Based on our key findings we suggest that further research focuses on the measurement of additional factors that possibly provide deeper insights into the subject matter.
We hope that qualitative research reveals novel startup specific factors that help to predict the success of startups in an even more precise manner or aid in the adaptation of the factors used within the present study.
Moreover, we want to encourage further research to investigate the cognitive abilities and functioning that startup entrepreneurs possess. Since cognitive factors as in aptitude or GMA might be correlated with the success of a startup, investigating and collecting data on those facets would contribute to a broader picture regarding the qualities a successful founder must hold.
Furthermore, the collection of data, regarding the startups’ financial circumstances, allows the derivation of broader and further conclusions about current startup success indicators. Moreover, this approach might provide the opportunity to make even more valid future predictions about a startup’s success.
In addition, future research should investigate to what extent a certain university or degree impacts a startup’s success. Similarly, the relationship between the founders’ personality structure and their university degree should be examined, since specific personality traits might interact with a certain university degree.
Moreover, we want to encourage further studies to consider the use of longitudinal study designs in order to eliminate biases due to maturation (cohort effects), historical events, and to assess the development and intraindividual shifts in the founders’ personality and their startups’ success over the course of the years. Longitudinal studies compared to cross-sectional studies dispose of the possibility to draw broader conclusions and enable the generalization to broader contexts (for instance extracting inferences over different cohorts).
Regarding intercultural research, we recommend taking into account country-specific norms and biases and their respective startup scene ecosystem. Generating data within the intercultural context would enable us to generalize our findings to a much broader context.
Besides, it might provide insights into specific stereotypical biases due to the countries’ specific socialization and culture. Those biases might interact with the founders’ personality, as in the degree certain traits are established. For instance, women in other countries that are facing different stereotypes might struggle less with the application of effective leadership skills.
With regard to our sample, we would suggest that future research additionally includes startups that have failed in order to possess more statistical data and be able to derive further inferences and differences.