It is no secret that (asset)managers are currently dealing with a difficult task to maintain and improve the quality of their assets. The main reason for this urgency is the change of use and the end of lifespan of these assets. This is especially the case regarding the inner-city quay walls. These quay walls are usually owned and managed by local governments. The city of Amsterdam in particular has a tough task ahead of them. Approximately 200 km of quay wall need to be maintained or renewed of which the technical state is unknown. A vast majority of these inner-city quay walls are retaining walls on wooden piles. The absence of this information makes it extremely difficult for the asset owner, to determine the current technical state of their quay walls. The combination of limited information and time have shown in practice that quay walls can fail at any moment. To prevent this from happening a variety of intervention measures can be deployed to ‘extend’ the lifespan of the quay walls (short-term). Thereafter a systematic approach can be applied to rebuild or renovate these quay walls (long-term). However, the implementation of intervention measures is an overall complex task due to the densely built area and the stakeholders with divergent interests. This study provides an objective conceptual decision-making model to determine which intervention method is best suited for a particular location while considering the impact on the city, stakeholders and organizations. The research revealed six important topics which need to be incorporated in to the decision- making model. The topics were determined based on literature review, a case study and interviews. These six topics are: the critical cases (1), failure mechanisms (2), intervention measures (3), characteristics of the physical surrounding and the intervention measures (4), decision- making criteria (5) and lastly mitigation measures (6). Additionally, three decision-making moments are identified.

Internal and external uncertainties like structural integrity, load, demand, weather conditions and spatial planning have an impact on Infrastructure assets. Incorporating uncertainties and flexibility to decisions by means of more information becoming available, adds value to new investments, life time extended maintenance and replacements. The traditional way to evaluate such projects, the Life Cycle Cost Analysis (LCCA) based on traditional Net Present Value (NPV) techniques fails to incorporate flexibility, and hence ignores extra value from expected future information. Decision Tree Analysis (DTA) and Monte Carlo Analysis (MCA) can actually allow for valuing flexibility in investments. If investments are subject to non-diversifiable uncertainties, investors should be compensated for associated risks by using time dependent risk adjusted discount rates for valuation practices. A discussion is taking place on difficulties that occur if this principle is applied to infrastructure investments. Conducted literature research shows that current techniques to correct for non-diversifiable cannot be applied directly to most engineering valuation problems. A MCA on investment alternatives regarding to the replacement of a bridge in the municipality of Amsterdam demonstrates how expected investment values can be calculated taking along multiple uncertainties and flexibility. Although the value of flexibility is always equal or greater than zero, case study results show that incorporating uncertainty and flexibility in the analysis can also affect the NPV negatively.