Identifying Strategies for Improvement of
Public Transportation Services

Bachelor’s Thesis - Department of Space, Earth and
Environment

Authors:

Fatimah Al-Nuwab, Global Systems Engineering

Ragnar Bergkvist Eriksson, Civil Engineering

Ida Kron, Global Systems Engineering

Erica Larsson, Civil Engineering

Adam Lindberg, Global Systems Engineering

Frida Lindgren, Global Systems Engineering

Gothenburg, 2024–06–02





Bachelor’s thesis 2024

Identifying Strategies for Improvement of Public
Transportation Services

Fatimah Al-Nuwab, Ragnar Bergkvist Eriksson, Ida Kron, Erica Larsson,
Adam Lindberg, Frida Lindgren

Department of Space, Earth and Environment
Division of Physical Resource Theory

Chalmers University of Technology
Gothenburg, Sweden 2024

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Identifying Strategies for Improvement of Public Transportation Services

© Fatimah Al-Nuwab, Ragnar Bergkvist Eriksson, Ida Kron, Erica Larsson, Adam Lind-
berg, Frida Lindgren, 2024.

Supervisor: Reema Bera Sharma, Department of Space, Earth and Environment
Examiner: Frances Sprei, Department of Space, Earth and Environment

Bachelor’s Thesis 2024
Department of Space, Earth and Environment
Division of Physical Resource Theory
Chalmers University of Technology

Cover: Linje 2 Vasa Viktoriagatan (Bo Randstedt, 2009). CC-BY-SA

Typeset in LATEX
Printed by Chalmers Reproservice
Gothenburg, Sweden 2024

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Abstract
Emissions generated by the transport sector have a major impact on the environment,
public health, and climate change. Promoting a shift from passenger car ownership
to public transportation (PT) modes can lead to a significant decrease in greenhouse
gas emissions originating from the transport sector. The study aims to identify man-
agement strategies for improving the PT service by (1) investigating the perception of
consumers’ importance and satisfaction with PT service attributes (2) identifying the
variation in perception for service attributes across consumers with different sociodemo-
graphic and trip-related characteristics (3) investigating the gap between consumers’ and
service provider’s perception for the current PT service. The target population of the
study was travellers within the city of Gothenburg, Sweden.

The study was based on a survey and was divided into three major components. Firstly,
the survey responses were analysed through revised Importance Performance Analysis
(IPA), based on derived importance and stated satisfaction. The result showed that the
attributes punctuality, fare and the number of transfers are the major priority areas to
obtain a higher overall customer satisfaction (OCS) in PT. Secondly, the study investi-
gated, through RIDIT ranking, whether perceptions of PT service varied across different
sociodemographic characteristics. The result showed that within the characteristics; age,
frequency of PT usage and income, the perceptions of satisfaction differ regarding which
areas to prioritise in order to obtain a higher OCS. Lastly, the service provider’s per-
ception of the PT service was obtained through interviews and a questionnaire. The
results were analysed and compared with the customers’ perception in order to identify
differences, where fare and crowding on board were found as two key attributes.

Overall, the present work demonstrates a comprehensive approach for identifying strate-
gies for improvement of the PT services in the context of a large city in Sweden. The
approach could be applied in larger cities of other developed and developing countries.
It can be used for deriving suitable policy interventions by transport planners and poli-
cymakers to improve the existing PT services, which could encourage a higher usage of
PT among commuters.

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Contents
Contents 5

1 Introduction 7
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2 Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 Aim and research questions . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.4 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2 Literature review 11

3 Theoretical background 15
3.1 Importance Performance Analysis . . . . . . . . . . . . . . . . . . . . . . 15
3.2 Revised IPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 RIDIT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.4 Spearman’s Rank-Order Correlation . . . . . . . . . . . . . . . . . . . . . 18

4 Methodology 19
4.1 Design of survey instrument . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.1.1 Identification of comprehensive set of attributes influencing user
perception for public transport services . . . . . . . . . . . . . . . 19

4.1.2 Design of questionnaire . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2 Data collection and organisation of data . . . . . . . . . . . . . . . . . . 21

4.2.1 Public transport users . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2.2 Service providers . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.3 Data analysis and result . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3.1 Revised IPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3.2 RIDIT scoring and Spearman rank . . . . . . . . . . . . . . . . . 23
4.3.3 Analysis of the gap between consumer and provider satisfaction . 23

5 Results 24
5.1 Preliminary investigation and description of the statistical data . . . . . 24
5.2 Priority areas of improvement in PT based on consumer perception . . . 25

5.2.1 Management scheme . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.2.2 Factor structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.2.3 Comparison of management scheme and factor structure to obtain

priority attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.3 Consumer perception of PT based on sociodemographic characteristics . 31
5.4 Service provider’s perception of PT . . . . . . . . . . . . . . . . . . . . . 33

5.4.1 Differences in satisfaction between PT users and service provider . 33
5.4.2 Interviews with PT service providers . . . . . . . . . . . . . . . . 35

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6 Discussion 37
6.1 Discussion and policy implications of improvement attributes . . . . . . . 37
6.2 Limitations of the study . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

7 Conclusion 41

References 42

A English questionnaire 46

B Swedish questionnarie 53

C Questionnaire for service providers 60

D Interview questions for interview with Nordberg 65

E Python-code for revised IPA 66

F Python-code for RIDIT analysis 69

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1 Introduction
This section presents the background for the study. It further describes why it could
be beneficial to study the public transportation (PT) system from a consumer-centric
perspective. The section continues with presenting the aim, research questions and scope.

1.1 Background

The emission of greenhouse gases (GHGs) into the atmosphere through human activity is
a major contributor to climate change and global warming (IPCC, 2018). Due to higher
dependency on fossil fuels, the transportation sector is regarded as one of the major emit-
ters of GHGs (Wimbadi et al., 2021). In 2022, the transport sector, with an emission of
8.1 Gt CO2 equivalents, was responsible for 14% of global net GHG emissions (UNEP,
2023). Population growth together with increasing interest in commercial activities has
led to rising trends of passenger car ownership, especially in the big cities (Nguyen-Phuoc
et al., 2020). This growing passenger car ownership and usage is further responsible for
aggravating negative externalities such as traffic congestion, delays, and vehicular emis-
sions. The toxic exhaust emissions released into the atmosphere substantially deteriorate
the urban air quality and are subsequently accountable for health concerns among urban
residents (European Environmental Agency [EEA], 2023). Exposure to such harmful pol-
lutants is responsible for increasing the risk of premature death in cities due to diseases
such as lung cancer, heart disease, stroke, chronic obstructive pulmonary disease, and
respiratory infections (World Health Organization, n.d.). Hence, there is a need to shift
towards a sustainable alternative to reduce traffic congestion and vehicular emissions.
One such solution is to encourage higher usage of PT among commuters in urban areas
(European Environmental Agency [EEA], 2023).

PT is defined as linking a city or different cities with the purpose of providing a convenient
travel service and reducing the demand for private car use, which in turn reduces traffic
congestion (Institute for Transportation and Development Policy, n.d.). It also has the
capacity of carrying multiple travellers, and therefore works most efficiently in large
cities with dense population and a higher demand for convenient commuting options
(Zheng & Krol, 2023). Alongside biking and walking, PT is also the preferred mode of
transportation from an environmental perspective, as it emits less GHGs than single car
use. Encouraging a transition from private to public transport can therefore result in a
substantial reduction in GHG emissions from the transport sector, which will in turn also
contribute to reaching local as well as global climate goals.

To accomplish a higher demand for the use of PT, it is important to identify improvement
strategies for the services to ensure that the system is well-designed with inclusivity and
convenience to the users (Zheng & Krol, 2023). A well-designed PT system will retain

7



the current users as well as attract new ones. Furthermore, a well-developed PT system
is important in terms of accessibility and affordability (Karjalainen et al., 2023). The
affordability is especially important for low-income households who solely rely on PT
system for travel purposes. Therefore it is important to have affordable, accessible and
well-connected areas through PT. Other sociodemographic characteristics such as gender,
age, income, education, etc. could also have an impact.

In 2022 the transport sector was accountable for about 26% of the GHG emissions in the
EU-27 (EEA, 2022). Among these emissions, road traffic was accountable for the largest
contribution of approximately 60%. In Sweden, the domestic transport sector accounts
for approximately one third of the country’s total GHG emissions, where 90% comes from
road traffic (Trafikverket, 2023). Sweden’s larger cities are also facing population growth
due to immigration and urbanisation, where the desire to live in or close to cities is rising.
One such city is Gothenburg, Sweden’s second largest city with a population of almost 600
000 inhabitants located on the southwest coast of Sweden (Statistikmyndigheten, 2022a).
As it is a large city, an optimised PT system is a well suited way of transportation (Zheng
& Krol, 2023).

PT in Gothenburg is based on a radial system, where trips are made from the outer
parts of the city to the centre (Västra Götalandsregionen et al., 2018). The system is
based on a tram network and a comprehensive bus network. Trams and trunk bus lines
forms the backbone of the network, with local bus lines supplementing and providing
more local trips. Alongside, there are a number of train lines originating from the Västra
Götalandsregion (VGR) running into Gothenburg city. The fare structure is based on
three fare zones covering the entire Västra Götaland region (Västtrafik, n.d.-e). The total
number of travellers in Västra Götaland is 376 000 per day (Västtrafik, n.d.-c). Among
these travellers, 55% are women and 45% are men (VGR, 2022).

1.2 Problem

Identifying strategies to improve the PT system requires insight in how the consumer
perceives the service attributes of PT in their everyday lives. Regular PT users may
perceive the service differently compared to the consumers who only uses the PT system
occasionally or not at all. It is important to identify which service attributes the users
perceive as most valuable and evaluate the result in order to find out what needs im-
provement. These findings will create opportunities for policy changes with the purpose
of increasing the attractiveness and appeal of PT services among the wider population.

An effective way of identifying improvements about the PT service is to base research
on the consumer’s perspective. Consumer-centric studies are essential to identify the
potential drivers and barriers in the transport system. In order to gain this knowledge

8



from the consumers, in depth research is necessary. This can be achieved by interviewing
the consumers about their experiences and opinions. In that way, valuable information
regarding improvements of the PT system can be obtained and later be used by the
service provider to further improve the existing service. Additionally, consumers with
different sociodemographic characteristics such as age, gender, education, income, etc.
and different trip-related characteristics such as trip length, trip frequency and trip pur-
pose, may have different perceptions towards various attributes of PT services. Hence, it
is important to identify such differences (if any) and include them in policy analysis to
attract a wider group of consumers to use PT.

Furthermore, the service provider may also have a different perception about the service
which they are providing. One problem is the gap between consumer- and management’s
perception of the service. This can cause dissatisfaction and decreased trust between the
consumer and the supplier, which can reduce the amount of users. The management of
the PT service needs to be able to understand the perspective of the consumer.

1.3 Aim and research questions

The main objective of the study is to identify management strategies for improving the
PT services in Gothenburg, Sweden. This will be done in terms of analysing consumers’
importance and satisfaction towards service attributes, perception of different population
sub-groups towards the service attributes, and the service provider’s perception towards
the current service.

The main objective of the study includes several sub-objectives. Firstly, identifying a com-
prehensive list of attributes influencing PT usage. Secondly, identifying the perception of
consumers’ importance and satisfaction with PT service attributes using two-dimensional
techniques for data analysis. Further, identifying the variation in perception for service
attributes across consumers with different sociodemographic and trip-related character-
istics using non-parametric methods. Lastly, to identify the gap between consumers’
and service provider’s perception for the current PT service by conducting gap analysis.
In order to address the aforementioned issues, this study aims to address the following
research questions:

1. What are the priority areas of improvement in public transport services based on
consumer perception and expectation?

2. Does consumer perception of public transport services vary based on sociodemo-
graphic characteristics? If that is the case, in what way?

3. What are the gaps between user perception and service provider’s perception of
public transport?

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1.4 Scope

The scope of the study is limited to investigating consumer perception of PT in Gothen-
burg city. The scope is further limited to transportation modes, geographical area and
time of study. PT in Gothenburg is made up of trams, ferries, local buses, regional buses,
express buses and commuter trains. The trams operate from a suburb, through the city
and out to another suburb (Västtrafik, n.d.-d). Some lines operate out to Mölndal mu-
nicipality. Local buses operate all around the municipality, as well as into neighbouring
municipalities. Express buses operate from neighbouring cities, through Gothenburg and
out to another city. The service provider of the PT system in Gothenburg is the regional
agency Västtrafik.

Västtrafik has divided the region into 3 zones, for ticket payment radiating out from
Gothenburg, see figure 1. (Västtrafik, n.d.-e). Zone A includes the municipalities of
Gothenburg, Mölndal, Partille and Öckerö, see figure 2. Zone B includes the neighbouring
municipalities surrounding Zone A. Zone C includes the rest of the region. The price for
a single ticket in one zone, that lasts for 90 minutes, is 36 SEK. The price and ticket
duration increases when travelling within multiple zones.

This study will investigate the consumer perspective of the buses and trams that operate
in zone A, Gothenburg, excluding ferries and commuter trains. As the PT system in
Gothenburg is structured in a manner where users utilise both buses and trams, the
study considers the two modes of transportation as one. The study has been carried out
independently, and not as a part of Västtrafik.

Figure 1: Ticket zones in Västra Gö-
taland Region. (Västtrafik, n.d.-e).
Reprinted with permission.

Figure 2: Close-up ticket zone A. (Väst-
trafik, n.d.-a). Adapted with permis-
sion.

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2 Literature review
This section presents a literature review of several different studies examining the subject
of public transport (PT). The aim of the literature review is to identify service attributes
that impact consumers’ perception of PT. Additionally, the review of literature includes
methodologies used in past studies, and key findings regarding the attributes influencing
PT users’ overall consumer satisfaction (OCS).

Moslem et al., 2023 performed a study in Mersin City, Turkey with the aim of gaining a
deeper understanding of the importance of different attributes associated with PT. This
was done in order to encourage a shift from private car usage towards PT. The study was
based on interviews to examine the perception of both PT experts and supply operators.
The authors categorised the attributes and found that perspicuity, physical comfort and
directness was the most important attributes to increase the usage of PT. Additionally,
the findings highlighted speed and distance to stop as important areas for improvement,
see table 1 for presented attributes in this study. Dong et al., 2021 conducted a survey-
based study in 8 cities in China, consisting of both sociodemographic and travel-related
questions. The aim was to investigate how the users’ pattern in PT have changed after
the COVID-19 pandemic. The results showed that in order to increase the OCS in the
aftermath of the pandemic, the service providers should improve areas such as service
frequency, information in mobile app, punctuality and comfort. Further, Hörcher and
Tirachini, 2021 conducted an exhaustive literature review regarding the subject of PT
economics and presented key attributes findings. The study showed that attributes such
as fare, frequency, in-vehicle travel time and waiting time was mentioned in the majority
of the analysed literature and therefore has influence on PT.

Van Soest et al., 2019 conducted a literature review with the aim to investigate how the
access and egress distances effects the usage of PT. The results showed that although
a longer access and egress time is beneficial for the health, the distances needs to be
shorter for people to increase their use of PT. Further, the authors conclude that so-
ciodemographics factors such as age, gender and income influence the consumer usage of
the PT system. Mouwen, 2015 conducted a survey-based study in Amsterdam, Nether-
lands, with the aim to analyse consumers perception towards several attributes regarding
PT. The respondents rated different PT related attributes as well as their overall satis-
faction with PT. The result showed that attributes such as on-time performance, travel
speed and service frequency has an major impact of the OCS. The authors recommend
service providers to make improvements that targets different sociodemographic groups
to maintain these travellers, rather than attract new PT users, see table 2.

Guirao et al., 2016 performed a survey-based study in Madrid, Spain with the aim to
identify attributes that has an influence on the service quality of PT. The authors analysed

11



the result of the questionnaire with stated importance as well as derived importance,
and hierarchy method by ranking attributes against each other. The results showed
that attributes evaluated using stated importance may have a high rank but does not
influence the OCS of the service, which makes the derived importance more useful. When
analysing stated importance, the attributes with the highest rank was cleanliness, seating
capacity and travel time. Furthermore, when analysing the derived importance the results
showed that route, driving security and frequency had the most impact on the OCS.
Karlsson and Larsson, 2010 conducted a survey-based study at Chalmers University of
Technology in Sweden, Gothenburg with the aim to investigate the perception of comfort-
related attributes which can affect the OCS. The result showed that factors such as
temperature, information regarding the trip, seating capacity and driving behaviour had
the most influence on experienced comfort with PT. Further, the findings indicated that
various factors related to trips and sociodemographics characteristics, including travel
time, income and gender, influence the perceived satisfaction with PT.

The review of literature shows that various PT related, sociodemographic, trip-related
attributes influence customer’s perception and experience of the PT system. The identi-
fied attributes influencing consumer perception of PT services are listed in the continuous
table 1, 2.

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Table 1: Summary of the studied literature

Study Presented attributes and characteristics
Moslem et al., 2023 Vehicle attributes: Physical comfort, safe of travel.

Trip related attributes: Mental comfort, distance to
stops, safety of stops, comfort in stops, need of transfer, fit
connections, reliability, journey time, awaiting time, reaching
time, time availability, info. before travel, info. during travel,
perspicuity.

Sociodemographic characteristics: -
Dong et al., 2021 Vehicle attributes: Secure onboard.

Trip related attributes: Information before trip, infor-
mation related to Covid-19, consequences related to Covid-19,
probability on mode related to Covid-19, long-term effects of
Covid-19, safe at stops, security against Covid-19.

Sociodemographic characteristic: Gender, age, educa-
tion, income.

Hörcher and Tirachini, 2021 Vehicle attributes: Invehicle travel time, invehicle crowding,
vehicle size, seat provision, number and operation of doors.

Trip related attributes: Access and egress walk time,
waiting time, peak time and off peak time, multiperiod services,
fare level, frequency, fleet size, representative (aggregate) OD,
schedule delay, station crowding, denied boarding, information
collection, transfer penalty, demand imbalance factor, line
with multiple sections, urban space with uniform demand,
monocentric city corridor, network with transfer, stop density,
line density, line structure.

Sociodemographic characteristic: -
Van Soest et al., 2019 Vehicle attributes: Vehicle type.

Trip related attributes: Frequency, density, access and
egress time, purpose, time, trip length, transfers, frequency of
use.

Sociodemographic characteristic: Gender, age, avail-
able vehicles, driving license, PT card, household size, income,
education, employment, ethnicity.

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Table 2: Summary of the studied literature (continued)

Study Presented attributes and characteristic
Mouwen, 2015 Vehicle attributes: On board information, cleanliness, ease of

boarding and alighting, seating capacity, on board noise, safety
on board.

Trip related attributes: On-time performance, travel
speed, frequency, fare, personnel behaviour, drivers behaviour,
ticket system, information at stops, safety at stops.

Sociodemographic characteristics: Gender, age, num-
ber of weekly PT trips, car availability, negative safety
experience.

Guirao et al., 2016 Vehicle attributes: Cleanliness, comfort.

Trip related attributes: Punctuality, frequency, info-
incidents, info-service, route, connections, access, journey time,
information and communication technologies.

Sociodemographic characteristics: Age, gender, trip
purpose, frequency of trip, ticket type, occupation.

Karlsson and Larsson, 2010 Vehicle attributes: Temperature, availability of seat, com-
fortable seat, cleanliness, smell, noise, illumination, crowd,
storage possibilities, smooth driving.

Trip related attributes: -

Sociodemographic characteristics: Gender, age, travel
time, travel frequency, car availability.

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3 Theoretical background
This section presents the theoretical background for the selected statistical analysis meth-
ods used to carry out the study.

3.1 Importance Performance Analysis

Importance Performance Analysis (IPA) is a statistical analysis technique, introduced by
Martilla and James in 1977 (Martilla & James, 1977). The aim of the technique is to
identify improvement areas of service by evaluating importance and customer satisfaction
of different attributes. IPA is commonly used among different service providers for service
evaluation and quality improvement. Data is typically collected through customer sat-
isfaction surveys where importance and performance (satisfaction) is measured through
some kind of self-stated measure, e.g. through a rating scale. The data is then compiled
into a two-dimensional matrix with attribute importance on the x-axis, and attribute per-
formance on the y-axis (Matzler et al., 2003). The matrix is divided into four quadrants.
Determining the axes placement can be done in different ways, the most common being
by taking the total means of importance, and the total means of performance. See figure
3. The mean values of importance and performance for each attribute are then to be
scattered as points in the matrix, in order to identify the priority areas of improvement.

Figure 3: IPA matrix

Attributes in Quadrant I are of high importance and high performance, with the man-
agement scheme "Keep up the good work" (Matzler et al., 2003). These attributes are

15



major strengths and their standards should be maintained to keep the current service
quality. Attributes in Quadrant II are minor strengths, with low importance and high
performance. Resources dedicated to these attributes could be of better use distributed
elsewhere, since these attribute are a "Possible overkill". Attributes in Quadrant III are
of low importance and low performance and therefore of "Low priority". These attributes
are minor weaknesses and do not require additional effort. Lastly, attributes in Quadrant
IV are major weaknesses, with high importance and low performance. This indicates that
they require effort for service quality improvement, and are therefore in the management
scheme "Concentrate here".

3.2 Revised IPA

IPA is based on two assumptions; (1) that attribute performance and attribute impor-
tance are independent variables and (2) that the relationship between attribute perfor-
mance and overall customer satisfaction (OCS) is linear and symmetrical (Matzler et al.,
2004). W. Deng, 2007 presents multiple studies showing that these assumptions are not
representative in the real world, as attribute performance and attribute importance are
dependent variables and that their relationship therefore is causal, as well as the rela-
tionship between attribute performance and OCS being asymmetrical. This means that
changes in attribute performance will in fact influence the relative importance of that at-
tribute, making the customer’s self-stated importance not practicable (W. Deng, 2007).
This has resulted in revised IPA, which is a modification of the traditional IPA where
these limitations are avoided.

Three factor theory of customer satisfaction suggests that service attributes can be di-
vided into three categories; basic factors, performance factors and excitement factors
(W. J. Deng et al., 2008). Basic factors, or dissatisfiers, are the minimum requirements
and attributes expected to be fulfilled. This means that they generate customer dissat-
isfaction when not exceeded, but no increased customer satisfaction when fulfilled. The
relationship between basic factors and OCS is non-linear and asymmetrical. Performance
factors produce satisfaction when delivered and dissatisfaction when not delivered. There-
fore, the relationship between performance attributes and OCS is linear and symmetrical.
Excitement factors, or satisfiers, are attributes that increase customer satisfaction when
exceeded but do not cause dissatisfaction when not exceeded. The relationship between
excitement factors and OCS, as for the basic attributes, is non-linear and asymmetrical.

Revised IPA uses implicitly derived importance instead of customer self-stated impor-
tance, which is based on the attribute’s correlation between performance and OCS and the
characteristic attribute categories from three-factor theory are incorporated (W. Deng,
2007; W. J. Deng et al., 2008). This removes the potential problems of linear and symmet-
rical relationships between the variables, which makes it superior to stated importance.

16



Since there is also potential for multicollinearity existing within the independent variables,
partial correlation analysis is a suitable method to determine the derived importance for
each attribute. This is used together with natural logarithmic transformation of the in-
dependent variables, which can give a better representation of diminishing returns and
better sensitivity in the data.

By first converting all the attributes’ performance to natural logarithmic form, partial
correlation analysis is used to determine the partial correlation coefficient for each perfor-
mance attribute with OCS (W. Deng, 2007; W. J. Deng et al., 2008). Partial correlation
is then executed for each value, with one performance value and OCS as dependent
variables, controlling for the rest of the natural logarithmic performance values as inde-
pendent variables. The partial correlation coefficient is the implicitly derived importance
for respective attribute.

To obtain the revised IPA matrix, the attribute’s derived importance is plotted as the x-
coordinate, the attribute’s performance is plotted as the y-coordinate and the respective
total mean values can be used as the axes dividing the quadrants (W. Deng, 2007). This
generates the management scheme explained in sub-section 3.1. The revised IPA matrix
for the factor structure is obtained by plotting the attributes, with stated importance
as the x-coordinate and the derived importance as the y-coordinate and the respective
mean values as the axes (Matzler et al., 2003). See figure 4.

Figure 4: Revised IPA providing the three-factor structure

17



3.3 RIDIT Analysis

In scientific studies it happens that researchers encounter response variables that lie be-
tween dichotomous classifications and refined measurement systems (Bross, 1958). These
variables can include subjective scales or numerical values influenced by various factors
such as experimental material quality or protocol details. Traditional statistical methods
like chi-square tests or t-tests may not fully capture the nuances of such "borderland"
variables. In such cases, RIDIT analysis, founded by Bross, 1958, provides a valuable
bridge between these two traditional families of statistical methods. Ridits are calculated
based on the observed distribution of the data. This approach is beneficial when dealing
with real-world data, as it allows for a more flexible and data-driven transformation.

RIDIT analysis, short for Relative to an Identified Distribution Integral Transformation,
is a statistical method designed for assessing the importance of service attributes using
ordinal data (Jiten Shah et al., 2021). This technique involves transforming the ordered
response variable into ridit scores through a probability integral transformation using
an empirical distribution function. Ridit scores represent the relative position of each
category within the distribution of the responses, ranging from 0 to 1. Lower ridit values
indicate lower satisfaction with the transit service attribute being assessed meaning a
higher importance. RIDIT analysis, involves several key steps that result in a ranking
of different variables (Bross, 1958). Initially, the ordinal categories are ranked according
to their inherent order or hierarchy. Following this, RIDIT scores are computed for each
category, meaning the level of satisfaction from the survey, representing the proportion
of observations falling below it. In the context of ordinal data, these scores are calculated
using cumulative probabilities or frequencies to accurately reflect the ordinal nature of
the data. These RIDIT scores then enable a comparison across different groups, enabling
the evaluation of distributional differences in the data. This methodology offers a ro-
bust approach to analysing ordinal data, accommodating the natural order of categories
while providing a non-parametric means of comparison that does not necessitate strict
assumptions about the data’s underlying distribution.

3.4 Spearman’s Rank-Order Correlation

Spearman’s correlation coefficient quantifies the degree of a monotonic association be-
tween paired data points (Aryan Gupta, 2023). Spearman’s correlation coefficient is
applicable when assessing the strength and direction of a relationship between variables
that may not have a linear association, making it suitable for when the data is being
ranked. It involves comparing ranks between different sub-groups, yielding a correlation
value ranging from 0 to ±1. A correlation value closer to ±1 suggests a stronger corre-
lation, indicating similar rankings between sub-groups. Conversely, a value closer to 0
indicates a lack of correlation, signifying divergent attribute rankings between sub-groups.

18



4 Methodology
This section explains the methods used to carry out the study. This includes identifica-
tion of attributes, design of survey instrument, data collection, data organisation, data
investigation and analysis.

4.1 Design of survey instrument

This sub-section delves into the process of identifying attributes influencing user percep-
tion and the design of the survey instrument.

4.1.1 Identification of comprehensive set of attributes influencing user per-
ception for public transport services

The first part of the project consisted of an exhaustive review of literature with the pur-
pose to identify key attributes that impacts user perception of PT services. This involved
an examination of scholarly articles and research papers from past studies conducted in
both developed and developing countries, see section 2. Based on the literature review, a
list of 20 attributes has been considered in the present study for analysing user perception
for PT services. The attributes and their definitions are presented in table 3.

From the review of literature it is evident that multiple sets of attributes influence con-
sumer importance and satisfaction for PT systems in different study contexts. However,
attributes such as frequency, punctuality, comfort, cleanliness, information related to the
trip, travel time, safety on board and at stops and security are identified common sets of
factors influencing user perception for PT in different studies, and hence are also con-
sidered as relevant in the present study context. To have detailed understanding on trip
related information this study include information in mobile app, ticketing system, on-
board information and information at stop as four separate attributes. The attribute
stop illumination has also been mentioned in some of the studies in reference to safety at
stops. This has been added as a separate attribute since the PT system in Gothenburg
extends into areas with less dense population and therefore less illuminated. Further,
attributes related to the trip and transfers, such as number of transfers, transfer time,
accessibility and time to stop, ease of boarding and alighting, crowding on board, seating
capacity and span of service have been included in past studies and is identified as rele-
vant for understanding user perception of the PT system in Gothenburg. Although fare
has been included as an attribute in only a few studies, it is identified as an important
attribute to analyse the user acceptance of PT services in Gothenburg.

19



Table 3: Attribute definitions and number in study

Number Attribute Definition
1 Punctuality Consistent and timely adherence to scheduled departure

and arrival times.
2 Service frequency Time interval of vehicle availability along a route.
3 Span of service Time duration for which the service is operational during a

day along a route.
4 Fare Amount of money required to be paid for using the service.
5 Comfort Degree of experienced comfort while travelling. For

example, comfort in terms of occupying a seat, standing,
on-board noise and vehicle temperature.

6 Information in
mobile app

Digital platform providing real-time and relevant data,
updates, or details catering to trip maker’s needs, or
inquiries through mobile application interface.

7 Ticketing system Type of ticketing system i.e., on-board, off-board and
online ticketing.

8 Travel time Total time spent inside a vehicle during a journey.
9 Cleanliness Maintenance of dirt-free and orderly environment inside

the vehicle.
10 Crowding on

board
Degree of crowding. For example seat availability, or
experience when standing in crowded conditions.

11 On-board
information

Real-time updates provided inside bus/tram during the
journey, including route information, announcements, etc.

12 Seating Capacity Maximum number of passengers the vehicle can
accommodate with designated seating arrangements.

13 Ease of boarding
and alighting

Convenience of getting on and off the vehicle.

14 Transfer time Total time taken for transfer from one bus/tram to another
to reach the destination, which includes walking from one
bus/tram stop to another and waiting time.

15 Number of
transfers

Total number of changes from one bus/tram to another
before reaching the destination.

16 Accessibility and
time to stop

Time taken to reach bus/tram stop from home and from
bus/tram stop to the destination.

17 Information at
stop

Information available to the trip makers at the bus/tram
stop, encompassing routes, schedule, delays, etc.

18 Stop illumination Provision of lighting at designated stops to enhance
visibility during low-light conditions.

19 Safety on board Precautions to reduce the risk of exposure to injury or
danger during the event of an accident.

20 Security Measures ensuring protection against any form of danger
or theft, within the vehicle, and at stops.

20



4.1.2 Design of questionnaire

After identifying the set of attributes for addressing the research questions, the question-
naire was designed. It was divided into four parts. The first part of the questionnaire
consisted questions regarding the user’s regular way of travelling, such as travel mode
and travel frequency. This was valuable in order to gain information about travel pro-
files of the respondents and PT usage. The second part contained both importance and
satisfaction rating-scale questions for each of the 20 chosen attributes. It also consisted
of one question about the traveller’s overall satisfaction with the PT system. This was a
key question in order for the statistical analysis to be done. The third part consisted of
questions about the traveller’s most common trip, which contributed with more informa-
tion about the traveller’s habits. The last part contained questions about the traveller’s
sociodemographic information. The characteristics chosen were gender, age, education,
income, occupation, travel frequency and car accessibility, from the literature study.

Before conducting the main survey, a pilot pre-test was conducted on 10 randomly selected
respondents from zone A in Gothenburg. The purpose of the pilot survey was to ensure
the clarity of the questions. After incorporating necessary refinements and corrections
based on the suggestions of the respondents, the final version of the questionnaire was
available to carry out the main survey. See Appendix A and B for the English and
Swedish version of the questionnaire.

4.2 Data collection and organisation of data

This sub-section explains the methodology of data collection and organisation, which was
conducted on PT users as well as the PT service provider in Gotheburg, Västtrafik.

4.2.1 Public transport users

The data collection on PT users consisted of an online questionnaire, which was limited to
travellers within zone A. Data was collected through the questionnaire being sent out in
Gothenburg-related Facebook groups and being shared on various social media platforms.
People were also randomly approached on trams, buses, at stops and other everyday
places around the city. When organising the data, each sociodemographic characteristic
was divided into two sub-groups. For gender, the counterparts are male and female, since
others were a significant small minority. For age, it was divided between people under
and over the age of 35 years, since this is the mean age of the population in Gothenburg
(Statistik och Analys stadsledningskontoret Göteborgs Stad, n.d.). The travel frequency
was divided so that people travelling 4 times or less are infrequent PT users, and people
using it more are frequent users. For income the counterparts are people with income
lower and higher than 35 000 SEK per month. This number represents the approximate
median income in Sweden 2022 (Statistikmyndigheten, 2022b). The car accessibility was

21



divided between people with and without access to a car.

4.2.2 Service providers

When beginning to investigate the service provider’s perception, the answers from the
service users questionnaire had already been obtained, providing an initial understanding
of customers’ perception of importance and satisfaction of the PT service. In order to
obtain the service provider’s perspective on the selected attributes, two extensive inter-
views were held with employees at Västtrafik, to gain qualitative data. A questionnaire
was also sent out to the employees, which yielded quantitative data. See Appendix C for
the questionnaire. The employees answered questions about Västtrafik’s perception of
the selected attributes in terms of importance and satisfaction of their provided service.

The first interview was held with Sharon Plotzki, development manager and Lovisa
Borgström, community developer at Västtrafik. They were asked about Västtrafik’s
perception of each of the selected attributes and encouraged to further develop their
thoughts. The interview was based on the same set of questions as the service provider
questionnaire, seen in Appendix C. The second interview was with Lisa Nordberg, head
of a customer strategy department, with the purpose of delving into the ticket pricing of
their service, since fare was a clear area of dissatisfaction obtained from the service users
questionnaire. The interview questions that were discussed during the interview can be
seen in the Appendix D. The data collected from the interviews and questionnaire was
later used to identify the gap in perceptions between the provider and the users.

4.3 Data analysis and result

The data analysis was made using statistical analysis methods; revised IPA and RIDIT
scoring and Spearman rank, presented in the Theoretical background, section 3. This
provided meaningful insights and results for the problem at hand.

4.3.1 Revised IPA

Revised IPA is a commonly used method to analyse consumer satisfaction and impor-
tance, and was conducted in order to answer research question 1: What are the priority
areas of improvement in public transport services based on consumer perception and ex-
pectation? The revised IPA was conducted using the digital statistical analysis tool
SPSS (IBM, n.d.). As a first step, the performance data for the PT users was con-
verted to natural logarithmic form. Then considering OCS data as dependent variable
and natural logarithmic form of individual attribute performance data as independent
variables. Partial correlation analysis was performed to determine derived importance
for each attribute. The values of derived importance, the mean stated performance and
mean importance were normalised for each attribute to achieve a standard data format

22



for comparison. Python programming language was used to plot the two dimensional grid
of IPA matrices. The mean of the normalised values of the attributes were used for the
placement of the axes of the matrices. A revised IPA matrix providing the management
scheme, with derived importance on the x-axis and performance on the y-axis as well as
a matrix providing the factor structure with stated importance on the x-axis and derived
importance on the y-axis, were plotted. See Appendix E for the Python-code.

Revised IPA was conducted for the overall sample, as well as for sub-groups comprising
individuals with and without access to a car. The reason to separately analyse car
accessibility with revised IPA was to gain insights on whether there is any difference
in perception for PT service attributes across car-users and non-car users. Attracting
car-users to choose PT services is one of the primary goals to reduce traffic congestion
and vehicular emissions. This analysis enables conclusions to be drawn about necessary
policies to encourage a shift from passenger car ownership to PT.

4.3.2 RIDIT scoring and Spearman rank

RIDIT analysis was conducted to enable a ranking of the attributes for all the sociodemo-
graphic groups. It is one of the few ranking systems that does not assume an underlying
distribution of the data and is relevant for ranking the ordinal dataset used in this study.
This multi-criteria decision making technique was used to address the second research
question: Does consumer perception of public transport services vary based on sociode-
mographic characteristics? If that is the case, in what way?

The following four sociodemographic and trip-related characteristics; gender, age, fre-
quency of PT usage and income, were analysed using this method. Ridit scores for each
attribute were derived for each sub-group. Subsequently, these ridit scores were used to
rank attributes based on both importance and satisfaction data. The ridit scores were
calculated for each group using python, full code can be found in the Appendix F. A
Spearman rank correlation was conducted using SPSS to investigate the extent of cor-
relation between sub-groups for each sociodemographic characteristic. This process was
repeated for all four groups, considering both importance and satisfaction data.

4.3.3 Analysis of the gap between consumer and provider satisfaction

An analysis of the gap in perception between PT users and the service provider was con-
ducted in order to answer research question 3: What are the gaps between user percep-
tion and service provider’s perception of public transport? The answers from the service
providers’ questionnaire were analysed by calculating the mean of the stated satisfaction
of each attribute. The same was done for the consumers’. Then the mean for the con-
sumers was subtracted from the service providers’ in order to receive the gap between
perceptions.

23



5 Results
In this section, the results of the revised IPA, RIDIT analysis, Spearman rank and gap
analysis are presented, in order to answer the research questions.

5.1 Preliminary investigation and description of the statistical
data

A total number of 674 answers were collected anonymously through the consumer sur-
vey. After data cleaning, the dataset for the analysis consisted of 638 answers. This is a
representative sample dataset to perform statistical analysis (Taherdoost, 2016). These
answers were collected in zone A, Gothenburg. The sociodemographic distribution of
the collected data was then compared with statistical data about the general sociodemo-
graphic information of Gothenburg. It was found that females were overrepresented in
the survey, as well as students and people under the age of 35. Simultaneously, people
with access to a car were underrepresented in comparison to the population of Gothen-
burg. This is shown in table 4. From the service providers’ questionnaire, five answers
were collected.

Table 4: Data comparisons

Sociodemographic
information

Respondents in this
study

Gothenburg

Gender Female: 64,6%
Male: 32,9%
Others: 2,5%

Female: 49,6 % ∗∗

Male: 50,4 % ∗∗

Others: -
Age ≤ 35 years: 72,1 %

> 35 years: 27,9 %
≤ 35 years: 48,6 % ∗∗

>35 years: 51,4 % ∗∗

Income ≤ 35 000 SEK: 72,1 %
>35 000 SEK: 27,9 %

≤ 35 000 SEK: ∼ 50%∗∗∗

>35 000 SEK: ∼ 50%∗∗∗

Access to car Access: 41,4 %
No access: 58,6 %

Access: 72 % ∗

No access: 28 % ∗

Frequency Frequent users: 51,9 %
Infrequent users: 48,1 %

Frequent users: -
Infrequent users: -

Students Studying: 48 % Studying: 10 % ∗∗∗∗

PT as main travelling mode Total: 66 % Total: 45 % ∗

* Västra Götalandsregionen, 2023
** Statistik och Analys stadsledningskontoret Göteborgs Stad, n.d.
*** Statistikmyndigheten, 2022b
****Sveriges Förenade Studentkårer [SFS], 2023 The number of students from the SFS data were
divided with the population of Gothenburg.

24



5.2 Priority areas of improvement in PT based on consumer
perception

The results in this sub-section addresses research question 1, using revised IPA in order
to obtain areas of improvement for the overall sample and sub-samples of car acces and
no car access.

5.2.1 Management scheme

Figure 5 shows the revised IPA matrix providing the management scheme for the overall
sample. The attributes in quadrant IV, the ones of highest importance and lowest per-
formance, are punctuality (1), fare (4), comfort (5) and number of transfers (15). These
have the management scheme "Concentrate here" and are the PT system’s major weak-
nesses based on the perception of the overall sample. See table 5 for the management
scheme for all attributes.

Figure 5: Revised IPA providing the management scheme for the overall sample

25



Table 5: Management scheme for overall sample

"Keep up the good work" "Possible overkill" "Low priority" "Concentrate here"

2: Service frequency 3: Span of service 10: Crowding on board 1: Punctuality

6: Information in mobile app 9: Cleanliness 12: Seating capacity 4: Fare

7: Ticketing system 11: On-board information 14: Transfer time 5: Comfort

8: Travel time 13: Ease of boarding and alighting 15: Number of transfers

16: Accessibility and time to stop 17: Information at stop

19: Safety on board 18: Stop illumination

20: Security

Figure 6 shows the revised IPA matrices providing the management schemes for the sub-
samples of car access and no car access. The matrices show that punctuality (1) and fare
(4) are the common major weaknesses according to both people with and without access
to a car. People with access to a car also have service frequency (2), travel time (8) and
numbers of transfers (15) in the "Concentrate here" category, while people without acess
to a car see comfort (5) as a priority. See table 6 for the management scheme of the
sub-samples car access and no car access.

Figure 6: Comparison of management schemes between car access (left) and no car access
(right).

26



Table 6: Comparison of management schemes between car access and no car access

Management
type

Car access No car access

"Keep up the
good work"

Comfort (5),
Information in mobile app (6),
Ticketing system (7),
Accessibility and time to stop (16),
Safety on board (19)

Service frequency (2),
Ticketing system (7),
Number of transfers (15),
Accessibility and time to stop (16)

"Possible
overkill"

Span of service (3),
Cleanliness (9),
On-board information (11),
Ease of boarding and alighting (13),
Information at stop (17),
Stop illumination (18),
Security (20)

Span of service (3),
Information in mobile app (6),
Travel time (8),
Cleanliness (9)
On-board information (11),
Ease of boarding and alighting (13),
Information at stop (17),
Stop illumination (18),
Safety on board (19),
Security (20)

"Low
priority"

Crowding on board (10),
Seating capacity (12),
Transfer time (14)

Crowding on board (10),
Seating capacity (12),
Transfer time (14)

"Concentrate
here"

Punctuality (1),
Service frequency (2),
Fare (4),
Travel time (8),
Number of transfers (15)

Punctuality (1),
Fare (4),
Comfort (5)

5.2.2 Factor structure

Figure 7 shows the factor structure for the overall sample. The revised IPA matrix for
the factor structure shows that the only basic factor is security (20), meaning that secu-
rity generates no satisfaction when fulfilled but great dissatisfaction when not fulfilled.
The important performance factors are punctuality (1), service frequency (2), fare (4),
information in mobile app (6), travel time (8), number of transfers (15), accessibility and
time to stop (16) and safety on board (19). These attributes generate satisfaction when
delivered and dissatisfaction when not delivered, and are of more important character
than the unimportant performance factors. The unimportant performance factors are
span of service (3), cleanliness (9), crowding on board (10), on-board information (11),
seating capacity (12), ease of boarding and alighting (13), transfer time (14), information
at stop (17) and stop illumination (18). Excitement factors imply the attributes gen-
erating satisfaction when provided but no extra dissatisfaction when not provided, and
consist of comfort (5) and ticketing system (7).

27



See table 7 for a clear summary over the attribute’s factor structure for the overall sample.

Figure 7: Revised IPA providing the factor structure

Table 7: Factor structure for the overall sample

Important performance factors Unimportant performance factors Basic factors Excitement factors

1: Punctuality 3: Span of service 20: Security 5: Comfort

2: Service frequency 9: Cleanliness 7: Ticketing system

4: Fare 10: Crowding on board

6: Information in mobile app 11: On-board information

8: Travel time 12: Seating capacity

15: Number of transfers 13: Ease of boarding and alighting

16: Accessibility and time to stop 14: Transfer time

19: Safety on board 17: Information at stop

18: Stop illumination

Figure 8 shows a comparison of the factor structures between the sub-samples of car
access and no car access. Most of the attributes have a similar factor structure, however
there are some differences. As to be seen in table 8, the excitement factors are the same
for both car access and no car access, consisting of comfort (5) and ticketing system (7).
The basic factors are similar for car access and no car access, consisting of transfer time
(14) and security (20). For people without access to a car, information in mobile app
(6) is also a basic factor. For people with access to a car, this attribute is instead an
important performance factor along with punctuality (1), service frequency (2), fare (4),

28



crowding on board (10), number of transfers (15), accessibility and time to stop (16) and
safety on board (19). Non car access have punctuality (1), service frequency (2), fare (4),
number of transfers (15), accessibility and time to stop (16) and safety on board (19) as
important performance factors. Lastly, the unimportant performance factors, that are
similar for people with and without access to a car, are span of service (3), cleanliness
(9), on-board information (11), seating capacity (12), ease of boarding and alighting (13),
information at stop (17) and stop illumination (18). For people with no car access,
crowding on board (10) and transfer time (14) are unimportant performance factors as
well. This is presented in table 8.

Figure 8: Comparison of factor structures between car access (left) and no car access
(right).

29



Table 8: Comparison of factor structure between people with access to a car and without
access to a car

Factor
structure

Car access No car access

Important
performance
factors

Punctuality (1),
Service frequency (2),
Fare (4),
Information in mobile app (6),
Travel time (8)
Crowing on board (10),
Number of transfers (15),
Accessibility and time to stop (16)
Safety on board (19)

Punctuality (1),
Service frequency (2),
Fare (4),
Number of transfer (15),
Accessibility and time to stop (16),
Safety on board (19)

Unimportant
performance
factors

Span of service (3),
Cleanliness (9),
On-board information (11),
Seating capacity (12),
Ease of boarding and alighting (13),
Information at stop (17),
Stop illumination (18)

Span of service (3),
Cleanliness (9),
Crowding on board (10),
On-board information (11),
Seating capacity (12),
Ease of board and alighting (13),
Transfer time (14),
Information at stop (17),
Stop illumination (18)

Basic
factors

Transfer time (14),
Security (20)

Information in mobile app (6),
Travel time (8),
Security (20)

Excitement
factors

Comfort (5),
Ticketing system (7)

Comfort (5),
Ticketing system (7)

5.2.3 Comparison of management scheme and factor structure to obtain pri-
ority attributes

Improvement strategies for PT services were identified by comparing the factor structure
and management scheme. The order of priority for improvement are as follows; (1) basic
factors falling under "Concentrate here", (2) performance factors falling under "Concen-
trate here" and (3) excitement factors falling under "Concentrate here" (Cheranchery &
Maitra, 2017).

As seen in table 9, there are no basic factors falling under "Concentrate here" for all the
investigated groups. Hence, for the overall sample, the performance factors; punctuality,
fare and number of transfers are the main areas of improvement in PT, followed by
comfort, which is an excitement factor. All these factors fall under "Concentrate here".
Punctuality, service frequency, fare, travel time and number of transfers are the priority
areas of improvement based on the perception of people with access to a car. For people
without access to a car, punctuality and fare are the the most important attributes to

30



improve, followed by comfort.

Table 9: Comparison of factor structure and management scheme

Overall sample Car acess No car access
Basic
factors in
"Concentrate
here"

- - -

Performance
factors in
"Concentrate
here"

Punctuality,
Fare,
Number of transfers

Punctuality,
Service frequency,
Fare,
Travel time,
Number of transfers

Punctuality,
Fare

Excitement
factors in
"Concentrate
here"

Comfort - Comfort

5.3 Consumer perception of PT based on sociodemographic
characteristics

The results of the RIDIT analysis shows the rank of each attribute for all the sub-groups,
to answer research question 2. For rank of the importance see table 10 and for the
satisfaction see table 11. For importance, the result of the Spearman rank correlation
showed that the rank for each attribute did not vary much in the sociodemographic
groups, since all the values are near 1, see table 10. However, for the satisfaction the
Spearman rank correlation showed that all the sociodemographics groups except gender
had a value close to 0, which means that the sub-groups rank the attributes differently,
see table 11. For instance, the group with the Spearman value for satisfaction closest to
0 was income, although the value for importance was closer to 1. This means that both
income above the median and income below the median value the importance of each
attributes similar but the satisfaction for each attribute are not alike.

31



Table 10: RIDIT Ranking of stated importance
M= male, F= female, Y= Age ≤ 35, O= Age > 35, Fr= Frequent PT user,
IFr= Infrequent PT user, LI= Income ≤ 35 000 SEK, HI= Income > 35 000 SEK

Attribute M F Y O Fr IFr LI HI

Punctuality 7 6 6 7 6 7 6 7
Service frequency 4 5 5 4 4 5 5 1
Span of service 12 18 13 20 16 16 14 19
Fare 1 1 1 5 1 1 1 8
Comfort 13 17 16 17 18 14 16 17
Information in mobile app 2 3 3 1 2 3 3 2
Ticketing system 18 16 18 14 19 15 19 16
Travel time 6 8 7 6 7 6 8 5
Cleanliness 11 4 10 16 11 11 10 11
Crowding on board 14 14 15 15 13 17 15 14
On-board information 16 10 12 12 10 12 12 12
Seating capacity 15 19 17 18 17 19 18 18
Ease of boarding and alighting 20 20 20 19 20 20 20 20
Transfer time 10 12 11 13 12 10 11 9
Number of transfers 9 9 9 8 9 8 9 6
Accessibility 8 7 8 10 8 9 7 10
Information at stop 17 15 19 9 15 18 17 15
Stop Illumination 19 11 3 11 14 13 13 13
Safety 5 4 4 3 5 4 4 3
Security 3 2 2 2 3 2 2 4

Spearman Rank 0,836 0,791 0,941 0,892

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Table 11: RIDIT Ranking of stated satisfaction
M= male, F= female, Y= Age ≤ 35, O = Age > 35, Fr= Frequent PT user,
IFr= Infrequent PT user, LI= Income ≤ 35 000 SEK, HI= Income > 35 000 SEK

Attribute M F Y O Fr IFr LI HI

Punctuality 16 11 16 11 16 8 14 11
Service frequency 18 15 9 20 12 19 6 20
Span of service 10 18 18 9 11 17 12 15
Fare 2 1 1 1 1 1 1 8
Comfort 1 2 2 3 2 2 3 3
Information in mobile app 14 20 19 15 20 16 19 16
Ticketing system 20 19 20 17 19 20 20 13
Travel time 15 12 6 19 3 18 4 19
Cleanliness 7 4 10 2 7 5 8 2
Crowding on board 19 10 14 18 15 14 16 14
On-board information 13 16 15 12 17 9 17 9
Seating capacity 8 6 7 7 13 4 9 7
Ease of boarding 12 17 17 8 14 13 15 12
Transfer time 9 13 4 16 8 11 2 18
Number of transfers 17 8 12 10 10 15 7 17
Accessibility 4 9 5 13 6 10 10 10
Info at stop 11 14 11 14 18 6 18 4
Stop Illumination 3 3 3 4 5 3 5 1
Safety 6 5 8 6 4 12 11 6
Security 5 7 13 5 9 7 13 5

Spearman Rank 0,692 0,337 0,392 0,008

5.4 Service provider’s perception of PT

The following sub-section outlines the disparities in satisfaction between service con-
sumers and the provider, and further presents insights into the service providers’ percep-
tion of PT obtained from interviews. This answers research question 3.

5.4.1 Differences in satisfaction between PT users and service provider

The differences between the customer and service providers satisfaction are shown by sub-
tracting the service providers satisfaction mean from the customer satisfaction mean for
each attribute. When the differences between the service providers and the customers are
a positive value it means that the service providers are more satisfied than the customers.
On the opposite, when the value is a negative number it indicates that the customers are
more satisfied than the service providers. For only one attribute the service providers

33



and the customers are equally satisfied, which is the attribute punctuality. The results
are shown in table 12.

Table 12: Comparison between service provider satisfaction and user satisfaction

Attribute Satisfaction
Service Provider

Satisfaction
Users

Satisfaction
Gap

Punctuality 3,0 3,0 0
Service Frequency 3,2 3,3 -0,1
Span of service 4 3,4 0,6
Fare 3,2 1,8 1,4
Comfort 4 3,2 0,8
Information in mobile app 3,8 3,5 0,3
Ticketing system 3,4 3,6 -0,2
Travel time 3 3,3 -0,3
Cleanliness 4,2 3,4 0,8
Crowding on board 3,8 2,7 1,1
On-board information 3,2 3,5 -0,3
Seating capacity 4 3,2 0,8
Ease of boarding 3,4 3,7 -0,3
Transfer time 3 3,1 -0,1
Number of transfers 3 3,2 -0,2
Accessibility 3 3,7 -0,7
Information at stop 3,2 3,3 -0,1
Stop illumination 2,8 3,6 -0,8
Safety on board 3,6 3,5 0,1
Security 3 3,4 -0,4

The most tangible differences between customers’ and provider’s perception is the fare,
where the provider is over 75% more satisfied than the costumers. The second largest
gap is crowding on board, where the provider is over 40% more satisfied. Other attributes
where the provider is significantly more satisfied than the customers are comfort, clean-
liness and seating capacity. However, there also exist attributes that the provider is less
satisfied with in comparison to the travellers. The most tangible ones being stop illumina-
tion and accessibility. There are several attributes where the gap in satisfaction between
the provider and customers are relatively low. However, that does not necessarily mean
that both parts are satisfied with it. Punctuality, with no difference in perception be-
tween users and provider, has for example one of the lowest combined satisfaction scores
of the attributes.

34



5.4.2 Interviews with PT service providers

This part presents summaries of the interviews with Sharon Plotzki, Lovisa Borgström
and Lisa Nordberg, providing useful insights about PT service providers’ perception of
PT in Gothenburg city.

Interview with Borgström and Plotzki
Borgström and Plotzki expressed their thoughts on each attribute, but made it clear
that some of the factors that were brought up in the interview were not in their area
of expertise. Some attributes were discussed more deeply in the interview, such as fare,
punctuallity and service frequency. As for punctuality, Västtrafik acknowledges that PT
users consider it as as an important attribute. Consequently, it is an attribute which
is important for them to continuously improve as it may be a determining factor for
individuals opting for PT over private car usage. The ambition for Västtrafik is to
maintain the timetables for every route, although the punctuality can be affected by many
different factors, some of which Västtrafik can not regulate themselves. One management
strategy that was discussed to mitigate these issues and improving the punctuality is for
the transportation mode to take a different route with less road congestion. However,
this often causes the trip length and travel time to be longer.

Another attribute that was brought up in connection to punctuality was service frequency.
Borgström and Plotzki were united in their views on this attribute, explaining that in-
creasing the frequency would further contribute to highly congested roads, making the
punctuality more difficult to control. They also said that increasing the frequency would
be costly if the demand for more vehicles is too low. If it is hard to compromise between
the punctuality and service frequency, Västtrafik look at other solutions, such as larger
vehicles or changes in line routes. They have no goal in itself to increase the service
frequency, as long as all the customers waiting for a vehicle are able to board it. This
affects the way they view crowding on board, as Västtrafik from an economic and logistic
standpoint are not able to motivate minimising the crowding on board, if the expense
of other attributes as a result becomes too big. In many cases, an increased amount of
comfort on the vehicles would for example directly translate to less capacity. This would
interfere with Västtrafik’s purpose and goals, as fewer people would be able to use their
service.

As for fare, they made it clear that Västtrafik does not have the authority of deciding the
ticket price. Instead it is Västra Götalands regionen (VGR) that makes those decisions.
Therefore, the ticket price is not something that they actively work on. However, they
are aware that the price is an important factor for their customers’ satisfaction. In that
regard, Borgström and Plotzki specifically mentioned that customers might not be aware
that 50% of the PT costs are subsidized by VGR, and that knowing this information may

35



change their perception of the price. As Västtrafik knows the real cost of their service,
they do not view the fare as too high. Furthermore, Borgström and Plotzki told us about
results from previous studies where the ticket price had been reduced to zero, and that
the result from such actions mostly made cyclists and walkers change to PT and that the
amount of car users remained somewhat intact. Nevertheless, Västtrafik still put in effort
in affecting the experience for the customer regarding the ticket price for the better. It is
for example possible for companies to pay for their workers PT tickets. One other aspect
to the ticket price is the amount of time a ticket is valid. In that regard, Borgström
and Plotzki told us that Västtrafik give recommendations to VGR. Västtrafik explains
on their website that if there were to exist a cheaper ticket with reduced duration time,
more short trips would be made and would therefore depend on them being able to put
even more buses and trams on the roads (Västtrafik, n.d.-b). This would increase the
crowdedness and stress on the PT system even further. Furthermore, the new vehicles
would also be of less economic value for Västtrafik in comparison to the already existing
ones, as the demand for them are lower. According to Plotzki and Borgström, this makes
Västtrafik less interested and able to make such investments.

Interview with Nordberg
In alignment with Bersgström and Plotzki, Nordberg also stated that Västtrafik is not
in power of the fare. It was for example a political decision not to include a discount for
students at one way tickets and only having a discount on period tickets. Consequently,
she stated that they have not been working with the aim of lowering the ticket prices,
rather working on improving their service in other areas. Nordberg also discussed the
proposed idea of introducing a new cheaper ticket type with shorter duration. It was
of her opinion that having two ticket types with different time duration co-exist would
lead to difficulties in today’s system. Nordberg explained that Västtrafik has a rule that
says that if you enter a vehicle with a valid ticket, you can continue to travel in the
vehicle for as long as you want, even if the ticket’s time validation would run out. Having
one short and one long ticket type available for the travellers would interfere with the
simplicity of this rule and would maybe force Västtrafik to remove the rule and start
checking traveller’s tickets on their way out of the vehicles as well as on their way in.
According to Nordberg, if some tickets were to be made cheaper, for example the one
way ticket, it would result in Västtrafik being forced to raise the price on other tickets,
such as the period tickets. Västtrafik would also not want to make adjustments of the
ticket price that would go against their aim of benefiting frequent travellers as well as
people travelling longer distances rather than shorter ones. Nordberg believes that the
PT system is designed to serve as a car substitute rather than an option for walking or
cycling. This could change if the ticket types changed.

36



6 Discussion
In this section, results are discussed, policy implications are presented, and limitations
of the study are highlighted.

6.1 Discussion and policy implications of improvement attributes

Several valuable insights were drawn from the results of the study. It was interesting to
note that for the overall sample as well for the sub-sample of car access and no car access,
none of the basic factors fall under "Concentrate here". However, among the performance
factors, punctuality and fare are the two common sets of attributes that fall under "Con-
centrate here" of the management scheme for the overall sample and the sub-samples.
This shows that these attributes are of high importance to users but are associated with
the least satisfaction. In the current scenario for a 90-minute trip, the fare of PT usage
is 36 SEK, which is perceived as substantially high among consumers. Therefore, an im-
portant policy recommendation to transport planners and service providers is to lay an
added emphasis on lowering the fare and improving punctuality of service to encourage
its higher patronage. Among consumers with access to a car, in addition to fare and
punctuality; service frequency, travel time and number of transfer are other important
performance factors grouped under the management scheme "Concentrate here". Hence,
it is imperative to focus on improving these attributes to attract consumers with access
to a car to shift towards PT service usage in Gothenburg city. Among the excitement
factors, comfort is observed as the attribute with high importance and low satisfaction
among overall sample, indicating that improvement of comfort quality on-board may
further increase appeal of PT services among consumers.

While investigating variation in consumer perception for PT services based on sociode-
mographic characteristics, it was interesting to note that there is no significant difference
in the RIDIT ranking of importance of the PT attributes among the different groups.
This means that the different sociodemographic sub-groups have a similar perception on
the importance of the different attributes. However, regarding the RIDIT ranking of sat-
isfaction there is a significant difference between the sociodemographic sub-groups, with
exception to gender.

Fare was the attribute that had the worst performance rate between all the sociode-
mographic groups. As presented in table 11, all groups rank fare high, indicating low
satisfaction. This means that in order to increase the OCS, this attribute should be
improved. The only sociodemographic group that stood out in the ranking of fare was
people with an income higher than the median. This group ranked fare as number 8, in
contrast to people with income lower than the median who ranked it as number 1. This
result indicates that for people with higher income, the price of PT is not as important to

37



prioritise for them to be more satisfied. They place greater emphasis on factors such as
comfort, cleanliness and stop illumination, which could influence their perception of the
service more. Additionally, this group’s financial capacity might allow them to absorb
higher ticket price more easily, making it a less decisive factor in their OCS with the
service. A policy implication for a reduced ticket price will therefore have less impact on
the satisfaction of people with an income above the median.

As for punctuality the RIDIT ranking does not vary between the sub-groups. The excep-
tion is the PT user frequency, where frequent PT users rank the attribute higher and their
counterpart rank the attribute significantly lower. A possible explanation for this could
be that infrequent users may travel for a specific purpose, thus depending on the PT to
be punctual. Frequent PT users may be aware of regular small delays in the PT system
and can therefore take those into consideration when planning a trip, resulting in less
stressful situations and higher satisfaction. Improvement in punctuality performance of
PT services may attract more infrequent users to choose PT as a mode. Furthermore, the
result of the RIDIT analysis regarding service frequency shows that the perception varies
between the different sub-groups. The groups with a significant difference are age and
income. Young people and people with income below the median ranked the attribute
higher possibly because they are more likely to be dependent on PT. These groups, who
mostly consist of students, tend to use PT more often, and it would be more beneficial for
them to have a higher service frequency. Their counterparts use PT less and most likely
for a specific purpose, resulting in a lower demand for high service frequency. Increasing
the service frequency may attract younger people and people with an income below the
median to choose PT services for travel.

The RIDIT analysis for travel time varies substantially for each sub-group. Older people,
infrequent users and people with an income above the median are generally more satisfied
with the travel time, while their counterparts are not as satisfied. The possible explana-
tion for this could be that the groups that ranked the attribute higher, indicating lower
satisfaction, tend to use the PT more. This likely results in more negative experiences
such as delays and disruptions, which means that if service providers were to prioritise
travel time it would increase their OCS. A policy implication regarding travel time should
attract both young people and people with income below the median. Regarding number
of transfers, the rank varies substantially within the sub-groups, with exception for age.
The rank is lower for infrequent PT users and for people with income above the median,
while it is higher for their counterparts who are less satisfied with that attribute. As
mentioned above, the explanation for this could be that the groups using PT more often
have more negative experiences regarding number of transfers. A policy implication re-
garding number of transfers should attract infrequent travellers and people with income
above the median.

38



As seen in table 12 the gap of perceived satisfaction among different attributes varies
between service users and service providers. For some factors the service providers are
more satisfied than PT users, while for other factors the PT users are more satisfied.
However, for most of the attributes, the PT users and service providers have a similar
perception regarding the satisfaction of the attributes. One attribute where there is no
existing gap is punctuality, meaning that Västtrafik and the service users have aligned
perceptions. Plotzki and Borgström from Västtrafik also stated that punctuality is an
area that needs to be improved and that they are currently working towards achieving
this. The perception of service providers and users aligning indicates good conditions for
future possible policy implication, which would result in increased OCS. One gap where
the service providers have a lower level of satisfaction compared to the PT users is stop
illumination. This aligns well with the management scheme presented in figure 5, where
this attribute falls under "Possible overkill". The gap can be the reason for the attribute
being in this category. Some resources invested into this area can be reinvested into other
more important attributes, which would have a bigger influence on the OCS.

The two attributes with the largest gap are fare and crowding on board. One reason for
the gap regarding crowding on board could be that, as Plotzki and Borgström explained,
Västtrafik prioritise that all passenger waiting at a stop will access the vehicle and not
leave passengers behind because of too high levels of crowding. For them, this can be
done at the expense of users having to travel in crowded conditions. On the contrary,
PT users may value lower levels of crowding more to increase OCS. The largest gap is
regarding the perception of fare. For PT users the ticket price seems unreasonably high,
and is therefore a major source for dissatisfaction among all user groups. Västtrafik,
however, claims to have a limited impact over fare, as this is decided by the Västra
Götalandsregionen (VGR). Västtrafik’s total revenues together with subsidises from the
region decide the valid ticket price, in order for Västtrafik to be able to continue its
services. The reason for the service providers having a higher level of satisfaction may
be because they are not in control of the price, as well as them knowing all their exact
expenses making the price more reasonable for them. Another possible reason for the
large gap is the fact that Västtrafik, stated by Nordberg, have not been actively working
towards reducing the fare, and rather focusing on other important attributes. To reduce
the gap between the service providers and the PT users and increase the OCS, it is an
important policy implication for transport planners and policy makers to reduce the price.
This could further retain and attract new PT users.

6.2 Limitations of the study

A limitation of the study is the respondent group’s representation of the society in zone A.
As seen in table 4, many of the groups have different distributions. The amount of people
using PT as the main source of travelling mode is 21 percentage units more in this study.

39



This has affected the distribution of several other sociodemographic groups. One of them
is females, where in this study they were almost 15 percentage units higher than in the
data about Gothenburg. However, the data from VGR, 2022, shows that women are more
frequent users of the PT system compared to men, and since the data collection method
led to more answers being collected from PT users, naturally more women have answered
compared to men. This argument also applies to young people, students and people with
a lower income, since these groups also tend to use the PT in higher frequencies, as per
Västra Götalandsregionen, 2023. Because the data primarily comes from people using
PT as a main transportation mode, the study emphasises the perspective of frequent
PT users. Consequently, their viewpoints have a greater significance within the research
framework. This alignment proves to be beneficial to the report’s objectives, which
specially focuses on the consumer’s perception rather than those of the broader public.

Another limitation is the division of the revised IPA matrix. The matrix was divided
into the two-dimensional grid using the mean value of the attribute’s performance and
derived importance. The placement of the axes can be done in different ways, which
would likely result in some attributes being in different quadrants, especially since many
of the attributes are adjacent to the axes in the results. Using a clustering method may
have been a more suitable and accurate method of determining the placement of the axes
of the revised IPA matrix.

40



7 Conclusion
This study has identified strategies for improvement of public transport services in Gothen-
burg zone A by a thorough data collection from both service users and the service provider.
It was found that the priority areas of improvement in public transport services, based
on consumer importance and satisfaction, are punctuality, fare and number of transfers.
In addition to these attributes, service frequency and travel time are specific areas of
improvement for people with access to a car. Policy implications regarding these areas
can therefore be beneficial to encourage a shift from passenger car ownership towards
PT usage. The consumers’ satisfaction varies among the majority of the investigated
sociodemographic characteristics, where the largest difference was found between people
with higher and lower income. This report also shows the gaps between consumers’ and
the service provider’s perception of the PT services, a main gap being their disparate
views on the fare. The findings and insights of this study contributes to further improve-
ments in the service of the PT system in Gothenburg, working as a basis for the policy
and decision makers to use for their advantage. Although the results are case specific, the
findings from the present study are expected to be of interest to transport planners and
policymakers in other developed and developing countries, who are trying to promote PT
services in larger cities to reduce vehicular emission and congestion in urban areas.

41



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20delomr%c3%a5den__Kommun__Befolkning__Folkm%c3%a4ngd__Folkm%
c3%a4ngd%20hel%c3%a5r/?rxid=b5e6cd19-c99b-4f4d-8ad1-448d4176c6e9

Västtrafik. (n.d.-a). Hållplatskarta och zonkarta.
H%C3%A5llplatskarta%20och%20zonkarta

Västtrafik. (n.d.-b). Så sätts våra biljetter och priser.
https://www.vasttrafik.se/info/sa-satts-vara-biljetter-och-priser/

44

https://www.simplilearn.com/tutorials/statistics-tutorial/spearmans-rank-correlation?fbclid=IwAR0Hh6pnfosLl6gSbKuKO7LfR0wOa7bV4B7pmCUry-kRUjdAkqwwrUagMQE
https://www.simplilearn.com/tutorials/statistics-tutorial/spearmans-rank-correlation?fbclid=IwAR0Hh6pnfosLl6gSbKuKO7LfR0wOa7bV4B7pmCUry-kRUjdAkqwwrUagMQE
https://www.simplilearn.com/tutorials/statistics-tutorial/spearmans-rank-correlation?fbclid=IwAR0Hh6pnfosLl6gSbKuKO7LfR0wOa7bV4B7pmCUry-kRUjdAkqwwrUagMQE
https://www.simplilearn.com/tutorials/statistics-tutorial/spearmans-rank-correlation?fbclid=IwAR0Hh6pnfosLl6gSbKuKO7LfR0wOa7bV4B7pmCUry-kRUjdAkqwwrUagMQE
https://www.simplilearn.com/tutorials/statistics-tutorial/spearmans-rank-correlation?fbclid=IwAR0Hh6pnfosLl6gSbKuKO7LfR0wOa7bV4B7pmCUry-kRUjdAkqwwrUagMQE
https://www.eea.europa.eu/en/analysis/indicators/emissions-of-air-pollutants-from
https://www.eea.europa.eu/en/analysis/indicators/emissions-of-air-pollutants-from
https://doi.org/10.1007/s11116-021-10239-8
https://doi.org/10.1016/J.SCS.2023.104530
www.sfs.se
https://bransch.trafikverket.se/for-dig-i-branschen/miljo---for-dig-i-branschen/minskad-klimatpaverkan/transporternas-klimatpaverkan/
https://bransch.trafikverket.se/for-dig-i-branschen/miljo---for-dig-i-branschen/minskad-klimatpaverkan/transporternas-klimatpaverkan/
https://doi.org/10.59117/20.500.11822/43922
https://app.powerbi.com/view?r=eyJrIjoiOWM0MzA4ZDUtYTRjOC00Zjg1LThlYmMtNzFjNmE4YmU0OWFlIiwidCI6ImU2MGZlYTk4LWRjNDUtNGZhMC04Y2E0LTFkODUwMDY0ZTllMiIsImMiOjl9
https://app.powerbi.com/view?r=eyJrIjoiOWM0MzA4ZDUtYTRjOC00Zjg1LThlYmMtNzFjNmE4YmU0OWFlIiwidCI6ImU2MGZlYTk4LWRjNDUtNGZhMC04Y2E0LTFkODUwMDY0ZTllMiIsImMiOjl9
https://climate.mit.edu/explainers/public-transportation
https://www.ibm.com/products/spss-statistics
https://itdp.org/our-work/public-transport/
https://statistikdatabas.goteborg.se/pxweb/sv/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den__Kommun__Befolkning__Folkm%c3%a4ngd__Folkm%c3%a4ngd%20hel%c3%a5r/?rxid=b5e6cd19-c99b-4f4d-8ad1-448d4176c6e9
https://statistikdatabas.goteborg.se/pxweb/sv/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den__Kommun__Befolkning__Folkm%c3%a4ngd__Folkm%c3%a4ngd%20hel%c3%a5r/?rxid=b5e6cd19-c99b-4f4d-8ad1-448d4176c6e9
https://statistikdatabas.goteborg.se/pxweb/sv/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den__Kommun__Befolkning__Folkm%c3%a4ngd__Folkm%c3%a4ngd%20hel%c3%a5r/?rxid=b5e6cd19-c99b-4f4d-8ad1-448d4176c6e9
https://statistikdatabas.goteborg.se/pxweb/sv/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den/1.%20G%c3%b6teborg%20och%20dess%20delomr%c3%a5den__Kommun__Befolkning__Folkm%c3%a4ngd__Folkm%c3%a4ngd%20hel%c3%a5r/?rxid=b5e6cd19-c99b-4f4d-8ad1-448d4176c6e9
H%C3%A5llplatskarta%20och%20zonkarta
https://www.vasttrafik.se/info/sa-satts-vara-biljetter-och-priser/


Västtrafik. (n.d.-c). Västtrafik AB - det här är vi.
https://www.vasttrafik.se/om-vasttrafik/vasttrafik-ab/

Västtrafik. (n.d.-d). Västtrafik: kollektivtrafik i Västra Götaland.
https://www.vasttrafik.se/

Västtrafik. (n.d.-e). Zoner - Västra Götaland | Västtrafik.
https://www.vasttrafik.se/reseplanering/abc/

World Health Organization. (n.d.). Air quality, energy and health.
https://www.who.int/teams/environment-climate-change-and-health/air-
quality-energy-and-health/health-impacts

45

https://www.vasttrafik.se/om-vasttrafik/vasttrafik-ab/
https://www.vasttrafik.se/
https://www.vasttrafik.se/reseplanering/abc/
https://www.who.int/teams/environment-climate-change-and-health/air-quality-energy-and-health/health-impacts
https://www.who.int/teams/environment-climate-change-and-health/air-quality-energy-and-health/health-impacts


A English questionnaire
See next page.

46



Dear Respondents,
Chalmers University of Technology is conducting research towards identifying strategies for improvement of public transport services in 
Gothenburg, Sweden. To carry out this research, it is important to know your perceptions towards various attributes associated with such 
services. 
We shall be thankful to you for spending a little part of your precious time filling the questionnaire. 
The survey will not collect any information that will identify you and hence protects your confidentiality. All the information provided will 
be strictly used for scholarly purposes only.
The survey is aimed at travelers within zone A.

Part A: Trip Characteristics 
How frequently do you make trip (two-way) by any mode in a week?

Less than 1 time

1-2 times 

3-4 times

5-6 times

7 times or more

Predominantly used mode for travel:

Bus

Tram 

Car

Two-wheeler 

Bicycle/E-bike/E-scooter 

Other:

How frequently do you use your predominantly used public transport service (bus or tram) for making trips within the city (zone A), per 
week?

Less than 1 time

1-2 times
3-4 times

5-6 times

7 times or more

Out of bus and tram - what is your predominantly used service?

Bus

Tram

You should base your answers on this mode of transportation for upcoming questions. 

Work

Business

Education

Recreation

Others

What is your predominantly used ticket type?

One-time ticket

Day ticket

Period ticket

Trip purpose for the most recent trip using predominantly used service:

Turn page



Punctuality: Consistent and timely adherence to scheduled departure and 
arrival times.

Not important 
at all

1               2               3              4               5

Very 
important

Service frequency: Time interval of vehicle availability along a particular 
route.

In your opinion, how IMPORTANT are the following factors regarding your predominantly used 
public transport service?

Fare: Amount of money required to be paid for using the service

Operation hours: Time duration for which the service is operational during 
a day along a route/route segment.

Information on mobile app: Digital platform providing real-time and 
relevant data, updates, or details catering to trip maker’s needs, or inquiries 
through mobile application interface.

Ticketing system: Type of ticketing system i.e., on-board, off-board and 
online ticketing.

In-vehicle travel time: Total time spent inside a vehicle