Although education programmes are constantly being renewed, innovation does not always lead to anchored changes in educational practice. One explanation is that educational innovation evolves more dynamics than often is assumed. Instead of following a well-designed plan, the core activities of innovation leaders hinge on the ability to swiftly identify and interpret situations with which they are confronted. This suggests that the Volatile, Uncertain, Complex, Ambiguous (VUCA) innovation process requires a specific repertoire from innovation leaders, including a better understanding of their internal decision-making processes. In our search for a fitting repertoire, we discovered the capacity for “situational awareness” as a concept to help understand complex situations and to determine very quickly what needs to be done. Additionally, we focus on how innovation leaders make decisions at significant moments during the innovation process in higher education. We describe how our discovery leads to the development of a lens for innovation leaders, with situational awareness as a starting point, and supplemented with the filtering, framing and guiding function of beliefs as steering principles of internal decision making-processes. This allows to gain a better understanding of how the innovation leader identifies critical situations and responds in terms of interpretation and action.
Concerns about the negative consequences of the excessive underpricing of the current arrangement in the initial public offering (IPO) market for the provision of entrepreneurial finance—book building—have led to research into the viability of auctions for IPO pricing and allocation. IPO firms face a trade-off between the benefit of accurate and reliable IPO price discovery and the cost of underpricing. The main aim of this paper was to gain new scientific knowledge about this trade-off by measuring the impact of two key variables on this trade-off: capacity restraint and discount on the auction clearing price. Using controlled experiment methodology in multi-unit uniform price auctions we found that the most capacity-restricted auctions that also offer investors a discount are likely to produce the most accurate and reliable price discovery and consequently, the most predictable auction outcome. There are indications that a discount of 8% may suffice to incentivize investors to reliably contribute to price discovery. The resulting underpricing (and its variability) of these auctions is likely to be significantly lower than if book building would be used to price and allocate IPOs. Technological innovation in the IPO market through the application of recent advances in data science, experimental economics and artificial intelligence allows for the optimization of IPO mechanisms and crowdfunding platforms which in turn improves the access to equity required for entrepreneurial finance.
