Large scale ideation continues to gain importance in today's economy, driving research and development. One of its best-known techniques is electronic brainstorming (EBS), which has proven to be successful at producing a large number of ideas but struggles with a high quantity of low-quality ideas. This weakness motivated the question: How can the quality of these ideas be improved?
While much research on the improvement of idea quality has been done regarding what kind of inspiration is given during ideation and in what way, little has been looked into individual differences of ideators who may have different needs in terms of inspiration and therefore show different behavior when exposed to inspiration. This thesis examines whether such types of ideators with individual differences can be identified.
As individual differences may have various dimensions, first, an in-situ exploratory study was conducted to identify individual differences in the context of inspirations, that can be tested for its impact on the ideation outcome in a subsequent, quantitative study. The exploratory study induced the idea of the existence of the ideator types inspiration seeker (benefiting from inspiration) and inspiration avoider (feeling distracted by inspiration). The analysis of data from previous EBS studies showed that this idea applies not only to classical group ideation but to a large-scale ideation setting as well.
In order to understand the impact of the identified ideator types, a quantitative study was conducted. It aimed at replicating a recent study on the influence of inspirational stimuli (Siangliulue et al., 2015), while additionally examining different effects of these stimuli on inspiration seekers and inspiration avoiders.
The analysis of the study showed that the ideator type did not seem to have an impact on the number of submitted ideas or their value. However, avoiders produced ideas with a higher maximum novelty per session than seekers across all inspiration conditions with the greatest difference between the types when no inspiration at all was provided.
The results show that individual differences regarding inspirational stimuli exist and do impact the fluency and quality of ideas. Paying attention to these differences is a promising approach to improve the quality of the ideas produced in electronic innovation systems. This classification could potentially be used to create personalized inspiration systems catering to the needs of different ideator types.