This thesis investigates how demographic and behavioural factors shape public support for sustainable mobility policies in the Netherlands. Motivated by climate ambitions such as the European Green Deal and the Dutch Climate Agreement, it recognises that technical solutions alone are insufficient. Public acceptance and behavioural change are essential to achieving a successful mobility transition. By focusing on which social groups support sustainable policies, and why, the study offers valuable insights for inclusive, context-sensitive policymaking.

A mixed-methods approach was adopted. The research draws on data from a large-scale Participatory Value Evaluation (PVE) involving 5,643 Dutch participants. The study first analyses quantitative data, applying correlation analysis, policy preference ranking, and K-means clustering to identify patterns in support. This is followed by qualitative thematic analysis of participants’ open-ended responses to capture underlying motivations.

The literature review provided the theoretical grounding, highlighting two key behavioural models: the Theory of Planned Behaviour (TPB) and the Norm Activation Model (NAM). These frameworks explore how attitudes, social norms, personal responsibility, and behavioural control shape mobility behaviour. The literature also classifies policy strategies as hedonic, gain-driven, or normative, and categorises tools as “carrots” (incentives), “sticks” (regulations), and “sermons” (information).

Key findings show that support for sustainable mobility varies significantly across demographic groups and mobility behaviours. Younger, higher-educated, and urban residents are more supportive of sustainability goals, while older, lower-educated, and rural populations tend to be less supportive. Behaviourally, frequent car use correlates negatively with policy support, while regular users of public transport and bicycles are more supportive. These relationships underscore how lived mobility experiences shape public attitudes.

Three distinct respondent clusters were identified:
• Suburban & Traditional: Older, moderately educated, frequent car users with moderate support for sustainability.
• Urban & Green: Young, highly educated urban residents using public transport and bicycles, showing strong support.
• Lower Educated & Motorist: Older, rural, lower-educated respondents with low public transport or cycling use and minimal support.

Policy preference analysis revealed broad support for measures that improve and subsidise public transport. These policies were favoured across all groups, especially by urban and cost-conscious respondents. Conversely, policies that raise fuel prices were unpopular across all groups. Young and urban participants supported policies related to cycling infrastructure and transit-oriented housing. Lower-educated groups preferred car-supportive policies like electric vehicle subsidies.

The qualitative analysis reinforced these findings. Supportive arguments commonly cited climate and environmental protection, the need to encourage sustainable travel, and the role of government leadership. Opposition was often rooted in scepticism, perceived overemphasis on sustainability, cost concerns, and mistrust in government.

The thesis concludes that effective sustainable mobility policies must be tailored to diverse societal groups. Policymakers should frame policies in ways that emphasise affordability, safety, and convenience. Information campaigns grounded in TPB and NAM principles can increase receptivity, especially among less supportive populations. Overall, the integration of demographic, behavioural, and motivational insights can enhance both the fairness and effectiveness of the mobility transition.

Mobility systems in municipalities will undergo significant changes over the next years. With increasing car usage among the Dutch population, streets become more crowded. However, with the need to comply with the Paris Climate Agreement, cities must redesign their streets and neighbourhoods to be less car dependent. Given the rising demand for public involvement in decision- making and the introduction of new environmental act, municipalities are legally required to engage citizens, entrepreneurs, and organizations in shaping public spaces. Therefore, it is essential for municipalities to consider how to involve the public to meet these impending legal obligations, especially on emotionally charged topics like parking. In the realm of public participation, numerous new methods are emerging. One such method is the Participatory Value Evaluation Method (PVE). A new research opportunity on the PVE lies between two levels, focusing on a 'street-level' issue on a larger scale.

The central research question in this thesis is: "To what extent does the use of PVE as a participatory method enhance the decision-making process within the mobility sector in Gouda?"

A case study method was used to assess PVE's added value, comparing Gouda with three other case studies using different participation methods on similar policy issues. An interpretivist assessment, involving document analysis and semi-structured interviews, evaluated the ten components of effective participation. The results indicated that PVE is more effective than other methods in achieving policymakers' goals, making participants feel heard, and managing a chaotic process. However, it scored lower in accessibility and inclusivity, with a quarter of participants dropping out and underrepresentation of those with practical education. Some participants felt constrained by the online format, feeling less free to express their views or influenced by the method.

Future research should explore participants' perceptions of being guided by online or deliberative methods and investigate dropout rates within PVE and other methods to improve retention and inclusivity. From a practitioner's perspective, aligning participation goals with policies and understanding which methods best achieve specific goals are essential. Policymakers thereby should reflect on how methods contribute to goal attainment to design more efficient processes.

This master’s thesis explores the future of citizen participation in public decision-making in the Netherlands. Citizen participation is regarded as an important aspect of the Dutch democracy since it is used to gain insights into what the citizens consider important. Currently, there is scarce scientific literature on the future of citizen participation. Besides most literature focuses on a specific case or method instead of the broader system of citizen participation. This thesis addresses this research gap by exploring scientific literature and interviewing thirteen leading Dutch practitioners.

Based on the resulting insights, it can be derived how citizen participation can be improved in the future. The findings indicate that digitalization and the rise of co-creation are two main developments that are going to impact citizen participation in the future. Policymakers should anticipate on these developments by adapting to digital developments and a changing participation need of citizens instead of ignoring it. Important challenges are the communication between policymakers and citizens and the lack of inclusiveness. These challenges can be addressed by using different participation methods that align with the needs of different groups of citizens, and encourage open and clear communication from policymakers towards citizens about the participation process. Another relevant finding is that practitioners emphasise the normative and substantive objectives of citizen participation, while instrumental objectives are barely identified.

This thesis emphasises the importance of discussing the role of citizens in different participation processes. Disagreement among practitioners about the general purpose and function of citizen participation in the Dutch democracy is not likely to be resolved. Hence it is important to keep addressing this during participation processes, because practitioners do agree upon the fact that citizen participation has added value.

Limitations of this research include the validity and the generalisability of this research. Validity can be anticipated on by conducting more interviews and a more extensive literature research. The generalisability can be improved by conducting similar research in different context and from the perspective of citizens instead of policymakers.

Key recommendations for practitioners include the fact that policymakers should be aware of the value of citizen participation, and they should experiment with (combining) different participation methods.

The transportation system in Israel is facing a crisis due to its heavy reliance on private vehicles. To shift towards sustainable mobility, improving public transport quality in the Tel Aviv metropolitan area is crucial. This research investigates the preferences of Tel Aviv citizens regarding transport projects aimed at enhancing public transport and encouraging alternative mobility methods. The study utilizes the Participatory Value Evaluation (PVE) method, where citizens curate their preferred project portfolio within a limited budget, assuming decision-making authority. The research also explores the face validity of PVE in Israel, considering the distinct governance perception in the country. This research provides valuable insights into Tel Aviv citizens' preferences for transport projects that enhance public transport quality and promote sustainable mobility. Through the application of PVE, the study reveals project preferences, face validity perceptions, and potential avenues for future research, contributing to the advancement of sustainable transport policies and decision-making processes in Israel.

With the increasing need for entangling the complexity around worldwide crises and transitions, the transdisciplinary collaboration between governmental organisations, multidisciplinary academic institutions and companies is becoming increasingly crucial. Involving citizens within the policy-making processes regarding those crises and transitions already led to various positive outcomes, for example increased awareness, understanding of policies, new innovations, and acceptance of decision-making. This participatory involvement is now effectively executed through the implementation of Participatory Value Evaluations (PVEs). Since HEIs need to fulfill a Third Mission, involving employees within their policy making might lead to several benefits as well. This master thesis explores the added value of applying a PVE within the higher education institution (HEI) context, analysing both the perspectives of employees and the policymakers, and therefore provide valuable insights for future implementations of PVEs within professional bureaucracies. The results show a pivotal role for using the PVE approach within HEIs, compared to the citizen-to-government context. However, further research is needed to establish design principles and preconditions around the PVE approach within a HEI.

Climate change is a topic being addressed by many countries worldwide. One of the most recent treaties is the Paris Agreement signed in 2015 by 196 parties, where they agree on a common goal: restrict global warming to be climate-neutral by 2050. Peru by being one of the signing parties that played a relevant role before and during the Paris Agreement discussions, submitted their Nationally Determined Contributions in 2016.

Even when climate policies are implemented, their success is found to be related to society's acceptance of them. Moreover, citizens' support for policies is related to the alignment of such policies with their preferences, and research shows that citizens' preferences are based on their values. Additionally, it is known that there are balanced tensions between values, which are translated into trade-offs. Different participatory methods have been used for preference elicitation. In Peru, however, it has been found that the processes followed have an apparent entry barrier for individuals, therefore, other methods can be explored. A recently developed method is Participatory Value Evaluation, in which the participants are asked to make a selection among a set of alternatives while considering its effects and one or more restrictions. This method has been mainly applied in Europe, with some of them being focused on climate change subjects. Based on this the primary and secondary research questions are defined as:

1. How do Peruvian citizens trade-off climate change mitigation measures among the two most polluting sectors, from a set of policy alternatives?
2. How is Participatory Value Evaluation perceived by Peruvian citizens and how does it differ from Dutch citizens' perception?

Based on the literature review done regarding the method, a Participatory Value Evaluation experiment is designed using the knowledge gathered from the research on the climate policy situation in Peru and its region. This includes a total of six policy measures part of the country's two most polluting sectors (i.e., Energy and Agriculture, Forestry and Other Land Use). The designed Participatory Value Evaluation is conducted between July 3rd and July 17th, 2023.

It can be concluded that Peruvian citizens prefer policy alternatives that yield positive and direct environmental outcomes, especially when accompanied by minimal monetary expense. Citizens would trade off a higher cost for even a moderate reduction in harmful emissions, provided the health benefits are explicitly articulated. The inclination to make a trade-off between cost and emission reduction diminishes when health and environmental benefits are either not explicitly outlined or fail to reach a significant threshold. Finally, based on the preference patterns of the individuals, four distinct groups were identified. These are mainly dependent on their considerations of the effects each policy alternative may bring. These insights reinforce the importance individuals across different education levels, attribute to the environment, particularly regarding deforestation.

Regarding the method, it can be concluded that Peruvian citizens had a positive and favourable experience when participating in the PVE for climate change mitigation. In a similar manner to the Dutch citizens, Peruvian individuals exhibited a positive perception of the method. In like manner, a majority of individuals believed it is a good method to involve citizens in governmental decisions regarding climate change policies. These insights seem to foster an inclination for continued engagement and provide their opinion on other subjects relevant to Peruvian society. Equally important, citizens would appreciate the real repercussions resulting from their input within the decision-making process.

The first registered infection with the COVID-19 virus occurred in China at the end of 2019. The virus spread all over the world, turning a single infection into a pandemic. Most countries implemented policies to limit the spread of the virus. In general, these policies can be divided into pharmaceutical and non-pharmaceutical interventions. Vaccines are pharmaceutical interventions. Examples of nonpharmaceutical interventions are temporary closure of restaurants and bars or a limit to the number of people that are allowed to gather for social events. Although, these non-pharmaceutical interventions were effective in slowing down the spread of the COVID-19 virus, they also severely affected people’s social and economic life. For example, freelancers who worked in restaurants and bars lost their income and students experienced a decrease in mental health due to the lack of social engagement. These societal impacts of COVID-19 policy gradually reduced the public support and adherence to these COVID-19 measures over the course of different pandemic waves. Measuring how people weigh the societal impacts of COVID-19 policy during these waves, provides interesting insights that can improve the effectiveness of pandemic policies for a future pandemic. A way to measure how people weigh the societal impacts of COVID-19 policy during different waves of the pandemic is by conducting Discrete Choice Experiments (DCE). These DCEs are often analyzed with Multinomial Logit (MNL) models. The MNL model is able to quantify the relative importance of different societal impacts for the population as a whole. However, there also exist other models, such as the Mixed Logit (ML) model and Latent Class (LC) model, and different types of DCEs, such as the labeled and unlabeled DCE, that have their own advantages and disadvantages in eliciting the relative importance of societal
impacts during different phases of the pandemic. For instance, ML models are able to elicit how preference heterogeneity is distributed among individuals and the LC model is able to divide people into different classes with their own preferences. Also, the labeled DCE is able to measure how people weigh societal impacts when the COVID-19 measures that cause these impacts are explicitly mentioned. Unlabeled DCEs do not explicitly mention these measures, but only weigh the societal impacts.
Over the course of the end of 2022 and the beginning of 2023, the pandemic transitioned into an endemic. Therefore, this study will not only evaluate the advantages and disadvantages of using these models and DCEs during the pandemic, but also during the endemic, by asking the following question: What are the (dis)-advantages of using ML and LC models over MNL models to analyze (un)-labeled DCEs that weigh societal impacts of COVID-19 policy during the pandemic and endemic? The eventual goal of this study is to find out where the added value lies of ML and LC models compared to MNL models and labeled compared to unlabeled DCEs in informing future pandemic policy makers during different pandemic waves and the endemic. To answer the main research question, this study formulated three subresearch questions. The first subresearch question is defined as follows: What are the differences in using ML, LC and MNL models to analyze (un)-labeled DCEs that weigh societal impacts of COVID-19 policy during the pandemic according to the literature? To answer this question, the study conducted a literature review on the results obtained from labeled and unlabeled DCEs with MNL, ML and LC models in different waves of the pandemic. In the second part of the study, the following subresearch question is addressed: What are the differences between the results produced by ML, LC and MNL models obtained from (un)-labeled DCEs that weigh societal impacts of COVID-19 policy during the endemic? This question is answered by conducting a labeled and unlabeled Discrete Choice Experiment during the endemic. The third and last sub research question asks: What are the (dis)-advantages of using ML, LC and MNL models to analyze (un)-labeled DCEs that weigh societal impacts of COVID-19 policy during the pandemic and endemic according to experts? To answer this question, three expert interviews were conducted.
The results of this study show that the main advantage of the ML model is its ability to test for the existence of preference heterogeneity among individuals in a sample. This can help to check the reliability of the estimates produced by the MNL model. The reason for this is that the existence of preference heterogeneity means that the estimates of the MNL model do not adequately represent the majority of the sample, if the heterogeneity is high. Additionally, the existence of preference heterogeneity is a reason for further research into the origins of this heterogeneity. In this case, the LC model is able to estimate different classes with different preferences and characteristics that represent different subgroups in society. Providing such a classification is the main advantage of the LC model. The main disadvantage of the ML model is that it is time consuming to estimate the model.
For the LC model the main disadvantage is its sensitivity to changes in covariates and initial values. With regards to the DCEs, the study shows that the main advantage of the labeled DCE is its ability to measure the effect of COVID-19 measures on how respondents weigh societal impacts. For the unlabeled DCE, the main advantage is its ability to measure how people view different societal impacts without explicitly mentioning the COVID-19 measures that caused these impacts. With regards to the added value of DCEs for informing future pandemic policy in different waves of a pandemic and in an endemic, the study shows that unlabeled DCEs are most suitable to give a baseline estimation of the preference for societal impacts at the beginning of a pandemic. So that, these insights can be taken into consideration when the first pandemic policy package is created. Further, the study shows that labeled DCEs should be applied during and in between pandemic waves to evaluate and adjust implemented pandemic policy. Finally, a labeled DCE can be implemented during the endemic, that follows the pandemic, to evaluate the impact of COVID-19 measures. The insights obtained from this can help to inform a future pandemic. With regards to the added value of the ML and LC model in informing future pandemic policy in different waves of the pandemic and the endemic, the study shows that the ML model can be used to test the reliability of the mean coefficients of important societal impact attributes. This helps to verify if a specific societal impact attribute is a good target for mitigation with generic pandemic policy during pandemic waves. In between pandemic waves, the LC model can be used to elicit the origin of preference heterogeneity among people in the sample for different societal impact attributes. These insights can be used to create customized pandemic policy with increased public support and adherence for when a next pandemic wave hits.
The most important limitation of this research is the lack of unlabeled DCEs from both the pandemic and endemic and the lack of labeled DCEs from the endemic that are included in the literature review. A drawback of the included DCEs is that these experiments do not include exactly the same societal impact attributes and that these experiments are conducted during different waves of the pandemic in different countries. These factors make it difficult to compare the results of the studies. Also, this thesis recommends that future studies conduct further research on the societal impacts of COVID-19 measures with models that are extensions of the models that are used in this study, such as the logit or probit model and the LC model with distributed preference coefficients. Furthermore, it would be valuable to analyze the societal impacts of COVID-19 measures with models outside the domain of choice modeling, such as data driven models. Furthermore, this study emphasizes that a lot of research can be done into how and by whom the insights of this research should be implemented in the pandemic policy decision making process. For instance, questions for future research could be, should the insights of this study function as advice for the creation of pandemic policy or as directive? And does the government or the National Institute of Public Health decide upon this?

A relatively novel approach of public participation is the Participatory Value Evaluation (PVE) in which a dilemma of a policymaker is provided to citizens (Mouter, Shortall, et al., 2021). In a PVE, citizens face a realistic choice task in which the policy dilemma is explained to the participant (Hernandez et al., 2023). Participants have to divide a set budget over several options.
Currently, there are three main methods for analyzing PVE datasets: descriptive statistics, Latent Class Cluster Analysis (LCCA) and choice modelling. A tool that can identify relations between participant features and their preferences can provide additional insights to policy makers and researchers. If machine learning is to be applied to PVEs, it could be used to predict choice task outcomes based on features of the participant. However, the opaque algorithms in machine learning can make it difficult for a human to understand how the results were produced, which can make it difficult to interpret.
The field of Explainable AI has risen as a response to this issue: the aim of explainable AI methods is to give insight in the inner workings of the machine learning algorithm. An example we further research is SHAP (SHapley Additive exPlanations). This thesis focuses on the implementation of SHAP in PVE analysis, under the following research question: ”What additional insights does machine learning with SHAP provide for PVE quantitative analysis compared to conventional methods?”
To answer the research question, a case study is performed by applying the SHAP method to the PVE of the National Programme Regional Energy Strategy (NP RES). A Random Forest machine learning model provided the best fit to the dataset. When these results of SHAP analysis of the random forest model are compared to the results of the LCCA, it is apparent that SHAP provides more insights (26 versus 11). SHAP is able to reveal patterns on a smaller scale than LCCA. The resulting insights are different to the results of the LCCA analysis. Many of the insights from SHAP analysis are not seen in the LCCA.
Overall, it can be concluded that applying SHAP results in new insights that were not found with other methods used on the NP RES PVE case. This study has shown that SHAP can be a relevant tool to gather insights about the PVE data and the differences among participants. It can gather individual effects of demographic variables on the choices participants make. Therefore it can lead to more and refined policy advice to governments.
PVE experiments are still in their infancy. The ability of SHAP to provide additional insights into PVE experiments within this thesis provides an incentive to further use SHAP in PVE experiments, including academic PVEs. SHAP predominantly provides insights into the relation between participant characteristics and their valuation of options in the choice task, allowing for the diversity of groups within the participant population to be directly addressed. This direct address broadens the range of results and does justice to the diversity of our society.

The major social issues currently faced by the Dutch government require the involvement of all stakeholders early in the policy-making process. A Participatory Value Evaluation (PVE) is a public participation method in which citizens can advise the government on a specific decision-making problem. The PVE information is becoming increasingly complex these days. This complexity makes it more challenging to process and accurately present this information to policymakers. Therefore, ensuring that this complexity of citizens’ opinions is preserved and communicated to policy-makers is essential. The PVE yields two types of information; the selection of policy options in the choice task generates quantitative data, while the motivations underlying the choices provide qualitative data. It is common to estimate a quantitative Latent Class Cluster Analysis (LCCA) model to get an overview of the population perspectives emerging from the PVE, but this has never been done with qualitative data, while the written arguments reflect the ideas, concerns, and values of PVE participants. Therefore, to investigate this knowledge gap, the following research question has been formulated:

What is the added value for policy-making of including the qualitative arguments from a Participatory Value Evaluation alongside the quantitative data in the Latent Class Cluster Analysis?

The Participatory Value Evaluation of the National Environmental Program (NMP) has been used as the case for this research. The qualitative arguments were coded with Qualitative Content Analysis (QCA) to include them in the LCCA.

It can be concluded that in the case of the NMP PVE, there was added value in including qualitative arguments in the LCCA. Not in the way of adjusting policies but to adjust governmental communication strategies accordingly. Additionally, because the complexity of citizens' opinions is preserved and communicated to policy-makers, this can lead to better policies that are more responsive to citizens' needs and concerns. Finally, citizens may feel more recognised and heard when the qualitative data is analysed comprehensively.\\

Next to this societal impact, this research also has an academic impact. It has never been tried to include the qualitative data of a PVE in an LCCA. This research has answered the curiosity of PVE researchers to analyse qualitative arguments more thoroughly. From a broader perspective, there was a lack of literature on a method to include qualitative data in an LCCA and an assessment of its added value. This study revealed that a qualitative LCCA model can serve as an additional validation step of the quantitative LCCA model.

The following recommendations are proposed to further optimise this new method: 1) Explore ways to standardise the QCA method, 2) Investigate the possibilities of automated QCA methods to save time, 3) Test the qualitative method on multiple cases and 4) Explore how governmental communication strategies can be tailored based on qualitative data to reach different subgroups effectively.

To mitigate climate change by transforming the energy system citizen involvement is crucial. Citizen involvement can help achieve these goals as well as accelerate the transition, by harnessing local knowledge for the improvement of plans, creating a support base and the opportunity for citizens to come up with their own initiatives. Therefore this research is evaluating the preference of citizen segments for different participation methods in the energy transition, for different governance levels. A Latent Class Cluster Analysis (LCCA) is applied to data received from a survey, resulting in a classification of respondents based on attitudes towards participation, which can be identified by some characteristics resulting from demographic values and attitudes towards climate change. Additional interviews with policy-makers and citizen representatives identified challenges and opportunities for the integration of citizens' attitudes towards participation and participation processes in The Netherlands. Primary conclusions are that there are no fundamental differences in the participation methods applied to different governance levels, just as the preferences themselves do not vary significantly. Moreover, the majority of citizens appreciate being involved with participation. Therefore, the effort for participation can result in automatic alignment between the preferences and central and decentral participation. One of the main barriers identified is the disparity between the system world, where policies are formulated and the energy transition is planned, and the living world, which represents how citizens experience and perceive these changes. Opportunities for closing this gap are sharing results of participation processes with different governance levels, improving information provided to citizens and improving connection with the community by becoming more visible and organizing more participation.

The Ministry of Infrastructure and Water Management, responsible for major infrastructure projects in the Netherlands, is exploring methods to incorporate well-being in its project evaluations and designs. To address the limitations of expressing well-being in monetary terms, a new evaluation method called Participatory Value Evaluation (PVE) has been developed. PVE engages citizens in policy decisions, mapping their values and concerns, and providing a more inclusive approach to decision-making. This research focuses on investigating the added value of the PVE when applied to national infrastructure projects, with a case study of the Lelylijn project, a proposed railway line connecting regions in the Netherlands. The research addresses three key areas: where the PVE can be applied in the project process and its perceived added value in the research phase, how policymakers experience the PVE, and how participants perceive their involvement in the PVE. Through interviews with policymakers and analysis of PVE responses, the study found that the PVE has the potential to incorporate public values into decision-making, enhance the quality of decisions, and promote accessibility and inclusivity. Policymakers perceive the PVE as valuable in understanding public opinion comprehensively and improving decision-making. Participants appreciate the PVE's accessibility and educational aspect but suggest improvements in question design and representation of diverse groups. In conclusion, this research highlights the potential benefits of using the PVE in national infrastructure projects, providing valuable insights into its impact on decision-making and public involvement. The study contributes to the growing emphasis on well-being in policy decisions and offers important considerations for the effective implementation of the PVE in future projects.

Train stations are developed by rail companies, for the benefit of travellers. Choices and trade-offs must be made. However, there are no guidelines on how to approach these trade-offs. This study aims to find out to what extent consulting train travellers from the station developer’s perspective contributes to making trade-offs in the development of train stations. We investigate how train travellers make a trade-off from the perspective of the station developer in comparison to professional station developers. Therefore, a consultation method is established using a qualitative and quantitative survey. The first part involves a trade-off in which the respondents have to distribute 100 points, representing the total available space, over eight access/egress facilities. It appears that both train travellers and station developers assign an increase or decrease in space to the same facilities. At the same time, we gain insight into how respondents approach the trade-off. Also, insight has been gained into a possible consultation method by which the making of trade-offs by train travellers and station developers can be investigated. For follow-up research, it is recommended to explore this approach for other trade-offs and in other contexts.

With what objectives do policymakers make transport policy? This fundamental question is subject to a paradigm shift within transport policymaking in the Netherlands. There is an increasing call to let go of the predominant focus on economic well-being and consider a broader notion of well-being instead. However, how exactly this 'broad prosperity' should be operationalized and integrated within ex-ante policy evaluations remains a challenge.

Therefore this thesis aims to aid this integration of broad prosperity, by suggesting an alternative approach to operationalizing broad prosperity. One that moves away from the content (i.e. what should it include) and towards the process (i.e. how should it be determined). By approaching broad prosperity as a context-dependent and normative concept, effective value-oriented participation becomes the vehicle to integrate broad prosperity into ex-ante policy evaluations. Through literature review and expert validation, this approach is translated into a practical framework with 5 categories of 11 process-related criteria. It is suggested that these criteria together constitute an effective integration of broad prosperity into ex-ante policy evaluations.

By performing desk research and semi-structured interviews, this practical framework is then applied to the ex-ante evaluations of two Dutch transport projects: the Meerjarenprogramma Infrastructuur, Ruimte en Transport (MIRT) projects Oeververbindingen Rotterdam and A15 Papendrecht-Gorinchem. The results suggest that while broad prosperity is being used to some extent in Dutch ex-ante policy evaluations, there is still room for improvement. The great efforts to reduce the information asymmetry among participants, appreciate the participants' knowledge, and ensure all participants' contributions within MIRT processes, suggest that the projects are on their way to integrating broad prosperity. The main areas for improvement include the limited influence of local stakeholders on project objectives and scope, the transport-oriented scope of the (MIRT) process, and the extent of representative value-oriented participation.

Future research could examine how to further improve in these areas, address the challenges of a process-based approach, improve the practical framework, or expand the data collection. Overall, a process-based approach to broad prosperity that prioritizes effective value-oriented participation is a promising direction for a more holistic transport system that better serves everyone's values.

Energy poverty is an increasingly important issue. While vulnerable households are especially at risk in the energy transition, energy poverty effects of the transition are unknown. In Delft, a district heating network based on geothermal energy is planned. The distributive justice aspects of heat networks in the heating transition remain largely unexplored. In this master's thesis, an agent-based model is developed to explore inequalities in energy poverty and access to energy that might arise from the switch to a heat network. The thesis aims to explore the scenarios in which these inequalities can occur and for what types of households, and to determine policy interventions that contribute to a just and inclusive heat network. The extent and distribution of energy poverty and heat network access was explored in multiple energy price contexts, in combination with the following interventions: lower energy tax for gas use below average use and high energy tax for gas use above average use; vouchers to cover upfront costs of heat network connection; renovation of dwellings with poor energetic quality; and awareness campaigns to reduce energy use. The results show that the current district heating pricing structure increases inequality. These costs should be shifted from the high fixed costs to the variable costs to reduce energy poverty in households with low energy consumption. In addition, it was found that building renovation could decrease inequality and energy poverty. Recommendations are made for policy, research and the development of new energy poverty indicators to reduce energy poverty and inequality in the energy transition.

This study evaluates the face validity of the Participatory Value Evaluation (PVE) method. The PVE is an online method that enables participation for a large group of participants. This method is designed for citizens to evaluate a complex situation from a policy makers point of view. If a consultation lacks face validity, there is a likelihood that the results obtained from this instrument provide false information and lead to decisions that are misleading. During this research face validity is assessed by a four-step mixed methods approach. First, a framework to assess face validity in the PVE method is drawn up and applied in a case study of the Schiphol Environmental Council. The goal of this case study is to research by means of a PVE consultation how to improve the participation and information facilities for local residents, which are the respondents, around Schiphol Airport. The framework consists out of the categories clarity, unambiguity, relevancy, readability and completeness. Second, the results of this framework are applied in an experiment. From this experiment it becomes clear that there is no difference in the evaluation of face validity by respondents between a ‘sliders’ choice task and a ‘points’ PVE. However, respondents are more indifferent towards the ‘sliders’ PVE. On average, clarity and unambiguity are evaluated the lowest and readability the highest. Third, comparing to other previous PVE case studies that includes elements of face validity, it becomes clear that the four properties impact on personal life, the respondents, the platform and who is in charge influence the differences in the evaluation of face validity between different case studies. With the three face validity categories included in previous case studies, benchmarks are established. If the goal is to score high on the clarity category, the aim should be to achieve an average evaluation score above 3,67 for clarity, above 3,88 for relevancy and around or higher than 4,11 for completeness on a five-point Likert scale. Fourth, the established framework from literature is compared with concerns about face validity in practice. In addition to the five categories, feasibility turns out to be a practical concern. It is remarkable from the results that 18- to 34-year-olds and people with a low level of education generally rate the face validity categories lower. Therefore, a recommendation for further research is to investigate how the face validity of these groups can possibly be increased and what their needs are regarding face validity.

In order to understand the impact of new infrastructure projects, appraisal tools are used to estimate the impact it will have on society. Infrastructure is a key part of society, enabling and disabling society to work and live, playing a vital part in everyone’s lives. Former studies by Annema, Frenken, et al. (2017), Niek Mouter (2017b) and Eliasson and Lundberg (2012) have researched how appraisal tools and especially CBA are used by decision-makers to get to a decision. Other research by Van Wee (2012) has shown the ethical problems which arise when using CBA as an appraisal tool. However, there has not been any research on the impact appraisal tools have on the process and outcome of infrastructure projects. This thesis will provide insights in the impact of appraisal tools on social and process equitability. By using a framework by D. Levinson (2002), case studies, interviews and policy documents, the incorporation of social and process equity factors can be depicted per country. Results show that the Dutch appraisal tools do not incorporate a wide array of dimensions and stratifications, which are depicted in literature. This lack of information results in social inequitable decision-making as well as inequitable outcomes due to negligence of not incorporating more dimensions. Two reasons can be found for this Dutch approach, namely the funding reason which results in solution-oriented design, and the general Dutch mindset of seeing and treating everyone as equal, resulting in inequitable outcomes due to not taking differences into account. The Dutch process equity is boosted by its near-perfect transparency in terms of accessibility of documents, but hurt by the lack of participation and the lack of impact when participation is present. The United Kingdom on the other hand has an elaborate appraisal process which analyses a much wider variety of dimensions and stratifications. However, due to a solution-oriented process design, the alternatives for a project have already been shot down when the social impact information is available to a decision-maker. Another reason which hurts the social equitability in the United Kingdom is the fact that it is necessary to have a high value-for-money project to receive funding, resulting in ignoring of social impact analyses due to this economic focus. In terms of process equity, the United Kingdom has a solid consultation process which is used consistently. However, a lack of transparency in the process with regard to decisions made and the availability of (policy) documents results in poor process equity overall. This thesis shows that social and process equity cannot be improved by simply adding tools which gather social impact information to the appraisal process. Political play, the drift for efficiency and cultural differences per country makes it difficult to create a single strategy to improve equity in appraisal processes. However, by improving transparency, focusing on getting a problem-oriented design and using a third party as a validation for the incorporation of equity factors, it is possible to improve the inclusion of equity factors in appraisal processes. This thesis can be used as a basis for analysing and understanding appraisal processes in other countries.

This thesis aims to support the design and implementation of energy-secure thermal energy communities (TEC) by investigating their technical, behavioural and institutional settings through a collective action perspective. The thesis shows that energy-secure TEC initiatives are collective energy systems with particular characteristics and surrounding conditions. The thesis demonstrates, by building and using a number of agent-based models, that behavioural and institutional settings are relatively more influential than technical settings for establishing and sustaining the functioning of energy-secure collective thermal energy systems. In particular, a combination of aquifer thermal energy storage with heat pumps positively impacted TEC initiatives' energy security. The most crucial technical requirement for the energy security of TEC initiatives is a connection to a natural gas grid. The thesis recommends that individual households initiate their own (thermal) energy communities, and policy-makers support such initiatives.

This thesis examines the energy performance of dwellings of Dutch non-profit housing associations towards a future sustainable housing stock. Improving the energy performance of dwellings aims to improve the quality of dwellings and therewith to lower the actual energy consumption. Lowering the actual energy consumption of dwellings contributes to the battle against climate change. This thesis addresses four studies. Study 1 assesses the energy performance progress of over two million dwellings of Dutch non-profit housing associations between 2017 and 2020. It gives insights into the development of the housing stock, the effect of changes of and within the stock, the effect of characteristics of housing associations and it relates the improvement of the energy performance to the sectoral goal. Study 2 assesses advanced models to improve estimations of actual energy consumption of dwellings and therewith to better estimate the effect of renovation measures on actual energy savings. Study 3 assesses the energy performance of dwellings with heat pumps. It gives insights into the energy performance of dwellings with heat pumps as a promising renovation measure towards a future sustainable housing stock. Study 4 assesses the process to create a model to benchmark the energy performance in a changing policy context. The four studies contribute to the understanding of the improvement of the energy performance of dwellings of non-profit housing associations towards a future sustainable housing stock.

Public transport networks are vulnerable to disruptions which have negative impacts on passengers, operator and society. New rescheduling link in PT networks has potential to increase its robustness value against disruptions. The research project deals with identifying the optimal locations of such rescheduling infrastructure in PT network which increases the robustness value against disruptions taking into account the case study of Amsterdam Tram Network.