Most technology startups are set up for exit through acquisition by large corporations. In choosing when to sell, startups face a tradeoff. Early acquisition reduces execution errors but later acquisition improves the likelihood of finding a better match since in the early market, there are...

Most technology startups are set up for exit through acquisition by large corporations. In choosing when to sell, startups face a tradeoff. Early acquisition reduces execution errors but later acquisition both improves the likelihood of finding a better match and benefits from increased buyer...

Startups in IT and life sciences appear to be flourishing. However, startups in other sectors, such as new materials, automation, and eco-innovations, which are often called "deep tech", seem to struggle. We argue that innovations with both technical and commercial challenges, typical of deep...

The determinants of transitions between different states of financial distress are analyzed using two versions of Markov chain models: a multinomial logit model without random effects and a multinomial logit model capturing such unobservable factors. The empirical analysis is based on a panel...

Can publicly available, web-scraped data be used to identify promising business startups at an early stage? To answer this question, we use such textual and non-textual information about the names of Danish firms and their addresses as well as their business purpose statements (BPSs)...

We investigate the workforce heterogeneity of startups with respect to education, age and wages. Our explorative study uses data on the population of 1,614 Danish firms founded in 1998. We track these firms until 2001 which enables us to analyze changes in workforce composition over time. Such a...