Political and societal attention on transport inequality, transport vulnerabilities and transport poverty risk has been increasing the last five years. The Dutch government has committed multiple large sums of resources to abate the issue, 120 million euros to cancel the increase in price of train tickets, 300 million to cancel the increase in price and preserve the provision of the regional public transit and 6 million to start a pilot of ‘innovative public transport’ in the Zeeland region. A review of the literature on transport poverty risk reveals that past studies analyze the concept using a limited number of pre-selected variables. For example, car ownership and residence area. This carries the risk for misinterpretation as an accurate representation can only be achieved by considering all relevant variables. Such a comprehensive analysis could allow policymakers to formulate tailor-made policies according to the specific problems and needs of certain groups in society. This study aims to include the entire complexity of the concept of transport poverty risk in the analysis. Relevant factors include affordability, accessibility and mobility. Then there are individual differences, and for every individual changing over time, between needs of participating in society and social life. This study aims to incorporate this comprehensive definition in a Latent Class Analysis approach to construct groups of individuals based on the MPN and ODiN national datasets. The different groups of individuals can be then used to indicate the effect of policies on transport inequality. Results show three groups that are most transport ‘fortunate’, with high income, high car ownership, high accessibility and the potential to use different travel modes. Results also show one group with substantial transport vulnerabilities due to higher car dependency, lower car ownership and lower household income. A policy thought experiment is established through the application of mobility policy packages of three political parties. Car policies that reduce costs per driven kilometer such as reduction in excise tax will increase transport inequality due to the three groups that are the most transport ‘fortunate’, which also have the highest car use. This study provides the scientific community with a comprehensive definition and conceptual model of transport poverty risk and for policymakers contributes a comprehensive understanding of transport inequality in the Netherlands. Future research needs to focus on identifying specific minority groups that are not or less captured in the national datasets. Transport problems are experiences by an individual, while transport inequality is represented by the differences in the extent of transport problems between certain individuals or groups. In this case, certain groups in the Netherlands. This calls for the need to differentiate the government levels at which transport inequality and transport problems are addressed. While this study presents the transport inequality at the national level, municipalities will be able to identify specific individuals and neighborhoods who are more prone to transport problems.

The residential energy consumption and energy affordability are crucial in policy design, with regard to energy efficiency and energy poverty. This has become even more relevant now, as the energy transition is taking off and the energy prices are soaring. Given the inequality in the energy consumption and energy affordability, it is therefore critical to know which factors are impacting these phenomena, and how they are impacting these phenomena. The housing-related factors are the least understood factors impacting the energy consumption and energy affordability, even though these factors are key pillars of energy policy. Thus, this research assesses how housing-related factors impact the residential energy consumption and energy affordability in the Netherlands. For this assessment, multiple data sources are combined over the years 2016 to 2018, covering a total of more than 8 million Dutch households. A regression analysis is performed on a postal code 6 level using the housing-related factors as predictors, while controlling for socio-demographic and weather factors. This revealed that the housing-related factors impacting energy consumption and energy affordability are relatively similar. This study finds that the WOZ-value is a strong predictor for both phenomena as houses with a higher WOZ-value have a lower energy efficiency. Furthermore, it shows that rental households consume less energy but spend a similar percentage of their income on energy, and that the impact of the year of construction on both phenomena has increased significantly, when compared to earlier studies. Based on this, it is concluded that rental houses and houses with an older year of construction deserve more attention in Dutch energy policy. Furthermore, low-income households should be targeted in short-term energy policy, as this study shows that the current soaring energy prices have a severe impact on the energy affordability in the Netherlands. Insights are however broader, and can be pivotal in energy demand and energy affordability projections, both in the Netherlands and the rest of Western Europe.

In today’s world, the transport system is essential in helping people reach the activities they want or need to attend. However, like in many other fields, inequality can exist in access to various opportunities based on personal characteristics. Little is known about how gender and intersectional factors impact people's perceived accessibility. This thesis aims to fill this knowledge gap using a mixed methods approach. First, desk research shows that perceived accessibility can be influenced by a large variety of factors, including, but not limited to, the primary mode used, perceived safety in transport and socio-demographic factors. Second, Structural Equation Modelling is used to investigate the strength of relationships between the various found factors and gender intersectional factors. This analysis shows that being a woman has a negative effect on perceived accessibility, which can for a part be explained by women feeling less safe in transport at night. Additionally, the analysis shows that for women having young children negatively impacts perceived accessibility, but not for men, while for men income positively relates to access to a car and in turn to perceived accessibility, an effect which is not found for women. Finally, the subsequent qualitative analysis, using workshops, shows that little attention has been paid in the past to (social) safety issues in transport and to differences in needs between different kinds of travellers. In the future, more cooperation between transport institutions and integrated intersectional policymaking in transport would be of significant value.

The Covid-19 pandemic has outlined the creativeness of each country in the definition of the most appropriate public health management strategies to curb the spread of the SARS-CoV-2 virus, ranging from total lockdowns to trusting in people’s common sense to act properly. Several non-pharmaceutical health interventions have nationally been issued either on a voluntary bases or required by law. Maintaining 1.5 m distance and wearing protective face masks provide two respective examples. Proximity contact-tracing apps have furthermore been launched at a national scale to alleviate the pressure on the overburdened testing capabilities by means of automatic contact-tracing. Also the Dutch Ministry of Health launched its CoronaMelder on October 10, 2020. However, its efficacy is being questioned with the consideration of its instigated user behaviour. More specifically, it is being hypothesized that the CoronaMelder app instigates users to comply less with the issued non-pharmaceutical health interventions, thereby countering their expected beneficial effects in curbing the spread of the virus. An explorative sequential design provided the answer, where literature review findings were combined to conceptualize the effect of the app on attitude, perception and eventually behaviour. Structural equation modelling performed on data collected through an online survey (N=776) outlined the lack of causality from the CoronaMelder to behaviour and as such, compensatory behaviour was excluded. Moreover, it was found that older and higher educated people were more prone to install the app, similarly to people at risk and those who had previously contracted the virus. Eventually these results were placed in the context of behaviourally-informed politics to assess the management of nationally launched digital contact-tracing apps.

The increased usage of Electric Vehicles and Renewable Energy Sources causes issues regarding the balancing of the electricity grid. To avoid investment costs, Distribution System Operators desire flexibility solutions. One of these flexibility solutions is the usage of the battery of the Electric Vehicle as an electricity source. This concept is known as Vehicle to Grid (V2G). However, providing V2G services might cause discomfort for the Electric Vehicle user. A contract can be used to compensate the user for the experienced discomfort. Literature on these contracts is lacking and the behaviour of EV user to these contracts is unknown. This study aims to close this gap. Data is collected by means of a web survey and evaluated with a multinomial logit model. It is shown that the difference in expected demand for price- and volume-based contracts is minimal. In addition, three contract elements can solely increase demand for V2G but require high levels. More value is created when a combination of these three contract elements is used. It would be valuable to understand how and where V2G can provide value. To do so, the results of this study can be used as input for a dynamic model that evaluates day-to-day electricity supply and demand.

The Ministry of Infrastructure and Water Management looks into the possibility of raising the awareness of Dutch citizens as policy measure to encourage travellers to travel in a more conscious and more climate-friendly manner. Scientific literature, however, shows contradictory results on the effectiveness of this measure. An ongoing academic discussion is present on the extent to which awareness about the consequences of behaviour results in a desirable change of that behaviour. This study applies structural equation modelling on Dutch Mobility Panel data to examine if and via which causal pathway of socio-psychological factors information and awareness about the relative impact of flying on climate change run to the intention to fly. We find that raising awareness of Dutch citizens about the relative impact of flying on climate change is not enough to change people’s intended flying behaviour. The current awareness only changes people’s attitudes and reasons used to justify their flying behaviour, not the intention to fly. Further research, however, is necessary to find out if raising awareness on other consequences or other alternatives result in the same findings. Only then it could be recommended to look into other measures to encourage travellers to travel in a more conscious and more climate-friendly manner.

Thanks to growing online shopping, last mile logistics is becoming a more relevant problem for cities due to its negative impacts, such as congestion and environmental problems. In this research, one of the urban freight transport services aiming to tackle these externalities is analysed: crowdshipping. Crowdshipping is a service where the package is delivered via a traveller who is already making an unrelated trip. Trust is a key concept affecting the adoption of crowdshipping yet to be explicitly investigated . Thereby, this research aims to explore the effect of trust and examine how users' adoption can be achieved. To analyse the stated gap, a stated choice experiment is conducted to test the effect of travel time, travel cost, track and trace, insurance, damage and reputation. A Mediation Choice Model is applied to explore how the relevant attributes would impact trust towards the service adoption. Based on the findings, the direct effects of all the selected attributes were found significant, except for tracking and tracing. Regarding the indirect effects, all the main attributes were statistically significant, meaning that trust has a mediating effect on the adoption of the service. Additionally, the heterogeneity in preferences is explored through a Latent Class Choice Model resulting in a two-class latent model, crowdshipping sceptics and crowdshipping enthusiasts, the latter being more likely to be composed of younger women. Although enthusiasts consider more features while opting for crowdshipping, the delivery company's reputation and delivery cost were the most important factors in crowdshipping service adoption.

Currently in the energy system of the Netherlands, lower level consumer demand flexibility is rather obsolete due to sufficient capacity limits of the distribution network and supply of capacity mechanisms by large industrial actors. However, in the upcoming 10- 20 years, the power system is in transition to become decentralised with a higher share of renewable energy sources and significant increase in consumption. An operational control structure in the power system, where private consumers provide flexible capacity, is an effective and economical efficient approach to make sure the regulated process of electricity generation to supply at consumers is secure and reliable. Currently as a result of the EU Energy Efficiency Directive of 2012, an institutional base is presented for development initiatives of demand response in Europe [17]. Technical and regulatory standards now enable demand response flexibility to be offered on the wholesale and retail energy market and allow for consumer participation [34]. Demand response schemes are usually distinguished by the various motivation methods offered to the participating consumers. Programs include in general two control methods, centralised direct load control or time-based and incentive-based DR. Because these schemes rely on demand response decision-making by means of a centralised (multi) aggregator perspective, direct load control can be precisely adjusted to technical (local) grid constraints [69]. Practically, the objective of DR in this research is used to reduce congestion in distribution grids by moving part of BEV energy demand from (evening) peaks to the afternoon or night with direct control. By achieving these measures potential benefits arise, including the most profound in the distribution grid [29]: • Optimising local grid assets by increasing the utilisation factor, and thereby maximise asset efficiency and subsequently decrease costs, which is beneficial for the DSO • Scheduling of peak charging demand to aid congestion in distribution grids. The modelling of the demand response charging strategies in Amsterdam fills the knowledge gap towards handling congestion for the DSO. It also provides a new study that addresses the potential to postpone future distribution grid investments by using charging strategies specifically for Amsterdam. The main research question that this study addresses is therefore: What is the value of demand response management in a Vehicle-to-Grid network and does it provide increased benefits to smart charging for consumers and the distribution system operator in Amsterdam? In order to grasp the subject of congestion prevention within the time limits of graduation, the scope of this study is limited to assess the first mentioned item by modelling charging demand, and subsequently simulate optimal demand response charging strategies for a case study in Amsterdam’s local power grid. The motivation for this study is threefold. Firstly, providing insight and recommendations in Amsterdam’s BEV charging demand to compute the potential to provide demand flexibility by making use of a large-scale charging sessions data (2017-2018). Literature that uses such a vast data set for Amsterdam is scarce. Therefore, typical demand behaviour for daily and seasonal variation or periodicity is assessed by using a method of time series analysis and local regression analysis to derive time- and load-flexibility parameters. These parameters de- scribe the measures for which demand response is generally defined. Secondly, a linear programming model is developed that optimises charging demand of smart charging and V2G charging strategies for demand response purposes to aid congestion at local feeders in the distribution grid of Liander. Lastly, an information-task exchange protocol is de- scribed from the perspective of a multi-aggregator to perform coordinated DR. Further investigation about the usable amount of flexibility is simulated with linear programming for charging strategies (smart charging and V2G charging) to aid in local feeder congestion. In this research a case study is performed on data of a low-voltage feeder under different congestion situations, and a range of different number of BEVS connected to explore future distribution grid implications. Results show that the model’s performance works especially well during peak demand periods throughout the day. In addition, the V2G strategy outperforms charged prices per kWh in almost every simulation compared to the uncontrolled scenario, by both charging during periods of low prices and discharging during periods of high prices even though the LP model does not optimise on prices. Thus, the V2G strategy allows the DSO to postpone grid investments in a number of cases while simultaneously the consumer almost always receives remuneration for its delivered services. The V2G strategy therefore provides a significantly added value over a smart charging strategy, by allowing electric vehicles to be charged whenever the feeder exhibits congestion. Future work includes analysis towards the value of DR in a liberalised system regarding the subject of the split-incentives challenge. Who initiates demand response (consumer, retailer, aggregator, DSO) and how should the benefits be divided along the supply chain. Handling an optimisation problem of DR for holds strong requirements for an global system balance in which neither participating actors are discriminated and the whole system benefits. An assessment of relational dependencies between participators in DR should be incorporated in designing charging strategies.

To be able to solve the increasingly complex problems, governments need to collaborate with various parties. This way of policy development is called interactive policy making. Citizen participation is a specific form of interactive policy making and focusses on involving citizens in the policy making process. A relatively new online participation method is Participatory Value Evaluation (PVE). It aims to facilitate mass citizen participation and to be inclusive. Everyone who wants to participate in the process should get the change to do so. At the same time PVE is an evaluation method for public policy. To be able to provide an accurate advice about the preferences of citizens regarding a set of policy options, the sample under study needs to be representative. Representativity and inclusivity seem to conflict with each other as making the research available for the public very often leads to a biased sample. The aim of this study is to examine the consequences of the trade-off between representativity and inclusivity for the usability of PVE in the policy context.

This research evaluates the Pollution Haven Hypothesis for the chemical sector across the globe. It does so by creating a regression model which incorporates five constructs (market potential, infrastructure, factor cost, governance factors and a measure of environmental stringency) to explain the variance of foreign direct investment (FDI) across countries specified for the chemical sector. The results are by no means unequivocally for or against a confirmation of the pollution haven hypothesis, but the evidence suggests a negative effect of the measure of environmental stringency when FDI is specified further to only the manufacture of chemical products and sampled by averaging as much annual FDI data as the dataset includes.

When a crime is committed, the task of the regional control rooms is to use the available situational information to identify the possible movements of a fugitive suspect to use in positioning police units. Currently, the methods to do this rely heavily on the intuition and experience of the control room employees and the speed of technology and communication. To reduce this reliance, there is an increasing demand for methods to objectively determine the tasks to undertake in a fugitive escape situation. Two methods to do this are under development which help in determining the location of a fugitive suspect and the optimal positioning of police units to these locations. However both of these methods still require a demarcation of the possible routes that a criminal fugitive will take to be used effectively. Therefore, this study explored the possibility of making likelihood estimations of possible escape routes. Because of a lack of reliable data, alternative methods to determine likelihood of escape routes are needed. A method that could be used is simulation. Simulation of human behaviour is however complex and careful consideration of the assumptions in such a model is needed to be able to have a high level of confidence in the resulting outcome. To do this, it is important that the theoretical background on which behavioural factors influence the criminal fugitive route-choice behaviour is complete and it is known how these factors affect the resulting routes. This is the knowledge gap addressed in this study. To address this knowledge gap, the question of what effect behavioural factors from criminal route choice behaviour have on escape routes will be answered. This is done by determining which main factors influence criminal fugitive route-choice behaviour and how these factors influence the resulting escape routes. The method used to answer these questions is a combination the development of a theoretical background based on a literature review of existing research and expert opinion and a quantitative sensitivity analysis on a simulation model. Because of a lack of research on criminal fugitive route-choice behaviour, it was necessary to use literature from the following research fields to find relevant topics: criminal decision-making, rationality in decision making and route-choice decision-making. From the literature in these fields, it was found that many different personal and crime characteristics exist, but it is unknown how these affect route choice behaviour. Next to this, it was found that rational decision-making cannot be assumed for the criminal situation and that bounded rationality needs to be considered. Lastly, from the route-choice decision-making literature, it was found that many different route-choice factors are relevant. The following list of route-choice behavioural factors was found: obstacle avoidance, risky behaviour, traffic avoidance, route distance and maximum speed, and preference for main or residential roads. For the route choice decision-making modelling methods, the following relevant topics were found: cost benefit calculations, short or long-term goals, emotional state, choice prioritisation and timing. These two lists of factors should be considered when conceptualising criminal fugitive route-choice behaviour. In the conceptualisation phase of this study, it was found that while many different suspect and crime characteristics might affect suspect behaviour, no specific behavioural profiles could be used to conceptualise route-choice behaviour. Therefore it was chosen to conceptualise the behaviour by creating dynamic strategy profiles based on behavioural route-choice factors. From the list of behavioural route choice factors to include in these strategy profiles, it was found that they can be described as either a preference or avoidance of road characteristics. The road characteristics seen to be avoided are cameras, obstacles, one-way roads and high traffic. The preferred road characteristics are a high number of lanes, residential roads, a high maximum speed and short roads. Next, it was found that there is a distinction in decisions based on long or short-term goals, which require either low or full network familiarity. For general route-choice behaviour, the conceptualisation of a route choice as a whole route between an origin and destination location was found to be most appropriate. When considering the rationality of the decisions made for the route choices, it was found that there is too much uncertainty and ambiguity in the considered bounded rationality conceptualisation to use them for aconcrete route-choice conceptualisation. Therefore, alterations to the assumptions of rationality are used to concentualise this. Finally, the emotional state of a fugitive is included in the conceptualisation through the possibility of changing route-choice strategies. This conceptualisation is further used to describe the general criminal fugitive route-choice behaviour in this study. To measure the influence of the behavioural route-choice factors in the conceptualisation, a route cost model was developed. In this model, the cost of a route is calculated using the characteristics of the edges in a road network. Based on this model, an experimental design is defined including a case study and sensitivity analysis to find the quantitative influence of route-choice behaviour on route metrics describing differences in escape routes through route length and overlap. When evaluating the results of the case studies and sensitivity analysis, it was found that the influence of behavioural route-choice factors on routes depends on the origin and destination locations and the distribution of edge characteristics over a road network. Next to this, it was found that there were no behavioural profiles leading to routes with specific characteristics and that in practical application, a broad set of strategies should be included when finding important locations is a road network to use for positioning police units. To do this, a method of using heat maps to find these locations was proposed. This method combined with the route cost model described in this study was found to have high applicability but more research needs to be done on the usability of this method. From the findings of this study, it can be concluded that criminal fugitive route-choice behaviour is complex and that different possible conceptualisations exist to be used for different purposes of studying general route-choice behaviour or specific behavioural factors. This affects the ability to measure the influence of behavioural factors on the resulting routes. Limitations were found on the measurement techniques used in the quantitative method to measure differences in routes which reduced the ability to interpret the resulting influence of behavioural factors on the routes. This showed that to find the influence of behavioural factors on the routes, the results of this study can show that the route-choice factors defined in the conceptualisation affect the routes but that more qualitative research is needed to find how these factors influence the resulting routes. To conclude, the findings of this study add to current research by showcasing the complexity of modelling route-choice decision-making and human behaviour in general and the many considerations that need to be taken when doing so. Next, it shows the difficulty of using quantitative and qualitative methods on the data type of routes to determine relations between factors influencing route-choice behaviour and resulting routes. And lastly, it adds to the current literature by developing an overview of the factors influencing criminal fugitive route-choice behaviour that need to be considered in the simulation of fugitive escape routes.

In an environment in which Public Transport plays an ever growing role in urban areas and passenger experience. In-depth knowledge on customer satisfaction is key in improving passenger experience. Crowding has shown to be an important aspect of route and mode choice, but its impact on customer satisfaction has not yet been quantitatively explored. This paper investigates this impact. Using a Structural Equation Model based on customer satisfaction survey data and corresponding occupancy and punctuality numbers a significant effect of occupancy levels on perceived crowding was found. In-vehicle crowding, both subjective and objective, seems to impact overall customer satisfaction indirect, with comfort being the main mediating variable. Model results were converted into a calculation tool which can be used to assess the impact of changes in passenger numbers, passenger distribution and frequencies on customer satisfaction. Further research can verify the linearity of the relation between in-vehicle crowding and customer satisfaction and deepen knowledge of external factors such as weather and disruptions have on experienced crowding.

There have been huge investments being made in direction of citizen science projects to enhance the engagement between science and society. To achieve goals and for the success of citizen science projects, a crucial element is getting more researchers to participate in citizens science projects. Besides harmoniously sustaining the participation of existing researchers who are already engaged in citizen science. While doing this, we identified two primary knowledge gaps: one, there is limited and insufficient research that articulates the perspectives of researchers to understand what motivates them to participate in citizen science. Two, even the limited available literature, is published by the researchers who are involved in citizen science projects themselves. That has more chance of publication bias and lacks critical scrutiny. For instance, these literatures give the impression that participation from researchers is because of their enthusiasm to enhance scientific awareness in society and to drive citizen’s positive attitudes towards science. Despite there have been projects where the participation from the researchers have not been particularly great.Q-method was identified as the suitable method to identify the perspective of the researchers, as it has been successfully applied in a range of disciplines from political science to environmental science. This method uses Q-factors analysis, that makes the researchers the variables of analysis. Stephenson (1953) argued, if there existed significant clusters of correlations in the participant’s profile, these clusters could be factorised and described as shared perspective and individuals could be measured in relevance to them. Overall, seven distinct perspectives of the researchers related to participation in citizen science are identified. These perspectives are divided into three broad groups based on their inclination to participate in citizen science projects. It is interesting that these groups exactly correlate with the experience of the researchers, that shows that perspectives are in association with on-ground thoughts. Group 1: represents the perspective of researchers who have intrinsic motivation to participate in citizen science and these researchers are experienced in citizens science. These perspectives are revealed by perspective 1 & perspective 2. These researchers are expected to participate on their own. Group 2: represents perspective of researchers who have no interested or inclination to participate in citizen science projects, as they consider it not suitable method answer their research question. These researchers have no experience in citizen science. These perspectives are revealed by perspective 4 & perspective 5. Group 3: these researchers are inclined to participate in citizen science, but some inhibitors in citizen science practise are preventing them to participate in citizen science. Perspectives of this group are revealed by perspective 3, perspective 6 & perspective 7. The policy recommendation is suggested to citizen science association, institutions framing ethical policy and to researchers. This research contributes in three different ways, one it provides critical scrutiny of the literature published on perspectives of researchers, by comparing with what is discussed in the literature with on-ground thoughts of researchers. Two, this research identifies latent perspectives that have not been disused in the field of citizen science. Three, the research identifies controversies in the perspectives of researchers. However, research has limitations due to choices made during the research. One, no concrete conclusions, could be made specific to any scientific discipline or level of engagement between high-level involvement actors, due to the broad scope of the research. Two, research focuses on participation between high-level involvement actors. Three, the use of free sorting of statements to reduce the time for answering the survey. For future research, two controversies in the perspectives of researchers are identified that can be scope for entire new research in the field of citizen science. One, compensation of citizens in citizen science projects. Two, different model to increase scientific literacy are identified between perspective 6, perspective 7 and perspective 1.

During the influx to mass events in the past, situations have regularly arisen that people experienced as unpleasant or even unsafe. Nowadays, many researchers focus on regulating this influx by influencing travel choices, where only little attention is paid to travellers’ preferences. This research identifies the preferences of different type of visitors towards receiving information, and the extent to which visitors with different information profiles act on the information messages they receive. A survey was distributed (N=378), and the number of variables was reduced by performing an Exploratory Factor Analysis. The Latent Class Cluster Analysis distinguished three clusters based on their information message preferences. The results show that people are most interested in receiving information via email a few days before departure and that it is challenging to inform them at a later time. The most impressionable cluster mainly consists of young people, unfamiliar with the event area. Event organisations can apply the results by better-aligning communication with the preferences of their visitors. The differences in behavioural intentions between the clusters turned out to be limited. This must be further investigated since it is not in line with expectations.

The Dutch Ministry of Infrastructure and Water Management is committed to enhancing the accessibility and sustainability of the Dutch mobility system. Working from home (WFH) has been discussed as a policy lever to decrease commute travel and, thereby, congestion for decades. During the COVID-19 pandemic, this discussion regained momentum. WFH was a key factor for the decrease in commute travel by public transport and car in the Netherlands, which decreased congestion. Against this background, the Ministry wants to stimulate WFH post-pandemic to retain some of the sustainability and accessibility benefits identified during the pandemic. WFH can enhance the accessibility of the mobility system thanks to reduced commute trips during peak hours. Although the stimulation of WFH may be a policy lever to increase the accessibility of the mobility system, the full effect of WFH on overall personal mobility is unknown. Studying pre-, during and post-COVID-19 measures data, this study assesses the impact of a change in WFH on activity-travel patterns. Commute travel, non-work travel, and mode use together define activity-travel patterns in this research. The main research question is as follows: How did changes in WFH influence activity-travel patterns during the pandemic in the Netherlands? To answer this question, data from the Netherlands Mobility Panel (MPN), collected between 2019-2022 is used. Latent class analysis is used to identify seven distinct activity-travel patterns. Next, two latent transition models are estimated. The first model, for 2019-2021, studies the effect of an increase in WFH on transitions in activity-travel patterns. The second model, for 2021-2022, studies the effect of a decrease in WFH on transitions in activity-travel patterns. The application of LTA, a longitudinal clustering method, sheds light on complex transition behaviour in the population during- and post-COVID-19 measures. The results show that activity-travel patterns before a change in WFH and the level of an increase in WFH matter for the impact of WFH on transitions. Depending on the initial class membership, differences in transitions emerged. To a certain extent, all effects of WFH on travel, substitution, complementarity, modification, and neutrality exist in the population, but these depend on initial class membership. The results for an increase in WFH are significant, while results for a decrease are not. For the time being, these findings do not exclude the existence of structural changes in working and travel behaviour. Significant effects on transitions appear for a small and a large increase in WFH. After an increase in WFH, most classes are more prone to take up another activity-travel pattern. In both cases, most classes have an increased probability of transitioning towards the low mobility class, which underpins more sustainable patterns. Nonetheless, more diverse results appear for a small increase in WFH, and significant transitions towards other car profiles appear. Analysing the impact of a small increase on class sizes confirms this. Overall, the car class sizes remain relatively high after a small increase in WFH. Thus, an increase by 1-3 days working from home may not lead to more sustainable activity-travel patterns in terms of trip rates per purpose and mode. Nevertheless, it needs to be kept in mind that this study only analysed trip rates per purpose and mode, a small increase in WFH may still lead to a peak-travel reduction, which benefits accessibility. Further analyses should investigate peak-travel to conclude on the accessibility benefits of small increases in WFH. At the same time, governments and employers should take measures to counter-act low mobility associated with WFH which is detrimental for physical health.

Accessibility is a fundamental concept concerning urban and transport planning as it is the elementary basis for socio-economic development in cities. It can be described as the potential to reach spatially distributed opportunities. Recent research has identified that excluding person-based features from this analysis might cause inaccurate measurement of accessibility. Age, gender, and income, for instance, are responsible for varying accessibility levels drastically. In addition, studies worldwide have shown that women face different challenges in reaching locations and spatially distributed opportunities. Despite the findings, this research identifies a gap in understanding how a person-based perspective, mainly gender, and other personal characteristics, affect accessibility levels, considering various travel purposes and transport modes. Thus, this research aims to answer the question, ”How do person-based characteristics, mainly gender, can impact accessibility levels?”. The primary objective is to explore how these characteristics influence accessibility metrics, identify the urban groups most affected by the absence of this perspective, and determine the key personal characteristics that significantly impact accessibility levels. To address these objectives, this study considers a combination of quantitative and case-study research approaches. It investigates the Metropolitan Region Rotterdam- The Hague in The Netherlands by applying surveys to obtain perceived accessibility data. In the same region, spatial analysis is conducted by mapping transport networks and points of interest. Then, this study compares spatially calculated accessibility with self-reported accessibility and the presence of mismatches. In addition, cluster analysis identifies the urban profiles most vulnerable to mismatches and their main characteristics. A Binary logistic regression is conducted to determine the variables’ importance in the mismatch occurrence. From the survey answers, it is identified that women have less access to cars than men. In addition, the comparison between perceived accessibility and spatial accessibility uncovers that women present the most critical mismatches to reach activities by car. In other words, several women perceive the car as an impractical option to access points of interest that are spatially considered reachable by car. It raises the hypothesis that the lack of car access highly impacts their accessibility perception. Furthermore, the clustering analysis reveals that foreign women exhibit a higher prevalence of car-related mismatches when compared to other urban groups. Moreover, this research identifies that fathers of young children also encounter greater disparities across all transportation modes. Additionally, the binary logistic regression underscores the importance of safety as a critical factor influencing women’s perception of walking as a viable mode of transportation. This safety importance is also identified from the survey answers. The findings raise new hypotheses that warrant investigation in transport engineering, urban planning, and social sciences. Consequently, this research can contribute to developing more inclusive transport policies and establishing a more equitable transport system.

Urban densification is one of the most relevant strategies to reduce the housing shortage in the Netherlands, as it also aims to prevent additional pressure on transportation networks and contributes to more sustainable travel. The effects of the built environment on travel behaviour have been studied extensively. To date, most studies focused on homogeneous effects of the built environment on travel behaviour indicators. Less attention is paid to possible heterogeneity in the effects dependent on other variables. This study applies moderated multiple regression on Netherlands Mobility Panel data to analyse possible heterogeneity of the effects of determinants of travel behaviour on daily travel distance, dependent on the level of urbanisation. The results show that various determinants indeed have effects with varying strengths, dependent on the level of urbanisation. The findings advance the understanding of the relationships between built environment and travel behaviour, which could be used to design tailor-suited policies that efficiently target specific groups. In relation with the built environment, the results show that densification strategies have the desired effects. However, accompanying mobility strategies are necessary to achieve the full potential of urban densification.

Short-haul flights, known for their high carbon intensity relative to distance, are increasingly challenged by high-speed rail (HSR), a viable and environmentally friendly alternative. This study develops a model adapting the “Transit Network Design and Frequency Setting Problem” to high-speed rail, focusing on optimizing existing networks rather than designing new ones. Two sequential algorithms are developed and integrated in the model, which initially generate the optimal paths in the network, and subsequently, set the appropriate frequencies to the existing and new lines. The model is applied to two scenarios within the European rail network, to assess the impact of network modifications on demand distribution, operational costs, and infrastructure development. The findings reveal that the impact of network modifications varies depending on the size and development level of the area. In smaller, well-developed networks, modifications mainly involve adjusting frequencies of existing services, while larger areas with diverse infrastructure levels necessitate new lines and modified configurations. The model offers varying implementation options, balancing capacity utilization and cost minimization, aiding stakeholders in making informed decisions. The potential of utilizing existing infrastructure for sustainable mobility is highlighted, suggesting that future endeavors should include diverse case studies and incorporate user and social cost perspectives, along with timetabling and operational factors for a more comprehensive evaluation

The discussion involving BRT and LRT is well alive among policymakers, who often rely on personal preferences or, as it is called in literature, on “blind commitment” towards one system or the other for their decision-making. The reason for choosing a system according to personal taste is also caused by the unknown preferences that public transport users have for the two systems. It is known from literature that there exists a “rail bonus”, but it is not clear to what extent this applies to LRT compared to BRT. Moreover, it is not known what are the causes behind the rail bonus black-box. This study wants to put some light on the dilemma by testing the existence of an “LRT bonus” and trying to explain it by analysing perceptions and how these relate to each other. Moreover, the study tries to understand how policymakers perceive BRT and LRT and how the decision-making should be done.