Article citation information:
Bugdol, M., Ober, J., Sitinjak,
C. Model of attitudes towards free public transport. Scientific Journal of Silesian University of Technology. Series
Transport. 2026, 132, 73-91.
ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2026.132.4
Marek BUGDOL[1],
Józef OBER[2],
Charli SITINJAK[3]
MODEL OF ATTITUDES TOWARDS
FREE PUBLIC TRANSPORT
Summary. The aim of the study was to find
passengers' opinions on the changes that took place after the introduction of
free public transport, both in terms of daily transport choices and the
assessment of service quality, transport accessibility, and changes in the
urban environment. A diagnostic survey method was used employing a proprietary
questionnaire. A total of 1,109 adults participated in the study. Passenger
opinions formed the basis for developing a novel and original model of
attitudes towards free public transport using PROFIT analysis. The developed
model clearly shows that preferences regarding the form of public transport
financing are closely related to how residents perceive the objectives and
effects of its implementation. The most comprehensive and positively motivated
are supporters of completely free transport for residents, who recognize the
broad social benefits and environmental, economic, and functional effects.
Respondents in favor of payment or limited
availability are more critical, emphasizing political motives and negative
consequences such as system overload. Practical recommendations for transport
policy in Poland add to the originality of the research.
Keywords: public transport, free transport,
fare-free, urban environment, passenger’s opinions
1. INTRODUCTION
Free bus transport is not a new
solution [1]. It operates in Brazil, Poland, France, the United States, and
Estonia [2-3]. However, most such solutions are found in Poland and France [4].
Several hundred cities implement free public transport programs. An analysis of
the literature showed that research in this area is concerned with economic
aspects [5-14], environmental [4, 11, 15-19] and social [9, 11, 20-25].
This article analyzes the case for the introduction of free transport in the city of Racibórz and its surroundings. The following research questions were formulated:
1. How do residents perceive the
motives behind the introduction of free transport – do they consider them to be
pro-environmental, social, economic, or political measures – and how do they
influence support for different variants of this solution (e.g., universal or
limited free transport)?
2. What are the effects, according to
the respondents, of introducing free public transport?
The motives and effects/consequences
of introducing free public transport have already been the subject of research.
However, in this article, they serve as an introduction to the development of
an innovative model of attitudes towards free public transport using PROFIT
analysis and the presentation of practical recommendations for public transport
in Poland.
The research objective was adopted
because, although previous studies have examined the motivations and effects of
free public transport, there is still a lack of research that integrates
residents’ perceptions of these factors with their preferences regarding
different transportation financing. This gap justifies the need to develop a
more comprehensive explanatory model of attitudes toward free public transport.
The remainder of the article is
structured as follows: Section 2 discusses the motivations for implementing
free public transport, Section 3 outlines its perceived effects, Section 4
presents the materials and methods, Section 5 reports the results, Section 6
provides the discussion and future research directions, Section 7 addresses the
study limitations, and Section 8 concludes with practical recommendations.
2. MOTIVES FOR IMPLEMENTING FREE
PUBLIC TRANSPORT
Many European municipalities
recognize that the main motive behind the changes is to reduce car use and the
pollution and noise associated with cars, thus improving quality of life and urban environment [4, 26-27]. The health benefits are
associated with the emission of the exhaust gases and the environmental
benefits. By reducing the concentration of fine particulate matter, free
transport programs are expected to contribute to improving air quality and thus
reducing mortality and healthcare costs [15, 18]. Free transport is being
implemented for environmental reasons, to relieve car traffic after various
epidemics and breakdowns [28].
In addition to environmental
considerations, economic considerations are not less important. Free public
transport is intended to stimulate economic activity [13]. By abolishing travel
charges, cities are trying to encourage people, especially car drivers, to use
public transport instead of cars. When authors refer to environmental effects,
they usually provide data on passenger numbers [19]. Of
course, to achieve an environmental effect, it is necessary to encourage as
many drivers as possible to leave their cars at home and switch to more
economical and environmentally friendly means of public transport [29].
However, this is not an easy task.
Firstly, the increasing demand for
bus services can also have a negative impact on traffic flow due to stopping
and starting at bus stops [30].
Secondly, with the increase in
private car use, the popularity of online car booking, and the popularity of
city bikes, public enthusiasm for bus travel is low [31].
Third, there are grounds for
believing that the implementation of a zero fare will not significantly reduce
car traffic but will also cause a decline in bicycle and pedestrian traffic
[11].
Social motivations are also
important. The main motivation is to increase mobility and improve quality of
life [20]. As N. Fearneley states, the aim of such
programs is to create a more inclusive society and to provide disadvantaged
groups with better mobility and prosperity [9]. The free transport system is
designed to improve quality of life, especially for people with disabilities
who are excluded from the inaccessible bus system [25].
The main benefit is a reduction in
CO2 emissions [17]. Health benefits are associated with exhaust
emissions and environmental benefits [15, 18]. The next benefit is a reduction
in the number of people using cars [19]. The increase in passenger numbers can
be huge – up to 13 times [9] – or negligible. For
example, studies conducted in Tallinn showed that free transport represented
only 1.2% increase in passenger demand [10]. Some cities have reported lower
than expected increases in passenger numbers [32]. Regardless of how many
passengers arrive, some researchers express an interesting view [33]. They
argue that free public transport will always improve cost efficiency, measured
by operating costs per passenger. The rationale is an increase in seat
utilization rates [9]. Making public transport free during off-peak hours means
that some cities are trying to promote free transport to increase the overall
efficiency of their services [8, 20]. The intention is to increase the number
of people commuting to certain areas of the city that offer certain services.
Other benefits include eliminating
the costs associated with setting and collecting fares (eliminating fares can
eliminate these costs and free up staff to focus on service quality and
efficiency, which is important for retaining and attracting high-quality
passengers) and the absence of inconveniences associated with having to search
for change and remember confusing details of the public transport system [27].
The purpose of the study was to find
out passengers' opinions on the changes that have taken place since the
implementation of this solution, both in terms of daily transport choices and
the assessment of service quality, transport accessibility, and changes in the
urban environment.
The survey research was conducted in
accordance with the ethical principles of conducting research with human
participants based on the guidelines of the Helsinki Declaration. Written
informed consent was obtained from all participants involved in the study.
The study was conducted using a
standardized questionnaire designed to gather residents' opinions on the
introduction of free public transport. The questionnaires were collected electronically
between 16 January and 10 February 2025 using the Google Forms platform. Adults
who used public transport in Racibórz and the
surrounding area were eligible to participate, both those who were users before
the abolition of fares and those who only started using them after the
introduction of free travel.
A total of 1,109 adult users of free
public transport participated in the survey. Cases with data gaps greater than
30% were removed from the analysis, while the remaining incomplete responses
were supplemented using non-parametric hot-deck imputation, which involves
assigning missing values based on the responses of individuals with similar
characteristics.
To estimate the minimum sample size,
the formula for sample size for qualitative characteristics (for a finite
sample) was used [34]:
where:
p – the proportion of the population with the characteristic of interest,
E – the maximum permissible error in estimating the proportion p,
N – the size of the general population,
tα – the number of standard deviations, to be
read from the normal distribution table for a confidence level of 1 – α.
When calculating the minimum sample
size, data from the website ‘Polska w liczbach’ (Eng.
‘Poland in numbers’) regarding the population of the Racibórz
municipality, 49,360 people, was taken into account [35]. A 50% proportion was
assumed, and a 95% probability was adopted that the result obtained in the
study would not deviate from the actual value in the population by more than
5%. According to these estimates, the minimum sample size is 381 people, which
means that in this study the minimum sample size was significantly exceeded.
The choice of statistical methods
was justified by the structure of the empirical data collected, which included
qualitative and quantitative variables derived from survey data based mainly on
ordinal scales (Likert scales). For this reason, descriptive statistics were
used to characterize the sample and the response distributions, the
Shapiro–Wilk test to verify assumptions regarding the normality of the
distribution, the nonparametric Kruskal-Wallis test with post hoc analysis for
comparisons between multiple independent groups, Spearman’s rank correlation to
assess relationships between ordinal variables, and Pearson’s χ² test to analyze
associations between categorical variables. In turn, the PROFIT analysis was
used as a multidimensional method, allowing the simultaneous capture of the
structure of similarities between groups of respondents and the graphical
interpretation of the relationships between preferences and the motives and
effects of implementing free public transport. The first stage of the PROFIT
analysis for the set of objects A = {A1, …, An}
and dissimilarities δij between Ai and Aj
(i, j = 1, …, n)
consisted in creating, using multidimensional scaling methods, a perception map
of objects in r-dimensional space (r is usually equal to 2 or 3)
in order to:
where:
The values were determined so as to
minimize the value of the STRESS (Standardized Residual Sum of Squares) fit
function. This was due to the fact that the quality of the fit of the
reconstructed data to the input data is measured using the above-mentioned
STRESS function, whereby the lower its value, the better the fit of the
reconstructed distance matrix to the observed distance matrix. The STRESS
function took the form:
where:
As a result of multidimensional
scaling, in the case of a two-dimensional perception map, each object was
described by two coordinates.
The second stage of the PROFIT
analysis consisted of using information about the preferences of the analyzed objects from the point of view of the features
adopted in the study. After creating a table of average ratings for individual
objects and features, regression models (multiple regression models) were
developed, in which the dependent variables were the ratings of objects in
terms of individual features and the explanatory variables were the coordinates
of objects on the perception map. Linear regression analysis made it possible
to estimate how the studied objects are distributed in terms of the intensity of
each of the characteristics describing them. The number of such estimates
carried out in the second stage was equal to the number of characteristics of
the studied objects.
For the multidimensional scaling
matrix of point coordinates X = [xia]
in r-dimensional space, normalized so that XT X = D (D –
diagonal matrix), and preference ratings pk = (pk1, …, pkn)T of objects with respect to the k-th feature, the standardized regression coefficients (beta)
for individual dimensions:
tk = (XT X)–1 XT pk (4)
determined the coordinates of the
vector of a given feature on the perceptual map.
PROFIT analysis functions allow for
a non-linear relationship between the explained variable and the explanatory
variables. In this case, the variable vector was the vector corresponding to
the smallest non-zero eigenvalue of the matrix XT Ak
X, where:
Ak =
The projection of points
representing individual objects onto feature vectors:
Hk = Xtk = X(XT X)–1 XT
pk (5)
allowed the position of objects to
be determined based on the intensity of these features in the given objects and
thus to establish a preference order.
Statistical analysis of the
collected data was performed using the Statistica v.13.3 PL statistical package
from Tibco Software Inc. A 5% risk of inference error was assumed, and p <
0.05 was considered statistically significant.
5.1. Motives for the introduction of free
public transport
The most frequently cited motive was
to increase the attractiveness of the city – 43.02% of respondents strongly
agreed with this justification, and another 22.21% chose the answer "I
rather agree". Similarly strong support was given to responses concerning
the promotion of innovation (38.58% "strongly agree") and the
improvement of public transport flow (39.34%). A high percentage of positive
responses also concerned environmental motives – 35.53% of respondents strongly
agreed with concern for the environment, and another 24.37% chose the answer
“somewhat agree”.
Social motives, such as concern for
the' health of residents (33.12% "strongly agree") and reducing
social inequalities (31.09%), received less, but still noticeable, support. In
the case of financial arguments, such as concern for residents' household
budgets, 32.87% of respondents expressed a positive opinion ("strongly
agree").
The political motive was the most
controversial. Although 32.74% of respondents strongly agreed with the
statement that the decision was political in nature, nearly one in four
expressed the opposite view – 23.73% strongly disagreed. A significant percentage
of "difficult to say" responses (19.04%) may indicate an ambiguous
perception of the intentions of decision-makers. A detailed breakdown of the
data is provided in Tab. 1.
Tab. 1
Reasons for introducing free public transport in the opinion of
respondents
|
Strongly agree |
Somewhat agree |
Difficult to say |
Somewhat disagree |
Strongly disagree |
||||||
|
n |
% |
n |
% |
n |
% |
n |
% |
n |
% |
|
|
Political
(decision influenced by political/electoral considerations) |
258 |
32.74 |
100 |
12.69 |
150 |
19.04 |
93 |
11.80 |
187 |
23.73 |
|
Care for the
environment (e.g., reduction of harmful emissions) |
280 |
35.53 |
192 |
24.37 |
108 |
13.71 |
95 |
12.06 |
113 |
14.34 |
|
Concern for
residents' financial resources |
259 |
32.87 |
131 |
16.62 |
126 |
15.99% |
137 |
17.39 |
135 |
17.13 |
|
Concern for residents'
health |
261 |
33.12 |
130 |
16.50 |
137 |
17.39 |
137 |
17.39 |
123 |
15.61 |
|
Reduced Noise in
the city |
245 |
31.09% |
131 |
16.62 |
156 |
19.80 |
119 |
15.10 |
137 |
17.39 |
|
Reducing social inequalities |
245 |
31.09 |
115 |
14.59 |
155 |
19.67 |
138 |
17.51 |
135 |
17.13 |
|
Reduction of
costs related to road infrastructure maintenance |
149 |
18.91% |
108 |
13.71 |
270 |
34.26 |
128 |
16.24 |
133 |
16.88 |
|
Increasing the
attractiveness of the city |
339 |
43.02 |
175 |
22.21 |
82 |
10.41 |
80 |
10.15 |
112 |
14.21 |
|
Promoting innovation |
304 |
38.58% |
171 |
21.70% |
121 |
15.36% |
83 |
10.53% |
109 |
13.83 |
|
Improvement of
public transport flow |
310 |
39.34 |
147 |
18.65 |
113 |
14.34 |
85 |
10.79% |
133 |
16.88 |
5.2. Effects of introducing free public
transport
Among the positive effects, the
highest level of agreement was recorded in the statement that free transport
contributed to improving the quality of the services provided; up to 58.76% of
respondents strongly agreed with this opinion, and another 16.62% somewhat
agreed. A similarly high level of agreement was recorded regarding the increase
in the number of passengers (53.05% of respondents “strongly agreed”) and
savings for residents (54.06%). Equally often, increasing the attractiveness of
the city (51.52%) and greater use of public transport for everyday purposes –
both for work (45.43%) and shopping (42.89%) – were indicated as positive
effects.
A significant percentage of the
respondents also pointed to positive changes in accessibility to transport
services – 43.53% strongly agreed with the statement that transport had become
more accessible. In addition, 37.18% of respondents believed that the
introduction of free transport contributed to a reduction in exhaust emissions,
and 36.93% agreed that it helped to reduce social inequalities.
Regarding some of the effects, the
opinions of the respondents were more scattered. This applies, among other
things, to the reduction in traffic from other vehicles – only 21.83% of
respondents strongly agreed with this, while as many as 29.95% answered
“difficult to say”. There was also a high degree of uncertainty regarding the
assessment of urban noise reduction (23.60% answered "difficult to
say") and significant costs for the city budget (31.85%).
In the case of effects such as
overloading of the transport system, irresponsible use of transport, or a
decline in the popularity of alternative forms of transport, most responses
denied these phenomena or expressed uncertainty.
The highest level of disagreement
was expressed on the potentially negative effect of a decline in the popularity
of alternative forms of transport – 44.29% of respondents disagreed with this
statement, and only 17.89% expressed any level of agreement. However, there was
a high level of uncertainty on this issue – as many as 37.82% of respondents
answered, “difficult to say”. Similarly, irresponsible use of transport was
rather rejected because of free public transport – 35.28% of respondents
strongly disagreed with this, and 28.43% had no opinion. A
detailed breakdown of the data is provided in Tab. 2.
5.3. Model of attitudes towards free public transport
According to the assumptions and objectives of the study, the PROFIT
model was developed to identify the characteristics most important for the
general attitude of the respondents towards free transport, and thus to
determine which factors (perceived motives for implementing free transport,
assessments of its positive and negative effects) have the greatest impact on
the general attitude towards free public transport.
Tab. 2
Respondents'
assessment of the effects of free public transport
|
Strongly agree |
Somewhat agree |
Difficult to say |
Somewhat disagree |
Strongly disagree |
||||||
|
n |
% |
n |
% |
n |
% |
n |
% |
n |
% |
|
|
Improvement in the quality of services
provided (e.g. drivers do not waste time selling tickets) |
463 |
58.76 |
131 |
16.62 |
51 |
6.47 |
46 |
5.84 |
97 |
12.31 |
|
Reduced traffic from other vehicles
(e.g. cars, motorcycles) |
172 |
21.83 |
140 |
17.77 |
236 |
29.95% |
119 |
15.10 |
121 |
15.36 |
|
More people use public transport to get
to work |
358 |
45.43 |
168 |
21.32 |
122 |
15.48 |
59 |
7.49 |
81 |
10.28 |
|
More people use public transport to go
shopping |
338 |
42.89 |
196 |
24.87 |
102 |
12.94% |
61 |
7.74 |
91 |
11.55% |
|
Reduction in exhaust emissions |
293 |
37.18% |
176 |
22.34% |
160 |
20.30 |
59 |
7.49 |
100 |
12.69 |
|
Reduction of urban noise |
261 |
33.12% |
146 |
18.53 |
186 |
23.60 |
95 |
12.06 |
100 |
12.69 |
|
Greater accessibility to transport |
343 |
43.53 |
153 |
19.42 |
114 |
14.47 |
65 |
8.25% |
113 |
14.34 |
|
Reducing social inequalities |
291 |
36.93% |
127 |
16.12 |
178 |
22.59 |
93 |
11.80 |
99 |
12.56 |
|
Savings for residents |
426 |
54.06% |
148 |
18.78 |
74 |
9.39 |
48 |
6.09 |
92 |
11.68 |
|
Increasing the attractiveness of the
city |
406 |
51.52 |
156 |
19.80 |
90 |
11.42 |
52 |
6.60 |
84 |
10.66 |
|
Increase in passenger numbers |
418 |
53.05 |
167 |
21.19 |
79 |
10.03 |
50 |
6.35 |
74 |
9.39 |
|
Significant costs for the city budget |
154 |
19.54 |
145 |
18.40 |
251 |
31.85% |
113 |
14.34 |
125 |
15.86 |
|
Overload of the transport system |
81 |
10.28 |
83 |
10.53 |
261 |
33.12% |
168 |
21.32% |
195 |
24.75 |
|
Irresponsible use of transport |
81 |
10.28 |
56 |
7.11 |
224 |
28.43 |
149 |
18.91 |
278 |
35.28 |
|
Decline in popularity of alternative
forms of transport |
77 |
9.77 |
64 |
8.12% |
298 |
37.82% |
140 |
17.77 |
209 |
26.52 |
The analysis distinguished four groups of respondents (objects),
depending on their preferred form of free transport: free transport for all
city residents (K1), for all interested parties (K2), for selected groups (K3)
and paid transport (K4). The variables (features) in the model under study were
the perceived motives for implementing free transport, such as: political (M1),
concern for the environment (M2), concern for residents' financial resources
(M3),concern for residents' health (M4), reduction of noise in the city (M5),
reduction of social inequalities (M6), reduction of road infrastructure
maintenance costs (M7), increasing the attractiveness of the city (M8),
promoting innovation (M9) and improving the fluidity of public transport (M10)
– as well as the positive and negative effects of this transport, such as:
improving the quality of services provided (P1), reducing traffic from other
vehicles (P2), more people travelling to work by public transport (P3), more
people using public transport to go shopping (P4),reduction of exhaust
emissions (P5), reduction of urban noise (P6), significant costs for the city
budget (N1), overloading of the transport system (N2), irresponsible use of
transport (N3) and a decline in the popularity of alternative forms of
transport (N4).
The model was developed based on the average degree of perception of
individual motives by respondents and the evaluation of the effects mentioned
above, expressed on a scale of 1–5. Detailed results of these data in groups
distinguished by their preferred form of free transport are presented in Tab.
3.
Tab. 3
Average
ratings of individual motives and positive and negative effects of implementing
free transport in groups distinguished by support for the form of free public
transport
|
Free for all city residents (K1) |
Free
for all interested parties (K2) |
Free for selected groups (K3) |
Communication should be paid for
(K4) |
|
|
Political (M1) |
3.17 |
3.36 |
3.08 |
3.66 |
|
Concern for the environment (M2) |
3.50 |
2.94 |
3.94 |
2.61 |
|
Care for residents' financial resources
(M3) |
3.25 |
2.78 |
3.70 |
2.34 |
|
Care for residents' health (M4) |
3.35 |
2.74 |
3.70 |
2.29 |
|
Reduction of noise in the city (M5) |
3.32 |
2.59 |
3.63 |
2.30 |
|
Reducing social inequalities (M6) |
3.21 |
2.59 |
3.66 |
2.32 |
|
Reducing road infrastructure maintenance
costs (M7) |
2.98 |
2.53 |
3.34 |
2.21 |
|
Increasing the attractiveness of the
city (M8) |
3.63 |
3.21 |
4.09 |
2.68 |
|
Promoting innovation (M9) |
3.53 |
3.00 |
4.03 |
2.70 |
|
Improving the flow of public transport
(M10) |
3.44 |
2.94 |
3.97 |
2.52 |
|
Improving the quality of services
provided (P1) |
4.09 |
3.30 |
4.39 |
2.91 |
|
Reduced traffic from other vehicles (P2) |
3.17 |
2.51 |
3.52 |
2.04 |
|
More people travel to work by public
transport (P3) |
3.91 |
3.19 |
4.18 |
2.55 |
|
More people using public transport to go
shopping (P4) |
3.89 |
3.09 |
4.13 |
2.54 |
|
Reduction in exhaust emissions (P5) |
3.73 |
2.99 |
3.97 |
2.27 |
|
Urban
noise reduction (P6) |
3.57 |
2.71 |
3.83 |
2.13 |
|
Significant costs for the city budget
(N1) |
3.13 |
3.42 |
2.95 |
3.43 |
|
Overload of the transport system (N2) |
2.62 |
2.94 |
2.47 |
2.71 |
|
Irresponsible use of transport (N3) |
2.42 |
2.90 |
2.14 |
2.68 |
|
Decline in popularity of alternative
forms of transport (N4) |
2.60 |
2.48 |
2.56 |
2.61 |
During the construction of this model, multidimensional scaling was
performed to develop a graphical presentation of the similarity (or
dissimilarity) structure between the analyzed objects
in relation to a selected set of variables (features). The uniform nature of
the analyzed features (5-point Likert scale) as
variables eliminated the need for their standardization. The classic Euclidean
distance was used for multidimensional scaling, and as a result, the 10
features that describe the four objects were reduced to two dimensions. The
STRESS coefficient for multidimensional scaling considering all features was
0.00, which indicates the high reliability of the results of the
multidimensional scaling procedure.
In the next step, the fits of individual objects were verified – a
regression analysis was performed, in which the explained variable was the
degree of perception of individual motives for implementing free transport,
while the explanatory variables were the values of two dimensions for each
unit, obtained because of multidimensional scaling: Dim. 1 and Dim. 2. The
criterion for considering a given tool as a key was a fit of R2
≥ 0.70. High values of the determination coefficients (from 0.87 to 1.00)
indicate that the adopted set of characteristics well reflects the structure of
the attitudes of the respondents. The exception was the effect in the form of a
decrease in the popularity of alternative forms of transport (N4) (R2
= 0.42), which was eliminated from the model in development. A detailed
breakdown of the data is provided in Tab. 4.
Tab. 4
Results of regression analysis between individual motives and positive
and negative effects of implementing free transport, and the dimensions of the
surveyed units obtained as a result of regression analysis (applies to groups
distinguished on the basis of their support for free public transport)
|
Free expression |
Dim. 1 |
Dim. 2 |
R2 |
||||
|
b0 |
p |
b |
p |
b |
p |
||
|
Political (M1) |
3.317 |
p
< 0.05 |
0.228 |
p
= 0.198 |
0.142 |
p
= 0.514 |
0.91 |
|
Concern for the
environment (M2) |
3.248 |
p
< 0.05 |
–0.549 |
p
= 0.179 |
0.010 |
p
= 0.98 |
0.92 |
|
Care for residents'
financial resources (M3) |
3.017 |
p
< 0.05 |
–0.535 |
p
= 0.216 |
–0.053 |
p
= 0.912 |
0.89 |
|
Care for residents'
health (M4) |
3.019 |
p
< 0.05 |
–0.584 |
p
= 0.164 |
–0.109 |
p
= 0.786 |
0.94 |
|
Reduction of noise in
the city (M5) |
2.962 |
p
< 0.05 |
–0.589 |
p
= 0.11 |
–0.014 |
p
= 0.956 |
0.97 |
|
Reducing social inequalities
(M6) |
2.944 |
p
< 0.05 |
–0.562 |
p
= 0.162 |
0.057 |
p
= 0.878 |
0.94 |
|
Reducing road
infrastructure maintenance costs (M7) |
2.767 |
p
< 0.05 |
–0.456 |
p
= 0.191 |
–0.020 |
p
= 0.956 |
0.91 |
|
Increasing the
attractiveness of the city (M8) |
3.403 |
p
< 0.05 |
–0.541 |
p
= 0.235 |
–0.111 |
p
= 0.837 |
0.87 |
|
Promoting innovation (M9) |
3.314 |
p
< 0.05 |
–0.542 |
p
= 0.197 |
0.060 |
p
= 0.893 |
0.91 |
|
Improving the flow of
public transport (M10) |
3.219 |
p
< 0.05 |
–0.572 |
p
= 0.22 |
–0.006 |
p
= 0.991 |
0.89 |
|
Improving the quality
of services provided (P1) |
3.673 |
p
< 0.05 |
–0.650 |
p
= 0.108 |
–0.087 |
p
= 0.766 |
0.97 |
|
Reduced traffic from
other vehicles (P2) |
2.811 |
p
< 0.05 |
–0.622 |
p
= 0.154 |
–0.118 |
p
= 0.768 |
0.94 |
|
More people travel to
work by public transport (P3) |
3.459 |
p
< 0.05 |
–0.682 |
p
= 0.143 |
–0.254 |
p
= 0.568 |
0.95 |
|
More people using
public transport to go shopping (P4) |
3.411 |
p
< 0.05 |
–0.688 |
p
= 0.118 |
–0.216 |
p
= 0.562 |
0.97 |
|
Reduction in exhaust
emissions (P5) |
3.239 |
p
< 0.05 |
–0.709 |
p
= 0.143 |
–0.324 |
p
= 0.504 |
0.95 |
|
Urban noise reduction
(P6) |
3.058 |
p
< 0.05 |
–0.738 |
p
= 0.115 |
–0.224 |
p
= 0.563 |
0.97 |
|
Significant costs for
the city budget (N1) |
3.233 |
p
< 0.01 |
0.217 |
p
= 0.103 |
–0.085 |
p
= 0.445 |
0.97 |
|
Overload of the
transport system (N2) |
2.686 |
p
< 0.01 |
0.154 |
p
< 0.07 |
–0.230 |
p
< 0.096 |
0.99 |
|
Irresponsible use of
transport (N3) |
2.534 |
p
< 0.01 |
0.281 |
p
< 0.05 |
–0.282 |
p
< 0.05 |
1.00 |
|
Decline in popularity
of alternative forms of transport (N4) |
2.559 |
p
< 0.01 |
–0.014 |
p
= 0.807 |
0.070 |
p
= 0.571 |
0.42 |
The multidimensional scaling presented in the PROFIT below (Fig. 1)
indicates that people in favor of free transport for
all city residents (K1) are located close to the group of vectors corresponding
to motives such as concern for residents’ health (M4), concern for the
environment (M2), reducing social inequalities (M6), reducing infrastructure
costs (M7), reducing noise (M5), promoting innovation (M9), improving the
fluidity of public transport (M10), increasing the attractiveness of the city
(M8), and concern for residents' financial resources (M3). This group is also
close to the vectors representing the positive effects of implementing free
public transport, such as improving service quality (P1), increasing passenger
numbers (P2), savings for residents (P3), greater transport accessibility (P4),
more people traveling to work (P5) and more people using transport for shopping
(P6). The proximity of these vectors indicates that respondents in this group
perceive free transport as a comprehensively beneficial measure – pro-social,
pro-environmental, and pro-development. Their attitude is more positively
aligned with the full spectrum of implementation objectives.
Supporters of free access for selected groups (K3) are also relatively
close to the aforementioned motivations and positive effects, suggesting
compatibility with many social and environmental aspects. Compared to group
(K1), however, their approach may be characterized by greater caution or
conditionality – they recognize the benefits but prefer a more selective model
of accessibility.
Respondents who are in favor of maintaining
fees (K4) are clearly distant from social and environmental motivations. Their
position is close to the "M1 – Political" vector, which means that
the main motive they perceive is the political interest behind the
implementation. This group's proximity to vectors corresponding to negative
effects – such as overloading of the transport system (N1), irresponsible use
of transport (N2) and a decline in the popularity of alternative means of
transport (N3) – demonstrates their critical attitude towards the effects of
introducing free transport.
The group that supports free transport for all interested parties (K2)
is closer to the political motivation (M1) and indications of negative effects
(N1–N3). This may suggest that people in this group see both the benefits and
the possible risks associated with full accessibility – they approach the
subject more cautiously and realistically, considering various aspects of the
system's functioning.
Fig. 1. Biplot considering the results of
multidimensional scaling for individual objects (groups distinguished based on
their support for free public transport) based on the assessment of
individual motives and the positive and negative effects of implementing free
transport
Explanation of abbreviations: K1 – Free for all city residents, K2 –
Free for all interested parties, K3 – Free for selected groups, K4 – Transport
should be paid for, M1 – Political, M2 – Concern for the environment, M3 –
Concern for residents' financial resources,
M4 – Concern for residents' health, M5 – Reduction of noise in the city, M6 –
Reduction of social inequalities, M7 – Reduction of road infrastructure
maintenance costs, M8 – Increasing the attractiveness of the city, M9 –
Promoting innovation, M10 – Improving the flow of public transport, P1 –
Improving the quality of services provided, P2 – Reduced traffic of other
vehicles, P3 – More people travelling to work by public transport, P4 – More
people using public transport to go shopping, P5 – Reduction of exhaust
emissions, P6 – Reduction of urban noise, N1 – Significant costs for the city
budget, N2 – Overloading of the transport system, N3 – Irresponsible use of
transport
6. DISCUSSION
AND NEW DIRECTIONS FOR RESEARCH
The most frequently mentioned motive was to increase the attractiveness
of the city. The responses to the promotion of innovation and the improvement
of public transport flow received strong support. A high percentage of positive
responses also involved environmental motives. Environmental motivations have
already been the subject of research by other authors [15, 26], but several
facts should not be overlooked. Firstly, car-restricted or car-free zones can
be introduced out of concern for the environment [36-37].
Second, when there is awareness of existing risks, analyses are carried
out to improve the quality of bus services [26]. Some cities even attempt to
estimate health effects [15].
Fourth, the example of some cities has shown that despite efforts to
achieve environmentally sustainable mobility, it remains an unattainable dream
[16]. Further research should include the number of passengers who have
abandoned private cars, as well as those who have switched to public transport
but abandoned bicycle travel. Such detailed data are available in other
publications [19, 20].
In the case of the city studied, no economic, environmental, or health
analyses were carried out, and free transport was introduced just before the
local elections, which proves why the political motive aroused the most
controversy. Political motivation is rarely recognized [14, 36, 38] and
therefore requires further research, especially on political bribery of the
electorate.
The problem is the lack of data on the entire life cycle of the product
and the service provided. For example, buses are very often assembled by
domestic manufacturers, while many components come from Germany, China, and
other countries. This line of research is also supported by the opinions of the
respondents themselves, who did not form clear opinions on the reduction of
vehicle traffic and noise in the city.
Both our research and the results of the systematic review of the
literature indicate the need for further research on health outcomes [39].
Regarding the effects of introducing free transport, it should be noted
that the highest level of agreement was recorded in the statement that free
transport contributed to improving the quality of services provided. A
similarly high level of agreement was recorded regarding the increase in the
number of passengers and savings for residents. In this case, however, quality
is understood in a normative sense as the level of satisfaction of passengers'
needs and expectations. Previous studies show that the improvement in the
quality of services provided depends on infrastructure factors (stops,
barriers, bus mobility, the possibility of using other means of transport)
[40-44] and behavioral factors (driver behavior, interactions, passenger behavior)
[45-47], but it should also be remembered that this form of transport can lead
to acts of vandalism [27]. Interviews with drivers confirmed that this is also
the case in the city in question. Therefore, the issue of service quality in
the context of changes in passenger behavior should
also be the subject of further research.
A significant percentage of the respondents also indicated positive
changes in the accessibility of transportation services. Perhaps one of the
most important effects is that some people use this form of transport more
often. Research by other authors indicates that the introduction of free
transport can increase the number of passengers from low-income households and
young and old people [23]. Therefore, it is important to take into account the
profitability of different passenger groups in further research. Therefore, the
proposal to first identify the population group that should be supported [11]
is very relevant. It should also be noted that this type of research should
take into account the city's income. In some cities, the income resulting from
an increase in the number of residents is significantly higher than the lost
income from travel fees [12]. However, a large number of factors influence this
situation, including the city's economic system, the importance of public
transport, ongoing economic development, etc.
Another noted problem is the need to create a benchmarking database for
all organizers and operators of free public transport, to begin the process of
developing environmental, health, and economic indicators regarding the various
effects of public transport. Previous research shows that formal and informal
knowledge exchange networks can be very helpful in adopting the same solutions
in other cities that, due to various crises, need to quickly introduce free
forms of transport [48].
Our multidimensional scale presented in the PROFIT chart above (Fig. 1)
proves that the assessment of economic, environmental, and social motives and
effects cannot fail to take into account the moral and ethical values of the
passengers. These values are of great importance for pro-environmental behavior [49]. This important area that determines
passenger behavior requires further research.
The results of our research also confirm previous findings that show
that increasing the share of public transport travel is a long-term activity
that requires continuous improvement of the offer [50].
Both a systematic review of the literature and survey research are not
the best ways to examine the motives and benefits of any issue. Diagnostic
research allows us to learn – which is a feature of this type of research –
only the opinions of respondents and their declarations, and not their actual behavior [51]. In the future, the authors plan to expand
their research using cost-benefit analysis (CBA). CBA allows for the
identification and assessment of net benefits associated with alternative
solutions dedicated to achieving specific goals [52]. This method enables
comparative analyses to be performed (e.g., of the economic and social costs of
using bicycle and bus transport) [53].
8. CONCLUSIONS AND PRACTICAL
RECOMMENDATIONS
8.1. Conclusions
These results suggest that residents most often attributed the decision
to introduce free transport to image-related, pro-environmental and city
improvement goals. At the same time, some respondents also saw the potential
political calculations behind the decision.
The results of the study indicate that the respondents clearly
recognized the positive effects of introducing free public transport, such as
improved service quality, increased passenger numbers, savings for residents,
and increased attractiveness of the city. At the same time, more controversial
or difficult to assess aspects, such as the impact on car traffic or the
consequences for the city's budget, clearly provoked greater hesitation and
diversity of opinion. Potential negative effects, such as system overload or a
decline in interest in other forms of transport, were rejected by most of the
respondents or remain unassessed. The PROFIT model clearly shows that
preferences for the form of public transport financing are closely related to
how residents perceive the objectives and effects of its implementation. The
most comprehensive and positively motivated are supporters of full free travel
for residents (K1), who recognize both the broad social benefits and the
environmental, economic, and functional effects. Respondents in favor of payment (K4) or limited availability (K2) are more
critical, highlighting political motives and negative consequences such as
system overload. Supporters of selective free travel (K3) take an intermediate
position, remaining cautious while recognizing some of the positive aspects of
free transport.
8.2. Practical recommendations
Based on the study, several practical recommendations can be formulated
in the context of transport policy:
·
Maintaining
and developing free transport: The positive reception of free public transport
and its impact on changing transport behavior
(reducing car use, increasing the number of passengers) confirm the validity of
continuing to maintain it, especially among new users.
·
Benefit-orientated
public communication: To strengthen support, it is worth emphasizing the social
and environmental benefits and the quality of services in communications, as
these have a greater impact on residents' attitudes than political or fiscal factors.
·
Adapting
solutions to different social groups: Due to differences in assessments between
age and occupational groups, transport policy should be flexible and take their
needs into account (e.g., better planning of services for younger passengers or
the self-employed).
·
Monitoring
system congestion: Although not widely recognized, some respondents identify
congestion as a problem – it is worth investing in infrastructure and
considering temporary solutions to support behavioral
change (e.g., tickets encouraging drivers to give up their cars).
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Received 19.01.2026; accepted in revised form 17.05.2026
Scientific Journal of Silesian University of
Technology. Series Transport is licensed under a Creative Commons Attribution
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[1] Quality Management Department,
Faculty of Management and Social Communication, Jagiellonian University, Łojasiewicza 4 Street, 30-348 Cracow, Poland. Email:
marek.bugdol@uj.edu.pl. ORCID: https://orcid.org/0000-0001-9993-7765
[2] Department of Applied Social
Sciences, Faculty of Organization and Management, The Silesian University of
Technology, Roosevelt 26-28 Street, 41-800 Zabrze, Poland. Email (corresponding
author): jozef.ober@polsl.pl. ORCID:
https://orcid.org/0000-0001-6290-381X
[3] Faculty Psychology, Universitas Esa
Unggul, West Jakarta City, Special Capital Region of
Jakarta 11510, Indonesia. Email: charli.sitinjak@esaunggul.ac.id. ORCID: https://orcid.org/0000-0002-2247-6777