The Port of Rotterdam is a major European hub for trade, logistics, energy, and industry. As the port faces increasing pressure from the energy transition, digitalisation, climate ambitions, and international competition, innovation has become essential for maintaining its competitiveness. Coordinating innovation within the port, however, is challenging because numerous stakeholders with different objectives and interests are involved. Leader firms play a particularly important role, as their investments, technological capabilities, and strategic decisions can shape innovation trajectories across the wider port cluster. For the Port of Rotterdam Authority (PoRA), understanding leader firm priorities is therefore essential for effective innovation coordination.

Although previous research highlights the importance of innovation ecosystems and the role of leader firms in port innovation, relatively little is known about how leader firms prioritise competing innovation proposals or how these priorities can be identified when firms are reluctant to share strategic information. This thesis investigates whether Discrete Choice Modelling (DCM), implemented through a Discrete Choice Experiment (DCE), can reveal leader firm preferences and trade-offs in a way that supports innovation coordination.

The research combines three complementary perspectives. First, Key Enabling Technologies (KETs) are used to map the technological positioning of leader firms. Second, an Innovation Readiness Framework structures the criteria used to evaluate innovation proposals. Third, a DCE quantifies the relative importance of these readiness criteria in innovation decision-making. The empirical analysis is based on a technology-domain mapping of 71 anonymised leader firms using public company information and patent data, complemented by an online survey containing KET-related questions and a DCE completed by 31 respondents with management, innovation, strategy, or business development responsibilities.

The results show that leader firms are unevenly distributed across technological domains, with Digital and Information Technologies, Chemical Technologies, and Engineering and Fabrication Technologies being most prominent. Patent-based technological activity and self-reported technological interests do not always coincide, suggesting that established capabilities and future innovation directions differ. The DCE indicates that commercial readiness has the strongest positive influence on proposal attractiveness, followed by legal readiness, business readiness, and social acceptance readiness, while technological readiness, although important, is not the dominant decision criterion. The study also demonstrates that obtaining reliable insights into leader firm priorities depends strongly on relational access, with personal networks and bridging ties proving substantially more effective than general contact routes.

Overall, this thesis demonstrates that DCM provides a valuable decision-support approach for innovation coordination by making leader firms' underlying prioritisation trade-offs explicit. When combined with insights into firms' technological positioning and the network relationships required to engage relevant decision-makers, the approach can support more informed strategic learning and innovation coordination within the Port of Rotterdam. While the findings are indicative because of the limited sample size and hypothetical choice setting, they provide a practical foundation for improving coordination between the PoRA and leader firms. ... Read more

Passenger transport demand in Sub-Saharan Africa is projected to more than triple by 2050 compared with 2019 (International Transport Forum, 2023). As a result, urban transport systems increasingly face congestion and pollution, making sustainable urban mobility planning a central policy challenge (World Bank, 2022). Ghana is a relevant case within this context. It is investing heavily in transport infrastructure through the government’s “Big Push” initiative while also committing to net-zero emissions by 2060 (Government of Ghana, 2023). Designing and appraising these investments and low-emission transport policies effectively requires reliable, context-specific evidence on how travellers value travel-time savings and cleaner transport. Yet such evidence remains scarce for Ghana, and for Sub-Saharan Africa more broadly.

This thesis addresses that gap by asking how different segments of urban travellers in Greater Accra value lower-emission transport relative to travel-time savings and other travel attributes. A stated-preference discrete choice experiment (DCE) was developed based on a literature review, an analysis of Accra’s transport context, expert sessions, and two pilot studies. The final experiment asked respondents to repeatedly choose between two unlabelled commuting alternatives, each described by three attributes: fare (GHS 10–40), total travel time (30–75 minutes), and vehicle type (fossil-fuel or electric). Lower-emission transport was operationalised through vehicle type rather than a direct emissions attribute, because respondents did not reliably associate their travel choices with emissions.

An interviewer-assisted survey was administered to 254 adult travellers who make regular motorised trips, yielding 2,032 observed choices. The choices were analysed using multinomial logit, covariate interaction, and latent class choice models. Because respondents were recruited in selected neighbourhoods, the sample is not statistically representative of Greater Accra and the estimates should therefore be interpreted as sample-specific.

The results show that fare and travel time are the dominant determinants of commuting choices, while vehicle type matters considerably less. The estimated value of travel-time savings is about GHS 53 per hour (USD 4.73), higher than national benchmark values transferred from a meta-study. Substantial preference heterogeneity was found: fare sensitivity was stronger among financially constrained respondents, women, trotro users, and those aged 46–55, while travel-time sensitivity was stronger among respondents of higher socio-economic status.

Although 93.7% of respondents reported worrying about vehicle-related air pollution, this concern did not translate into a willingness to pay for cleaner technology. Average WTP for the electric-vehicle alternative was slightly negative, at −GHS 2 per trip, indicating near-indifference to vehicle technology rather than active opposition. Preferences for electric vehicles were associated with EV knowledge rather than concern about air pollution. The latent class model identified five behavioural segments: a time-sensitive class (33.1%), a time- and cost-sensitive class (27.5%), a cost-sensitive class (24.1%), an EV-oriented class (9.3%), and a weakly fossil-fuel-oriented class (6.0%). Only the EV-oriented class showed a clear positive preference for electric vehicles.

The findings indicate that vehicle technology is secondary to fare and travel time in concrete commuting trade-offs. Electric services therefore have to compete on fare and travel time, while increasing familiarity with electric vehicles may raise willingness to pay. The thesis provides context-specific evidence on travel-time valuation, EV willingness-to-pay, and preference heterogeneity in an African urban setting, and contributes to transport appraisal and the design of electric vehicle initiatives in Greater Accra. These findings should be read in light of the small, non-representative sample, the hypothetical nature of stated-preference choices, and the use of vehicle type as a bundled proxy for lower-emission transport.
... Read more

Infrastructure and spatial planning decision-making has traditionally been dominated by expert-driven frameworks that prioritise technical feasibility, efficiency, and financial performance, often overlooking broader societal value considerations. Participatory Value Evaluation (PVE) has emerged as a method that enables citizens to evaluate policy and project alternatives from the perspective of a policymaker, revealing societal preferences and value trade-offs. Yet little is known about what happens after a PVE is conducted. This research addresses that gap through an abductive qualitative multiple-case study of five Dutch infrastructure and spatial planning projects, complemented by a literature review and an expert focus group. In doing so, it examines how participatory insights inform and interact with expert-driven processes and which factors shape their influence. The empirical findings showed that PVE outcomes rarely play a directly decisive role in subsequent optimisation and decision-making processes. Instead, their influence is typically indirect, predominantly serving supportive, legitimising, agenda-setting, and confirming functions, while strategic, symbolic, and decisive uses occur only to a limited extent. Their influence is shaped by a complex interplay of contextual, methodological, epistemological, and institutional factors. The findings further suggest that explicit consideration should be given to the intended application purpose of the PVE, its timing within the project life cycle, the level of abstraction, the institutional conditions, and the mechanisms through which participatory knowledge is translated and integrated into expert-driven planning and optimisation processes. The research concludes that PVE can meaningfully inform and interact with expert-driven optimisation and decision-making when appropriately designed, timed, and embedded. Rather than treating PVE outcomes merely as contextual information, its outcomes should become an integral part of broader project assessments, knowledge environments, and decision-making processes, enabling participatory insights to be considered throughout the project life cycle. The value of PVE therefore lies not in replacing expert judgement, but in enriching the knowledge environment within which optimisation and decision-making take place. By identifying the conditions and mechanisms that facilitate this integration, the study advances current understanding of participatory knowledge utilisation while providing practical guidance for developing more socially embedded infrastructure and spatial planning processes.
... Read more

The Environment and Planning Act (EPA) has increased the emphasis on decentralised policy and public participation in the Dutch built environment. One area where these two aspects come together is participation policy for BOPA applications. Non-governmental parties that want to commence a project that conflicts with the physical environment plan can apply for a BOPA (vergunning voor Buitenplannelijke Omgevingsplanactiviteit). Public participation is always advised, but not required for these applications, unless the municipality where the project is located specifically determines that participation is mandatory. If participation is mandatory, it is a compulsory application requirement; insufficient participation means the application is incomplete and will not be considered further. What counts as insufficient participation is difficult to determine exactly, because municipalities only check the completeness of the application. As long as the initiator provides a participation report that explains how participants were involved and what the outcome of the participation was, the application is complete. This research has analysed how different municipalities have shaped their policies on mandatory participation and how they take the participation report submitted by the initiators into account in their decision-making.

By analysing the policies of 50 representative municipalities, three categories emerge: all projects have mandatory participation (n=11), some specific projects have mandatory participation (n=36), and no projects have mandatory participation (n=3). Even within the largest category, the policies differ widely. This indicates how varied the different municipal policies are. Of these municipalities, four have been selected for further analysis, with each category represented. This analysis included their reasoning for choosing their policy, their evaluation of the policy, the way they evaluate the participation reports, and their success factors for participation.

This analysis highlighted varied reasons for choosing their policy, including minimising workload, maintaining a sense of community, and avoiding legal issues. All municipalities report tangible benefits of participation in the form of improved project designs, fewer official complaints, and better public acceptance. Still, the influence the participation reports have on the decision-making is minimal. Participation outcome is more important than the participation process, but neither is ever a decisive factor. The participation is mostly used as an instrument to determine what aspects lead to concerns with the public and what the public opinion is on the project. Lastly, municipal success factors mainly include good transparent collaboration between the initiator and participants and public acceptance.

The outcome of the research includes recommendations for both the national and local governments, as well as future research. The way the EPA is currently set up, the minimal required standard for participation is extremely low. Municipalities are not able to set any requirements for the participation, but are only able to check the completeness of the application. This system makes it impossible for municipalities to hold initiators accountable for failing to facilitate meaningful participation. This research suggests changing the EPA to make it possible for municipalities to set requirements for the projects that have mandatory participation. By communicating these requirements clearly with the initiators, it becomes possible to ensure a higher standard for participation in these projects through an objective evaluation system. Projects where participation was not mandatory are excluded to not discourage initiators from facilitating participation.
... Read more

This thesis examines whether explainable machine learning can support bid/no-bid decision-making for large Dutch construction projects. The study is conducted as a case study at Count & Cooper, a Dutch project-management and tender advisory consultancy active in complex construction tenders. The bid/no-bid decision is a critical early decision point, because contractors must decide whether to invest substantial time and resources in preparing a tender while important project information is still uncertain. To address this problem, the thesis first analyses the Dutch tendering context and identifies decision factors from literature, desk research, and expert validation. These factors are then operationalised into a structured dataset based on 101 historical tender opportunities. Several supervised learning models are compared, including Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and XGBoost. Because of the limited dataset size and data-quality constraints, model performance is evaluated using repeated 5-fold cross-validation. In addition to predictive accuracy, the thesis emphasises interpretability by analysing model coefficients and SHAP-based feature importance. The results show that bid/no-bid outcomes can be predicted to a moderate extent using characteristics that are available early in the tendering process. Random Forest achieved the strongest overall predictive performance, with Logistic Regression and linear SVM performing similarly well. Across models, tender duration, contract duration, project value, project type, and contract form emerged as influential drivers. At the same time, the analysis shows that important internal decision factors, such as strategic fit, current workload, and client capability, were not consistently documented in the available historical records and therefore remain outside the current modelling scope. The thesis concludes that explainable machine learning can provide useful and transparent screening support for bid/no-bid decisions, but that the current results should be treated as a proof-of-concept rather than a deployable decision tool. The main practical recommendation is therefore to improve the structured capture of tender characteristics, internal decision context, and decision rationale, so that future models can become more robust, realistic, and decision-relevant.
... Read more

This thesis investigates the potential of Augmented Reality (AR) headsets to enhance field technicians’ performance (in terms of efficiency and effectivity) in Operations and Maintenance (O&M) processes in Offshore Wind Farms (OWF), with Vattenfall’s operations serving as the case study. The key deliverable of this report has been the Business Case (Chapter 9), which provides a qualitative and quantitative analysis of the AR enhanced business process innovation. A critical gap for such empirical case studies was identified in the field of industrial AR applications, especially in offshore wind contexts, as noted in Chapter 1. The research is further motivated by the generation of a generalisable multi-framework approach for business process innovation. This approach evaluates the business case of novel technologies such as AR in capital-intensive industries, fitting in Vattenfall’s (generalisable) Stage-Gate innovation model (Chapter 2). Furthermore, societal impact is granted through accelerating the energy transition, by providing the first step in a business process innovation that should lower the O&M costs (which is about 30% of the Levelised Cost of Energy (LCOE, full lifecycle cost) (Bosch et al., 2019)) of renewable energy, improving its competitiveness against fossil fuels (Chapter 2). ... Read more

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.
... Read more

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.

... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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.
... Read more

The first registered infection with the COVID-19 virus occurred in China at the end of 2019. The virus spread worldwide, turning a single infection into a pandemic. Most countries implemented policies to limit its spread. These policies can be divided into pharmaceutical and non-pharmaceutical interventions. Vaccines are pharmaceutical interventions, while non-pharmaceutical interventions include the temporary closure of restaurants and bars or limits to the number of people allowed to gather for social events.

Although these non-pharmaceutical interventions were effective in slowing the spread of COVID-19, they also severely affected social and economic life. Freelancers working in restaurants and bars lost their income, and students experienced a decrease in mental health due to reduced social engagement. These societal impacts gradually reduced public support and adherence to COVID-19 measures across different pandemic waves.

To measure how people weigh these societal impacts, Discrete Choice Experiments (DCEs) are used. These are often analyzed with Multinomial Logit (MNL) models, which quantify the relative importance of attributes for the population as a whole. However, alternative models exist, such as Mixed Logit (ML) and Latent Class (LC) models, as well as different DCE designs, such as labeled and unlabeled DCEs. Each approach has advantages and disadvantages. ML models capture preference heterogeneity across individuals, while LC models identify groups with distinct preferences. Labeled DCEs explicitly include COVID-19 measures, whereas unlabeled DCEs focus only on societal impacts without reference to the measures causing them.

As the pandemic transitioned into an endemic in late 2022 and early 2023, this study evaluates the advantages and disadvantages of these models and DCE designs in both contexts. The main research question is: 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?

Three subquestions are addressed through a literature review, an empirical DCE conducted during the endemic, and expert interviews. The literature review compares results from MNL, ML and LC models in labeled and unlabeled DCEs during pandemic waves. The empirical study applies both labeled and unlabeled DCEs during the endemic to compare model outcomes. Expert interviews are used to assess methodological advantages and limitations.

The results show that ML models are useful for detecting preference heterogeneity, which helps assess the reliability of MNL estimates. If heterogeneity is substantial, MNL results may not adequately represent the sample. The LC model identifies subgroups in society with distinct preferences. However, it is sensitive to initial values and covariate specifications. ML models are computationally demanding.

For DCE design, labeled experiments are useful for assessing the impact of specific COVID-19 measures, while unlabeled experiments provide baseline preferences for societal impacts without contextual framing. Unlabeled DCEs are most suitable at the start of a pandemic to inform initial policy design. Labeled DCEs are more appropriate during and between pandemic waves to evaluate and adjust policies, and during the endemic to assess long-term impacts.

ML models are valuable for testing the robustness of MNL estimates, while LC models help explain heterogeneity and support tailored policy design to improve public acceptance and adherence.

A key limitation is the limited availability of comparable labeled and unlabeled DCEs across pandemic phases and countries, as well as differences in attributes and timing, which reduce comparability. Future research should explore extended choice models, such as mixed or latent class models with random parameters, as well as data-driven approaches outside traditional choice modeling. Further research is also needed on how these insights are integrated into pandemic policy decision-making and whether they should serve as advisory input or formal guidance. ... Read more

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.

... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more