Entrepreneurial agency reloaded: Intentions, capabilities and the dynamics of entrepreneurial ecosystems

Increasing attention has been paid in the literature on entrepreneurial ecosystems (EE) concerning configurational microfoundations. The need for a better understanding of the causal channels driving these configurations stems from the view that entrepreneurial ecosystems operate as complex adaptive systems (CAS). Within this paradigm, one dimension that has gained prominence is entrepreneurial agency (EAG). Considered a key element in understanding how EEs are structured, EAG generate outputs, and follow specific evolutionary trajectories. The entrepreneurial agency construct used in this research captures two key subdimensions of entrepreneurial agency: intention and capability. With the consideration of these two subdimensions, the possibility of a mismatch arises (e.g high intention/low capability or low intention/high capability). Yet, significant gaps remain in understanding the subdimensions of EAG and their interplay. Here we aim at further developing the theoretical dimension of entrepreneurial agency by answering the following question: How does the match/mismatch dynamics between the subdimensions intention and capability of EAG affect the configurations and outputs of EE? Using the agent-based modeling (ABM) methodology our results indicate that a mismatch between entrepreneurial intention and capability leads to a decrease in EE output compared to settings where no mismatch is present. Our inquiry identifies key differences between types of mismatch, revealing non-trivial and heterogeneous impacts of intention and capability on the aggregate output of the modeled EE. Our main insight derived from ABM simulations and analyses is related to the dominance of entrepreneurial intention over capability vis-à-vis their impacts on aggregate EE output. This dominance has both academic and policy implications and call for a deepening of the microfoundation paradigm on the field of EE.