Search results

To support the advancement of an underrepresented category of research in the field of entrepreneurial teams, this study proposes and tests a novel empirical model that connects two team emergent states, namely team entrepreneurial passion (TEP) and transactive memory systems (TMSs), and their influence on team performance.

The data were gathered using an online questionnaire distributed to undergraduate students who had formed entrepreneurial teams as part of a course assignment. Two methods were executed on the obtained data, namely partial least-square structural equation modelling (PLS-SEM) and necessary condition analysis (NCA).

The results uphold the hypothesised mediation role of TMSs between TEP and team performance. Of the two direct relations in the model, only the necessary conditions were present for the effect of TEP on TMSs.

The issue of the small sample size, a common feature in entrepreneurial team research, as discussed in the methodical section of the paper, is sidestepped with the use of PLS-SEM tools. Nonetheless, a larger sample size could have increased confidence in the results' validity. In addition, a longitudinal approach to data collection and analysis could have been used to augment that confidence further.

Three practical implications stem from the empirical findings. First, it lends support for implementing teaching approaches and task designs that are envisaged to improve team functioning in university classrooms. Making a business plan boosts students' desire to exploit the received knowledge and find a venture, so the teaching effort in entrepreneurship courses can have real-world consequences.

By testing the mediation model, new insights are made into the associations between team emerging states and, subsequently, team performance. In addition, this study responds to recent calls in the literature to incorporate NCA in an entrepreneurial setting.

This study responds to calls by researchers to examine the relation between innovation and entrepreneurial ecosystems more closely, and also to further broaden our understanding of regional intellectual capital formation.

A cross-sectional analysis was conducted on NUTS 2 regions of the selected EU countries. In the empirical part of the research, multiple linear regression approaches were carried out using secondary data.

In sampled regions, the entrepreneurial ecosystem positively affects levels of high growth firms and levels of regional innovation capital.

Results lend further support to policymakers to develop and implement a regional-specific policy for fostering entrepreneurial ecosystems. However, given the multiple output nature of entrepreneurial ecosystems, this issue becomes more complicated than ever before.

This study builds upon previous research and complements it by widening the range of effects that the entrepreneurial ecosystem has. In doing so, this study is the first to examine the concurrent effects of these ecosystems on levels of high growth firms and innovation capital while using a regional innovation capital outlook.