The on-time completion of light rails in the United States: a qualitative comparative analysis

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Table of Contents
List of figures and tables..............................................................................................................................................4
Summary............................................................................................................................................................................5
1 Problem statement....................................................................................................................................................6
1.1 The problem definition & relevance...........................................................................................................................6
1.1.1 The research objective & research question ..............................................................................................7
1.2 The unit of analysis...........................................................................................................................................................7
2 The outcome and the conditions..........................................................................................................................8
2.1 The outcome........................................................................................................................................................................8
2.2 The explanatory factors .................................................................................................................................................8
2.2.1 Project modifications............................................................................................................................................8
2.2.2 Funding.......................................................................................................................................................................9
2.3 The context factor: public resistance............................................................................................................................9
3 Case studies...............................................................................................................................................................12
3.1 Data collection ................................................................................................................................................................12
3.2 Case selection and distribution.................................................................................................................................12
3.3 Case Descriptions...........................................................................................................................................................13
4 Calibration.................................................................................................................................................................15
4.1 Outcome: On-time Completion..................................................................................................................................15
4.2 Project Modification......................................................................................................................................................16
4.3 Funding..............................................................................................................................................................................17
4.4 Public Resistance............................................................................................................................................................18
4.5 Calibrated data...............................................................................................................................................................19
5 Analysis ......................................................................................................................................................................21
5.1 Software.............................................................................................................................................................................21
5.2 Comparison ......................................................................................................................................................................21
5.3 Interpretation..................................................................................................................................................................23
5.4 Within-country lessons ................................................................................................................................................24
6 Cross-country lesson .............................................................................................................................................25

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6.1 Differences and similarities between the US and Canada..............................................................................25
6.1.1 On-time Completion ...........................................................................................................................................25
6.1.2 Funding....................................................................................................................................................................25
6.1.3 Project modifications.........................................................................................................................................26
6.1.4 Context: public resistance................................................................................................................................26
6.2 The adaptation of policies with lessons from other contexts........................................................................26
6.2.1 Project modifications.........................................................................................................................................27
6.2.2 Funding....................................................................................................................................................................27
6.2.3 Public resistance..................................................................................................................................................27
6.3 Measures based on lesson drawing.........................................................................................................................28
7 Process reflection...................................................................................................................................................29
8 References.................................................................................................................................................................30
9 Appendix....................................................................................................................................................................38
9.1 Appendix A - The raw data matrix..........................................................................................................................38
9.2 Appendix B – Internal group evaluation...............................................................................................................44

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List of Figures and Tables
Table 2.1: Factors to describe Public Resistance in a qualitative way................................................................ 10
Figure 3.1: Map of case distribution. Data: Natural Earth, 2019........................................................................... 13
Table 3.1: The summarized data matrix......................................................................................................................... 13
Figure 4.1: Explanation of the cross-over and anchor point of the outcome................................................... 15
Table 4.1: The calibration values for each factor of the outcome......................................................................... 15
Table 4.2: explanation of the factors for the condition of project modification.............................................. 16
Table 4.3: The calibration values for each factor of the condition........................................................................ 16
Figure 4.2: Explanation of the crossover and anchor point of project modification..................................... 17
Table 4.4: The calibration values for each factor of the condition......................................................................... 17
Figure 4.3: The calibration values for each factor of the condition....................................................................... 17
Table 4.5: The calibration values for each factor of the condition........................................................................ 18
Figure 4.4: Explanation of the crossover and anchor point of public resistance............................................ 19
Table 4.6: The calibrated data matrix.............................................................................................................................. 19
Table 5.1: The raw truth table.............................................................................................................................................. 22
Table 5.2 The final truth table.............................................................................................................................................. 22
Table 5.3 Complex solution from the fsQCA.................................................................................................................. 23

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Summary
In this study, the combined effect of three conditions on the on-time completion of light rail projects is
explored, namely the presence of public resistance during the construction phase, the occurrence of
modifications to the project plan during the construction phase, and the government level that provided
funding for the project. A fuzzy set Qualitative Comparative Analysis (fsQCA) is used in order to compare
the contribution of those three conditions to on-time completion for sixteen cases in the United States
(US). The outcome shows that three combinations of those conditions contribute to an on-time
completion of light-rail projects: the absence of project modifications combined with the presence of
public resistance, local funding combined with the presence of public resistance and the absence of
project modifications combined with local funding. Although the results mainly align with the literature,
one striking outcome is observed: a presence of public resistance, combined with other conditions,
contributes to on-time completion. The case study explains that in most cases, because of public
resistance, a collaborative process is started that leads to better outcomes.
Eventually, a comparison is made between the US context and the Canadian context in order to draw
lessons for policy making with regards to light rail projects in Canada.

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1 Problem Statement
1.1 The problem definition & relevance
With the growing environmental awareness on the one hand and the pressing congestion issues in urban
areas, on the other hand, sustainable modes of transport are gaining more and more importance (De
Bruijn & Veeneman, 2009; Sovacool & Yazdi, 2019). Policymakers have to come up with innovative
solutions to tackle these increasingly complex problems. Light rail systems are an attractive option to
improve the accessibility of urban areas, reduce air pollution, and improve traffic congestion (De Bruijn
& Veeneman, 2009; Sovacool & Haieri Yazdi, 2019).
The term ‘light rail transit’ appeared in the United States (US) in 1972 and it served as a promising
concept for an inexpensive form of rapid transit on a city scale (Thompson, 2003). Within the past few
decades, light rail systems got widely implemented in cities in the US (Kuby et al., 2004; Greater Greater
Washington, 2015). Currently, almost 30 American cities make use of a light rail system (Greater Greater
Washington, 2015). However, construction delays are typical for major transport projects in the US
(Pickrell, 1990; Touran et al., 2006). According to Touran et al. (2006), 90% of rail projects in the US until
2006 experienced some form of delay. Even recently, delays in construction are a topic of relevance: in
cities such as Maryland and Minneapolis the construction of light rail projects got delayed due to public
resistance (Construction Dive, 2019), and the construction of a new light rail line in Seattle is on the edge
of being delayed (The Seattle Times, 2019). This indicates that not much has been learned in the past
thirty years. This observation makes the US a research area of interest with regard to light rail projects.
A delayed project is problematic for a number of reasons. First, project delays often go hand in hand with
cost overruns in the construction phase (Flyvbjerg et al., 2018; Flyvbjerg & Turner, 2018). Second, due
to delay, light rail operators will miss out on a part of the revenue (in the period that the light rail system
should have been delivered). This means that it will be more difficult to reach the forecasted amount of
revenue (Flyvbjerg et al., 2018; Flyvbjerg & Turner, 2018; Pickrell, 1990). Third, public resistance can
arise or increase because of time overruns (Richmond, 2011).
A lot of research has been done on the causes of delays in construction projects (Assaf & Al-Hejji, 2006).
However, most studies particularly focus on technical elements, such as the design and the materials
used in construction projects, or on the type of contract that is used (Assaf & Al-Hejji, 2006; Odeh &
Battaineh, 2002). Not much research has been done on the combinations of different factors that can lead
to “on-time” completion of light rail projects. Therefore, this study is of relevance to this research area.

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In this study, the combined effect of three conditions on the on-time completion of light rail projects will
be examined: the presence of public resistance during the construction phase, the occurrence of
modifications to the project plan during the construction phase, and the government level that provided
funding for the project. These conditions have been pointed out as important factors. In order to
investigate this, a fuzzy set Qualitative Comparative Analysis (fsQCA) will be conducted.
1.1.1 The research objective & research question
The aim of this research is to contribute to improving on-time completion of light rail expansion projects
in the US by comparatively analyzing combinations of public resistance, project modifications, and
funding. Consequently, this study consists of a comparison to light rail systems in the Canadian context
in order to provide possible policy adaptations based on lessons drawn from US case studies.
To achieve this objective, the following research question will be used:
What combinations of public resistance, project modifications and funding are necessary and/or sufficient
for realizing on-time completion of light rail expansion projects in the United States?
1.2 The unit of analysis
For the present purpose, in this research light rail projects are considered as cases and different policy
measures as conditions that might produce the desired outcome. The investigated cases are light rail
systems in the US on the meso-level. According to the Transportation Research Board (1978), light rail
transit is a metropolitan electric railway system characterized by its ability to operate single cars or short
trains along exclusive rights-of-way at ground level, on aerial structures, in subways or, occasionally, in
streets, and to board and discharge passengers at track or car-floor level. According to Garret (2004),
there are two types of light rail systems. The first system involves light cars, sometimes called trolleys,
trams or street-cars, which run along the streets and share space with motor vehicles. The second light
rail system consists of multicar trains that operate along their own right-of-way and are separated from
roadways. In this study, the second definition of light rail systems is used.
All light rail systems are powered by electricity, provided by either an overhead wire or a third rail. Light
rail systems are generally cheaper to operate than buses and have a greater ability to maneuver sharp
curves and much steeper grades (Garret, 2004). The first seven cities that operate the modern light rail
system in the US are Boston, Newark, New Orleans, Philadelphia, Pittsburgh, San Francisco, and
Cleveland. As of April 2018, as counted by Light Rail Transit Association, there are 27 light rail systems
all throughout the US. In our study, we will examine cases in Colorado, Virgina, Minnesota, New Jersey,
Texas, North Carolina, California, Oregon, Arizona, and Washington.

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2 The Outcome and The Conditions
2.1 The outcome
Since this study aims to understand configurations that lead to the on-time completion of light rail
projects in the US, the on-time completion is defined as the outcome. According to Menches and Hanna
(2006), on-time completion is an important aspect of determining a project’s success. The study will
focus on the implementation phase of light rail projects. The starting point of implementation is defined
by the moment that construction begins (T0), while the end is defined as the date of the completion (TEC).
However, public construction projects are frequently behind schedule due to various uncertainties
(Harun et al, 2017). Elinwa and Joshua (2001) defined delay as the time lapse between the agreed
estimation or completion date and the actual date of completion. Referring to Flyvbjerg et al (2018), this
study measures time overrun as the actual completion time (TAC) in the percentage of estimated
completion time (TEC). Research by Majid & McCaffer (1998) showed that 50% of delays in construction
projects can be categorizedas non-excusable delays. They state that in 50% of the casesproject managers
were able to prevent the delay since the reason for the delay was within the scope of the project (Majid
& McCaffer, 1998). In this study, the success of the light rail project will be further categorized as low and
high overrun. The combinations of factors that contributed to on-time completion received a value of 1
(positive cases) and those that did not contribute to on-time completion received a value of 0 (negative
cases).
Much research has been done on delays within rail projects, especially on Asian cases (Morris, 1990;
Heon Han et al., 2009, Memon et al., 2011). According to Cantarelli (2009), the average time overrun in
Dutch rail projects is 2,2 years. She specifies this in research conducted several years later: the average
time overrun for the rail projects in the Netherlands is 18,5% (Cantarelli et al., 2012). Further research
by Majid & McCaffer (1998) states that >50% of a time overrun of can be determined non-excusable.
Glaister et al. (2010) state that cities in the US belong to the same political context category as many
European cities. Cities in this category have a fragmented authority, but a normally successful, though
challenging project planning process. Therefore, the research conducted by Cantarelli et al. (2012) about
Dutch transport projects will be seen as representative for cities in the US in this study.
2.2 The explanatory factors
2.2.1 Project modifications
Verweij et al. (2013) explain that changes in contracts can cause cost overruns in infrastructure projects.
The modification of the contract might also result in a time overrun of the project. In this study, the role
of project modifications (among other factors) in the on-time completion of a light rail project in the US
is researched. A project modification is defined as an addition to the original contract, a change to the
implementation of the original plan, in response to unexpected internal and/or external circumstances.
As seen in Australia, for example, the South East Rail project proposed in 2012 to connect Sydney’s

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central business district with surrounding suburbs dealt with several changes to its original plan which
led to it having an unclear completion date. “But once the deal for the project was closed in February
2015, … it received a set of completely different and more stringent requirements,” (Railway Technology,
2018) due to poor infrastructure planning practices.
Another case is the light rail project in Toronto (Ontario Auditor, 2018) where the municipality and the
province have made changes in the plans after the contract was signed, seemingly to result in delays and
cost overruns. Page (2013) explains that in his research of the light rail project in Seattle the change of
executives in the project caused delay of the implementation. A similar case is seen with the Purple Line
in Maryland (Bethesda Magazine, 2013) where there was a change of CEO during the project. In this
study, however, we consider physical changes to be more contributing to delay than non-physical
changes (e.g. the change of authority within the project).
2.2.2 Funding
Funding for light rail projects can come from several levels in the US, including the federal government,
state, or local sources. Newman et al. (2018) argue there are four different degrees of funding and
delivering public transport infrastructure through Full public sector capital; Some private and
substantial public capital; Substantial private and some public capital and totally private capital. Most
rail infrastructure in the second half of the 20th century and still today, are delivered through the first
model (Newman et al., 2018). Edwards (2013) considers three parties that can fund infrastructure
projects and he divides the types of the public sector: the federal government, state and local
governments and the private sector (Edwards, 2013). Historically, he argues that experience has shown
us that when the federal government gets involved in infrastructure projects, cost overruns, inefficient
management, and political conflicts occur (Edwards, 2013).
Verweij (2015) states that the involvement of the private sector can have positive benefits in terms of
costs and time reduction in infrastructure projects. Papajohn, Qui & Bayraktar (2010) too, described that
public-private partnerships (PPP) speed up the planning process in comparison to public projects.
Funding in the context of this QCA study refers to the sources of revenue that can be used to pay for a
project or service (NCCRP, 2015). The public sector and the private sector have different interests in
funding because the former is focused on enabling public benefits and minimizing negative externalities,
while the latter is focused more strictly on private (financial) returns (NCCRP, 2015).
Lowe (2012) argues in contribution to this that local funding in railway projects has proven to have a
positive influence on the speed of a project’s development. Lowe (2012), as well as Edwards (2013),
focused their research on the US. Edwards (2013) concludes in his paper by arguing that decentralizing
infrastructure projects to the states and the private sector is the best way forward.
2.3 The context factor: public resistance
One contextual condition this study will look into is the influence of public resistance on realizing an on-
time completion. In Minneapolis, local news agencies reported about delays in the extension
implementation of an existing light rail line, because of public resistance (MPR News, 2014). In Phoenix,
a planned light-rail extension might be delayed or even canceled because of public resistance (CityLab,

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2019). Lastly, in Washington DC the construction of a new light rail line was delayed because of activist
lawsuits (Slowey, 2019a). These examples show resistance and delays prior to the actual implementation
of light rail projects. The question that arises is whether public resistance during the implementation
phase also affects the realization of on-time completion. For example, public resistance also occurs
during the implementation phase as has been shown in Washington DC (Shaver, 2019; Slowey, 2019b).
According to Naderpajouh et al. (2014), it seems that planning processes are not prepared enough to deal
with oppositional voices, which might influence the time that is used to complete an infrastructure
project. Rucht (2002) also shows examples of how public resistance caused delays in the planning and
implementation phases of big techno-industrial projects. The research shows that in the implementation
phase, public resistance might cause delays or cancellation of techno-industrial projects. On the other
hand, Rucht (2002), addresses that looking at a longer period of time, public resistance during
implementation often only seems to have little effect.
In order to make a usable definition of public resistance for this QCA study, the focus will be on citizens
who have a stake in the project. Opp, (2009) defines protest as a “joint (i.e. collective)action of individuals
aimedat achieving their goal or goals by influencing decisions of a target” (Opp, 2009, p. 38). In this study,
the term public resistance will be used to describe all kinds of protests against light rail project
implementations. The difficulty, however, is that public resistance is often measured in a quantitative
way, with self-established datasets (Coppens et al., 2018; Valentin et al.,2012).
McAdams et al, (2010) use a qualitative way to measure public resistance and analyses it with a fuzzy set
score. Because Public Resistance is a variable that is difficult to describe in a binary way this study will
use a fuzzy set score as mentioned in Gerrits & Verweij (2018). The definition of Opp (2009) is too broad
to use for this study, therefore, it will be made more specific by five factors that are taken from examples
from media and scientific sources as shown in Table 2.1.
Factor Description Source
Flyers/posters Spreading flyers and hanging posters to
draw attention against the implementation
of a light rail project.
(Rucht, 2002; CityLab, 2019)
Petitions Organizing petitions against the
implementation of a light rail project.
(McAdams, 2010; Rucht, 2002;
CityLab, 2019; Boehm, 2019)
Protest groups The presence of protest groups organizing
their protest against the implementation of
a light rail project.
(McAdams, 2010; Opp, 2009;
Rucht, 2002; CityLab, 2019)

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Demonstrations Demonstrations of citizens and protest
groups against the implementation of a light
rail project.
(ABC News, 2016; Fish & Boehm,
2018; McAdams, 2010; Rucht,
2002)
Lawsuits Lawsuits of citizens and/or protest groups
against the implementation of a light rail
project.
(McAdams, 2010; Shaver, 2019,
Slowey, 2019b)
Table 2.1: Factors to describe Public Resistance in a qualitative way.

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3 Case Studies
3.1 Data collection
This study used exceptionally secondary data to investigate the cases. The collected data consisted
mainly of policy documents, local newspapers, and some academic sources. Policy documents from
local light rail operators were used to gain insights into project modifications made during the
construction, the type of contracts and the government levels that provided funding. Besides, policy
documents from local governments were used to complement the information on the conditions that
are mentioned above. On top of that, some additional insights were gained from documents from the
Department of Transportation and the Federal Transit Administration. The latter was in some cases
involved in the contracts or funding of the light rail projects. Local newspapers were used to gain
insights into public resistance against light rail projects and public or local opinions of the project in
general. Lastly, some academic case studies were used since some cases overlapped with the cases
used in this study.
3.2 Case selection and distribution
Currently, 27 cities have modern light rail systems in the US (Greater Greater Washington, 2015).
These light rails all meet the definition of light rail systems used in this study. In this study, only
completed light rail projects can be considered, because otherwise the degree of delay cannot be
determined. In order to carry out representative research for the US, cases have been selected
throughout the country. This can be seen in Figure 3.1, the light rail systems are spread all over the
country.
During the case selection, a few limiting factors emerged. The available information on the different
light rail projects was not equal, and therefore this influenced what cases were selected. In general,
most light rails that were constructed in the previous century were not described or analyzed
extensively, and therefore most of the lines were implemented in the past twenty years. However,
this contributes to the relevance of this study because the way of developing light rails has
presumably been changed over the years. In several cities, in Minneapolis for example, two light rail
lines were selected. This can be a limitation because the factors of two lines in the same city may have
overlap and therefore it influences the analysis. Because the lines are constructed in different time
periods and the factors are not similar, the decision has been made to include some of these cases to
the study.

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Figure 3.1: Map of case distribution. Data: Natural Earth, 2019.
3.3 Case descriptions
Table 3.1 below shows all the cases in rows, with a short qualitative description of all the conditions
and the outcome in the columns. The detailed version of the raw data matrix can be found in Appendix
A.
Case Summarized data
Project
Modification (M)
Funding (F) Public Resistance (R) Outcome (O)
Gold line, Denver
(GL_Den)
No modifications PPP, locally funded No resistance Delay of 2
years and 5
months
The Tide, Norfolk
(TT_Nor)
Change of project
leader
Federal funding No resistance Delay of 1 year
and 7 months

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Case Summarized data
Project
Modification (M)
Funding (F) Public Resistance (R) Outcome (O)
Purple Line, Houston
(PL_Hou)
No modifications Local and federal
funding
Concerns from students Delay of 1 year
and 8 months
Green Line, Minneapolis
(GL_Min)
funding
Lawsuit On-time
Hoboken Line, Hudson-
Bergen (HL_HudB)
Alignment with the
railway system
Local and federal
funding
Opposition among
citizens
Delay of 1
month
Orange Line, Dallas (OL-
Dal)
funding
No resistance Delay of 6
months
Lynx Blue Line, Charlotte
(BL_Cha)
funding
Criticism from political
interest groups
Delay of 1 year,
6 months
MTS Green Line, San
Diego (GL_SanD)
funding
No resistance On-time
Westside Blue Line,
Portland (BL-Por)
funding
No resistance Delay of 1 year
Valley Metro Rail,
Phoenix (VMR_Pho)
funding
Max Yellow Line,
Portland (MYL_Por)
funding
Resistance by county
commissioners
On-time
Blue Line, Minneapolis
(BL_Min)
Change of Station Local and federal
funding
Strike by labor union Delay of 2
months
Red Line, Seattle
(RL_Sea)
Change of route Local and federal
funding
Initiative against the
construction
Delay of 3
years
Green Line, Los Angeles
(GL_LosA)
Change of route and
change of station
Local and federal
funding
No resistance Delay of 2
years
Red line, Houston
(RL_Hou)
No records Local funding Lawsuit On-time
Green line, Dallas
(GL_Dal)
No records Local and federal
funding
Table 3.1: The summarized data matrix.

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4 Calibration
4.1 Outcome: On-time Completion
As stated in the theoretical framework, the research on Dutch transport projects is considered to be
the most representative for cities in the US. Hence, in this research, a cross-over point of 18,5% will
be used to mark the anchor point between a high and a low amount of time overrun. The anchor
points lie between the scale of 0.0 (low time overrun) to 1.0 (high time overrun) as can be seen in
Figure 4.1.
Figure 4.1: Explanation of the cross-over and anchor point of the outcome.
The three main thresholds in determining time overrun are set as 1.0 (full membership); 0.0 (no
membership); and 0.5 (crossover point). In this research, we define an additional threshold because
of another finding by Majid and McCaffer (1998) that has been mentioned before. According to this
calibration, time overrun in projects between 18.5% < x < 50% are categorized as ‘excusable time
overrun’ and will be given the value of 0.3. This additional threshold allows assigning degrees of
involvement instead of applying a dichotomous assessment (Gerrits & Verweij, 2018). Calibration
values are given in Table 4.1.
Factor Description Value
Time overrun Cases with a delay of over 50% 0,0
Excusable time overrun Cases with a delay between 18,5% and 50% 0,3
On-time completion Cases with a delay below 18,5% 1
Table 4.1: The calibration values for each factor of the outcome.

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4.2 Project Modification
In order to calibrate the condition project modification, Table 4.2 is constructed based on the
literature.
Leading
authority
Change of leader within the project (Page, 2013; Bethesda Magazine, 2013)
Route Change of the route of the project (Verweij et al., 2013; Railway Technologies, 2018)
Stations Change of stations within the project (Verweij, 2015)
Table 4.2: Explanation of the factors for the condition of project modification.
In this project, a change of authority, a non-physical change, is assigned lower than the anchor point
of 0.5 since there is a minority in theory that supports a change of authority within the project leading
to delay of the project (Page, 2013; Bethesda Magazine, 2013). Physical delay, as described by the
theory (Verweij, 2015; Railway Technologies, 2018), seems to have caused provable delay of
infrastructure projects. Therefore, in this study, those cases receive a score of 0.33 and 0 for
respectively a change of stations within the projects and a change of route within the projects. The
latter being a bigger change of the project and therefore a bigger factor of change. In order to conduct
the calibration, values are given in Table 4.3 to the different factors of project modification. The
anchor points can be seen in Figure 4.2.
No modification
Leading authority
No modification
Change of leader within the project
1
0.67
Stations Change of stations within the project 0.33
Route Change of the route within the project 0
Table 4.3: The calibration values for each factor of the condition.

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Figure 4.2: Explanation of the crossover and anchor point of project modification.
4.3 Funding
Based on the arguments provided in the theoretical framework, this study focuses on decentralization for
the calibration of the factor funding. Initially, a distinction was made based on whether projects were
funded publicly or privately. However, due to the absence of private funding in the cases that were
selected for this study, this calibration had to be adapted. Taking the discussed literature into
consideration, it is assumed that when funding is achieved by a more local government level, this
contributes to the on-time completion of the project. This results in the calibration as shown in Figure 4.3.
The crossover point is based on the percentual amount of funding that the government level has
contributed. When the federal government has contributed 50% or more funding to the project, the case
is calibrated as 0.33. When the state or local government has contributed 50% or more, the case is
calibrated as 0.67. This has resulted in the calibration values of Table 4.4.
Full Federal
Federal + State / Local
Cases that are fully federal funded.
Cases that have more than 50% federal
funding and State / Local funding.
0
0.33
State / Local + Federal Cases that have 50% or more State / Local
funding and Federal funding.
0.67
Full State / Local Cases that are fully State / Local funded. 1
Figure 4.3: The calibration values for each factor of the condition.

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4.4 Public Resistance
In order to calibrate the data that has been collected, the factors of Table 2.1 (Chapter 2) will be used.
Since these factors are the appearances of public resistance during the implementation that have
been found in the literature, these factors will be used as anchor points in the calibration were 1 will
be no public resistance towards the implementation of a light rail project and 0 will be a sum of flyers,
petitions, protest groups, demonstrations and lawsuits.
Based on the findings in Table 2.1, fuzzy set scores were given to the different forms of public
resistance. The crossover point is put between organizing petitions and forming protest groups. This
is done because McAdams (2010) defines petitions and less public resistance below the crossover
point of 0.5. Besides that, Rucht (2002) indicates that moderate forms of protest (like petitions and
flyers) prove to be ineffective. In Table 4.5 the values are given to calibrate the data. Since flyers and
petitions is a form of public resistance, the fuzzy set value of 0.67 is given. McAdams (2010)
differentiates between the presence of protest groups and actual action being taken, therefore there
is a differentiation between protest groups with 0.33 and demonstrations and lawsuits with 1.
Demonstrations and lawsuits are assigned a score of 1 because according to both McAdams (2010)
and Rucht (2002) they seem to have the most influence on the implementation of infrastructure. The
anchor points are visualized in Figure 4.4.
No public
resistance
No public resistance towards the implementation of a light rail project. 1.00
Flyers/Posters Spreading flyers and hanging posters to draw attention against the
0.67
Petitions Organizing petitions against the implementation of a light rail project. 0.67
Protest Groups The presence of protest groups organizing their protest against the
0.33
Demonstrations Demonstrations of citizens and protest groups against the implementation of
a light rail project.
0.00
Lawsuits Lawsuits of citizens and/or protest groups against the implementation of a
light rail project.
0.00

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Figure 4.4: Explanation of the crossover and anchor point of public resistance.
4.5 Calibrated data
After calibrating the qualitative data, Table 4.6 was constructed to quantify the data in order to make
an analysis with the fsQCA software.
Case Calibrated Data
Project
Modification
(M)
Funding
(F)
Public
Resistance
(R)
Outcome
(O)
Gold line, Denver (GL_Den) 1.00 1.00 1.00 0.30
The Tide, Norfolk (TT_Nor) 0.67 0.00 1.00 0.00
Purple Line, Houston (PL_Hou) 1.00 0.33 0.67 0.30
Green Line, Minneapolis (GL_Min) 1.00 0.67 0.00 1.00
Hoboken Line, Hudson-Bergen (HL_HudB) 0.00 0.67 0.33 1.00
Orange Line, Dallas (OL_Dal) 1.00 0.33 1.00 0.30
Lynx Blue Line, Charlotte (BL_Cha) 1.00 0.33 0.67 0.00
MTS Green Line, San Diego (GL_SanD) 1.00 0.67 1.00 1.00
Westside Blue Line, Portland (BL_Por) 1.00 0.33 1.00 0.30
Valley Metro Rail, Phoenix (VMR_Pho) 1.00 0.67 1.00 1.00
Max Yellow Line, Portland (MYL_Por) 1.00 0.33 0.67 1.00
Blue Line, Minneapolis (BL_Min) 0.67 0.33 0.33 1.00
Red Line, Seattle (RL_Sea) 0.00 0.33 0.67 0.00

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Case Calibrated Data
Project
Modification
(M)
Funding
(F)
Public
Resistance
(R)
Outcome
(O)
Green Line, Los Angeles (GL_LosA) 0.00 0.33 1.00 0.30
Red line, Houston (RL_Hou) 1.00 1.00 0.00 1.00
Green line, Dallas (GL_Dal) 1.00 0.33 1.00 1.00
Table 4.6: The calibrated data matrix.

21
5 Analysis
5.1 Software
For the data analysis, the fsQCA software is used. This software is suitable for analyzing conditions
with a fuzzy set scale. A table with cases and calibrated values is used as an input in order to obtain
a truth table and a complex solution.
5.2 Comparison
The first analysis of the data in the fsQCA software showed limited diversity of 3 configurations of
conditions. Furthermore, the combinations of conditions with a consistency below 0.75 represented
11 cases, which according to Gerrits & Verweij (2018) is rather low to be compared in the software
to get a trustworthy outcome. In order to conduct an analysis with more combinations of conditions
to be compared, the data was reviewed and recalibrated. The funding condition got a new scale and
accordingly, a new calibration table has been set up. Table 4.6 presents this newly calibrated data.
After the recalibration, there was still limited diversity, but it has been reduced from 3 configurations
of conditions to 2 as can be seen in the last two rows of Table 5.1. The combinations of conditions
with a consistency below 0.75 represent 9 cases after the recalibration. Two strategies as mentioned
in Gerrits & Verweij (2018) have been applied to handle the limited diversity. First, a recalibration
was done, and second, an exclusion was executed for the combinations of conditions that did not
represent any case. Therefore, the last two rows of Table 5.1 were excluded. The outcome values
were given manually to the combinations of conditions. The software set the cut-off point on 0.75188
since this is seen as a natural gap. The cut-off point is checked manually, but the choice has been made
to keep the cut-off point at that place since the gap in consistency between the first four rows and the
last two rows is relatively big. The third and fifth row have contradicting outcomes. The third row
had only 1 contradiction and still a high consistency. Therefore, the choice is made to include the
third row in the analysis. The rows with low consistency, namely the last two rows, were removed
from Table 5.1 since these rows consisted of a majority of cases that don’t have a membership in the
outcome.

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Conditions Outcome Consistency Cases
M F R N O Raw PRI SYM
1 1 0 2 1 0.879599 0.866171 0.866171 GL_Min, RL_Hou
1 0 0 1 1 0.819095 0.786982 0.786982 BL_Min
1 1 1 3 1 (C)* 0.75914 0.675362 0.739683 GL_Den, GL_SanD, VMR_Pho
0 1 0 1 1 0.75188 0.75188 0.75188 HL_HudB
1 0 1 7 0 (C)* 0.568662 0.487448 0.487448 TT_Nor, PL_Hou, OL_Dal,
BL_Cha, BL_Por, MYL_Por
GL_Dal
0 0 1 2 0 0.412017 0.325123 0.325123 RL_Sea, GL_LosA
0 0 0 0
0 1 1 0
Table 5.1: The raw truth table.
*The (C) in the column outcome indicates a contradictory row.
Conditions Outcome Consistency Cases
M F R N O Raw PRI SYM
1 1 0 2 1 0.879599 0.866171 0.866171 GL_Min, RL_Hou
1 0 0 1 1 0.819095 0.786982 0.786982 BL_Min
1 1 1 3 1 (C)* 0.75914 0.675362 0.739683 GL_Den, GL_SanD, VMR_Pho
0 1 0 1 1 0.75188 0.75188 0.75188 HL_HudB
Table 5.2: The final truth table.
*The (C) in the column outcome indicates a contradictory row.
What is striking in Table 5.2, is the contradiction in the third row. GL_Den is the only case in that row
that doesn’t have a membership in the outcome. This is especially interesting since this case rejects
this research’s hypothesis that a combination of a membership in all three conditions contributes to
membership in the outcome. Going back to the case, we see that an outcome of 1 (on-time
completion) was not realized for the Gold Line in Denver since that case was delayed for 2 years and
5 months (RTD, 2015; RTD, 2019). Even though the project experienced no project modifications, no
public resistance due to a participatory approach, and a locally funded PPP, the project got delayed.
This delay was caused by crossing gate issues (The Denver Post, 2016). The Regional Transportation
District in Denver (RTD) made an automated crossing gate system, and they failed to get approval for
that system from the Federal Railroad Administration. The RTD had to wait for that approval for over
two years. That indicates that this delay has a communicational nature, which is beyond the scope of
this research.

23
5.3 Interpretation
Complex Solution Path 1 Path 2 Path 3
M*~R F*~R M*F
Cases GL_Min, RL_Hou,
BL_Min
GL_Min, RL_Hou,
HL_HudB
GL_Min, RL_Hou,
GL_Den, GL_SanD,
VMR_Pho
Raw coverage 0.347368 0.347368 0.547386
Unique coverage 0.0705264 0.0705264 0.270526
Consistency 0.901639 0.827068 0.822785
Cutoff point: 0.75188
Solution coverage: 0.688421
Solution consistency: 0.818523
Table 5.3: Complex solution from the fsQCA.
As can be seen in Table 5.3, the complex solution consists of three paths. As described in Verweij et
al. (2013), raw coverage is the relative amount of cases covered by the specific path. As can be seen,
the third path covers more cases than the first and the second one. Unique coverage is the relative
amount of cases covered by the specific path only. Consistency is the degree to which the membership
scores of the cases in the configuration are sufficient for the outcome.
Table 5.3 shows that there are no necessary conditions, nor any sufficient conditions. The conditions
within the configurations are INUS conditions: ‘Insufficient but Non-redundant parts of a configuration
which is itself Unnecessary but Sufficient for the occurrence of the outcome’ (Verweij et al., 2013). For
example, the first path shows that ‘M’ (Project Modification) is an INUS condition. An absence of
project modifications is important, but not necessary because on-time completion can also be
realized without membership of ‘M’ (Project Modification), or in other words, without an absence of
project modifications. The HL_HudB case is an example of this.

24
5.4 Within-country lessons
Three lessons have been found after the data analysis. Three configurations that result in a successful
outcome are:
M*~R + F*~R + M*F → O
This outcome shows that the membership of ‘M’ in combination with a negation of ‘R’ causes a
membership in the outcome. Translated to the research objectives, this means that the absence of
project modification in combination with the presence of public resistance leads to on-time
completion. In addition, the outcome shows that the membership of ‘F’ in combination with a
negation of ‘R’ causes a membership in the outcome. Translated to research objectives, this means
that state/local funding in combination with the presence of public resistance leads to on-time
completion. Besides that, the outcome shows that the membership of ‘M’ in combination with a
membership of ‘F’ causes a membership in the outcome. Translated into the research objectives, this
means that the absence of project modification in combination with a state/local funding leads to on-
time completion.
It is surprising that the presence of public resistance in two combinations seems to cause an on-time
completion, while it is expected to cause the opposite according to the literature review. Therefore,
the cases have been reviewedagain to see what happened with the public resistance and how it could
have contributed to on-time completion. The GL_Min (Green Line Minneapolis) showed that because
of the public resistance (lawsuit), the different actors involved started to collaborate and consensus
was achieved without implications to the time management. In the HL_HudB (Hoboken Line Hudson
Bergen) case, the lawsuit was stopped without implications on the time management. The BL_Min
(blue Line Minneapolis) got a minor delay of two months because of strikes. The RL_Hou (Red Line
Houston) showed that after the public resistance (lawsuit) no further resistance took place. There
were no implications for time management. The examples show that public resistance seems to start
a better collaborative and communicative process between the actors which, according to De Roo,
(2003) can help in reducing the possibility of a time overrun. So instead of the presence of public
resistance, the presence of a collaborative process between the actors involved seems important for
on-time completion of a light rail project in the US. Concluding, the following lessons can be drawn
from this study:
1. A light rail project that is not modified but utilizes a collaborative process between the actors
during the implementation leads to on-time completion.
2. A light rail project that is funded locally (state/local level), in combination with a
collaborative process between the actors during the implementation, leads to on-time
completion.
3. A light rail project that is not modified during the implementation, in combination with local
funding (stale/local level) of the project leads to on-time completion.

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6 Cross-country Lesson
This study has chosen to use Canada as a recipient country. This has been done because different
light rail projects in Canada have faced major difficulties implementing light rail systems (Citylad,
2019; Hilton & Stoney, 2007) since Canada has ambitious plans to construct many light rail systems
(Constructconnect, 2018). The lessons that have been drawn from this study can provide guidelines
in order to ensure that the implementation of light rail projects in Canada will proceed in a better
and smoother way resulting ideally in more projects being completed on-time. To transfer the lessons
of this QCA study into policymaking in the donor country, Canada, it will be necessary to take the
differences between Canada and the US into account with the use of literature about policy transfer
and policy translation. First, the differences and similarities between light rail systems in the US and
Canada will be compared, and afterward, lessons will be drawn using literature and the results from
this study.
6.1 Differences and similarities between the US and Canada
There are currently only four light rail systems in Canada:
1. C-Train - Calgary, Alberta
2. Edmonton LRT - Edmonton, Alberta
3. O-Train - Ottawa, Ontario
4. Ion rapid transit - Waterloo Region, Ontario
However, there are several light rail projects in development throughout Canada, most still in the
planning process with a wide range of expected completion dates. The existing and future
developments in Canada’s light rail provide an opportunity for lessons to be drawn from the cases
seen in the US in order to strive towards effective management strategies for light rail projects.
6.1.1 On-time Completion
Light Rail Transit (LRT) development in Canada is now facing the same problem as the US regarding
on-time completion. Most of the LRT constructions were delayed due to technical problems
(Lindeman, 2019). The current issue is the delay construction of LRT in Ottawa that has already been
delayed for more than 500 days by now or 66% time overrun; Edmonton LRT is having 36% time
overrun (Dyer, 2019); and Waterloo LRT had 25% time overrun (Bueckert, 2019). If we reflect on
the literature used in this study, all LRT constructions are delayed above 18.5%, which is the
crossover point in this study.
6.1.2 Funding
The funding of light rail infrastructure projects in Canada is very similar to the US. Like in the US,
most light rail systems have received federal funding. These federal funds are often completed with

26
the help of state and/or provincial funding (Ruffilli, 2010; Stage 2 LRT, 2018). This is also what we
have seen in the US light rail projects.
In Edmonton and Calgary, the first light rail lines were developed in the last century which is
comparable with the case studies in this QCA. Project modifications also occur in Canada during the
planning and implementation phase of the light rail. Interesting is the expansion of the Ottawa O-
train, however, it should be mentioned that this enlargement was not realized in the end. In this
specific case, the contract and plan details were not available for the public because this project was
partly completed by a private party (Hilton & Stoney, 2007). Because contracts between the public
sector and private sector are more common in Canadian context, the changes that are made within
the project in PPP contracts often remain closed to the public, while the project modifications in the
US are mostly public or federal and therefore display in public.
6.1.4 Context: public resistance
While Canada has implemented four light rail systems in the country, there has not been public
resistance recorded in those projects during the implementation. Canada is actively stimulating PPPs
to prevent public resistance according to Canada Commerce (2013). The dialogue with the public is
one of the key aspects to prevent public resistance during the implementation process. This is the
main national strategy of Canada. Infrastructure is to be seen as a “public good like education, health
care, recreation, and public safety” (Canada Commerce 2013, p. 26). Within the projects, it is
important to communicate well with the private stakeholders that are involved. The Ontario
Chamber of Commerce (2017) for example has tried to communicate with the public as a
fundamental priority of practice because there needs to be good communicative action towards
smaller communities to prevent public resistance in those areas. According to a report by the IRRP
Insights (2017) the government of Canada has tried to reduce public resistance against infrastructure
projects by governing infrastructure at a local level.
6.2 The adaptation of policies with lessons from other contexts
Policy transfer or lesson drawing refers to “a process in which knowledge about policies,
administrative arrangements, institutions, etc. in one time and/or place is used in the development
of policies, administrative arrangements and institutions in other time and/or place” (Dolowitz &
Marsh, 1996, p. 344). In policy transfer, both positive and negative lessons can be drawn from the
donor country.
One essential aspect that needs to be considered in policy transfer, is the difference in context of both
countries. According to Peck (2011) and Mukhtarov (2012), context plays a key role in policy
transfer. Both scholars refer to not only the political context, but also to the geographical context,
economic context, path dependency, and the global architecture. The extent of lesson drawing from
the US case study depends on the context of the US and Canada. An important difference between the
US and Canada is the number of inhabitants, resulting in much fewer light rail projects in Canada.
Geographically seen, cities in the US and in Canada are comparable since in both counties cities are

27
organized by grid structures. From a political perspective, both countries use a democratic system.
While in the US the states operate on a regional level, Canada is divided into several provinces.
Furthermore, different meanings of concepts in different countries should be considered. For
example, the definition of light rail in different countries may vary. Besides, the foundations of
concepts such as PPP can be different in varying countries. Mukhtarov (2012) refers to this
phenomenon as ‘meaning destabilization’.
As seen in the US cases, project modifications lead to a delayed completion of light rail projects. In
order to draw a lesson from this in the planned light rail projects in Canada, a comprehensive plan
anticipating unexpected changes should be implemented in order to achieve on-time completion.
While it is difficult to anticipate unforeseen changes, it is important to notify that early changes need
to be detected as soon as possible. Looking at project modifications as a factor in the US case studies,
a collaborative approach, which will be mentioned later, can help in developing a comprehensive and
supported plan. This will increase the ability to anticipate budget overruns, environmental
constraints, and other factors that will contribute to an undesired outcome.
6.2.2 Funding
The funding between the countries is very similar. Due to these funding similarities, this study
concludes that in order to maximize the possibility of an on-time completion in Canada’s planned
light rail projects, a combination of federal and local funding contributes to the desired outcome.
Barriers to adopting this lesson can be seen through lack of funds, as seen in the US, and lack of
consensus of disbursement of funds as seen in both the US and Canada. However, this study
recommends a federally subsidized local funding system. By dispersing the financial investments
across governing authorities and other stakeholders, there is less risk of a delay in project
completion.
6.2.3 Public resistance
This study concluded that the presence of public resistance contributes to on-time completion of light
rail projects in the US. During the analysis, we came to the conclusion that the presence of public
resistance in itself is not the reason why the projects were finished on time, but that the collaborative
process that was started because of the presence of public resistance seemed to contribute to the
project finishing on time. Within the context of light rail projects in Canada, an increased level of
communication between stakeholders is necessary for achieving an on-time completion. Since this
study has not looked into the collaborative process as a condition, it is only a substantiated
assumption that collaborative planning has a relation with public resistance and contributes to on-
time completion.

28
6.3 Measures based on lesson drawing
This study produced three lessons for light rail projects in the United States.
The first lesson is that ‘a light rail project that is not modified, but utilizes a collaborative process
between the actors during the implementation leads to an on-time completion’. Regarding differences
and similarities as being described in section 6.1, the part of the lesson about the ‘project
modifications’ can be transferred to Canada. The part of the lesson about the ‘utilization of a
collaborative process’ is already integrated into Canadian policies. Dolowitz & Marsh (1996) indicate
that a more complex policy or program is harder to be transferred. The part of the lesson about
‘project modifications’ is a relatively simple policy, while the part about ‘utilizing a collaborative
process’ is a more complex policy, but this is already integrated into policies in Canada. Therefore,
the first lesson is transferable to a Canadian context.
The second lesson is that ‘a light rail project that is funded locally (state/local level), in combination
with a collaborative process between the actors during the implementation leads to an on-time
completion’. Regarding differences and similarities as described in section 6.1, the part of the lesson
about ‘local funding’ can be transferred to Canada. Funding policy is a complex policy that affects
multiple actors, but light rail projects in Canada do already make use of a similar funding system as
the US. In the theoretical framework, the positive influence of private funding has been
acknowledged. This should be taken into account for Canada as well. The part of the lesson about the
‘utilization of a collaborative process’ is already integrated into Canadian policies, as described above.
Therefore, the second lesson could be transferred but this should be done with care, and as described
in Mukhtarov (2014) and Peck (2011), the context needs to be taken into account.
The third lesson is that ‘a light rail project that is not modified during the implementation, in
combination with local funding (stale/local level) leads to on-time completion’. Regarding the
differences and similarities as being described in section 6.1, the part of the lesson about the project
modification can be transferred to Canada. As described above, this policy is relatively simple.
Funding policy is a complex policy that affects multiple actors, but light rail projects in Canada do
already make use of a similar funding system as the US. In the theoretical framework, the positive
influence of private funding has been acknowledged. This should be taken into account for Canada as
well. Therefore, the third lesson could be transferred but this should also be done with care, and as
described in Mukhtarov (2014) and Peck (2011), the context needs to be taken into account.

29
7 Process Reflection
Determining the subject of this study was because of the language limitations and the size of the
group partly driven by the data availability, while actually research is supposed to start with a
research problem. This led us to come up with a research topic that was partially unknown to us.
To really understand the variables of this study more time is needed to get enough understanding on
topics such as the question of how a planning and implementation process proceeds, the different
contract forms and the associated financing and funding that exist in construction of infrastructure,
the question of how infrastructure projects take into account (legal) resistance. This resulted in the
problem that sometimes the data did not fit within the theoretical framework, which ideally should
have led to a reframing of the theoretical framework. From the case studies, for example, it seems
that often there were technical reasons for the delay, which were other reasons than described in our
theoretical framework.
Regarding the research design, the conditions that were determined were not able to be researched
as deeply in the case studies as proper scientific research would expect because of the time frame of
this assignment. In some cases, for some of the chosen conditions, there was no evidence of the
presence of that condition. This made it hard to assume that there was no presence of those
conditions in those cases at all. This should be taken into account while reading the results since more
time to conduct the case studies could lead to another outcome.
During the analysis a lot of considerations needed to be made regarding anchor points, cut-off points,
recalibrations, limited diversity, and contradictions. This turned out to be complex. It was challenging
to make this process transparent, especially when we were not sure if we made the right choice.
Therefore, together with the points mentioned above, this study is of an exploratory nature.
Nevertheless, did this study deliver some surprising outcomes, which could be used as an incentive
and starting point of further academic research
Besides, the choice for Canada as a recipient country is an interesting consideration. On the one hand,
the Canadian context has a lot of similarities compared to the US context. This makes it easier to
transfer policies. On the other hand, these similarities make it hard to stay critical about the barriers
of policy transfer. A comparison between the US and another country would make the research more
challenging.
The internal group evaluation can be found in Appendix B.

30
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38
9 Appendix
9.1 Appendix A - The raw data matrix
Cases Project modifications Funding Public resistance Outcome
Gold line,
Denver
No records can be found of any
form of project modifications
during the construction phase.
The Gold Line is funded by a
public-private partnership,
called Eagle P3 (RTD,
2019). This consortium
consists of local parties.
No records can be found of
any form of public resistance
during the construction
phase.
More than 2 years of a
delay:Aprill 2019 instead of late
2016.
The construction of the Gold line
started in 2011.
The Tide,
Norfolk
No records can be found of any
form of project modifications
phase. There was a change in
leaders during the construction
process.
This project was federally
funded (public).
phase.
The line opened in August 2011,
while it has been planned to open
in January 2010 (Hampton Roads
Transit, 2015).
Red Line,
Seattle
In 2000 the project was
modified. Due to soil conditions,
and thereby rising costs in the
project and new executives
were appointed. In 2001
changes were made about the
routes in the project. (Seattle
Times, 2001)
Federal funding was approved
in 2003. Sound Transit, the
public transit authority of
King County, is the main
owner of the project. (Seattle
Times, 2001)
In 2002 conservative activist
Tim Eyman started the 776
initiative (I-776) along with
several other civil
organisations to undermine
the project’s funding by
resisting against the local
motor fees in Seattle.
(Permanent Defense, 2002)
Construction started in 1996 and
the line was stated to be opened
in 2006, but due to the
circumstances, it was postponed
until 2009.
METRORail
RED,
Houston
No records No federal funding. Entirely
local funding.
(public) resistance, lawsuit,
temporary delay and extra
costs
Opened without delay.
13 march 2001
1 january 2004

39
Green Line,
Dallas
No records Locally and federal funding.
Extra federal with Recovery
and Reinvestment Act.
No records Construction 2006 - 6 december
2010. Opened ahead of schedule.
Green Line,
Los Angeles
Changes in the plans of the
route were made between the
stations of the system. (Los
Angeles County Metropolitan
Transportation Authority,
2016)
No federal funding. The Green
Line of Los Angeles is
maintained by the Los Angeles
County Metropolitan
Transportation Authority.
(Los Angeles County
Metropolitan Transportation
Authority, 2016).
No records. Construction started in 1987.
Opened in 1995, delayed. New
extensions are still under
construction.
Lynx Blue
Line,
Charlotte
The record of decisions for this
case was completed by the
Federal Transit Administration
in 2011. However, in 2015, in
order to stay within the initial
deadline of the project, the city
council of Charlotte increased
the contracts by $19.5 million
(Harrison, 2015). Furthermore,
additional funding was
provided as a loan through the
Transportation Infrastructure
Finance and Innovation Act to a
total of $180 million for
construction of the Blue Line
(Trains Magazine, 2015).
The Charlotte Area Transit
System, the University of
North Carolina, and the state
and local government agreed
to fully fund the extension.
Half of the costs covered by
the Federal Transit
Administration and the
remaining covered by a sales
tax for transit (Federal Transit
Administration, 2011). As for
a public-private partnership,
it is not possible in this case as
it is in Denver, for example,
because “Charlotte doesn’t
have enough money to pay
back a private developer”
(WBTV, 2012).
The presence of public
resistance in this case
consisted of criticisms from
traditionally conservative
political interest group
Americans for Prosperity
Foundation. They were calling
for a more inclusive
discussion in the allocation of
federal funding for this
project (Charlotte Business
Journal, 2006).
Blue line construction finished in
2007. The latest extension was
planned to be finished in August
2017, however was not
completed until March 2018.
(Harrison, 2018)
MTS Green
Line, San
Diego
The original contract from 2005
was modified in 2012 in order
to include an extension of the
green line, along with several
other renovations of the San
Diego Transit System
The extension projects were
funded by “the $720 million
Trolley Renewal project
(Metropolitan Transit System,
2013).
There were no circumstances
of public resistance relevant
in this case. However, there
are calls for more funding in
the public transit sector
(Baxamusa 2017).
The project was completed within
the original proposed time frame
in 2005. It was also successfully
extended in 2012 (Metropolitan
Transit System, 2013).

40
(Metropolitan Transit System,
2013).
Max Yellow
Line,
Portland
No records of project
modification during the
construction phase.
Public funded.
74% of the project cost was
federally funded by Federal
Transit Administration (FTA);
11% TriMet; 8.3% city of
Portland; 6.7% Regional
Transportation Funds
(Trimet, 2012).
Resistance by the county
commissioners which
opposed the expansion of the
urban renewal district, but
the Portland City Council
approved it anyway (Cascade
Policy Institute, 2019)
Construction started in February
2001 and finished on 1 May 2004,
four months ahead from expected
completion time in September
2004 and rerouted in August
2009 (Portland Tribute, 2009).
Blue Line,
Minneapolis
Changes of plan of American
Boulevard Station that is
postponed until 12 December
2009
Public funded
The project was funded by
Federal Transit
Administration (FTA); State of
Minnesota; Metropolitan
Airports Commission (MAC).
In March 2004, the labor
union representing Metro
Transit bus workers went on
strike.
The groundbreaking for
construction is on 17 January
2001 and finished on 26 June
2004. It was delayed from the
expected completion time on 3
April 2004.
METRORail
Purple Line,
Houston
A minor project modification
has taken place during the
implementation of the Purple
Line. An access road was
changed in order to solve a
problem with the University of
Houston (Houston Chronicle,
2012).
Public Funded
54.86% of the implementation
costs are funded by the
federal government of the US
and 45.32% is locally funded
by METRO, the Metropolitan
Transit Authority of Harris
County (METRO, 2011). Both
are completely publicly
funded and no private parties
participate in funding the
Purple Line (METRO, 2011).
Because of the
implementation of the purple
line that crosses the property
of the University of Houston,
they got concerns regarding
the accessibility of their
facilities, but the dispute was
settled quickly (TheCougar,
2012; Houston Chronicle,
2012). there have been public
hearings were residents
asked for modifications and
some of the residents were
dissatisfied with certain
aspects of the plan, but this
hearings haven taken place
before the implementation
(Houston Chronicle, 2012).
The Federal Transit
Administration signed the
contract for the implementation
of the Purple Line on the 16-07-
2008 (Federal Transit
Administration, 2008a;
WebArchive, 2008). The
construction began on 15-06-
2009 (Lee & Sener, 2017;
WebArchive, 2009) and at that
time the expected opening date
was October 2013 (Federal
Transit Administration, 2008b;
Fox, 2010). But the opening got
delayed and the line opened on
23-05-2015. (Lee & Sener, 2017;
Infrainsightblog 2015).

41
Metro Green
Line –
Minneapolis,
Minnesota
Before the project
implementation in the planning
phase three stations were
added to the project as a result
citizens protest (MPR News,
2014). Any modifications during
the implementation are
unknown.
The Green Line is funded in
the following way: 50.00% of
the implementation costs are
funded by the Federal Transit
Administration (federal
government of the US) and
50.00% is locally funded and
divided by the Counties
Transit Improvement Board
with 30%, State of Minnesota
Bonding with 10%, and the
Regional Rail Authorities
(Ramsey and Hennepin
Country Regional Rail
Authorities) with 10%. (The
Metropolitan Council, 2008).
Both are completely publicly
funded and no private parties
participate in funding the
Green Line (The Metropolitan
Council, 2008).
The Minnesota Public Radio
(MPR) started another
lawsuit before the
implementation of the line to
prevent possible effects of
sound and vibrations, but a
judge dismissed it later on
during the implementation
(MPR News, 2011). After that
the Minnesota Public Radio
and the Metropolitan Council
kept collaborating in order to
reduce sounds and vibrations
that could be caused by the
light rail (MPR News, 2014).
This is the only case of public
resistance during the
implementation that has been
found for the Green Line.
The construction began in
October 2010 (Owen & Kadziolka,
2015; Metropolitan Council, 2014;
MPR News, 2010) and at that time
the expected opening date was an
unspecified date in 2014 (Federal
Transit Administration, 2013;
Star Tribune, 2008). The opening
of the line took place on 14-06-
2014 (Metropolitan Council,
2014; Owen & Kadziolka, 2015;
MPR News, 2014). There is no
evidence of a delay in the
implementation of the Green Line
light rail project.
Westside
MAX Blue
Line -
Portland
The project did experience
major project modifications
during the construction of the
project. However, project
modifications were taken into
account before the construction
of the project. (Rail Technology,
2010) Several alternatives
alignments through the West
Hills were studied in case the
tunnelling at the original route
would be impossible in case of
rock would not be strong
enough to carry the tunnel
(Trimet, 2012).
The total cost of the project is
963,5 million US dollars. 145
million US dollars (15%) is
funded by the Regional and
Local bond measures and
113,6 million US dollar (12%)
by the State. The major part of
de funding, 704,1 million US
dollar (73%) is paid by the
Federal Transit
Administration (Trimet,
2012).
Before the construction of the
Westside Max Blue Line, in
1990, 73 percent of the voters
approved a bond measure for
the Westside extension.
During the constriction of the
Westside MAX blue line no
form of any public resistance
is registered due to work
activities (Portland
Community Newspaper,
2011).
The construction of the Max Blue
Line started in 1983 and opened
in September 1986. The
construction of the Westside
extension of the MAX Blue Line
started in July 1993 and in
September 1998 the Westside
Max Blue Line service began. This
was one year later than scheduled
(Trimet, 2012). The main cause of
this delay was caused by
tunnelling work. During the
tunnel boring the rock turned out
to be highly fragmented.
Modifications to the tunnel-

42
boring machine were required to
continue the tunnelling (Trimet,
2012).
Valley Metro
Rail -
Phoenix
During the implementation
phase the project did not
experience modifications to the
plan. There are no signs within
newspapers and policy
documents indicating
modifications during the
project.
The Valley Metro Rail project
is funded by several parties.
The total cost of the
construction of the Valley
Metro Rail was 1,4 billion US
dollar. Due to cracks in the
system’s rails, caused by
improper use of plasma
cutting torches by
contractors, the construction
cost raised by 600.000 US
dollars (EconWorks, 2014).
62% percent of these costs
were funded by the city
members. 32% of the cost
were funded by fares. The
Federal Transit Organisation
funded 3% of the project. The
last 3% percent is earned due
to advertising (Valley Metro,
2018).
The Light rail was created by
the Transit 2000 Regional
Transport Plan which
involved a 0,50 cent sales tax,
and was approved by Phoenix
voters in 2000 (Global Mass
Transit, 2016). The
construction of the first phase
of the light rail between 2005
and 2008 did not lead to
public resistance. On the
other hand plans for
expansions of the Valley
Metro Rail do lead to public
resistance. The group
Proposition 105 supported by
the Building a Better Phoenix
campaign reject the
expansion plans (U.S. News,
2019).
The construction of the Valley
Metro Rail began in March 2005
and the operation started in
December 2008. The project has
not experienced delay during the
construction (EconWorks, 2014).

43
Hudson-
Bergen Light
Rail phase 1
The project experienced a
project modification. The mayor
and the city council urged the
governor to accept an alignment
of the railway system (United
States Department of
Transportation (2019). This
was because the system would
have an impact on traffic and
parking in downtown Hoboken
United States Department of
Transportation, 1999).
The project is funded by the
Federal Transit
Administration (FTA) and the
state trust fund (FHWA,
2019). The contract itselfs
was a so called DBOM-
contract which stands for
Design-Built-
Operate-Maintain contract
The project had much support
under policy-makers but
there was opposition among
citizens. Citizens were against
the proposed route because
they were concerned the
noise would have a negative
impact on the quality of living
in the neighbourhood
(Sedelmaier, 2004). The
residents were at one point
close to complementate legal
action, but this suit seems not
have ever been filed.
In september 1996 the contract
was signed, and line opened at 15
april 2000, one month later than
expected
Dallas
Orange Line
(Irving 3)
After performing an impact
assessment, the DART carried
out several changes in the
project to reduce the
environmental effects (DART,
2019). This means different
contract modifications were
implemented.
The expansion was funded by
the public sector by the
federal state (United States
Department of
Transportation, 2019),
phase. Several meetings with
the community were planned
in the planning phase as well
as the implementation phase
(DART, 2019).
The construction began on april
2012 and the expansion opened
at june 2014. The goal was to
reach the airport in december
2013, so this means a delay of 6
months (DART, 2019).

44
9.2 Appendix B – Internal group evaluation
Reflecting on the process of working on the assignment there are some things to be noted for our group.
The start of constructing the basis of our research has been a time consuming process because there was
some disagreement of picking the subject of our project. Further on in our project we did not fully agree
on the specification of an outcome. That resulted in disagreement about the calibration. So being more
specific in the earlier steps would have prevented some uncertainties in the process later. That is
something that we could have improved on.
This kind of disagreement was not caused necessarily by the number of people in our group, nevertheless
the fact that we were with eight people was a time consuming factor. In other words: in our opinion the
assignment could’ve been done more effectively with less people. While on the other hand the number of
people was convenient due to the fact that there were more viable cases in our project. In a smaller group,
discussions would be less time consuming and it would be easier to divide tasks.
As mentioned it is harder to work together and divide tasks with eight people, nevertheless the group
members have worked more or less an equal amount. We had a fixed weekly meeting were all of the group
members were most of the time present, besides that we often planned extra meetings in order to discuss
the progress, make decisions and work together. In addition to that we tried to make use of the open office
hours of our supervisors, and if needed we went to them for extra consultation during our project.
While there have been significant disagreements the atmosphere among the group members was good
and we worked together quite smoothly. We tried to make a proper time management so that well before
the deadline the work was done and could be uploaded. The last days of finalizing the project were
exhausting, but we managed to meet our own deadline so that we had enough time to make the last
modifications.

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