Big data and start-up performance - Elisa Rodepeter; Christoph Gschnaidtner; Hanna Hottenrott (ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung, 2023)
Big Data (BD) is becoming widely available and manageable. This raises the question of whether Big Data Analytics (BDA) in companies leads to better decision-making andhence performance. Based on a large, representative set of start-ups in Germany, we study the adoption of BDA among small and young ventures and analyze its economic effects using various short- and longer-term performance measures. We investigate the effect of adopting BDA on the new ventures' cost structure, sales, profits, survival rate, growth, and their probability of receiving Venture Capital (VC) financing while taking into account fac tors that drive BDA adoption. Our findings, however, show that using BDA does not lead to an immediate competitive advantage in terms of the classical short-term performance measures. BDA adoption is rather associated with greater sales/profit uncertainty, higher (personnel) costs, and a higher probability of failure. Yet, the increased risk of adopting BDA is compensated by a prospect of higher long-term performance conditional on survival. BDA-adopting start-ups perform better than comparable ones when considering longer-term performance measures such as their growth and their ability to secure VC.
Keywords: 330; Big data; Innovation; Productivity; Start-ups; Survival; Venture capital