Measuring incubation performance in Bergen teknologioverføring : a quantitative study on the effects of business incubation

As the perceived value of innovative start-up environments has accumulated, the measurement of performance in business incubators have become a topic of increasing interest (M'Chirgui, 2012). Innovation is a key performance driver of the economy and supporting the growth and creation of new establishments is therefore becoming one of the priority policies in Norway (SIVA, 2013). Studies analysing the relation between being part of business incubator and enhanced value creation compared to non-incubated firms have shown various results. The purpose of this thesis is to evaluate to which degree BTO’s incubator Nyskapingsparken adds value to its associated firms and use our findings to propose how their performance measurement system can become more efficient and decision relevant information more available in the future. Our study will build on other empirical studies by Schwartz (2010) and Mian (1997) amongst others. The study is an attempt to assess the performance of incubatees in Bergen Teknologioverføring with the aim of enhancing our understanding of the evolution of incubators in Norway and their impact on regional value creation. The analysis is two-fold: First, we describe how optimal performance measurement of the incubator should look like taking previous empirical studies into account. Secondly, using the optimal analysis as a starting point we evaluate past performance of incubatees in BTO based on collected data from multiple datasets. Drawing on the commonly used indicators of firm success, we evaluate the survival and growth rates of incubatees from BTO in the period from 2007 to 2017 comparing the results to a representative control group. Our results cannot support nor deny previous research on the topic. We find indications suggesting that incubated firms in BTO develops a different growth path than similar firms that are not involved in an incubation process. However, the different key figures are not altogether consistent nor statistically significant.nhhma