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.