Surveys on flexible working and supplementary statistical data sources indicate that several types of flexible working, including working at home and shifting working hours to avoid car use during peak hours, have increased in the Netherlands from 2000 to 2016. An analysis using logistic regressions revealed that possibilities for flexible working as a working condition and type of work are key determinants of flexible working. Moreover, analyses of survey data and statistical data reveal that from 2000 to 2016 all types of flexible working in the Netherlands collectively accounted for a 3% reduction in car kilometers and 2% reduction in public transport kilometers on working days. When combined with traffic data analyses, the development of flexible working seemingly reduced congestion levels on national roads by 18% from 2000 to 2016.

Flexible working, enhanced by information and communication technologies, seems relevant for transport policy, but information about the development of flexible working in the Netherlands and the impact on mobility and congestion is incomplete. The KiM Netherlands Institute for Transport Policy Analysis devised a method to identify the development of flexible working and its impacts on mobility and congestion using an online panel survey and other data. The research findings reveal that working at home and shifting hours to avoid using cars during peak hours are the most important types of flexible working in the Netherlands and that they increased between 2000 and 2016. If there had not been flexible working, the number of car kilometers on working days in the Netherlands from 2000 to 2016 on all roads would have increased by 2.6% more than the observed development. Total public transport kilometers would have been 2% higher. The hours of delay with all types of flexible working on national roads in the Netherlands from 2000 to 2016 increased by 42%, instead of by the 60% it would have been had there not been flexible working (an impact of 18%). Working at home had the largest impact on congestion avoidance over the entire day. During peak hours, peak hour travel avoidance by car had the largest impact. Delay was reduced by approximately 0.1 h on national roads by working 1 day at home or by shifting hours from morning peak to off-peak on one occasion. This reduction was approximately 0.2 h during the afternoon peak.

The increase in traffic volume that arises after opening of new road infrastructure, is often attributed to ‘induced demand’. The objective of this study is to provide empirically derived insights in this phenomenon, in the amount of induced demand and in the benefits that adding road infrastructure has for users. Based on multivariate analyses of detailed data in The Netherlands from 2000-2012, it is concluded that the amount of induced demand in total is relatively low and that the relatively large increase in traffic volume during peak hours on roads that were congested before adding lanes mainly has been caused by shifts in route and departure time. The benefits of the new infrastructure for users have been calculated in terms of savings of travel time and travel time reliability. Implications for cost-benefit analyses of road investments have been reviewed.

This study aimed to demonstrate that travel time reliability and road network robustness from the user's perspective could be measured with the use of detailed traffic data and according to a definition proposed by international experts. These measurements can be used to describe and explain the trend of travel time reliability and to describe the trend of extreme travel time delays (or nonrecurrent congestion). In the Netherlands, the trend of travel time unreliability increased until 2008 but was followed by a decline in subsequent years until 2011. Socio-economic factors, such as population growth and employment, appeared to be the underlying factors for the increase in travel time unreliability. Serving as a counterbalance were various transport policy measures, such as the addition of lanes, traffic management, and speed limitation and control, which were implemented primarily during the years 2009 to 2012. Finally, the study demonstrated how the volume of travel time reliability could be used as a component for the cost–benefit analyses of adding infrastructure and for calculating the social costs of travel time unreliability for users of the main trunk road network.

High-speed rail is seen as a factor contributing to the attractiveness of a location for economic activities. This paper focuses on how the level-of-service characteristics of railway stations, and in particular the presence of high-speed train services, influence the attractiveness of locations for specific types of offices. The results are presented for a stated choice experiment for location choices of offices in the Netherlands. It is concluded that the availability of high-speed train services contributes to the attractiveness of a location for offices. For internationally-oriented offices the areas around stations with international high-speed train services are attractive because of their good international accessibility. We also found an indication that high-speed train services can raise the status of an office site. In the Netherlands, the domestic high-speed train services are less relevant for location choices, because of the small domestic distances. Besides high-speed train services, other location characteristics that determine how well a site is connected to the railway network are also found to be important for location choices. Thereby differences between offices occur, which can partly be explained by the number of trips to/from an office.

Dutch Railways (NS) and Significance have developed a new model system to provide train travel demand forecasts for NS's strategic decision making. The model is among others used for the evaluation of timetable alternatives, forecasting of volumes of new stations, evaluation of tariff policies, all under different exogenous scenarios for demographic, economic and car-related developments. This paper focuses on the design of this model system from two, seemingly conflicting, perspectives. The first perspective is about the user requirements which were formulated and relate to how the model should work in practice, such as: 1) the model should have a clear structure and be transparent in how its results have been calculated; 2) input data and model coefficients should be up-to-date; 3) the model should be able to interact and be consistent with other, complementary models currently in use by NS; and 4) the model should be user friendly and easy to maintain. These user requirements were derived from a thorough investigation within NS among users of forecasts in a wide range of disciplines. The bottom line from these interviews was that forecasts, even based on complex models, should be in a way easy to understand and made plausible. This transparency is the most important condition for forecasts really to be used by the decision makers. Hence from the second perspective the model system has to have sufficient technical detail, complexity and flexibility to provide passenger forecasts for different scenarios, time horizons and study areas and to be adequate in its forecasting precision. It is this trade-off between easy-to-understand forecasts and the necessary complexity of the model to be adequate in its forecasting results which has been the main challenge of this project. As a solution a modular system has been developed to fulfill all these requirements, while finding a trade-off point where both perspectives might oppose each other. Significance contributed in developing a new module to the model system for forecasting demand volumes per station pair for different exogenous scenarios. The module consists of four sub-modules, each with a clear function and output that can be viewed and confirmed. The first sub-module uses an exogenous scenario of demographic, economic and car-related variables to create a year-by-year dataset on the municipal level. A station assignment sub-module forms a station level dataset of these same variables. An elasticity sub-module uses growth factors for scenario and time table developments to forecast demand volumes between station pairs, separately for each of six travel purposes. And a final sub-module forecasts demand volumes for newly opened stations. All sub-modules have been estimated and validated by time series and cross-sectional data. The model system's design has been greatly influenced by the precondition of transparency: the contribution of separate modules in the final forecasting result can be easily visualised. This has contributed to the understanding and acceptance of the model results by the decision makers. Yet the model system is capable of modelling complex processes, such as competition between stations and lagged response to time table changes. The year-by-year forecasts thereby provide insights into the timing and development of dynamic processes. After completion of the first version of the model system in 2009, it has been used for a wide range of forecasting projects, varying from infrastructural studies for Dutch government to minor timetable studies for Dutch Railways.

The Netherlands National Model System (NMS) is known as one of the first disaggregate national travel demand forecasting systems used in practice. The model system has been in use since 1986, and has been extensively updated and extended through its lifetime. Disaggregate discrete choice models are applied in the various modules of the modeling system. These modules simulate the different choices in travel behavior: tour frequencies (TF), mode and destination choice (MD), time of day choice (ToD), secondary and lower level destinations and the choice of a train route. This paper presents the re-estimation and improvements of the Netherlands National Model System (LMS). These include integration of logsums from subsequent choices and combined revealed preference/stated preference (RP/SP) estimations for the mode/destination (MD) models.

Accessibility is often seen to be an important determinant of the location of economic activities. This paper focuses on the specification of accessibility indicators for modelling the location choices of offices, with particular application to the upcoming implementation of a high-speed railway line in the Netherlands. Potential accessibility indicators are formulated, whereby attention is given to the shape of the impedance function and to the role of competitive transport modes in a transport mode's accessibility effect. These indicators are then tested in a discrete choice model on the location of office employment. Finally the accessibility indicators are used to explore the effects of the upcoming domestic high-speed train services in the Netherlands. The analyses show that a Box–Cox impedance function performs best for this application and significantly better than the exponential and power functions. The derived potential accessibility indicators have much explanatory capability for location attractiveness at a regional level, but at an intraregional level connectivity measures become more influential. Finally, it has been found that the accessibility effect of the future high-speed train connection is larger for business travel than for commuting, the value of time of travellers being a dominant factor.

The transport sector has a large share in many environmental problems. Several new transport systems, including various forms of underground freight transport, have been proposed to reduce the environmental impact. However, literature on the life-cycle and environmental impact of such systems is very scarce, reason enough to focus this paper on the assessment of the energy use of and resulting emissions from transport systems, in which the emphasis will be on underground freight transport systems. Evaluation of the energy use and its environmental effects necessitates a complete as possible analysis of the energy use, both directly and indirectly arising from the transport process. Direct energy use is the energy necessary for actually moving the passengers or goods, in most cases the energy used by transporting vehicles. Indirect energy use results from processes like the building and maintenance of infrastructure and vehicles. Whereas direct energy use is typically calculated by sophisticated models, methods for the analysis of indirect energy use are much less developed. This paper will examine one of these methods, the process energy analysis, along with the process emission analysis, which is the process energy analysis equivalent for calculating indirect emissions of greenhouse gases (CO(2)), acidifying gases (SO(2), NO(x)) and other air-polluting substances (VOC, PM(10)). The total lifetime energy use and emissions are estimated using these methods in two case studies. In the first case, transport of crude oil by Dutch long-distance pipelines is evaluated, while the concern in the second case is the so-called Underground Logistic System (ULS) Utrecht concept for the underground distribution of packed goods in the city of Utrecht. This is an innovative concept that makes use of automatic guided vehicles. Each case revealed very distinct characteristics related to the proportion of direct versus indirect energy use and emission levels. Crude oil pipelines have, typically, low direct energy intensities and emission factors, and also very low indirect energy use and emissions compared to other transport modes. Contrarily, the ULS Utrecht is characterised by low direct energy and emission intensities. However, the high indirect energy use and emissions require very high transport intensities to result in a net reduction compared to the alternatives: road transport in most cases. Furthermore, the relationship between direct and indirect emissions of different substances is highly variable.

With the upcoming implementation of high-speed railway infrastructure in the Netherlands, interest has arisen in the spatial-economic effects this might have. Experiences with high-speed rail outside the Netherlands have shown that effects at a local or regional level can be important, due to relocation of employment within regions and cities. This paper focuses on this issue by presenting the results of discrete choice models for office location choice. Both stated choice data and revealed choice data are used. The discrete location choice models give information on to what extent the introduction of high-speed rail in the Netherlands can change the attractiveness of individual cities within the Randstad area on the one hand and of places within these cities on the other hand. As accessibility is an important concept in this topic, attention is given to the specification of accessibility indicators. Hereby, distinction is made between centrality and connectivity. Centrality refers to the position of a location within the transport network and relative to possible origins and destinations. Potential accessibility indicators based on a spatial interaction model are used to represent centrality. Connectivity refers to how well a location is connected to a transport network. Indicators for connectivity are for example the distance to the nearest railway station or motorway access ramp and also the level-of-service provided, such as the train frequency at a station. Furthermore, the paper focuses on a segmentation of employment that reflects this paperÂ’s purpose of studying the influence of (high-speed) rail on location choices. Whereas accessibility by car is relevant for location choices of all types of office employment, accessibility by rail in general and accessibility by high-speed rail in particular seem important to more distinct groups of office employment.

New high-speed railway infrastructure is to be implemented in the Netherlands in the year 2007. In the context of land-use/transport interaction, this paper ex ante evaluates the possible effects of this new infrastructure on employment location. A revealed choice model indicates that the current location of employment is not significantly influenced by the existing high-speed train services on conventional track. However, according to a stated choice model international high speed train services do have an impact when running with frequencies higher than the current services. Experience with these model estimations suggests that using a combination of revealed choice and stated choice data might improve the capability of a land-use/transport interaction model to evaluate high-speed railway developments. Furthermore, the use of perceptions data additionally to calculated indicators can have a beneficial impact on model estimation.

Accessibility is a major factor that determines the effects of transport infrastructure developments on corporate location decisions. High-speed railways have an impact on accessibility by reducing travel times and increasing comfort. However, little research on its effects on location choices has been carried out so far. Still, high-speed railway infrastructure development is advocated for these effects on regional economy. This research uses interviews among corporate decision makers to determine how a change in accessibility due to new high-speed rail infrastructure is perceived by these corporate decision makers and what impact HST infrastructure has on the location choices of firm branches. Firstly, in-dept interviews are held among recently (re)located firm branches to identify accessibility related factors that play a role in the location decision process. For the in-dept interviews we start from the assumption that for firms three aspects of accessibility by passenger transport systems are of importance: access and accessibility for (1) current and potential employees, (2) current and potential business partners, and (3) current and potential customers. Furthermore, corporate decision makers perceive different transport modes in a distinct way. Hereby for example, the level of comfort of the transport mode can be of importance ? it might be of more importance for business trips than for commuting. In this paper special attention is given to how the accessibility by high-speed trains is perceived. The perception of the accessibility of a certain place will differ among firms, because distinct firms appreciate the several facets of accessibility differently. This depends on the activities that take place in the firm branch, for example how often face-to-face contact with (international) business partners occurs, and on the cost structure of the firm. An improved accessibility will reduce transport costs, but on the other hand better accessible locations are likely to have higher prices of real estate. Probably for firms a trade off exists between these opposite cost effects, based on their characteristics. But beside these ?objective? factors, subjective properties of accessibility might also be of importance to corporate decision makers. Being settled on good accessible transport hubs can contribute to the firm?s image. The interviews shed light on how new high-speed rail infrastructure affects the perception of accessibility by corporate decision makers. By questioning different firm types and sizes it is made clear what types of firms are mostly influenced by this change in accessibility. In a later stage of the research, these factors will be quantified by means of stated preference interviews. The results of these interviews will then be used to improve the way accessibility is embedded in land-use transport interaction models, an important instrument for the ex ante evaluation of transport infrastructure.