Tech Stack Analysis
Drivers and Risk-related Outcomes in the Process of Digital Infrastructure Adoption
Matthias Schulte-Althoff (FUB)
Prof. Dr. Daniel Fürstenau (FUB, ECDF)
We wish to suggest a dynamic model of digital infrastructure of startups in ecosystems. This model builds on technology stacks as found in public data aggregators. In the first part of the thesis, we examine which factors drive the digitial infrastructure of startups to become more homogeneous or heterogeneous over time. Using technology stack adoption as dependent variable and applying advanced time series analysis and network evolution modeling, we investigate to what extent similar or different technology stacks occur and how this is driven by the ecosystem in which a startup is embedded. In the second part of the thesis, we shed light on technology stack-related risks in start-up ecosystems that combine vulnerability, technology stack, and start-up data by providing a quantification of the criticality of technology stacks.