MaaS in station areas

MAAS IN STATION AREAS

A RESEARCH ON THE IMPACT OF MAAS ON

THE NODE- AND PLACE-VALUE OF TRAIN STATIONS

Damen, A.P. Master’s Thesis for the Spatial Planning programme Urban and Regional Mobility Nijmegen School of Management Radboud University September, 2020

MaaS in station areas

Colophon

Document

Type Master’s thesis

Master’s programme in Spatial Planning Urban and Regional Mobility

Nijmegen School of Management Radboud University

MaaS, railway stations, station area, Handelingsperspectief 38,252

(ITS New Zealand, n.d.) Education

Keywords Wordcount Photo front page Thesis supervision Supervisor Second reader Company Company Supervisors Author Author Student Number City Date Dr. Frits Verhees Dr. Sander Lenferink ProRail Stations

Afdeling Ontwikkeling en Beleid Jantinus Hagens Sandra Belde Art Damen s1030105 Nijmegen September,2020

Preface

On March 2, 2020, ProRail Stations welcomed me at their office in Utrecht, where I would start the last phase of the master’s programme in Spatial Planning. Writing my master’s thesis, but at the same time, having the opportunity to be part of an organisation that always had my interest, was something I desperately was looking forward to. Unfortunately, after two weeks, COVID-19 broke out, which meant that everyone in the Netherlands had to work from home, including me. As a result, my desk was no longer in Utrecht but could be found with my parents, in my student room and in the library of the university.

Despite this unexpected change, now, eight months later, I proudly present my master thesis ‘’MaaS in station areas’’, which also marks the end of my study career in Nijmegen. For the last two years, I cycled to Radboud University with great pleasure to attend lectures, study for exams and socialise with fellow students. I will remember this time with warm memories, but am looking forward to what the future will bring.

I would like to express my appreciation to a number of people. First of all, Rosalie Nijenhuis for the opportunity she gave me to conduct my research at ProRail Stations. Next, Jantinus Hagens and Sandra Belde from ProRail and Frits Verhees from Radboud University for their guidance, feedback and involvement throughout the research. In addition, I would like to thank the respondents for their cooperation and inspiration. Without them, I would not have been able to conduct this research. Finally, I would like to thank my dear parents and friends, Jason and Simone for their support and help throughout the entire study.

In conclusion, I would like to end this preface with a quote that has been very applicable to the subject of this research and the special time in which this research has been carried out.

‘’It is always wise to look ahead, but difficult to look further than you can see.’’ - Winston Churchill

Art Damen

Summary

Train station areas in the Netherlands have to deal with ever-increasing circumstances. Stations in urban areas have to deal with more traffic and spatial developments that are being built closer and closer to the station. Contrarily, stations in rural areas have to deal with a decrease in the number of travellers and disappearing services and facilities. In both situations, the quality of life and accessibility are under pressure. A development that may respond to these changing circumstances is Mobility as a Service (MaaS). In broad terms, MaaS refers to the integration of, and access to, a variety of transport services, real-time travel information and payment in one digital mobility app (UITP, 2019). With that, MaaS is seen as a solution to guarantee and improve the accessibility of various areas, and at the same time create more efficient use of transport modes, and with that land use. However, since MaaS is still a new phenomenon, its influence on the use of various pre- and post-transportation modes and spatial planning at different types of train stations still uncertain. Therefore, this research aims to gain more insights on the development of MaaS and its impact on train stations by trying to find an answer to the following main question: How does MaaS affect the node- and place-value of train stations?

In order to answer this question, first, a literature study has been carried out on the two main elements that arise from this question: MaaS and the characteristics of train stations. Subsequently, the empirical research that followed from this comprises fifteen interviewees with stakeholders who are involved in the development of MaaS and/ or train station areas in the Netherlands. A distinction is made between large train stations in urban areas, medium-sized train stations in suburban areas and small train stations in rural areas. In addition, a real station in the Netherlands has been selected for each area to illustrate the impact of MaaS in an existing situation.

The impact of MaaS is most significant on stations in urban areas. More people will have access to (a variety of) pre- and post-transportation modes that can be used to travel to and from the train station. In particular, small transport modes will play an essential role in these areas. The number of people who can be reached from the station will increase by the better accessibility that comes together with the range of MaaS-services offered. Besides, more homes and offices can be built on the same plot of land because MaaS create more efficient use of transport modes and requires less (parking) space. The main added value of MaaS at train stations in suburban areas is that it can improve the position of the station in the various transport networks. Small modes of transport and public transport are mainly used for journeys in the area itself and towards urban areas. Public transport and the car are mainly used for journeys towards rural areas. Besides, opportunities are seen for station areas in these areas to combine (car) parking of train travellers and companies with MaaS-services for residents of (new) housing projects. This can reduce the dominance of the car in these areas.

The impact of MaaS on the node- and place-value of train stations in rural areas will be smaller compared to (sub)urban areas. This is mainly because the overall demand for these services is smaller, by which fewer services will be offered. However, MaaS does provide the opportunity to guarantee accessibility in these areas at an affordable price. New forms of public transport and the car, in particular, play a role in this. This will mainly be done through the application of new forms of public transport, supplemented by small amounts of MaaS-services on a local level.

Based on this research, it is recommended to give the highest priority to the implementation of MaaS at stations in urban areas. Besides, one party must be designated to advise how MaaS must be implemented in station areas. This ensures that MaaS is applied in the same way at all stations in the Netherlands. The main recommendation for further inquiry is to investigate whether the results of this research hold up at other stations with similar characteristics.

Table of content

1. INTRODUCTION... 6

1.1. INTRODUCTION TO THE RESEARCH ... 6

1.2. PROBLEM STATEMENT ... 7 1.3. RESEARCH AIM ... 7 1.4. RESEARCH QUESTIONS ... 7 1.5. RELEVANCE ... 8 1.6. READING GUIDE... 9 2. THEORETICAL FRAMEWORK ... 10

2.1. PRE- AND POST-TRANSPORTATION ... 10

2.2. THE RISE OF MOBILITY AS A SERVICE ... 13

2.3. TRAIN STATIONS ... 18

2.4. OPERATIONALISATION OF TRAIN STATIONS ... 22

2.5. CONCEPTUAL MODEL ... 28 3. METHODOLOGY ... 30 3.1. RESEARCH PHILOSOPHY ... 30 3.2. RESEARCH APPROACH ... 30 3.3. RESEARCH STRATEGY ... 31 3.4. DATA COLLECTION ... 33 3.5. DATA ANALYSIS ... 35

3.6. RELIABILITY AND VALIDITY ... 36

4. DESCRIPTION OF TRAIN STATIONS ... 38

4.1. ‘S-HERTOGENBOSCH ... 38

4.2. AMERSFOORT SCHOTHORST ... 41

4.3. LAGE ZWALUWE ... 44

5. THE IMPACT OF MAAS ON TRAIN STATION ... 47

5.1. GENERAL ... 47

5.2. MAAS IN URBAN AREAS ... 52

5.3. MAAS IN SUBURBAN AREA... 61

5.4. MAAS IN RURAL AREA ... 66

6. CONCLUSION AND DISCUSSION ... 71

6.1. CONCLUSION ... 71

6.2. DISCUSSION ... 76

6.3. RECOMMENDATIONS ... 76

REFERENCES ... 79

APPENDIX ... 87

APPENDIX 1:STATION DOMAINS ... 87

APPENDIX 2:INTERVIEW GUIDS ... 89

1. Introduction

This introduction discusses the future challenges raises as a consequence of the changing demand for mobility and the possible outcome that the development of Mobility as a Service (MaaS) offers. This shows that it is important to investigate what contribution MaaS makes to the solution of this problem.

1.1. Introduction to the research

Mobility is deeply embedded in Dutch society. It provides the opportunity to travel between cities and villages to live, work and recreate. Every year, the Dutch travel around 180 billion kilometres within their own national borders (KiM, 2019c). And it is expected that this will increase in the future. Until 2040, the National Market and Capacity Analysis (NMCA) from 2017 predicts an increase of 17% to 44% in the number of kilometres travelled by car and 25% to 45% in the number of kilometres travelled by train (Ministerie van Infrastructuur en Milieu, 2017). However, technological and social developments change the requirements of the Dutch mobility system. For example, climate change makes it necessary to look for new, more sustainable forms of transport in order to reduce CO2 emissions. In addition, there are also growing regional differences for the requirements for the mobility system.

Urban areas are facing a further increase in the number of inhabitants. Until 2035, the CBS and PBL (2019) expect a national grow of one million inhabitants. Nearly three-quarters of this growth will end up in large and medium-sized cities. As a consequence, railway stations are facing a significant increase in travellers. Besides, more and more new-build homes are being built near train stations, which further increases the pressure on the available land around station areas. For example, between 2012 and 2018, 44% of the number of new-build homes in the province of Noord-Holland were built within a radius of 1200 meters from a train station (Provincie Noord-Holland, 2019). Almost 60% of these homes were realised around the various train stations within the municipality of Amsterdam. With that, train stations in urban areas are gaining an increasingly important place within the city. The demand for space for real estate and infrastructure creates a tension in land use, as space is scarce and more people tend to use the station.

Opposing to the increasing number of inhabitants in urban areas, it is expected that one out of five municipalities will decline until 2035 (CBS& PBL, 2019). These mainly involve municipalities in rural areas on the edges of the Netherlands. The reason for this is that young people move to more attractive urban areas. Besides, the population in these areas is ageing faster and further compared to urban areas. The result of this population decline is that a self-reinforcing effect is created: facilities such as the supermarket, school and police station disappear. This also affects the local transport offered. Buses are not profitable anymore and are being cut out. As a result, railway stations have to deal with poor accessibility by local public transport services. This increases the need for alternative modes of transport to keep these stations within reach of the people who still live in these regions. In order to keep both urban and rural areas liveable and accessible now and in the future, it is crucial to respond to these changing circumstances right now. Technological developments can play an essential role in this. One of those developments is Mobility as a Service (MaaS). In broad terms, MaaS refers to the integration of, and access to, a variety of transport services, real-time travel information and payment in one digital mobility app (UITP, 2019). With that, the overall aim of MaaS is to reduce (private) car use by stimulating the use of and transfer between public transport and other, more sustainable, modes of transportation. At the same time, less space is required for these means of transport because more people can make use of the same transport service. Transport hubs, like train

stations, play an important role in MaaS and function as the locations where people can easily transfer between different transport modes.

The development of MaaS thus offers possible solutions to the challenges of urban and rural areas outlined above. However, since this development is still relatively new, there is still a lot of uncertainty about it, and certainly on its influence on train stations. ProRail is responsible for the management and maintenance of the national Dutch rail network and train stations and wonders which impact this development has on train stations and how to deal with it. Which modes are influenced by this development and certainly need more space? And how effects this the land use for a mode differently in rural areas compared to suburban or even urban areas? This study looks at the development of MaaS and the influence it has on train station areas in the Netherlands.

1.2. Problem statement

The research problem central in this research is the fact that the impact of MaaS on train stations is still uncertain, while it is seen as a solution to several problems. On the one hand, MaaS is seen as a solution to guarantee and improve the liveability and accessibility of various areas. On the other hand, MaaS is seen as a solution for more efficient use of transport modes, and with that land use. However, it is not yet known what and how great the effect of MaaS is on the use of various pre- and post-transportation modes at different train stations and the spatial planning in these areas. As a result, ProRail does not yet know how to include this development in the (re)development process of station areas. This research forms a first step in charting the impact of this development on railway stations and their vicinity, with which ProRail is better able to respond to this development.

1.3. Research aim

This research aims to gain insights on how MaaS will develop in the upcoming years and affect the use of various pre- and post-transportation modes at different train stations and the spatial planning in these areas. With the results of this inquiry, ProRail must be able to better forecast the impact of MaaS on train stations and to what extent this should be taken into account in the (re)development of station areas.

1.4. Research questions

In order to achieve the research aim, the following main research question has been formulated: How does MaaS affect the node- and place-value of train stations?

In order to answer the main research question, five sub-questions are formulated. These questions derive from the main research question and are bundled following the main steps taken throughout the research.

- What is MaaS?

- What characterises a train station?

The first two research questions are used as a starting point of the research and discuss the two main elements of the main research question. In order to answer these research questions, a literature study is carried out. This information will be combined and used as a starting point for the empirical research, by which the following sub-questions are answered.

- How will MaaS develop in the coming years?

- Which differences can be distinguished for MaaS at different types of train stations?

The next sub-questions focusses on the development of MaaS and its influence on the node- and place- value of different types of train stations. In order to visualise this impact, a distinction is made between three different train stations, which all differ in size and location.

1.5. Relevance

Scientific relevance

In recent years, much research has been carried out on all kinds of aspects related to MaaS. For example, Smith, Sochor and Karlssona (2017) and Karlsson et al. (2020) researched how MaaS could develop and affect the use of different types of transport modes. Moreover, research of Kim (2019b) and Schikofsky, Dannewald and Kowald (2020) focused on key characteristics and motivations of travellers to adopt MaaS-services. However, less research has been carried out on the relationship between MaaS and land use. Rantasila (2015) mentions that MaaS creates the possibility to use means of transportation more efficiently, which results in the fact that less parking space is required for example. In order to make this possible, Rantasila mentions that transport hubs, like stations, are becoming more important. However, this research and other researches do not discuss the spatial effects that MaaS may have on these transport hubs. This research does address this by looking at the effect that MaaS has on the use of different transport modes at train stations, and also the spatial effect that arises from this.

Also, some researches have been carried out on the elaboration of MaaS in (various) countries or cities. For example, Smith, Sochor and Sarasini (2018) researched the different developments of MaaS between Sweden and Finland. Research of Audouin and Finger (2018) focused on the development of MaaS in Helsinki. What these studies have in common is that they investigate the overall impact that MaaS has between different countries or in a particular place. Much less research has been conducted on the different outcomes of MaaS within a country. Rantasaki (2015) already mentions in his research that MaaS has different effects in urban areas compared to suburban areas and rural. However, he does not go into this in detail and only mentions that urban areas can be organised more efficiently and suburban areas and rural can become more vigorous and attractive. This research further examines the different outcomes of MaaS between urban, suburban and rural areas in the Netherlands. As mentioned above, the focus is on station areas.

Social relevance

As mentioned in the introduction, the available space in and around train station is under pressure from two sides. The developments and impact of MaaS influences the accessibility and spatial design of train stations in different areas and, therefore, may require adjustments of the public space to facilitate these modes. However, it is not yet known how this development will develop in the upcoming years. At the same time, the available land in the direct surroundings of railway stations is scarce and expensive, but also very popular due to the high accessibility of the area. Rising real estate prices make it now possible to build next to and even above train tracks and railway stations (Hermanides, 2019). However, this development creates the fact that less space is available to facilitate different pre- and post-transportation modes and possibly clashes with the development of MaaS. ProRail, therefore, wants to gain more insight into the developments of MaaS in order to know how this development will influence station areas.

In addition, it is crucial to manage and implement MaaS in a proper way, that is the same everywhere in the Netherlands. At the moment, already many different parties work on their own MaaS-ecosystem, with their own platform, services, revenue model, service areas and target groups. Because all these parties have their own ecosystem, MaaS may look different in different cities and even differs within the same city at various train stations. For example, travellers in one city may have to use a

different MaaS-app than in another city. This makes the use of these MaaS-services in both cities less attractive. Besides, since there are no national laws or guidelines on how MaaS-services should be offered at specific locations, unclear situations can arise. For instance, a cluttered street scene or duplications may arise. In order to avoid these situations, it is import to create a MaaS-ecosystem which is the same throughout the Netherlands and clear to everybody. This research contributes to this.

1.6. Reading guide

This thesis consists of six chapters. Following the introduction, chapter two contains the theoretical framework which first introduces the characteristics of multi-modal transportation in the Dutch context since MaaS is seen as a pre- and/ or post-transportation service of train journeys in this research. Next, the concept of MaaS, and related developments in the transport sector that influence the number of transport options that can be used via MaaS, are described. Subsequently, this chapter describes the different types of train stations ProRail distinguishes and the model of Bertolini (1999) that characterises train station based on the node- and place-value. Also, the model that derives from the model of Bertolini (the Handelingsperspectief) and is used in this research is elaborated. In conclusion, this chapter provides a summary of the most important elements that will be included in the rest of the research in the form of the conceptual model. Next, chapter three describes the qualitative research approach used to collect and analyse the data that arises from the semi-structured interviews. Chapter four provides an overview of the current node- and place-value of the three different train stations that are used as illustrations to visualise the possible impact that MaaS may have on the different railway stations distinguished. This information is then combined with the results of the empirical research and presented in chapter 5. What clearly stands out is that MaaS affects stations in urban areas in a different way compared to stations in rural areas. Finally, chapter six will discuss the conclusion of the research. First, answers are given to the sub-questions, after which the main research question is answered. In addition, the limitations of this inquiry and recommendations are presented in this final chapter. These recommendations consist of practical recommendations for ProRail how to implement MaaS in station areas and recommendations for further research.

2. Theoretical framework

This chapter contains literature and theories that relate to the subject of this research which answers the first two sub-questions. Firstly, chapter 2.1 discusses the role of pre- and post-transportation in relation to train use in the Netherlands. Next, the development of MaaS and associated developments in the transport sector, that also affect the development of MaaS are debated. This answers the sub-question:

- What is MaaS?

Chapter 2.3 presents the characteristics related to Dutch railway stations. Finally, chapter 2.4 presents models to operationalise railway stations based on their node- and place-value. In addition, the model used in this research will be elaborated. This answers the sub-question:

- What characterises a train station?

2.1. Pre- and post-transportation

As this research focuses on the impact of MaaS, as pre- and post-transportation, of train journeys. This paragraph will first define multi-modal transportation, of which pre- and post-transportation modes are always part of. Next, the relation of pre- and post-transportation modes and time/ distance is presented. Paragraph 2.1.3. discusses the modal split of pre- and post-transportation at different types of train stations in the Netherlands.

2.1.1. Multi-modal transportation

When speaking about pre- and post-transportation, it is always about multi-modal transportation. Van Nes and Bovy (2004) describe multi-modal transportation as:

‘’The combination of two or more different forms of transport within a single trip from origin to destination’’ (p. 226).

These trips can include a combination of the train, bus, tram, car, bicycle, and other transportation modes. The mode used to travel the longest distance is defined as the main-mode of transportation, whereas the other modes are seen as the pre- and post-transportation modes or ‘feeder services,’ respectively, on the origin and destination side of the trip (Krygsman & Dijst, 2001). In this research, the train is always seen as the main-mode of transportation, whereas the other modes of transportation are seen as the pre- and post-transportation modes. These can include walking, bicycle, car, taxis, or other forms of public transport. The transfer between these pre-, main- and post-transportation modes takes place at post-transportation nodes, like, railway stations, bus stops, park and ride facilities, etcetera. In this study, the transfer between different modes always takes place at railway stations. Figure 1 presents a schematic outline of a multi-modal journey.

Figure 1: Schematic outline of a multi-modal journey (own ill.).

A multi-modal trip from origin to destination is seen as one product. Different modes are chained together in which each transport mode serves a particular stage in the transport chain. With that, the trip combines the strong points of each transportation mode, which increases accessibility, efficiency,

and speed, and decreases travel time and space (Van Nes & Bovy, 2004). Besides, multi-modal transportation, in which public transport is the main mode, is seen as a sustainable and environmentally alternative to the car and fulfils the social objective of providing transport and accessibility to everyone (Krygsman & Dijst, 2001).

On the other hand, multi-modal transportation creates space-time limitations to travellers, such as longer travel times, transfers between different modes, and longer access and egress distances between travel modes and origins/destinations (Kumar, Parida & Swami, 2013). These system-characteristics can constrain travellers in their activity engagement opportunities and need to be taken into account when designing the transport system and transfer locations.

2.1.2. Pre- and post-transportation in relation to time and distance

The time that travellers accept for their pre- and post-transportation depends on the distance travelled by train (Peek, 2006). It applies that for longer train journeys, pre-and post-transport may also take longer and that people accept twice as much time for pre-transportation as for post-transportation. Assuming an average travel time for commuting of 45 minutes, walking as the main post-transportation (45% of train travellers walk to their destination (KiM, 2017)) and ten minutes as maximum walking time (Peek, 2006), there are only 35 minutes left for the train journey and pre-transport together. This means that the number of activities/ destinations in the direct surrounding of a station has a significant influence on the network position of a train station.

Figure 2 presents the preferred pre- and post-transportation modes in relation to the distance to the station (Bureau Spoorbouwmeester, 2012). As can be seen, walking is highly preferred for short distances up to ten minutes, which corresponds to a distance up to 1.1 kilometre (Peek, 2006; Debrezion, Pels & Rietveld, 2009). As the distance to/ from the station increases, the preference for other modes increases as well. The bicycle is preferred mostly for distances up to fifteen minutes which correspond to 4.2 kilometre (Debrezion et al., 2009). Public transport (bus, tram, metro) is preferred in urban areas for distances up to 10 kilometres. Where the range and frequency of these services decreases, increases the preference for the car rapidly. This mode is preferred for longer distances which are not located in urban areas.

It is, however, important to keep in mind that the preference for a specific mode of transportation also depends on several factors and, therefore, may differ from person to person and from day to day. Li and Kamargianni (2018) distinguish these factors into natural and built environmental conditions (weather and topography), trip and mode attributes (time and purpose) and socio-economic characteristics (age and gender).

Figure 2: preference of pre-/ post-transportation mode in relation to the distance to the station (Spoorbouwmeester, 2012).

2.1.3. Modal split in the Netherlands

In 2017, the share of multi-modal trips was approximately 3% of all trips in the Netherlands (474 million journeys) (KiM, 2019a). Although the proportion of multi-modal journeys is small in the total share of movements, it play an important role in the use of public transport, especially for train use. The train is the main mode of transportation for 62% of the multi-modal trips in the Netherlands (KiM, 2019a). Nearly 15% of the total distance travelled by travellers (2,8 billion kilometres) is travelled by multi-modal transportation. The share of multi-multi-modal travel and the distance travelled have been fairly constant over the last ten years (KiM, 2019a).

Multi-modal transit is the most popular between urban centres; 19% of these movements take place by multi-modal transportation. Of these movements is 79% made by the train as the main-mode of transportation. Only 7% of the movements are made by multi-modal transportation between an urban centre and non-urban areas. (KiM, 2019a)

According to KiM (2019a), the combination of the bicycle and the train is the most common multi-modal movement. Particularly for movement to and from the railway station, on the origin side of the journey, the share of this multi-modality is high. This statement corresponds to the data of NS, see table 1. On average, 41% of the travellers who travel by train arrive at the railway station by bicycle. This share is higher at larger train stations compared to smaller train stations. In addition to the bike, ProRail and NS distinguish five other transport modes which can be used as pre- and post-transportation modes. These are walking, bus/tram/metro (BTM), car as a driver, car as a passenger and (shared) taxi. Table 1 and 2 present the use of all these modes as pre- and post-transportation in relation to the type of train stations, which are discussed in paragraph 2.3.3.

ProRail distinguishes five types of train stations (see paragraph 2.3.3.). The bicycle has the largest share as pre-transportation mode for all these types of train stations, in which this share is larger for bigger train stations compared to smaller train stations. The proportion of the bicycle is much smaller on the side of the post-transportation since people do not have their own bike at the egress stations. Because of that, a more significant share of the travellers walk to their destination. The percentage of walking is larger for smaller stations compared to larger stations, both in the pre- and post-movement. Conversely, in both situations increases the share of BTM as the size of the station grows. This is because the accessibility by these modes is better in larger cities. The car as a driver is primarily used as a mode to access smaller railway stations. This can be the fact due to the larger distances between the residence (origin) and the railway station, the bad accessibility by BTM and the free parking spaces. The car as a passenger is mainly used at smaller egress stations, where travellers do not have their own vehicle at their disposal and BTM and, an own bicycle is not available. Taxis have a small share in the total modal split in both pre- and post-movements.

2.2. The rise of Mobility as a Service

This paragraph discusses first the development of MaaS, after which other related developments in the transport sector that also affect the use of MaaS are discussed. Paragraph 2.2.3. discusses the potential target group and catchment area of MaaS according to the literature. Next, the different stakeholder’s, like customers and transport service providers, who are involved in the development of MaaS, are presented. Finally, the advantages, like the lower transport costs for customers, and disadvantages, like the stimulation of the use of services such as Uber instead of conventional public transport, of MaaS are presented in paragraph 2.2.5.

2.2.1. The concept explained

As could be seen in the previous section are there several modes used to access/ egress train stations. As the amount of transport options differs from place to place, it can be challenging for travellers to be confronted by all these options when choosing the best way to travel. A development that responds to this dilemma is ‘Mobility as a Service’, also known as MaaS.

In broad terms, MaaS refers to the integration of, and access to, a variety of transport services (such as public transport, ride-, vehicle-, bicycle-sharing, car rental and more), real-time travel information and payment in one digital mobility app, see figure 3 and 4 (UITP, 2019; Johansson, 2017). Based on people’s preferences, tailor-made suggestions are presented for the most suitable travel solution at any given moment of the day. Public transport forms the backbone of the concepts, and with that, it

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aims to increase and improve the use and transfer of different transport modes as alternatives to the car.

Despite the characteristics of this relatively new concept, there is no commonly agreed definition. Hietanen (2014) is seen as the first person who defined MaaS. He describes the concept as a mobility distribution model which delivers users’ transport needs through a digital application offered by a service provider. It combines various transport means to provide a tailored mobility package. The overall aim is to decrease private car ownership and improve the effective use of shared resources (Hietanen, 2014). This definition contains some of the main characteristics of MaaS: customer’s need-based, cooperating and interconnected transport modes, service bundling and service providers. MaaS Alliance (n.d.) adds to the definition of Hietanen the aspect of ‘suitable transport means’. Even if the overall aim of MaaS is to reduce the number of journeys by private cars, this addition suggests that no travel mode is favoured over others and that the term ‘suitable’ varies between each trip and from person to person. Other researchers emphasise other aspects of MaaS, such as the collaboration of multiple actors, use of technologies or one platform aspect. For example, Nemtanu, Schlingensiepen, Lordache and Buretea (2016) focus on the collection, transmission and presentation of the information required for travellers to choose the best transport option.

This research focuses on the influence that MaaS, as pre- and post-transportation modes of train journeys, has on station environments. Therefore, the definition used in this research is the one of Atkins (2015). He defines MaaS as:

‘’The provision of transport as a flexible, personalised on-demand service that integrates all types of mobility opportunities and presents them to the user in a

completely integrated manner to enable them to get from A to B as easily as possible’’ (Atkins, 2015, p. 19).

This definition enables to focus on the spatial influence that MaaS has on the integration of and transfer between different types of pre-/post-transportation modes and the train as the main mode. The impact of MaaS on the collaboration of multiple actors, use of technologies or the platform aspect is less relevant in this study.

2.2.2. Related developments in the transport sector

In addition to the developments of MaaS, there are three other developments taking place in the mobility sector that also affect the development and possibilities of MaaS (Sprei, 2018). These developments are the electrification of vehicles, shared mobility and autonomous vehicles. Down below, these developments and their impact on MaaS are briefly described.

Electrification

The first development that forms an essential element of MaaS is the rise of electric vehicles (EV’s). EV’s make use of a battery which can be recharged by electricity, instead of a combustion engine which uses fossil fuels. With that, EV’s are seen as one of the most potential alternatives to replace these polluting modes of transport, which result in cleaner and quieter transportation (Stock logistic, 2019). This corresponds to one of the main aims of MaaS to reduce emissions from traditional combustion engines (Atkins, 2015). Even though different car manufactures predict contrasting trends of sales in different markets and countries, they all agree on an increasing market share for EV’s (Pereirinha et al., 2018). This trend can also be identified in the Netherlands, where the number of full EV’s is increasing for years. Between 2018 and 2019, the number of EV’s increased with 63,000 (RVO, 2020). However, the share of EV’s is in the Netherlands is only 2.4% and still has a long way to go.

An important contributor to (city) pollution is the public transport sector. Studies of Carrilero et al. (2017) and Lotrakul, Pereirinha and Bouscayrol (2017) showed the effectiveness of electric buses in decreasing the greenhouse gases in cities. This interest is shared by the Dutch public transport authorities, which want to have a fully electrified bus fleet by 2030 (Wever, 2019). In 2019, already 10% of the total bus fleet was full electric (Wever, 2019).

The electric engine also has potential for bike use, as the average distance cycled by commuters is increased by 3.5 kilometres compared to ordinary bicycles (from 6.3 to 9.8 kilometres) (TNO, 2008). With that, electric bikes can form an alternative to cars and public transport in the pre- and post-transportation of train journeys. According to TNO (in CROW, 2012) can electric bicycles increase the total bicycle use in the Netherlands by 43% for distances up to 7.5 kilometres and by 38% for distances up to 15 kilometres. In 2018, 40% of all sold bicycles within the Netherlands was electric, which results in a share of almost 10% on the total amount of bikes (Van Es, 2019; Bremmer, 2019).

In addition, the electric motor has increased the number of vehicles which can be used to travel the first- and last-kilometre of the journey, especially in the form of personal light electric vehicles (PLEV’s). These are small, lightweight, and often

foldable vehicles, powered by an electric motor. Examples of these vehicles are the electric step, -skateboard, -(self-balancing) unicycle, see figure 5. The major advantage of these vehicles is that they are portable and can, therefore, easily be taken along in public transport for example (BMVI, n.d.). However, a lot of these PLEV’s are not (yet) allowed on the Dutch public roads.

Shared mobility

The second significant development that will influence the development of MaaS is the shared use of vehicles. In fact, this development is seen as one of the major requirements to implement MaaS. Shaheen, Bell, Cohen and Yelchuru (2017) state that shared mobility is an ‘umbrella’ term that refers to a broad array of transportation modes with different business models, use cases and travel behaviour impacts. It enables users to have short-term access to a transportation mode instead of owning the transport mode. Users only have to pay for the time they use the service. As a result, it is expected that this increased accessibility can increase multi-modality, reduce vehicle ownership, vehicle kilometres travelled (in some circumstances) and provide new ways to access goods and services, as well as reduce greenhouse gas (Shaheen et al., 2017). According to Machado, de Salles

Hue, Berssaneti and Quintanilha (2018), shared mobility can be defined as a trip alternative that aims to maximise the use of mobility resources.

Overall two types of sharing systems can be distinguished in the transport sector; vehicle-sharing and ride-sharing. Vehicle-sharing contains the share of a vehicle, which can be a car, scooter or bicycle (Machado et al., 2018). This service provides members of a community access to a vehicle for a short-term. The shared vehicles can be distributed across a network of locations within a city or region. Members can access the vehicles at a specific time which is reserved in advance. When they are using the vehicle, they are charged by the time and/ or distance they use it. The most well-known forms of car-sharing are round-trip (in which the car must be returned at the same place as where it is borrowed) and one way (in which the car can be returned somewhere else than where it was picked up). The share of bicycles, and to an increasing extent, the share of scooters and e-steps, is very similar to car-sharing models and can often be found in dense areas/ cities. The two most well-known forms of bike-sharing systems are dock-based (bike must be returned in one of the docks across the service area) and dockless-/ GPS-based (bike can be parked anywhere within the service area) systems (Machado et al., 2018).

The second form of a sharing system is ride-sharing. In essence, ride-sharing fills empty seats in vehicles, which increases the occupancy of the vehicles and reduces the number of vehicles on the road. It serves multiple travellers with identical or overlapping paths (origins and destinations) and departure time in the same vehicle (Shaheen et al., 2017). The two most well-known forms of ride-sharing are carpooling (in which commuters drive together to/ from the workplace) and ride-hailing (which is an online platform that connects passengers with drivers). In addition, public transport and taxis are also a form of ride-sharing.

Autonomous vehicles

Autonomous vehicles are seen as the last major development in the transport sector, which at the same time will influence the development of MaaS. It creates the possibility to drive vehicles around without parking them and thus reduce the total required number of vehicles. These vehicles use sensors, cameras, radar, and artificial intelligence to travel between destinations without human involvement (Gamer, Hoernicke, Kloepper, Bauer and Isaksson, 2019). The development of this technology went very fast in the last decade, and nowadays there are self-driving features in cars which are available for consumers. In addition, there are also tests with self-driving buses and trains (Jacobs, 2019; Fraanje, 2020). Gamer et al. (2019) distinguish six levels of autonomation:

0. No autonomy: driver is in complete control of the vehicle without any assistance.

1. Driver assistance: An advanced driver assistance system (ADAS) in the vehicle can assist or take control of the lane position or speed through lane guidance. However, the driver is always responsible.

2. Occasional self-driving: the ADAS in the vehicle can take control of lane position and speed in certain situations. However, the driver is always responsible.

3. Limited self-driving: an automated driving system (ADS) in the vehicle is in full control in certain situations and informs the driver when to take control (fallback).

4. Full self-driving in certain situations: the ADS in the vehicle is in complete control in specific conditions (e.g. on the highway), the driver might supervise.

5. Full self-driving in all situations: The ADS in the vehicle acts as a virtual chauffeur and can drive in all circumstances. The human occupant is a passenger and does never have to drive the vehicle.

It is being thought that autonomous vehicles can accelerate the growth of MaaS when more people are willing to use car-sharing systems (Jittrapirom, Marchau, Heijden & Meurs, 2017). In that case, transportation options will be needed for everyday use. However, questions like liability and needed technological support will play a role in the way autonomous vehicles will develop. The question that arises from this is not whether the autonomous vehicle will drive around, but when. Some already state that this will be the case shortly after 2020 (Arbib & Seba, 2017), while other state that this will not become reality until the 2030s or even -40s (Litman, 2017).

2.2.3. Target group and catchment area

According to Matyas and Kamargianni (2018), MaaS offers a lot of potential for the mobility sector in the (near) future. However, this development will not be an outcome for everyone at any location. In 2019, the Knowledge institute for Mobility (KiM) in the Netherlands asked 100 experts for their opinion on the development and potential of MaaS. The results of the study show that experts see young adults aged between 18 to 30 as the most promising target group for MaaS (KiM, 2019b). This group is followed by adults aged between 30 to 44 years old. Elderly of 75 years or older are considered as the least promising target group for MaaS. A possible explanation for this is the relatively low possession of smartphones and the limited technological and digital skills among this group. Research from ITS Australia (2018) and Jittrapirom et al. (2018) confirm that younger people are more likely to adopt MaaS.

In addition to these potential age groups, experts see singles and families without children as the most potential households to adopt MaaS (KiM, 2019b). With that, it can be concluded that the presence of children in a household is seen as an obstacle to embrace MaaS.

According to the same experts are business-related and commuting journeys, the most promising travel motives for the use of MaaS (KiM, 2019b). Experts surveyed by Jittrapirom et al. (2018) add to this that they see more potential for MaaS for trips with higher economic values. Visiting family and friends, leisure and education are also considered promising motives to use MaaS (Kim, 2019). On the other hand, trips to sports and grocery shopping are seen as the least potential motives to use MaaS. Both authors also confirm that they expect MaaS to be first implemented in urban areas (Jittrapiron et al., 2018; Kim, 2019b). Experts in the research of KiM (2019b) explicitly mention the centres of metropolitan areas as the most potential. The edges of these areas and medium-sized cities follow hereafter. Suburban regions and rural areas are considered to be the least promising areas to implement MaaS. Jittrapirom et al. (2018) confirm this potential for metropolitan areas. Experts in this research expect that the required transport infrastructure and organisations to implement different services are more available and developed in urban areas. With these results, it is being expected that train stations in metropolitan and urban areas are the most potential stations to adopt MaaS.

2.2.4. Stakeholders

The creation of a MaaS-ecosystem is built on the interaction between different groups of actors. In order to reach this ecosystem, Juniper and Moovel (2017) distinguish four main different types of stakeholders:

- Customers: travellers are the potential customers and users of MaaS-services. These can be both private customers or business customers.

- Transport service provider: these are the actual mobility services, like car- and bicycle-sharing companies. Public transport is also a transport service provider but is described separately by Holmberg, Callado, Sarasini and Williander (2016) since local/ regional authorities often subsidise this service, and with that, pursues a different aim.

- Platform service provider: the platform service provider provides the interface between the customers and the mobility service providers via a smartphone application. Transport service providers can offer their service real-time. For customers, it must be possible to search and compare several transport options, after which a reservation and booking can be made. To do so, platform service providers need real-time information from transport service providers and require the help of payment services and telecommunication-/ data management companies. - Policymakers: local-, regional-, and national policymakers are important actors towards the way MaaS can and will develop. Legislation can shape the nature of MaaS as it can allow and restrict specific transport modes and business models.

2.2.5. Advantages and disadvantages of MaaS

The potential benefits of MaaS can be seen from different perspectives. For users, MaaS can meet the mobility needs of the traveller with same or lower costs than their current transport choices. At the same time, the benefit can be added that enhance the user experience by more useful/ enjoyment travel (Rantasila, 2015). It may even be possible that trips will be eliminated completely (Civitas, 2020). From a transport service providers’ perspective, MaaS can increase the market share of their service, by a better understanding and access to its (potential) users. However, MaaS can be a competitive threat to those service providers who will or cannot integrate their service in a MaaS-ecosystem (Civitas, 2020). For platform service providers, MaaS should deliver a profit as they earn money by the number of travellers who use a transport mode offered by their service. The interest of policymakers lies in a safer and more efficient transport system (including infrastructure and services), and thus a better allocation of transport services (Hietanen, 2014). This should decrease car use which would result in less congestion and emission of greenhouse gases. Besides, a well-functioning transport system promotes a better living environment.

On the other hand, MaaS may cause some disadvantages. Where the aim of policymakers is to decrease car use may MaaS stimulate the use of services such as Uber instead of conventional public transport (Civitas, 2020). And in addition, the use of autonomous vehicles by young people, elderly and people with a disability (Arbib & Seba, 2017). This can cause additional driven vehicle kilometres and congestion. At locations where the use of traditional public transport is not strong, these developments may lead to cuts in public transport services which impact the accessibility of people who do not use MaaS, like elderly and poor people without access to smartphones and credit (Civitas, 2020).

Also, MaaS transport- and platform service providers are to an increasing extent virtual multinational companies that locate themselves in countries with low corporation taxes. This creates the fact that countries and cities where the majority of the actual services are running, but with higher corporation taxes are limited to generate income from these companies by which for example, social infrastructure could be paid (Civitas, 2020). In addition, the rise of MaaS-services requires new regulatory systems. For countries and cities that need regulation in order to promote goals such as environmental protection and public safety, this can be a real disadvantage (Civitas, 2020).

2.3. Train stations

Train stations come in all shapes and sizes: from large to small, from old to new and with or without a station building. This section discusses the characteristics of train stations. Paragraph 2.3.1. and 2.3.2. will describe the definition of train stations and its areas of influence. Next, the five different types of train stations ProRail distinguish are described and finally, paragraph 2.3.4. describe the stakeholders who are involved in the development of station area’s and their relation in the Netherlands.

2.3.1. Station buildings

In essence, the term ‘train station’ refers to the building or complex where trains stop and consists of rails, platforms, and amenities: ticketing and service, shops, toilets, etcetera. Stations are seen as the links between the train service on the one side and villages and cities on the other side. To improve the transition between these different sides of the station, Bureau Spoorbouwmeester (2012) developed, in collaboration with the Dutch Railways (NS) and ProRail, ‘the station concept’1_{. This document forms}

a guideline how the desired experience, appearance and layout of station buildings and their direct vicinity can be created. In order to do so, four different domains are distinguished. Appendix 1 provides a discretion of these four different domains.

2.3.2. Station areas

The station area starts where the station building stops. However, there is no clear spatial definition of a station location or area in the literature (Hasiak & Bodard, 2016). Different disciplines use different views which have led to various discourses. For example, station designers describe a station area as the location in which a fast and pleasant transfer between different modalities takes place (Peek, 2006). Another description is that of urban economists. They see an inner-city station area as a location, where the combination of multi-modal accessibility, the inner-city location and the presence of facilities create an unique business location (Peek, 2006). Simkens (2020) refers to the station area in a more practical sense as the area from which the station building is directly visible.

The same applies to the area of influence of train stations. In general, no fixed spatial area of influence can be determined. Rail operators and network owners use the term ‘area of influence’ to define the area in which travellers are likely to take the train (Hasiak & Bodard, 2018). The definitions of these perimeters are primarily based on the consideration of an acceptable amount of time for travellers to reach the station, see paragraph 2.1.2. These geographical representations take the form of isochronous. An isochronous indicates the travel time to or from a place with a specific means of transport, or in other words; how far can you get with a particular mode of transport within a certain travel time? (Isochroon.nl, n.d.)

According to the Province Noord-Holland (2019), there are three main isochronous which need to be taken into account when looking at the catchment area of the railway station. First of all, the direct station environment with a maximum radius of 300 meters. This area contains the spatial infrastructure and amenities to facilitate all pre- and post-transportation modes, e.g. bus station, bicycle parking and K+R. Next, the primary area of influence with a radius of 1,200m. This scale shows the main walking-routes between nearby origins and destinations. Finally, the secondary area of influence with a radius of ten-minute cycling. This scale shows the main cycle-routes from the surrounding residential areas and the number of inhabitants and workplaces that can be reached by bike. Besides, the radius of 1,200m and ten-minute cycling also show the main bus- and car network. Although these different descriptions, ProRail does not apply a fixed spatial delimitation to define the station areas. According to them differs the size of the station area and its area of influence per station (R. Egberts, personal communication, April 15, 2020). Therefore, this should be determined in agreement with the local stakeholders involved.

2.3.3. Train stations in the Netherlands

By 2020, there are 401 railway stations in the Netherlands (ProRail, 2020). ProRail distinguishes five different types of railway stations based on the number of people arriving and leaving from the train

station per day (from now on referred to as ‘travellers a day’). Travellers who transfer between trains are not taken into account. Table 3 presents an overview of the different types of train stations, and figure 6 shows the location of these stations in the Netherlands.

Type of train station

Description

Halte A maximum of 1,000 travellers a day, no elevators and escalators or if the total transfer area is smaller than 2,000 m2, of which less than 20% is roofed. In the Netherlands there are 115 Halte stations.

Basis Between 1,000 and 10,000 travellers a day. Or if there are elevators and/ or escalators. In the Netherlands there are 233 Basis stations.

Plus Between 10,000 and 25,000 travellers a day. In the Netherlands there are 27 Plus stations.

Mega Between 25,000 and 75,000 travellers a day. In the Netherlands there are 20 Mega stations.

Kathedraal More than 75,000 travellers a day. In the Netherlands there are 6 Kathedraal stations.

Table 3: Type of train stations (Stations.nl, n.d.).

2.3.4. Stakeholders

Rail network

The institutional context of the Dutch railway system is, to a great extent, influenced by the railway policy of the European Union (Van de Velde, 2013). Liberalisation was an important theme at that time, with the idea that this would lead to more competition among transport operators, which would have a positive effect for travellers. A core part of this policy was to divide train operation and infrastructure management, in order to give potential competitor train operators a fair chance to tender (Van de Velde, 2019). As a result, this has led to various elaborations in various countries. The Dutch government decided to gradually unbundle the integrated Dutch railway company (Nederlandse Spoorwegen N.V.) into a train operations company (NS N.V.) and a rail infrastructure management company (ProRail N.V.). Both companies are still state-owned (Van de Velde, 2013).

ProRail divides the space on the track to the different goods and passenger operators. Besides, they maintain and manage the tracks and are responsible for the safety systems. NS is the passenger operator on Dutch main rail network. However, it has so far been given a monopoly position from the Dutch government because this tender is awarded privately (ANP, 2015). Only for regional lines competition has been introduced with open tenders. Next to NS, nine other passenger operators and nineteen freight operators operate on the Dutch railways (ProRail, n.d.). Figure 7 shows the institutional context of the three parties.

Train stations

Several stakeholders are also involved in the development of train station areas. In addition to the responsibility that ProRail bears for the rail network, it is also responsible for the development and maintenance of railway stations (Haffner, Agterberg van Achterberg, de Bas, Van Hussen & Spit, 2014). ProRail is also responsible for the bicycle facilities, such as bicycle parking’s and -lockers. The daily management (in particular consisting of cleaning and maintenance tasks) of these stations is carried out by NS Stations, which is a separate department of NS. NS Stations also has the rights to exploit the retail stores at all existing and new stations (Haffner et al., 2014).

In addition to these actors, there are also other actors involved in the development of train station areas. Local and regional governments occupy the land next to the station and are therefore always involved in the development of station areas (Tudorica, 2014). Besides, they occupy the land of bus and tram stations, which are located next to the railway station. Also, real estate developers and housing associations are important actors in the realisation of property in station areas (Tudorica, 2014). Figure 8 presents an overview of all actors involved in the development of station areas.

Legenda:

Yellow – NS, Blue – ProRail, Pink – Transport service provider (NS, Arriva, etcetera), Green – Province, Light blue – municipality, Red – property owners

Figure 8: Involved actors in (the surroundings area of) a train station (Tudorica, 2014).

2.4. Operationalisation of train stations

The previous paragraph showed the ‘general’ features and actors involved of train stations in the Netherland. This paragraph describe the way train stations can be operationalised. The node-place model of Bertolini (1999) is seen in the scientific literature as the model that underlies this. This model is presented in paragraph 2.4.1. Subsequently, section 2.4.2. discusses a number of models that derived from the node-place model of Bertolini and are used to characterise train stations in the Netherlands. These models partly formed the basis of the model which is used in this research. This model is described in section 2.4.3.

2.4.1. Node and place-value

It is generally recognised that land use and transportation patterns are closely related to each other. This interaction can be illustrated by the ‘land-use transport feedback cycle’ (Wegener & Fürst, 1999). The spatial separation of human activities create a need for travel of people and goods, and thus influences people’s travel behaviour. The other way around, the availability of infrastructure makes certain locations (better) accessible, which affect the locational behaviour of investors, firms and households.

The node-place model of Bertoline (1999) follows the reasoning of the land-use transport feedback cycle but is focused explicitly on station areas. The basic idea of the model is that improving the transport system of a station area, or the node-value, creates favourable conditions to further development of the location. In turn, the development of the area, or the place-value, will lead to an increase in the further development of the transport

system. Bertolini emphasises the term ‘’conditions’’, as other indicators influence the development potential of a train station as well. For example, Meijers (in Simkens, 2020) refers in this respect to the collaboration of stakeholders, such as municipalities and real estate developers.

The model of Bertolini, see figure 9, distinguishes five ideal-typical situations (Bertolini, 1999). Each situation reflects a particular relative position of a station area on the node and place scale. Along the diagonal line are the

equal positioned on both the node and place scale. At the top of the diagonal line are ‘stressed’ locations situated. Both the diversity and density of urban activities and mobility flows are maximised. This results in the fact that the development of activities is high and that this potential has also been realised (strong place). The same applies to the potential of the transport system (strong node). As a result, these concentrations of activities and flows may result in conflicts between several stakeholders over the use of space, which makes further development of the location difficult. At the bottom of the diagonal line are the ‘dependent’ locations situated, where the struggle for space is minimal. Both the node and the place values are relatively weak, which creates the fact that factors other than internal node-place dynamics (e.g. subsidies) must intervene to sustain the area. Besides, two ‘unbalanced’ locations can be detected. At the top left are ‘unsustained nodes’ located. These are locations where the transport systems are relatively further developed than the urban activities. An example of such a place can be a recently opened station in an area which is still in development. At the bottom right are ‘unsustained places’ located. These are locations where urban activities are relatively further developed than the transport systems. An example could be a city centre which is challenging to reach by several modes.

Following the reasoning of the land-use transport feedback cycle, both unbalanced situations are expected to move towards a more balanced situation over time (Chorus & Bertolini, 2011). This can be done in two different ways. An ‘unsustained place’ can either grow in node-value, for example by implementing new transport options, or decrease in place value, for example by developments in lower densities. The same applies to ‘unsustained nodes’ but the other way around. Either the place-value is stimulated, for example by attracting new property developments, or decrease in node-place-value, by a reduction of its transport services.

Peek (2006) has tried to further define the ‘node’ and ‘place’ concepts based on two different levels at which a station can be seen. These levels are the ‘network-’ and ‘location’ levels, see table 4. This results in four perspectives in which the node- and place-values of a train station can be seen. For the node-value, the ‘connection link’ perspective concerns the extent to which the station is linked to other stations via different transport networks. Rietveld (2002) distinguishes the car, public transport (train, bus, tram and metro) and non-motorized traffic (pedestrian and cyclist). These transport modes each have their own network and scale level at which it serves travellers.

As a ‘transfer machine’, it is about the transfer between different modes at a station. It is important to minimise the transfer-resistance for travellers as much as possible in order to improve the quality of a multimodal journey. According to Van Hagen and Peek (in Staps, 2012), this can be done in three different ways: accelerate, densify and improve experience. By accelerating, the travel and waiting time and thus the total journey time can be decreased. Accelerating mainly concerns a faster train journey. Densify creates the fact that origins and destinations are closer to the station which decreases travel time of pre- and post-transportation and also waiting time. Improving experience is about low-valued moments in the journey, for example during transfer. Facilities at stations can increase the amenity value, which improves the transfer experience.

The place value can be seen from an ‘urban centre’ and a ‘meeting place’ perspective. The urban centre refers to the diversity of functions that are present in the station area, which stimulate economic growth and spatial quality (Peek, 2006). This can include housing, offices and leisure activities. This mix of functions have to make sure that there are few or no moments during the day that no visible activity takes place. Finally, a station can be seen as a meeting place. This mainly concerns the interaction between people in and around the station and primarily happens when people are waiting for the train or bus, in one of the shops or at the information desk (Peek, 2006).

Network level Location level

Node Connection link Transfer machine

Place Urban centre Meeting place

Table 4: Interpretation of a station location (Peek, 2006).

2.4.2. Elaborations of node-place model

Bertolini’s node-place model has been used in many studies and forms the basis of several follow-up models (Caset, 2020). This paragraph briefly discusses three models which derive from the node-place model and underlie the model used in this research.

Butterfly-model

One of the most well-known elaborations of Bertolini’s node-place model is the Butterfly-model of the province of North Holland and Vereniging Deltametropool (Provincie Noord-Holland & Vereniging Deltametropool, 2013), see figure 10. The model distinguishes three characteristics for both the node- and place-value of train stations. The node-place-value positions the station in the public transportation network, road network and slow traffic (pedestrian and cyclist) network. The place-value positions the station based on the intensity of inhabitants, workers and visitors, the degree of functional

diversity and its proximity. The ‘Butterfly’ functions best when both sides of the wings are in the right balance (Provincie Noord-Holland & Vereniging Deltametropool, 2013). For this, the centre aspects of the wings (public transport and intensity) are in particularly strongly related to each other and should ideally be in balance.

Quadrant model

A second model that underlies the model used in this study is the Quadrant model from the Province of Noord-Brabant (2018). This model is being used to describe the current and potential situation of different types of transport hubs. These include both (inter)national, as regional and local hubs. The model shows the characteristics of a transport hub using four quadrants. These are space (opportunities to densify), connections (opportunities for acceleration), transfer (opportunities to link different networks to each other) and experience (opportunities to improve comfort). Every quadrant has three

characteristics, see figure 11. Besides, the document of the province of Noord-Brabant describes the desired situation of all aspects per transport hub.

Figure 10: Butterfly model (Provincie Noord-Brabant & Vereniging Deltametropool, 2013).

TOD-Radar

Another model which underlies the model used in this study is the TOD Standard from ITDP (2017). The model has been used by the state of Zuid-Holland to evaluate 67 train station environments (Staat van Zuid-Holland, n.d.). The model describes eight principles divided into 25 indicators that measure the implementation of the specific indicator. Every indicator receives a score which contributes to the total score of the train station. The spatial analysis is executed for the area up to one-kilometre walking distance from the station. Also, the analysis is executed separately for both sides of the train station environments, as the values of the indicators can differ from each other. The indicators are: 1) walking, 2) Bicycle, 3) connect, 4) public transport, 5) diversity, 6) intensify, 7) build compact, and 8) change. Figure 12 provides a schematic representation.

(Dis)advantages of models

As stated before, the models presented above are all different elaborations of the node-place model of Bertolini. With that, they all have their own (dis)advantages. The Butterfly-model only focuses on the node- and place- value of train-station, the quadrant model focuses on both train stations and bus stations, and the TOD-radar also focuses on train stations, by which a distinction is made between the different sides of the station. Besides, the quadrant model and TOD-Radar both take into account more characteristics related to a station area than the Butterfly-model does. A disadvantage of all models is that all indicators are based on quantitative data, which makes it harder to come to final findings. Besides, these data may present bad or low characteristics while this is not a problem in the real situation.

2.4.3. The Handelingsperspectief

The models presented above have contributed to the design of the model which will be used in this research. This model is called the ‘Handelingsperspectief’ and has been developed by ProRail, in collaboration with the Ministry of Infrastructure and Water Management (Ministry I&W), regional-, and local governments and transport providers (Toekomstbeeld OV – Kernteam Kwerkstroom Ketens & Knopen, 2019). Also, other (policy) documents and consultations between these stakeholders have contributed to the design of the Handelingsperspectief (S. Belde, personal communication, April 8, 2020).

The Handelingsperspectief is an instrument intended to jointly outline the current and future situations of public-transport hubs (Toekomstbeeld OV – Kernteam Kwerkstroom Ketens & Knopen, 2019). To do so, all relevant stakeholders must be involved. Depending on the size and national importance of the node, the presence of the Ministry of I&W is desirable. ProRail and NS are always involved for the 401 train stations in the Netherlands. Also, the relevant municipality, province and regional transport providers are involved (depending on their position as a contractor for the regional train, bus, tram and metro). Depending on the location of the station, stakeholders as educational institutions, travel interest groups, local entrepreneurs and/ or large companies must be involved as well.

Figure 12: TOD Radar executed by Staat van Zuid-Holland (n.d.).