abstract
- Effective decision-making is crucial amid uncertainty in the early stages of a business venture. Due to the lack of historical data, decision-makers face real-time challenges, relying on financial key performance indicators (KPIs) trends. This research addresses the need to overcome the uncertainty of initial public offerings (IPO) by analysing the trends using engineering control functions (first/second order with open/closed loop) to model the stock price in real-time, taking advantage of behavioural finance concepts. Stakeholders, including decision-makers, may anticipate and react to the initial steady state of a new venture in real-time. This approach sheds light on the role of behavioural factors and closed-loop adaptive control in shaping steady state outcomes in new market ventures. The contribution of this research is twofold: a) a transdisciplinary decision support framework to analyse the initial stage of IPOs and their behaviour; and b) two actual IPO analyses to illustrate the framework¿s capabilities. © © 2025 Inderscience Enterprises Ltd.