Ensuring the air we breathe is clean and healthy is one of the core tenets of developing a more sustainable living environment, but even in the Netherlands up to 11,000 premature deaths occur every year. These deaths could be reduced if the air quality standards outlined by the World Health Organization are met. To achieve these standards however, significant changes have to be achieved in Dutch society. In the Netherlands currently, air quality is regulated at all four of the major levels of government, that is the supranational, national, provincial and local (municipal) level. Each of these levels of government play a key role in ensuring that the air in the Netherlands is safe to breathe. Up till now however, only limited research has been performed on how air quality governance occurs at the municipal level. Furthermore due to the diffuse characteristics of air pollution, where emission and deposition may occur in places significantly geographically situated, reducing air pollution is very difficult. To aid with this a wide variety of models have been developed for use in supporting policy processes. These models allow municipalities to determine aspects like exposure of the population and sources of emissions. The use of these models is not always straightforward however, as political considerations regularly take precedence in the municipal air quality policy process. It therefore remains a challenge to determine how the municipality might improve its air quality governance, and the role that models might.
With this in mind, this thesis aims to develop an understanding of the municipal air quality policy process, and the role of models therein. This is reflected in the research question, which is as follows: What potential improvements in the Dutch municipal air quality policy process can be made, and what role can models play in this? To answer this question, this study used a qualitative research approach, making use of a combination of scientific and grey literature as well as expert interviews to create a representation of the municipal air quality policy process in case study of Eindhoven. The interviews were conducted with representatives from key organizations in the air quality policy process. This was combined with scientific literature on multi-level governance, air quality modelling and policy processes as well as grey literature on air quality governance in the Netherlands. The results of this research was then tested in interviews with experts from other regions in the Netherlands.
It was found that there are a host of areas that could be developed to improve the municipal air quality policy process, with four key ones. These improvements applied to all levels of government, from the European Union all the way down to the municipal policy advisors, and were found in four main areas: (1) Increased air quality standards and cooperation frameworks. (2) Improved modelling tools for air quality modelling and monitoring. (3) Increased citizen engagement and awareness on air quality. (4) Improved air quality regulation through integrated decision making with other relevant issues facing the municipality.

The Dutch Government has prioritized the construction sector for a circular economy transition. This research aims to understand the circular transition in the context of the Netherlands’ construction and demolition waste management system. By using a mix-methods approach based on systems analysis and a material flow model, this study assesses the environmental impacts of 7 identified policies. The results found that implementing mandatory pre-demolition audits performed the best in increasing the upcycling and reuse rate from 8% to 23% by not only focusing on source reduction but also prioritizing reuse. The policy measure which focuses on waste identification, separation, and collection at the source with sorting obligations performed the best to recover the most amount of waste (20.3 million tonnes/year) and increase the total recovery rate to 83%. A scenario analysis done by clustering policies for a strategic focus found that recovering more waste on its own will not reduce carbon emissions in the long run unless it’s redirected towards low-carbon destinations. A recommendation to design effective circular policies for waste management is to include carbon emissions and upcycling and reuse-based indicators.
From an academic perspective, this study integrates a partial life-cycle assessment into a material flow analysis by integrating carbon emissions into a material flow model. By synthesizing and using a multi-criteria framework to calculate potential impacts, this research adds to a growing literature in policy design. The mix-methods approach used can also be adapted to other waste-based industries with a similar supply chain background.

Energy transition has become the lead focus of the European Union (EU) agenda. The introduction of European Green Deal (EGD) has further raised the targets regarding greenhouse gas emissions, Renewable Energy (RE) and Energy Efficiency (EE) and strengthened legislation concerning the circular economy and biodiversity. Forest biomass energy has been at the forefront of the EU policy-making.

In Central and Eastern Europe (CEE), where the forest biomass is mainly used for domestic heating in the form of round-wood, the issue of AQ has a significant role in the energy transition agenda. The burning of round-wood in old low-efficiency stoves cannot produce sufficient energy while exposing people to indoor and outdoor pollution. Moreover, the Particulate Matter (PM) from wood burning is associated with multiple health conditions.

The research aims to understand the impact of the forest bio-energy policy mix on EP; hence the following research question is formulated: How is the forest biomass energy policy mix affecting energy poverty alleviation in Sofia, Bulgaria? The case study approach is suited to answer the main research question. Furthermore, the case study approach allows for in-depth exploration of complex issues and uses multiple research methods.

The theoretical framework of the research is based on the policy mix conceptualisation proposed by Rogge and Reichardt (2016). Rogge and Reichardt define three building blocks of the policy mixes: elements, process and characteristics.

The conflicts existing between the national level policy instruments and the rest of the policy mix result in vertical and horizontal inconsistency. Nevertheless, synergies between the EU instruments and the appliance change programs result in synergies. The lack of capability of the local and national institutions and the perceptions conflict indicate a lack of policy mix coherence. At the same time, the policy mix does not have any instruments to cover market failures exposing households to higher energy cost and include policy instruments outside the national energy plans indicating a lack of comprehensiveness.

While the lack of consistency, coherence and comprehensiveness have some positive impact on energy cost, thus reducing energy poverty, the conflicts in the policy mix are sustaining the use of
traditional fuels. Overall, in the situation of surging energy prices, the forest bio-energy policy mix is sustaining the EP; however, in the case of lower energy costs, the existing conflicts constitute a significant obstacle in alleviating EP in Sofia.

The evaluation of the impact of the policy mix on energy poverty in Sofia shows that the lack of constancy, coherence and comprehensiveness and credibility does not always lead to adverse effects on the energy poverty indicators. Nevertheless, the results support the findings of other articles focusing on the impact of the energy transition on energy poverty and that the way to achieve energy poverty alleviation is to strive for consistent, coherent and comprehensive energy transition policies. In terms of the policy mix concept, the study shows the need for further empirical research on the multi-dimensional policy mixes and more emphasis on the instrument’s design features.

Increasing demand for passenger services in densely populated urban environments, are currently covered overwhelmingly by private vehicles. Their impact on CO2 emission, present a serious obstacle to the reduction objectives, in the Netherlands alone the target of 45% by 2030, for limiting the global warming to 1.5°C degrees. Autonomous Vehicles (AV) and Ride-Sharing services are believed to be offering a crucial technological and perception shifts to reducing emission. In this work, a methodology for assessing the impact of a large-scale AV fleet ride-sharing system to replace the one-two passenger vehicle traffic using Rotterdam as the case study is designed and proposed.

The approach includes three stages: 1. Building and finetuning a traffic model using publicly available data 2. Designing and implementing a trip merging component, in the form of two distinct heuristic greedy algorithms and a variation of the second one, using Python programming language. 3. Evaluating the impact of each merging scenario on the network in SUMO.

The system’s influence and results are driven from the deployment of the ride-sharing service on the 2016 traffic model. The decrease in total number of trips, vehicle kilometres travels, and subsequent improvements in traffic flow resulted in 39% reduction in CO2 emission with the third algorithm. This result not only establishes the extent of AV ride-sharing service’s potential for emission reduction and traffic quality improvement. This adaptable methodology also operates as a proof of concept for a preliminary step for policy makers when considering implementing such service in any urban setting. Two of the major elements not included in this research are multimodal travel, like combination with public transport, and changes in demand for each mode choice based on traveller’s behaviour. These elements thus remain open for future consideration.

Despite the fact that everyone has the right to adequate housing, this fundamental human right has become a critical manner in several European Union (EU) nations, especially in the Netherlands (OHCHR, 2009; Rosenfeld, 2015; European Parliament, 2020). Despite being the largest social sector in Europe, accounting for approximately 30% of the Dutch housing market, recent research suggests that housing associations are unable to properly handle their social responsibilities in the current environment in the Netherlands (Penders, 2020). First of all, recent changes in the housing market demonstrate that the demand for social housing has not only expanded but also diversified its target audience (Madsen & Ghekière, 2021). Recent studies indicate that aside from the poor and vulnerable, also the elderly, young adults (starters), and middle-income families, along with vulnerable and special groups are becoming increasingly interested in this housing aid (OECD, 2020; Madsen & Ghekière, 2021).

In order to meet the rising social housing demand, housing associations are expected to construct more than 25,000 new social houses each year until 2035, with the number of dwellings that must become more sustainable gradually increasing from 25,000 to over 60,000 (Penders, 2020; Madsen & Ghekière, 2021). According to Penders (2020), approximately €116 billion is required for all investments up to and including 2035, however, around €30 billion in social tasks (nearly 25% of the total amount) will not be accomplished since housing associations’ expenditures (interest, taxes, maintenance, and management) are rising faster than their income, namely rentals. In the Netherlands, the creation and management of social housing is the responsibility of social housing associations. However, the different actions that these housing associations can take in order to fulfil their social obligations depend mainly on the housing policies that the Dutch policymakers implement. As a result, it has recently come to light that a significant portion of the social housing stock in the Netherlands is unfit for habitation. One in five of all social rental dwellings in the Netherlands, which is estimated to be home to 312,500 households, are expected to be energy-poor, according to recent studies (P. Mulder et al., 2021; Aw, 2021). In addition, according to current Autoriteit woningcorporaties (Aw) data, the housing associations themselves provided about 80,000 social rental houses in (very) poor conditions (De Regt & Bunskoek, 2021).

Given that the Dutch social housing is currently struggling to meet its social obligations due to a paradox of rising demand and constrained financial means. More legislative actions will be required to alleviate the current housing crisis through the social housing market. Therefore, this study aims to answer the following research question: What policy strategy could Dutch policymakers put in place to assist social housing providers to ensure that there are enough adequate rental properties available to meet the rising housing demand?

In this study, this research question will be answered by means of a simulation modelling approach. It was decided to investigate the underlying mechanisms in the social sector in the Haaglanden urban region by conducting various analyses (including uncertainty analysis and policy analysis) using the system dynamics (SD) simulation model, the Dutch Social Housing Model, which was created during the execution of this study. Contrary to the conventional SD approach, this study is accomplished by combining the SD approach with the Exploratory Modeling and Analysis (EMA) methodology – which employs computer experiments to support decision-making under uncertainties. Given the dynamic complexity and deep uncertainty linked to the researched system, this method was performed to draw valid conclusions regarding the Dutch social housing market under deep uncertainty (Adams, 2011; Le Roux et al., 2011; Jonsson et al., 2021; Kwakkel & Pruyt, 2015).

First of all, the results show that up to and including 2050 there will be a housing shortage in both the social housing market (hereinafter referred to as SGEI) and the housing market for middle-low-income households (hereinafter referred to as Non SGEI) in the Haaglanden urban region. In particular, the shortage of SGEI homes will remain at around 60,000 homes from now until 2050, while the shortage of Non SGEI homes will continue to rise to about 20,000 homes. This can be explained by the difficult financial situation of the social housing associations, which cannot meet their social obligations. Despite the anticipated gradual increase in the social housing associations’ financial sources, this study shows that these corporations will only have enough financial resources to invest in the social housing market. Due to this, it is expected that the housing quality of SGEI houses will improve, while that of the Non SGEI houses is expected to deteriorate. The reason being, that if the housing association has sufficient financial resources for a particular house (in this case the SGEI houses), it can ensure that the homes in question can undergo maintenance, which improves the housing quality.

Given that the main purpose of this study is to identify policies that will enhance the system behaviour of the social housing market, it was decided to examine the following social housing regulations: Increase Average Rent, More Subsidy for Social Housing, More Planning Capacity for Social Housing, Lower Interest Rate, and Eliminate Landlord Levy. This is due to the fact that the policies Increase Average Rent, More Subsidy for Social Housing, and Eliminate Landlord Levy all improve the cash flow of social housing associations, with Eliminate Landlord Levy lowering the expenditures while the other two policies increase the income of the social housing associations. The expectation is that improved income flow will put social housing businesses in a stronger financial position, allowing them to make more investments to address the housing shortage and quality. Furthermore, More Planning Capacity for Social Housing guarantees more land at the disposal of housing associations compared to the current situation for the construction of new social housing to ensure that the growing housing demand will be met by the housing supply.

It is advised to use a combination of these policies to address the issues with the social housing system because no single of these policies can effectively address both the housing scarcity and the poor housing quality of both housing markets. Based on the results, it can be concluded that the combination of the following policies should be used in Dutch social housing: (1) More Planning Capacity for Social Housing, (2) More Subsidy for Social Housing, and (3) Eliminate Landlord Levy. However, it is advised to ascertain the value of the most influential uncertain parameters prior to the selection of the policy strategy because the majority of the KPIs, with the exception of the housing shortage for middle-low income households, are behaviorally sensitive to the uncertain parameters investigated in this study. Moreover, it is challenging to assess the robustness of the investigated policies because of the significant overlap between the findings of the several policies reviewed by the robustness study. The efficiency and robustness of the various policies mentioned in this study and their combination should therefore be thoroughly examined using the data that have been gathered of the most influential uncertain parameters. This information allows for the most precise mapping of the researched system’s behaviour during the application of the policy interventions. Policymakers are then able to decide on a course of action that is supported by empirical facts as a result. Ultimately, it is recommended that the other actors also be included in the policymaker’s selection procedure, as they may have differing opinions about the different policy candidates. The many perspectives that the actors involved have regarding the social housing system must therefore be thoroughly researched.

For several years, the importance of a neighborhood-specific approach to tackling overweight has been emphasized. However, to date, no simulation model has been encountered that provides insight into the determinants of becoming overweight in a specific neighborhood. It is therefore difficult for policymakers to decide on a set of appropriate policy interventions to reduce overweight in their neighborhood. In this study, a System Dynamics model was constructed to provide insight into which factors play a role in the problem and to what extent with the Schildersbuurt in The Hague as an example. Implementation of policy interventions as experiments in the model has shown that an integrated approach of both targeting energy intake and energy expenditure yields the best results considering possible future situations. More research into neighborhood-specific data for parameters input in the model and the suitability of the model to support policy advice in other neighborhoods is recommended.

Following the Paris Agreement, the national government of the Netherlands reached the Climate Agreement together with more than 100 organizations. As part of this agreement, the industry sector is faced with the ambitious goal of 59% CO2 reduction in 2030 with respect to 1990 levels. Since the naphtha cracking industry is one of the most emission-intensive industries worldwide, decarbonization of this industry can deliver a significant contribution to reaching the climate goals. Among other transformations, electrification is regarded as an important decarbonization strategy. However, electrification in the naphtha cracking industry currently faces several barriers. For an important part, these stem from fundamental uncertainties concerning the future markets, the availability of renewable electricity and the capacity of the electricity grid. Moreover, high investment costs combined with a lack of financial and fiscal incentives and low carbon prices make the business case for electrification currently unattractive. In addition, the high degree of systems integration onsite and the baseload nature of the cracking process make the implementation of electrification challenging. Government policy could play a pivotal role in resolving these barriers. The purpose of this research is therefore to explore policy options at a national level that enable an acceleration in the chemical industry’s electrification while being robust against uncertainty. For this purpose, the Robust Decision-Making (RDM) framework was applied. As part of this framework, a system dynamics (SD) model was built to describe the behavior of the socio-technical system of the naphtha cracking industry. This model was then subjected Exploratory Modelling & Analysis (EMA) to simulate the impact of various policy options on the electrification rate against a large number of plausible future scenarios. Moreover, a robust policy search was conducted using a multi-objective robust optimization algorithm.The analyses of the simulation results suggest that profound changes in current policy instruments are required to achieve a significant degree of electrification in the naphtha cracking industry with sufficient certainty. It is advised to increase government funding for electrification, implement a fiscal shift away from gas towards electricity and to increase the effective carbon levy imposed on the industry. However, though the analyses show that government policy has a significant impact on the development of electrification, its success appears conditional on external factors, most importantly, developments in the energy and carbon markets. In fact, the electricity price and the ETS carbon price turn out to be more influential on emission reduction than most policy interventions. The availability of renewable electricity is the single most influential factor affecting CO2 emissions and hence, is considered paramount in achieving emission reduction. Therefore, policy aimed at accelerating electrification should be accompanied by decisive government action regarding the development of renewable electricity sources.

At the UN conference of 2015, the promotion of inland waterway transport (IWT) was named as a Sustainable Development Goal by the United Nations. While IWT has been identified to make goods transport more CO2- efficient, the long-term viability of the Dutch IWT sector is at risk.

Currently, Dutch IWT businesses benefit from increased demand for transport capacity during climate change induced periods of low river depth by being able to charge higher prices to shippers, thereby increasing short term profits. This thesis research project concludes that this behaviour is unsustainable due to the disregard for providing price competitive and reliable services to shippers, which will ultimately damage the reputation of the Dutch IWT sector. This can lead to shippers choosing other modes of transport, which will damage the long-term viability of IWT demand.

A lack of evident optimal climate adaptation measures that would better guarantee the long-term viability of an IWT business under any climate scenario is one of the reasons why IWT businesses have thus far been hesitant towards implementing climate adaptation measures. This thesis research project studies the potential of using a robust decision analysis in supporting IWT businesses’ decision-making on climate adaptation measures that could safeguard the long- term viability of the Dutch IWT sector. It conducts a robust decision analysis and then evaluates its potential using feedback from stakeholders of the Dutch IWT sector.

This thesis research project present the results from the robust decision analysis to IWT stakeholders to evaluate how these could impact their decision-making. Stakeholders noted that they believe that the produced influence diagram could be used as a standard communication object to produce a better consensus of how measures influence the long-term viability of IWT demand. Furthermore, stakeholders expressed that the robust decision analysis provided them a better understanding of which measures were able to better guarantee the long-term viability of IWT demand. Results from evaluation interviews with stakeholders therefore provide grounds to believe that robust decision analyses have potential to support IWT businesses’ decision- making on climate adaptation measures that could safeguard the long-term viability of the Dutch IWT sector.

Traffic congestion has proven to be a wicked problem that is affecting people's economy and health. Until now, traditional policies have not yet been able to solve the problem entirely. To tackle such a challenge, new innovative measures are needed. Mobility as a Service (MaaS), a new paradigm in mobility where all modes of transportation are offered to the user in packages through a digital platform, offers a new approach with a service that could compete with private car ownership, the main cause of traffic. However, there is no policy research on the implications of MaaS and whether an intervention from the government is necessary to boost the reduction in traffic congestion in this new paradigm. MaaS is a system full of uncertainty and it's adoption is a time changing complex process. System Dynamics is an interesting method to close the research gap identified, since it is commonly used in time changing systems with high uncertainty. However, this is a method not commonly use for the study of mobility, and there is a need to identify the challenges when using this method. The main objective of this thesis project is to evaluate the use of System Dynamics as a research method to understand MaaS.

The starting point of the thesis is that national CO2 policy options are complex. In other words, that there are non-economic factors that are play at the implementation of the CO2 options. Why do some CO2 options not materialize in the market, despite favorable economic conditions? Current methods for answering such questions are strongly embedded in financial assumptions and monetary units (e.g. the MACC). The statement is that complementary methods are needed that focuses on other factors. Experts are proposing the Y-factor (factors about 1. physical interdependencies, 2. multiple actors and 3. behavior), but the method lacks empirical evidence. The objective of the thesis is to gather empirical data to underpin the Y-factor. The chosen research perspective is a transition perspective and empirical data is collected through six case studies and in-depth interviews. Six policy options in six sectors are analyzed: 1. the heavy industry, 2. built environment, 3. energy production, 4. forestry, 5. agriculture and 6. waste. For each case study, 3 to 5 interviews are carried out, a total of 21 interviews are analyzed.

The need for water, energy, and food resources is central to human being. Demand of these resources will increase as global population increases. By 2050 it is expected that combination of population growth and economic development will lead to 50% increase of global water and food demand, while energy demand will be doubled. Addressing sustainable water, energy, and food consumption has also been emphasized in United Nations’ Sustainable Development Goals; among others, this applies to consumption at household level. Sustainable household consumption of water, energy, and food here implies not only the objective to improve the resource durability, but also to reduce environmental footprint. The unsustainable management of these resources will potentially harm the climate objective addressed in the Paris Agreement in which The Netherlands, among other countries, have been participating.

Acknowledging the importance of household consumption on the environment, a joint research team funded by the National Science Foundation named INFEWS (Innovations at the Nexus of Food, Energy, and Water Systems) is commissioning this research project to investigate policy measures to sustainably reduce greenhouse gas emission concerning Dutch household food, energy, and water consumption sector. The main objective of this research is to obtain insight on the dynamics and interrelations of Dutch household water, energy, and food consumption; and to develop policy recommendations based on the insight toward reducing the direct and indirect greenhouse gas emissions (GHG) level associated with the household consumption over time in the Netherlands.

To achieve this objective, this research mainly utilizes data-driven exploratory modeling approach in which the interrelations of water, energy, and food consumption system are modeled and simulated over time, while acknowledging the plausible parametric and structural uncertainties natural to the state of modeled subsystems. System Dynamics methodology is used to conceptualize the causal relations among the relevant subsystems and to computationally develop the model in a form of stock-flow diagram. Based on the developed model, the Exploratory Modeling and Analysis methodology is used to explore the model within the associated uncertainties. Through these methods, two types of policy frameworks can be respectively tested and explored. The first one consists of the policy approaches within household consumption domain. The second one consists of the plausible policy options outside of the household consumption domain which are relevant to improve the GHG indicator.

A System Dynamics study towards the potential effects of interventions on the food waste produced by households. Households are a major contributor to the waste of food within the Netherlands. There are negative consequences regarding the waste of food. A causal relation diagram is created, a set of interventions is defined, and based upon a System Dynamics model is created. Based upon the simulations, it is concluded that the process in which food is wasted is fragmented. Reducing the waste of food effectively demands combining multiple interventions. There are two important aspects within a household when multiple interventions are applied. Interventions should focus on the 'willingness' and on the 'knowhow' within a household. Focusing on both aspects results in a synergy. The combined effects of the interventions is bigger than the individual effects accumulated.

The environmental and social impact of the energy generation and distribution industry on the biosphere is negative or unknown due to a lack of supply chain transparency. For electricity and gas distribution system operators (DSOs), the opportunity to contribute significantly to more environmental and social sustainable development in the energy industry is large. DSOs own and use large amounts capital assets that consist of finite materials, are focal actors in large global supply chains, and are able to make large purchases due to their public role and their financial means. The long (20-80 years) useful lifetime of infrastructure assets puts great emphasis on asset risk management, and operation and maintenance strategies to optimize technical and economic performance. As a result, the purchase decision of the assets mainly focusses on technical and economic requirements and criteria. This purchase moment can be considered to be the start of the assets’ life cycle and its outcome thereby determines to a large extend the design and use of the asset. To reduce the social and environmental impact of the asset, environmental and social demands must thus be incorporated in this procurement process. Currently, a matured approach to sustainable procurement is unavailable within the infrastructure industry. Alliander, a large Dutch DSO, attempts to include sustainability as an addition to the existing procurement process. However, procedural integration in the existing processes is required to successfully and effectively integrate sustainability in asset procurement. Infrastructure asset management, and DSO asset management in particular, are embedded in a risk-averse culture with high emphasis on technical, legal ,and economic values. Introducing innovative and more sustainable asset alternatives in daily decisions generates resistance among actors as no compromise on existing technical and economic values is desirable. This actor resistance needs to be overcome as procurement decisions are made by a team of actors. Decisions therefore require group consensus rather than actors that unwillingly agree to the decision. The long asset lifetimes, dispersed and interdisciplinary knowledge, and uncertain need for specific DSO asset functions and services in the future complicates optimal decision-making even further. The infrastructure procurement process is an assessment process in which multiple suppliers and their asset alternatives are appraised using a large set of demands. By adding environmental and social sustainability demands to this assessment, procurement becomes partly value-based. Actor-dependent prioritization of demands leads to divergent and/or contradictory objectives. The subsequent trade-offs between individual (actor) and mutual (organizational) objectives are therefore embedded in a multitude of different interests, perspectives, and values. To overcome this decision-making difficulty, effective and goal-oriented collaboration among the actors that are involved is required. Multiple scientific and corporate sustainability assessment and decision frameworks are currently available. However, a proven approach that can facilitate interdisciplinary group decision-making in the procurement processes is not yet available. A general sustainable procurement policy needs to be developed to provide formal guidance in the complicated procurement. Developing such a policy will provide an answer to the research question in this report:
How can sustainability goals be incorporated in the multi-actor decision-making process of infrastructure asset procurement by Dutch distribution system operator Alliander?
To develop the sustainable procurement policy and answer this question, four procedures were followed. Firstly, problems related to sustainability in (public) procurement were explored via an explorative and systematic literature study, as well as 23 informal expert interviews. Policy development goals, constraints, and criteria were taken from this first procedure into the second procedure, namely: the development of the policy. Developing a robust and suitable policy was done by merging the insights from the following five knowledge areas: sustainable development, asset life cycle management, multi-actor networks, multi-criteria decision-making, and (sustainable) procurement. The third procedure validated the policy through two case study applications at Alliander. Insights from these practical cases and the consultation of Alliander experts served as input for the final procedure: the evaluation of the policy. In this procedure, the added value and compliance with the policy constraints and criteria were evaluated.

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Figure 1 Sustainable procurement policy overview

The resulting policy, depicted in Figure 1, discusses the methodological steps that are required for successful sustainability-focused procurement in eight sequential phases. The core elements of this methodology are four-fold: (I) Collective formulation of procurement goals and the function of the asset; (II) Formulating technical, economic, environmental, and social demands throughout the complete asset material life cycle; (III) Expanding the perceived added value concept from technical and economic values to equally important environmental and social values; and (IV) Establishing unanimous consensus in decisions with diverging actor priorities to put the interests of the organization above those of individual actors, and to make long-term actor collaboration possible. In addition to the methodology, a decision support tool was developed, based on the matured Analytic Hierarchy Process and pairwise comparison weighting method, which facilitates essential dialogue within the multidisciplinary procurement team throughout the procurement process. The tool offers a structured and logic-based decision-making approach: actor-specific value judgements, drivers, and priorities are made explicit by transparent documentation and visualization of individual criteria weight distributions. The differences between individual and group priorities regarding asset demands hereby become clear. The actor dialogue can thereby be limited to major differences in actor priorities rather than discussing numerous minor or non-existent differences. Future scientific research is required on how to deal with interrelations between high amounts of procurement demands from different knowledge disciplines. To make sustainable procurement business-as-usual within the infrastructure industry, committed and inspiring leadership is required. A crucial step is the acknowledgement and of environmental and social added value, in addition to the current appreciation of technical and economic added value. Expanding the concept of added value creation, and thereby the core values of infrastructure organizations, makes sustainable procurement more accepted within asset management and incentivises supply chain actors throughout the supply chain to act more sustainably.

The United Nations' Sustainable Development Goals (SDG) form potentially a great communications framework for financial institutions to report on their indirect environmental sustainability performance. To date, however, no serious effort has been made to specifically assess a financial institution's indirect impact - its impact through the balance-sheets - in terms of the SDGs. Therefore, this thesis sets out to address the following objective: To introduce a prototype system, also referred to as a tool, which is capable of incorporating components of the SDGs so that they may form the criteria based on which financial institutions’ core business activity, their balance-sheets, can be assessed in terms of environmental sustainability. The result of this thesis is a prototype tool programmed in Microsoft's VBA language, aimed to fulfill this objective.

Although the motivational capacity of serious games is well supported in theory, few experimental studies have been conducted so far. This study contributes to this knowledge gap by using a serious game to try and increase the currently low student retention in Massive Open Online Courses (MOOCs). For this, a serious game was specifically designed to influence factors that have shown to influence student retention in other MOOCs. A randomized post-test only control group experimental design was used, in which the impact of the serious game on student retention was evaluated with quantitative and qualitative data from questionnaires and the edX MOOC platform. While it was found that the serious game had a negative impact on the intrinsic motivation of students, it appeared that intrinsic motivation did not influence student retention in this MOOC, therewith explaining why no difference in student retention was observed between the control group and game group. This shows that in order to improve student retention in MOOCs with serious games, further research on factors affecting student retention in MOOCs is required first.