Research project completed
The objectives of this PhD are: (I) extend existing real option theory (ROT) literature to complex spatial projects and planning, (II) address the long existing concern of uncertainty in planning literature with a new theory and approach, and (III) impact planning and design practices by offering project stakeholders an innovative and hands on management framework for adaptive planning.
Our planning environment has become more dynamic, complex, and uncertain, but dominant planning approaches still rely on deterministic and static views of the future, wrongly believing the future is controllable and predictable. This growing mismatch between planning context and adpproaches led Planning scholars to increasingly advocate a paradigm shift towards adaptive planning and uncertainty acknowledgement. However, planning practice runs behind due to a lack of hands-on adaptive planning approaches, a lack of successful precedents and empirical studies, and institutional constraints. This PhD researches the potential of the economic real option theory as an adaptive planning approach to better cope with uncertainties in complex spatial projects (large infrastructure and urban (re)development). Real option theory offers a generic set of flexibility options to develop adaptive strategies in a structured way and uses mathematical models to value flexibility.
Thesis: Real options for real urban projects: Uncertainty and adaptive planning in complex spatial projects
Articles in academic journals
- Real option applications in megaproject planning: trends, relevance and research gaps. A literature review
- Uncertainties in the decision-making process of megaprojects: the Zeebrugge new sea lock
- Explaining Uncertainty Avoidance in Megaprojects: Resource Constraints, Strategic Behaviour, or Institutions?
- A real options framework for adaptive urban design
- Stakeholder perceptions of uncertainty matter in megaprojects: The Flemish A102 infrastructure project
- Creating Flexible Plans for an Uncertain Future: From Exploratory Scenarios to Adaptive Plans With Real Options