Facility management focuses on the maintenance, development, and enhancement of physical assets to expand and progress commercial value, as well as the design and upkeep of an appropriate physical workplace for the organisation’s employees and work. Enterprise facility management may be challenging with regionally scattered assets and a high number of assets and stakeholders. Filling stations in the Netherlands are not an exception. The Netherlands had 4,147 gas stations, including uncrewed stations, in 2021. Managers must make everyday strategic judgments as it's "the core of a manager's job" and "essential to organizational existence." Facility managers quickly grasped the value of data in operational and strategic decision-making. In doing so, they have faced various obstacles, including data overload and biases in their conceptualisation, making them inadequately rational. Decision support systems have been used in different forms to overcome the mentioned obstacles. Business intelligence systems are instances of data-driven DSS and refer to a collection of concepts and approaches for enhancing corporate decision-making via the use of fact-based support systems. Often, “business intelligence” software is used to query a database and generate reports. Investigations show that Business Intelligence (BI) dashboards are only used within AECOM for reporting to the client. This study proposes BI and BI dashboards also be used for decision-making. In this research, Business intelligence dashboards were introduced as the successor to the DSS to aid with decision-making difficulties within enterprise facility management. With the objective of determining if the use of BI dashboards in the facility management of filling stations can yield the anticipated advantages. According to the findings of the interviews, the ultimate goal behind decisions is business continuity and growth. Post-experiment surveys show that utilizing a dashboard is only effective if users are educated to make data-driven decisions based on the information supplied. This is known as information relevance, and it is critical for customers to comprehend how the information supplied to them will influence their decisions. Furthermore, the data source must be trustworthy. Also, dashboards could not totally replace site visits in terms of safety. As a result, they may not give the expected value. The dashboard has the benefit of informing clients by providing safety benchmarks, allowing them to detect problematic places and make further decisions. All of the project managers who reviewed the dashboard agreed that it might help reduce the Total Cost of Ownership (TCO). Using business intelligence to make data-driven facility management decisions improves investment decisions. The Other biggest value of using BI dashboards turned out to be time-saving.

The majority of existing infrastructure assets are ageing, and sooner or later, they will have reached the end of their service life. As a result, many asset owners are confronted with large-scale replacement projects in the coming decades. Annually, they allocate a significant number of resources, but these budgets are never adequate for executing all maintenance and replacement activities for their respective assets. It can be said that the same pattern of consequent cost overruns and budget exceedance that is observed in new infrastructure projects over the years also exists for life-cycle budgets. Based on the literature, some scholars investigate the various factors that can lead to budget overruns in new infrastructure projects. Accordingly, others are trying to deal with this issue for new infrastructure projects by proposing different models. However, little information about this issue exists for replacement projects. This research attempts to fill this gap by identifying the factors contributing to the cost overrun problem in replacement projects and providing a model to deal with them. The first part of the research contains a theoretical and practical analysis. In the first, a literature review is conducted to determine the cost overrun factors other scholars have spotted for new infrastructure projects and examine their applicability to the replacements. Once these factors are identified, then a practical examination of these factors is conducted by examining multiple case studies concerning past replacement projects. In that part, all the available cost assessments between different cost estimation phases are revied, and valuable findings are extracted, leading to the development of a conceptual model capable of explaining the cost overrun issue in reconstruction projects. Based on that, two essential characteristics of replacement projects influence the accuracy of their cost assessments. The first is associated with the fact that their budgets are usually structured based on preliminary cost estimations with a high error range and low reliability. The second is related to the fact that usually, replacement budgets are structured many years before the actual initiation of works. During this long-time frame, many changes can happen, such as price (de) escalation, which can significantly influence the initially estimated cost. All this information extracted from this twofold analysis is used in the second part of this research, which includes the process of developing and validating a model capable of dealing with these identified factors. The proposed model consists of two building blocks, each intended to target the factors that originate from the two specific characteristics of replacement budgets. More particularly, the first building block suggests a probabilistic model that can improve the current ways of preliminary estimating costs. The second intends to incorporate the price escalation effect into the estimation by using historical prices and a stochastic model. Based on the validation process, the proposed model could provide more accurate results than the current practices but also a probable range of costs and a projection of them in the future. Consequently, its use can contribute to reducing the cost overruns in reconstruction projects.

The global population is growing rapidly, so the construction sector must keep up by increasing the number of houses and improving the infrastructure. The construction sector is importance to support economic growth and social development within society. However, the conflict that arises here is that the activities of the construction sector are also responsible for a tremendous amount of greenhouse gas (GHG) emissions. This makes the construction sector a key player in the fight against global warming and its consequences. The construction sector can help reduce its emissions and slow down global warming by constructing more sustainable. Sustainable construction minimises the impact on the environment and assures safety and comfort while a financial profit is made. However, the most significant barrier to the implementation of sustainable construction is the affordability of sustainable projects. Sustainable construction often results in higher costs than conventional construction methods, which slow down the return on investment for the project owner.

In 2005, the European Union (EU) introduced the emissions trading system (ETS). The ETS is a policy measure aimed to lower the European emissions by letting the polluter pay for its emissions of GHGs. This policy measure could help overcome the barrier of affordability towards implementing sustainable construction. This research aims to find the ETS allowance price tipping point that financially stimulates the use of natural construction materials like timber over conventional materials like steel and concrete. The tipping point results could stimulate the implementation of sustainable construction and help to slow down global warming.

The results show that the allowance price could help lower the barrier of affordability because a higher allowance price increases the market price of carbon-intensive construction materials like steel and concrete. However, the found allowance price tipping point is unlikely to occur based on the current allowance price of around € 85. Therefore, the current ETS can be considered helpful but not decisive towards a financial favourable timber structure for buildings in the Dutch built environment.

Although the construction industry has made considerable progress in reducing the environmental impacts by waste diversion, the consumption rate of natural resources for construction material is still on the higher side. Hence, there needs to be a higher emphasis on reusing old building components in new construction without down-cycling them and retaining their original functions. Barriers involved in reusing recoverable building elements have multiple dimensions. Based on the current development of the industry, the solutions exist as isolated digital tools and focus only on one issue. This calls for a holistic approach to develop a solution which not only focuses on developing a technical tool but also focuses on embedding the solution in the process of reusing building elements. The main objective of this research is thus, to investigate the application of 'Systems thinking' as a holistic approach that focuses on developing a digital platform ecosystem based on the interventions amongst the actors and processes within the system. A serious gaming approach was used to simulate the system such that it can effectively derive its needs. Through the application of systems thinking and modelling approach to the problem, a set of six intervention strategies were derived. These strategies indicated that the digital platform ecosystem for enhancing reuse will fundamentally rely on these intervention strategies and thrive on reinforcing power from one side of the market to the other. By building on these intervention strategies, four propositions of change were given by comparing the existing scenario of the industry to the desired structure of a digital platform ecosystem. The research is concluded with the acknowledgement that implementation of the intervention strategies will require certain adaptations in the system. A conclusive, but not an exhaustive list of recommended adaptations in the design process and actor-network is provided to accompany the interventions strategies.

This past century the demand for raw materials has risen sharply. This demand is expected to rise even further, which is not sustainable. Changing the linear model of consumption to a circular model can help to decrease levels of raw material demand. The application of service­oriented business models, called Product­Service System (PSS) can contribute to this change. For this application to become a reality within the highway infrastructure sector an approach is needed to determine the residual value of the asset beforehand, as it is an important element of PSS. No such approach is currently avail­able in practice or literature within the highway infrastructure sector....

Expansions for future demand? How much capacity will be required? Until when the decision can be postponed? When to expand? What should be the magnitude of expansion? What is the position of such an investment? These are the kind of questions which a port authority is subjected to while making a decision to expand or develop a port. The decision to invest in the expansion of the port is based on the anticipation of the market in future. The port authorities try to bridge the gap between “What the port is doing?” and “What the port should be doing?”. The choice of timing and expansion is of extreme importance as it allows the port authority to ensure that the project is financially viable and at the same time they achieve its objectives. During the feasibility stages, while making these decisions, a static discounted cash flow (DCF) model is used to calculate the financial outcomes of the expansion plans. However, such a model gives an impression that the decision-maker is obliged to the expansion decisions and cannot delay or alter their scale of investments. However, the reality is otherwise, the decision-maker is an active manager, who adapts the development/expansion plans to the changes based on the project progress.

The current study presents an alternative to the Predict and Control approach of the static DCF model. This is done using Real Options Analysis(ROA). Within the scope of the research, a conceptual framework for ROA for port decision making was derived. The conceptual framework is translated into a mathematical numerical model for a test case in Southeast Africa. The numerical model values the option of multi-stage capacity expansion for the port. Focus is maintained on incorporating flexibility “on” infrastructure based on timing and magnitude under the uncertainty of demand. Through the use of stochastic processes, Monte Carlo simulations, solution algorithm and sensitivity analysis a total of 96 strategies have been evaluated.

Through the analysis of results, it was understood that flexibility has a monetary value when the expansions are done using multi-stage sequential methodologies. Sequential expansions allow the port authority to gain more information based on which the supply can be adapted. In the short term, rather than installing extra capacity, optimising the current operations has a greater benefit for the port authority. While for the long term, the port authority should hold their flexible options until the boundary value wherein the probability of pay-offs exceeding the initial capital expenditures drastically reduce. The option value was seen to be influenced the time until expiration, lead times, number of stages of expansion, modal split factor and dwelling times. ROA was seen to be more of a decision support tool to understand the position of the investment rather than a financial valuation model.

The Dutch railway system is the most intensively used in Europe. This fact, although fascinating, it creates complexity and many interfaces in its operation. The performance of such a system is governed by many aspects and involves many parties. Furthermore, these aspects and parties will have different needs and perceive performance in a different way. In order for the system to operate as smooth as possible, performance agreements are being made in different organizational levels. These agreements guide ProRail on how to manage the railway system and what it should achieve regarding several performance aspects. However, the railway system, as well as ProRail, are not single entities. They are comprised of several organizational levels. Each of these levels has its own needs and peculiarities, which in theory should be represented by their prescribed performance requirements. This creates a coupling between the performance agreements. They should be suitable for each organizational level while at the same time connected. These interrelationships can provide an overview of how the system performs and where adjustments should be made. Nevertheless, if their coupling is too strong, the organization can become cumbersome and stagnate. On the other hand, if their coupling is too relaxed, there will be no guidance and connection to what ProRail wants to achieve regarding the performance of the system. This thesis would like to examine the interrelationships between three performance agreements of ProRail. The Management Concession, Plan and its Performance Management System. The examination is focused on how well these agreements are coupled regarding different performance areas. Its proposed advice is a framework which can potentially alleviate the weaknesses described above. Its purpose is to strengthen the coupling of performance agreements while at the same time, leave enough room for adjustments and innovation. Moreover, the structure of the framework intends to minimize shielding behaviours by providing a process-based approach in the communication of performance requirements. In order to achieve its goal, the thesis formulates one Main Research Question with three Sub Research Question to help build its line of reasoning. The following list presents these questions to the reader.

One of the many challenges in infrastructure management lies in managing built assets. Managing means repairing, rehabilitating and replacing assets to ensure they are able to safely fulfill their functions. To manage infrastructure assets, detailed information about the condition of all components of the asset is required to make substantiated decisions. Assets are composed of several elements and components. Individual component condition reports represent the condition found during visual inspection. The challenge for infrastructure asset managers is how to convert data about component inspections into useful information which are aggregated to make sounds decisions on the maintenance of assets in systems. Useful data that provides information about the condition of assets in systems, which are used to support budget allocation and to prioritize maintenance, is scarce. Information may be lacking, may be incomplete, may be unorganized or may need to be deciphered before it becomes useful in decision making. Furthermore, this data would be unhelpful statistics if one does not know how to apply this information to identify problems and create solutions. At a system level, infrastructure managers need to prioritize maintenance and allocate scarce resources.

Objective: Static long-term decision-making processes for road assets adaptation on the dynamic effects of climate change seem to be ineffective because the proposed proactive measures might not address the actual climate at the fixed date the decision-maker imposes them to be implemented but by giving a time range of expected implementation in the future by following the actual evolvement of climate seems to be much more beneficial. This research recognizes that a methodology for dynamic planning is needed and a study of the climate variables that are correlated with and affect the road tunnel systems in the Netherlands is carried out. Research's main goal is to develop a structured methodology for long-term road tunnel adaptation on the effects of climate change in a dynamic rather than a static way, proposing multiple adaptation actions of increasing robustness and time range of expected implementation in the future, avoiding fixed date ones. Method: The Dynamic Adaptive Policy Pathways (DAPP) approach was chosen because it is the model that realizes dynamic long-term decision-making by proposing strategic pathways of actions. This research investigated the 6 out of 10 DAPP steps and executed them through known methods and tools in three phases. Firstly, the identification and analysis of the climate variables that were correlated to road tunnels are conducted. Phase I started with the Function Breakdown Structure analysis of a road tunnel system defining functional requirements, the Hamburger model for functional decomposition, and Fault Tree Analysis for function failure modes identification was conducting. Additionally, quantification of the failures in unavailability rate terms and qualitative analysis of the corresponding impact on six organization values were executed. Then, in Phase II, the definition of adaptation measures for road tunnel unavailability prevention and consequences mitigation was carrying out and visualized through BowTie analysis diagrams. Finally, in Phase III, the modeling of the adaptation strategy for cause prevention and impact mitigation was presented in DAPP maps. Result: The ongoing climate change in the Netherlands showed that changes in several climate variables affect some primary road tunnel infrastructure functions in an analysis until 2100. By implementing DAPP, I was able to define and conclude to simpler and more compact decision-making plans dealing with deep uncertainty over longer timeframes. These adaptation plans for cause prevention and impact mitigation can be applied regardless the actual climate conditions. In the DAPP methodology, the actual climate conditions indicate the moment the proposed adaptation actions are taken and consequently time flexibility is achieved. The research results seem more effective than the ones of the currently applied decision-making practices. The added value of the DAPP approach lies in its flexible character compared to the to date practices, which mainly define robust adaptation actions that deal with any extreme future and propose strict implementation times. With DAPP, a decision-maker can propose actions of different robustness, that can tackle the same issue by allowing him to select the desired robustness considering the implementation timeframe. As far as the impact mitigation is concerned, the DAPP approach helps a decision-maker to define multiple mitigation actions, which deal with the same function impact and to select the most appropriate. This selection depends on the scoring of the mitigation actions regarding their individual contribution on impact mitigation. Therefore, a useful decision-making methodology for long-term road tunnel assets adaptation, led by environmental changes, was established.

The operation and maintenance of most of the Dutch primary navigation locks are the responsibility of Rijkswaterstaat. The portfolio of Rijkswaterstaat consists of 52 primary navigation locks that are part of the primary flood defence. All these navigation locks are assigned a safety norm together with the adjacent water-retaining bodies. For both main functions, norms and acts are defined that prescribe a certain level of performance. Rijkswaterstaat is responsible that all its primary navigation locks do meet the safety or nautical requirements.Most of the primary navigation locks are built in the first two decades of the 20th century. In principle, Rijkswaterstaat considers a functional lifetime of their navigation locks, equal to 100 years. A number of these navigation locks are technically modified to extend the functional lifetime. In the coming decades, many of these navigation locks have to be renovated in order to meet new norms or requirements. It might that not all the renovation work can be executed in the same period of time. Therefore, the works have to be scheduled and given a priority when they will be renovated. In the existing method, the ”Vervanging&Renovatie” (V&R) prioritisation, one indicator is considered that entails the remaining lifetime as a function of the design lifetime.A risk analysis is conducted regarding the flood safety and nautical requirements of navigation locks. Given the requirements for the flood safety and nautical function, three drivers are defined that affect these functions: climate change, intensity growth, and ageing of material. For these drivers, a number of aspects are distinguished that affect either the flood safety or nautical function. The combination of aspects is framed in a method that can be used to assess the urgency of renovation, relative to the norms en requirements that are linked to the aspects. For each aspect, it is assessed at what moment in time the norm is exceeded. This result is compared to the existing V&R prioritisation of renovation works. Given both methods, it can be concluded whether or not the proposed moment of renovation is according to the required moment of renovation, to safeguard the nautical and flood safety functions.Validation of the proposed method of prioritisation is established via two case studies. The main conclusion of the case studies is that the existing method of prioritising the renovation work of primary navigation locks is not optimal. A number of aspects, as these are assessed in the case study, indicate that the required moment of renovation is before the moment according to the V&R prioritisation. This conclusion is based on the expected performance in the (near) future relative to the required performance that follows from legislation. Some aspects show deviations of up to 40 years relative to the V&R prioritisation Apart from the assessment of the aspects based on the norms, a criticality assessment is conducted. For all aspects as defined in the prioritisation method, the effect of a ”postponed” moment of renovation is balanced with a proposed mitigation measure. This is done with the use of a modified FMECA. It is assumed that the mitigation measure reduces the likelihood of occurrence of the aspect to zero. The costs that are the result of a mitigation measure are compared with the costs of ”doing nothing”. This implies that the consequences of a postponed renovation are expressed in financial terms, in order to balance this with the mitigation measure. In this way, the results of the case studies are financially weighted, independent of whether or not they serve the nautical function or the flood safety function.

Maturity model is widely known as an assessment tool to understand an organization management capabilities and identifying potential improvement. The model demonstrates informative results towards the organization management maturity but hard to acknowledge the influence of potential improvement towards the organization’s asset performance. There have not yet been a study on measuring the asset performance conditional of the organization management maturity. This research objective is to develop an approach to translates maturity model to an asset lifecycle cost and performance by using Dynamic Bayesian Network (DBN). This research uses semi-hypothetical case to see how the model might unfold and to learn the possibility of maturity model development. The chosen hypothetical case is the organizational decision-making process of grass revetment maintenance during winter season based on information management maturity. The output of the DBN is the expected annual cost of the asset for a grass revetment maintenance conditional to organization information management maturity. The result is analyzed by using Value of Information (VOI) which enables us to understand the influence of information management maturity towards the asset lifecycle cost. This research has led us to the conclusion that it is feasible to associate asset lifecycle cost and performance with the organization information management maturity by translating the case into a DBN. In general, this research can potentially lead to a better application on the maturity model and might be used for the organization decision process. This study is the first step towards enhancing our understanding of maturity model application and its implication towards the asset performance.

Asset degradation and maintenance strategies are driving factors that cause the variation in life cycle cost (LCC) of infrastructure assets. In the railway industry, several researchers have analyzed the impact of the uncertainty on LCC, but the emphasis was laid on traditional ballasted tracks. Another type of track structure, embedded rail system (ERS), has not received much attention to date. The research screens the problem to Harmelen level crossing system (LCS), one of the applications of ERS, and proposes a reliability-based LCC model for this type of railway assets, which incorporates the uncertainty associated with rail degradation and maintenance interventions to LCC analysis in order to optimize the maintenance strategies and achieve a cost-effective life cycle management of Harmelen LCS. The model application is demonstrated in Microsoft Excel and partly validated by field data. With the rail failure data, cost information and pre-defined maintenance policies (3 conditions), the model output is able to answer two practical questions for asset managers: ‘when would be the most cost efficient to preventively replace the rails in Harmelen LCS’ and ‘how much money does one asset manager have to save to own the asset in the optimized lifecycle’. Sensitivity analysis is further performed to take more different settings into account and facilitate better understandings about the connections between model outcomes and input variables. Recommendations concerning the model application are provided both for Harmelen LCS and other types of railway assets.

Water Treatment Plants (WTPs) play a key role in assuring water availability to citizens and businesses. Long term availability of these plants is the interest of the asset manager of a WTP and can be influenced by maintenance strategies and modifications of the system. A WTP is characterized by a complex configuration and repairable, deteriorating assets. Currently, no method in the literature is known for modelling the long term availability of systems with these characteristics. This research introduces a two level hierarchical model: it deals with complexity at the system level and with repairable, deteriorating assets at the component level. At the component level the asset manager has to select between a condition based or failure event based model. A flowchart supports the decision making process for this choice. The result is a method which allows the asset manager to (1) learn about what key components affect long term availability of a WTP and (2) explore maintenance strategies and modifications to the WTP and their effect on long term availability.

The municipality of Amsterdam is facing the challenge to deal with uncertainties accompanied with the maintenance planning of maintenance activities on bridges. Long term asset planning (LTAP) has the goal to show the proposed expenditures, capital and operational expenditures (CAPEX and OPEX), for the long term to be able to build up a monetary buffer to absorb the CAPEX which is necessary when a period of large expenditures due to multiple major overhauls and replacements comes up. LTAP also gives the opportunity to program the more expensive activities which create the advantage of spreading expenses over a longer term. The Long Term Asset Planning of Amsterdam makes use of a deterministic time value for activities on bridges, while in fact this value does not give a reliable image of the actual situation. The majority of maintenance activities seems to be performed after the deterministic time value has been reached. Thus, the long term asset planning copes with uncertainties which results in an unreliable outcome and prospect in the expenditures for maintenance. Uncertainties can partly be solved by the use of deterioration models. The parameters involved that predict the physical behavior are mostly an assumption and not known with certainty. Data can be derived from historical maintenance data. A problem faced by all municipalities in the Netherlands is the absence of reliable registered quantitative data. Even the presence of past data would not guarantee its future reliability due to the dynamic characteristic of an urban environment. A method has to be found to retrieve the necessary data alternatively to improve the reliability concerning maintenance intervals for bridges in order to improve the reliability of long term asset planning for municipalities like Amsterdam. Expert judgement is a method that has proven to be a mature and scientific tool for achieving the necessary data that is unavailable at this moment and will be used for this research to develop probabilistic intervals for maintenance activities. By qualifying and quantifying the uncertainties regarding the maintenance on bridges, improvements may be realized on the short- and long term for the costs in maintenance planning. A questionnaire reveals that experts in the field have trouble assessing condition over time. A recommendation is given to solve this issue in the future.