Research on technology entrepreneurship and accelerators

The last few years, accelerators are quickly proliferating across the globe. To illustrate, the F6S-platform for founders indicates that the worldwide number of accelerators has grown from 194 in 2012 to 793 in 2015; an increase of 308%. However, there is quite some confusion about what an accelerator is and what its impact is on early-stage technology ventures. To add to the confusion, many programs are continuously evolving their models. Understanding the organizational design of accelerators, its effectiveness, and its role in the startup ecosystem is key if we want to properly advise policy makers, investors, and corporates looking for new ways to spur the development of innovative ventures. Furthermore, focusing on accelerators provides an opportunity to extend the learning and experimentation literature as it offers a natural lab setting. Accordingly, the overarching research question of this dissertation is: what do accelerators do and how do they impact the entrepreneurial trajectory of ventures? This study uses theory elaboration methods to suggest how accelerators are configured and what happens within an accelerator program. The research setting is 40 accelerators across Europe—cohort-based startup support programs that accelerate learning and are seen as problem solvers for various actors in the entrepreneurial ecosystem such as venture capitalists, governments, corporates and even incubators. For instance, setting up an accelerator benefits venture capitalists by facilitating investments in a larger number of early-stage ventures at relatively low cost. It also benefits governments and corporates to streamline technology commercialization efforts. Thus, accelerators are an important phenomenon and this study provides several insights. On the one hand, it opens the ‘black box’ by highlighting the design and practices of the accelerator. By recognizing the heterogeneity among accelerators, it is clear that more robust metrics have to be developed in order to monitor the effectiveness of the different models. Although classifications of accelerator programs based on their relative performance (e.g. the Seed Accelerators Ranking Project) could be of importance to startups, it may also provide a distorted view considering programs can differ in their strategic objectives. On the other hand, it explains to policy makers, accelerators and early-stage technology ventures the boundary conditions of acceleration. First, policy makers need to take a long-term budget view when they consider to support startups through accelerator programs. Second, many ventures may not be investor-ready or commercially viable at the end of an accelerator program. Therefore, a systematic policy approach is needed for startups to thrive. Third, both early-stage technology ventures and individuals interested in setting up an accelerator should take into account the specific program components such as the selection process and the learning approach when respectively considering to apply for a program or configure one. Taken together, these essays demonstrate that accelerators occur in various forms, are constantly evolving and can differently impact the development of early-stage ventures