorn; Digital platform; Venture capital; Lifecycle (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:169:y:2021:i:c:s0040162521002262

DOI: 10.1016/j.techfore.2021.120794

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