This interdisciplinary project aims to develop an innovative approach for design and decision-making in complex spatial projects (CSPs) and (urban) planning based on the real options theory (ROT) from economics and finance. The real options approach offers a flexible way for coping with dynamic uncertainties and to make projects more adaptive to a dynamic and ever changing environment.
CSPs are large-scale projects (e.g. transport and urban infrastructure) that require a high investment cost, take many years to develop and involve multiple public/private stakeholders. Decision makers have to face a great deal of uncertainties and risks in CSPs. Predicting future private and social costs and benefits is difficult, since they can be impacted by multiple interacting uncertainties. Managing uncertainties is therefore an important task in project management. However, dominant practices that support decision-making in CSPs are deficient and inflexible. Cost benefit analysis (CBA) and environmental impact assessments (EIA) do not properly take into account how uncertainties impact predictions that result in different future scenarios. Traditional risk management therefore tries to push out risks and uncertainties as much as possible through risk avoidance, risk reduction or shifting risks to other parties. In nine out of ten projects, costs are underestimated and/or benefits are overestimated.
In the past two decades, ROT has increasingly been advocated as an alternative and flexible approach in fields such as energy planning and (transport) infrastructure. The ROT integrates the concepts of irreversible decision-making, uncertainty and flexibility in the decision analysis. ROT considers flexibility options ("real options") as valuable to deal with multiple uncertainties. Instead of making every decision based on possibly inaccurate forecasts early in a project, keeping flexibility options alive can help a project better to adapt to possible future changes. This requires identifying and monitoring uncertainties and risks, rather than pushing them out, along with identifying flexibility options as responses to these uncertainties. ROT is a quantitative approach using methods and models that allow to quantify flexibility options' value, as well as determining the optimal timing (future scenario) for exercising options. It not only helps to better protect projects against possible downside losses, but also allow projects to capture the upside value of strategic and better balanced decisions
References of real options applications in planning and design remain however limited. Furthermore, its proven (theoretical) potential and increasing popularity are in contrast to its lacking practical value, leading to a gap between real option theory and planning and design. We identified three sources for this gap in our review paper on real options applications in transport infrastructure and megaprojects: (I) simplification of case-studies leads to a simplification of the complex reality in which projects are planned, neglecting multiple interacting uncertainties and embedded flexibility options; (II) quantitative real options methods require (advanced) mathematical knowledge which decision makers often lack; and (III) real options applications lack interaction with practitioners from the field.
How to bridge the real options planning/design gap? How to turn real options' theoretical methods and models into practical relevant methods and tools for CSPs and planning processes? Our main goal is to develop a ROT based framework – in cooperation with experts and practitioners from CSPs in Flanders – for adaptive planning that allows to better identify, assess, manage and monitor uncertainties and flexibility options in CSPs. This will help improve decision making and planning practices in Flanders, by making CSPs more adaptive and robust in a dynamic and complex environment.