Determinants of Public Transport Choice in Łódź: Reasons for Use and Incentives for Non-Users

Abstract

Public transport is a critical instrument for mitigating traffic congestion, reducing environmental pollution, and promoting social inclusion in urban areas. This study presents the results of a quantitative survey conducted among 406 residents of Łódź, Poland, aimed at identifying the determinants of public transport use and the factors influencing modal choices. The findings indicate that 89% of respondents had used public transport within the past three years, with over half reporting the use of both buses and trams. However, public transport is predominantly chosen out of necessity rather than preference, driven by limited access to private vehicles, absence of a driver’s license, or the high costs of car ownership. Environmental considerations and service quality factors play a comparatively minor role. User satisfaction with public transport services in Łódź is moderate, and current users express limited intention to increase their usage or actively recommend the system, suggesting constrained potential for demand growth. In contrast, non-users declare a willingness to shift to public transport if travel costs are reduced and service quality is improved. Measures aimed at restricting private car use demonstrate limited motivational impact, whereas enhancing the reliability, accessibility, and affordability of public transport emerges as the most effective strategy. Methodologically, the study contributes by combining bibliometric mapping with quantitative survey analysis, providing a replicable framework for assessing urban mobility determinants in other cities with similar socio-economic and transport contexts.

1. Introduction

Promoting sustainable urban mobility, including the use of public mass transit, is a key strategy for addressing urban environmental and health challenges. In particular, traffic congestion, air and noise pollution, and the resulting health problems of urban residents underscore the need to transition urban transport systems toward sustainability. Public transport (PT) is widely recognized as an effective solution for reducing road traffic volumes, limiting transport-related emissions, and supporting socially sustainable development [1,2].

The provision of appropriate and well-adapted transport services plays an important role in ensuring a high quality of life for residents and in supporting their health [3,4,5]. Public transport enables access to essential activities, regardless of gender, age, or other socio-economic factors [6]. At the same time, research indicates that people who use public transport walk more, and that good accessibility to PT further increases interest in walking [7]. Consequently, the development of public transport services in cities can support residents in achieving recommended levels of daily physical activity. This effect is potentially beneficial for public health.

The attractiveness and perceived accessibility of urban public transport systems result from the interplay of interrelated environmental, economic, and social factors that shape residents’ transport decisions. Research demonstrates that the choice of public transport is determined by service quality, including reliability, service frequency, travel comfort and safety, as well as network coverage and connectivity [8,9,10,11,12]. Spatial conditions, including urban form are also of considerable importance. Compact, mixed-use neighbourhoods generate shorter trips and higher transit demand [13]. Economic factors, including the financial affordability of services, also play a significant role [14]. Equally important are social and affective motivations, including the perceived environmental benefits associated with choosing more sustainable modes of mobility [15,16]. In recent years, increasing attention in the literature has been devoted to improving accessibility and first- and last-mile connectivity. Studies have shown that integrating public transport with shared mobility services, such as bicycles and electric scooters, substantially enhances the efficiency of urban travel by enabling users to complete entire mobility chains more effectively [17,18]. Researchers also indicate that among emerging mobility options, Demand-Responsive Transport (DRT) may constitute a viable solution, provided that it is properly implemented, effectively communicated to passengers, and well integrated with conventional fixed-route public transport services [19,20].

High levels of congestion, as well as prolonged or uncertain travel times, in turn weaken the competitiveness of public transport relative to private car use. When combined with inadequately designed urban spaces that hinder access to stops, these factors contribute to the perception of public transport as a less convenient and less efficient alternative [21]. Adverse weather conditions may additionally increase access time, transfer time, and overall travel duration, while also causing schedule disruptions [22], thereby contributing to perceived travel discomfort and reinforcing the belief that the service is unreliable. Excessively high ticket prices and insufficient subsidization raise the cost of using public transport, particularly for low-income households [23,24]. In addition, inadequate service quality, limited perceived accessibility and safety, and an unfavorable cost–quality ratio reduce user satisfaction and undermine trust in public transport systems [22,25].

Understanding the factors that determine public transport use is important for the effective planning of attractive public transport systems, the design of efficient transport policies, and spatial planning oriented toward improving quality of life in the city. Łódź, which constitutes the study area of this research, is a large city in central Poland that faces several significant challenges related to its transport system. These barriers affect both residents’ mobility and the overall accessibility of the city.

Łódź suffers from one of the highest levels of congestion among Polish cities, caused by the growing number of private cars and a low car occupancy rate [26,27]. This trend has intensified in recent years, particularly during and after the COVID-19 pandemic [28]. This has led to a decrease in the efficiency of the urban transport system. The modal split is becoming increasingly unfavorable, with the share of public transport declining and the use of private vehicles rising [27]. In this context, analyzing the transport preferences of Łódź residents gains particular cognitive and practical significance.

This article presents the results of a quantitative study conducted among residents of Łódź, a city selected as a case study due to its combination of severe traffic congestion, a historically car-oriented mobility structure, and ongoing efforts to modernize public transportation systems typical of post-socialist Central and Eastern European cities. This specific urban context provides a valuable setting for examining public transportation choice in environments where private car use remains dominant despite policy interventions.

The primary objective of the study is to identify the factors influencing the selection of public transportation as the main mode of urban travel. The novelty of the research lies in its simultaneous inclusion of public transportation users and non-users within a single analytical framework, allowing for a direct comparison of motivations, barriers, and perceptions across these groups—an approach still underrepresented in studies focusing on Central and Eastern Europe.

Methodologically, the study employs a standardized, survey-based research design to assess factors that encourage or discourage public transport use. The framework is intentionally designed to be transferable and can be replicated in other cities facing similar congestion and structural mobility challenges, thereby enhancing the broader applicability of the findings.

By combining a context-specific case study with a replicable methodological approach, the article contributes to the academic debate on strategies to increase demand for public transport and addresses a gap in the literature on the determinants of public transport choice in highly congested urban settings in Central and Eastern Europe.

2. Materials and Methods

2.1. Selection of Determinants Influencing Urban Public Transport Choice by Residents

To identify the determinants of urban public transport choice relevant for this study, we conducted a bibliometric analysis using VOSviewer 1.6.20 software (Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands), a free tool for creating and exploring maps based on network data. VOSviewer analyzes co-authorship, co-occurrence, citation, bibliographic coupling, and co-citation links using one of three possible visualizations: network, overlay, or density [29].

The bibliometric analysis was conducted using data retrieved from the Scopus database. The search was performed with the query: “public transport” AND “determinants,” without any time restrictions. Filters were applied to include only English-language publications classified as research articles or book chapters, resulting in 718 records. After reviewing the abstracts and full texts, and excluding studies that were thematically irrelevant or focused on the COVID-19 pandemic and the travel behavior of individuals aged 65 and older (due to their distinct focus and potential to bias the results), 134 publications were included in the subsequent analysis.

The bibliographic data were exported in a format compatible with VOSviewer and underwent preliminary cleaning, which included: removing the names of cities and countries, excluding keywords referring solely to statistical methods, and standardizing synonyms and spelling variants. A keyword co-occurrence analysis was conducted in VOSviewer using the following settings: analysis type—co-occurrence; unit of analysis—Author Keywords; normalization method—association strength; minimum number of occurrences of a keyword—3 (Figure 1).

The bibliometric analysis revealed a coherent thematic structure in studies on the determinants of public transport use. Applying the minimum occurrence threshold of 3, a network of 493 keywords was included, forming 29 significant co-occurrence links. The resulting network map allowed the identification of six thematic clusters differing in substantive focus and level of centrality (Figure 2).

The largest and most central cluster was the red cluster (Determinants & Travel Behavior), encompassing concepts related to travel behaviors, mode choice, and the influence of the urban environment. Its central position in the network and numerous connections with other clusters confirm that issues concerning travel behavior form the foundation of contemporary public transport research. This cluster plays an integrative role, linking the perspectives of service quality (green and turquoise clusters), accessibility and behavioral theory (blue cluster), transport policies (yellow cluster), and demand analysis methods (purple cluster).

The green cluster (“Service Quality, Satisfaction & Loyalty”) focuses on public transport service quality, user satisfaction, reliability, and loyalty. Its high internal coherence and strong links with the red cluster indicate that service quality is one of the key factors influencing the perception and choice of public transport.

The blue cluster (“Accessibility, Urban Mobility & Behavioral Frameworks”) encompasses concepts related to accessibility, urban mobility, and theories explaining travel behavior. Its role lies in providing theoretical frameworks that clarify the relationships between user perception and transport behaviors.

The yellow cluster (“Transport Policies & Sustainable Transport”) represents institutional themes (while the other clusters focus on the user perspective) related to transport policies and sustainable transport. Its relatively lower number of connections suggests that this cluster emphasizes applied aspects of transport knowledge, where research findings from other clusters are translated into planning actions and strategic decisions.

The turquoise cluster (“Service Quality & Urban Mobility”) extends service quality topics by incorporating the perspective of urban mobility, functioning as a bridge between the green and blue thematic groups. Its position highlights the growing importance of interdisciplinary research on service quality in the context of urban mobility.

The purple cluster (“Ridership & Stated Preference”) addresses issues related to demand analysis and stated preference studies. It is a methodological cluster that provides empirical tools used in studies conducted within the red and green clusters.

In summary, the concept of “public transport” functions as the main node with the highest centrality, connecting all thematic clusters. The next most central nodes are travel behavior, mode choice, and service quality. This indicates that the literature is dominated by two streams:

• Research on user decisions and determinants of public transport choice;
• Studies on service quality assessment and passenger satisfaction.

In our quantitative study, which identifies the opinions of residents of the Łódź metropolitan area, we adopt an approach that combines both perspectives to determine the factors influencing public transport use.

The relatively lower centrality of the yellow and purple clusters should be interpreted in light of their functions—applied (transport policies) and methodological (preference studies), respectively.

2.2. In-Depth Literature Review: Determinants of Use of Urban Public Transport

An in-depth review of research articles focused on studies that met the following criteria:

• Identification of factors influencing users’ decisions regarding the choice of public transport modes in daily urban travel.
• Conducting studies in urban areas.
• Considering the opinions of current or potential users of the urban transport system.
• Focus on passenger transport.
• Adopting a broad research perspective that includes infrastructural, financial, organizational, contextual, and behavioral determinants of public transport choice.

The literature review allowed us to identify certain groups of determinants of public transport choice in European cities

Table 1. Categories of Determinants of Urban Public Transport Choice in European Cities.

Group of Determinants	Determinants	Key Research Findings
Built environment (BE)	Accessibility: stops and stations; Parking spaces	In cities with dense, well-connected networks, public transport use is higher. A reduced parking supply and higher parking costs can decrease private vehicle use and encourage a shift toward more sustainable alternatives [30,31]. Policy measures should aim to provide safe infrastructure that promotes sustainable mobility, as well as to implement an equitable transport system and urban space allocation [32].
Service quality and affordability (SQaA)	Frequency, reliability, comfort, safety, cleanliness, ticket prices, travel time	Service quality—including frequency, reliability, comfort, safety, and cleanliness—significantly influences both satisfaction and usage [33,34]
Socio-economic factors (SE)	Gender, income, vehicle ownership	Socio-economic factors influence transport preferences. Women, senior citizens, students, and individuals who have limited access to a car tend to rely on public transport more frequently [35,36,37]
Attitudes and Values (AaV)	Preference for lower travel costs, shorter travel times, and environmental or social norms	User attitudes influence their choice of transport mode, with environmental considerations typically rated lower than other aspects of service quality [38]. There is a lack of research on the relationship between transport decisions and the perception of negative externalities, such as congestion, noise, pollution, and safety issues, as well as on the assessment of measures that encourage changes in travel behavior, including road pricing, infrastructure investments, or demand-reducing interventions [39].
Contextual (trip-related) (C)	Purpose of travel, travel frequency, traffic congestion and road disruptions	There is a relationship between the travel purpose of urban residents—particularly commuting to work or school—and the use of public transport. Trips unrelated to commuting show greater variability in the choice of transport modes [40]. Traffic congestion and road delays, due to negative emotions and the difficulties of driving a private car, encourage a shift toward public transport [41,42].

Source: own elaboration.

.

2.3. Data Collection

The bibliometric analysis revealed six thematic clusters related to travel behavior, mode choice determinants, service quality, accessibility and behavioral frameworks, transport policy, and demand-analysis methods. These clusters highlighted the conceptual domains most frequently addressed in contemporary research and thus informed the operationalization of the study’s research questions (RQ1–RQ6). Insights from the bibliometric network—particularly regarding dominant mobility patterns, contextual determinants of transport choice, environmental attitudes, and the perceived quality of public transport services—were translated directly into questionnaire items. This ensured that the survey captured both user-oriented and system-oriented factors identified in prior studies, aligning the measurement framework with established knowledge while adapting it to the local mobility context of Łódź.

The quantitative research was conducted among residents of the Łódź metropolitan area, a large city in central Poland characterized by high traffic congestion and increasing private car use. The sample consisted of 406 respondents, selected to ensure a mix of public transport (PT) users and non-users.

The choice of Łódź as a case study is justified by its representativeness for Central and Eastern European cities facing similar transport challenges, allowing the methodology to be replicated in other urban contexts.

Of the 406 respondents, 362 were users of public transport services, while 44 had not used public transport in Łódź in the past three years (

Table 2. Study Sample.

Respondents		n	%
Total		406	100.00
Gender	Male	224	55.20
	Female	182	44.80
Education	Primary	18	4.40
	Vocational	15	3.70
	Secondary	300	73.90
	Higher	73	18.00
Driver’s License	Yes	293	72.20
	No	113	27.80

n—number of respondent, %—percent of respondent, Source: own elaboration.

).

The study addresses six research questions focusing on urban mobility patterns, determinants of public transport use, and the perceived quality of public transport services in Łódź:

RQ1:

What urban mobility patterns dominate among Łódź residents?

RQ2:

How do demographic and socio-economic factors (age, education level, and possession of a driver’s license) influence the choice of public transport?

RQ3:

Does a positive attitude toward reducing the environmental impact of urban transport determine the use of public transport services?

RQ4:

Do travel context factors (purpose, road conditions) and conditions of private car use in the urban space influence the choice of public transport in Łódź?

RQ5:

How do Łódź residents evaluate the quality of public transport services in the context of their daily mobility needs?

RQ6:

Which improvements in public transport service quality in Łódź would be necessary to encourage non-users to start using public transport?

To ensure clarity and analytical coherence, the research questions are summarized in

Table 3. Operationalization of research questions.

Research Question	Research Scope	Key Variables	Analytical Method
RQ1	Identification of prevailing mobility behaviors and travel modes	Primary mode of transport; frequency of public transport use; trip purpose	Descriptive statistics; frequency analysis
RQ2	Impact of individual characteristics on public transport use	Gender; education level; driver’s license	Chi-square test/Fisher’s exact test; Cramer’s V; Spearman’s rho correlation
RQ3	Role of environmental attitudes in mobility decisions	Environmental attitudes; frequency of public transport use	Frequency analysis
RQ4	Influence of contextual factors on mode choice	Trip purpose; road conditions; congestion perception; car availability; alcohol consumption	Frequency analysis
RQ5	Assessment of perceived service quality and satisfaction	Satisfaction with public transport; fulfillment of expectations; perceived adequacy of services	Descriptive statistics; frequency analysis, Public Transport Satisfaction Index
RQ6	Identification of measures with potential to attract new users	Service frequency; travel time; accessibility; pricing; comfort; parking conditions; regulatory measures	Descriptive statistics frequency analysis

Source: own elaboration.

together with the corresponding research scope, key variables and methods.

Respondents answered questions regarding their use of public transport (PT) for travel within Łódź, including the purposes and frequency of these trips. The questionnaire focused on:

• Public transport usage patterns (bus, tram, or both).
• Demographics: age, gender, education, and driver’s license ownership.
• Trip purpose and frequency.
• Reasons for PT use (15 items) categorized as: built environment (BE), service quality and affordability (SQaA), Socio-economic factors (SE), Attitudes and values (AaV), Contextual factors (C), and Other.
• Non-user motivations for future PT use (17 items).
• Satisfaction with PT services (3 items on a 5-point Likert scale).
• Future intentions to use PT (4 items on a 5-point Likert scale).

The 15 reasons for PT use and 17 factors for non-users were derived from literature review and prior studies [30,31,32,33,34,35,36,37,38,39,40,41,42], ensuring coverage of economic, social, environmental, contextual, and service quality factors.

2.4. Data Analysis

Statistical analyses were conducted using methods selected according to the type of variables and the structure of the data. The chi-square test of independence was applied to examine associations between categorical variables measured on nominal or ordinal scales, including: Public transport usage (0/1) and gender (0/1), education (1–4), and driver’s license ownership (0/1); Reasons for PT use (0/1) and the same sociodemographic variables; Trip purpose and frequency (1–5) in relation to gender (0/1) and driver’s license ownership (0/1); and Future intentions to use PT (1–5) in relation to gender (0/1) and driver’s license ownership (0/1)). The test was used when the assumption of sufficiently large expected cell frequencies (≥5) was met [43]. When this assumption was violated, Fisher’s exact test was employed, as it does not require minimum expected frequencies and provides reliable estimates in small subsamples [43]. The strength of association between nominal variables was assessed using Cramér’s V, which ranges from 0 to 1 and is relatively robust to differences in sample size.

For relationships involving ordinal variables (Trip purpose and frequency (1–5), Future intentions to use public transport (1–5), and Non-users’ motivations for future public transport use (1–5) in relation to education (1–4)), Spearman’s rank correlation coefficient was applied. Spearman’s rho was also used to examine associations between the ordinal variable measuring non-users’ motivations (1–5) and the dichotomous variables gender (0/1) and driver’s license ownership (0/1), in order to determine whether the probability of possessing a given attribute (e.g., being female or holding a driver’s license) changes systematically with increasing motivation ratings. In addition, Spearman’s correlation complemented the chi-square test in analyses of the relationship between reasons for public transport use (0/1) and education (1–4), enabling the assessment of ordinal trends (i.e., whether the likelihood of indicating a given reason increases or decreases with education level). In these analyses, dichotomous variables were coded as 0 and 1, allowing them to be treated as two-level ordinal variables, which is a common approach in studies involving ordinal data [44,45]. Spearman’s correlation does not assume normality and performs well in both small (N = 44; non-users) and large (N = 362; users) samples, providing stable estimates of the direction and strength of monotonic relationships. Its application was therefore appropriate given the characteristics of the data and the research objectives.

Means and medians were reported exclusively for variables measured on ordinal scales (Trip purpose and frequency (1–5), Future intentions to use public transport (1–5), and Non-users’ motivations (1–5)), enabling a concise description of central tendencies while respecting the properties of the measurement scales. The selected analytical procedures ensured statistical adequacy in light of the heterogeneous nature of the variables and the varying subsample sizes. A significance level of α = 0.05 was adopted for all analyses. This approach allows for methodological replicability in other urban contexts, as survey structure, determinant categories, and analytical methods can be applied to study PT use in different cities.

3. Results

3.1. Patterns of Public Transport Use

In the study sample of 406 respondents from the Łódź metropolitan area, 362 had used public transport in Łódź over the past three years, of whom 192 individuals (53%) traveled using both buses and trams (Table 3).

The chi-square test indicated a statistically significant association between gender and public transport use (p = 0.044); however, the effect size was small (Cramer’s V = 0.10). Men were more likely than women to report not using public transport in the past three years (59.1% vs. 40.9%), whereas women predominated among public transport users (56.9% vs. 43.1%) (

Table 4. Public Transport Usage.

Respondents	n	%
Total	406	100.00
Public transport users in the past 3 years, including:	362	89.16
Bus users	274	75.69
Tram users	254	70.17
Both bus and tram users	192	53.00
Non-users of public transport in the past 3 years	44	10.84

n—number of respondent, %—percent of respondent, Source: own elaboration.

). These findings suggest that women use public transport more frequently than men, although the strength of this association is weak.

To examine the relationship between public transport use and education level, Fisher’s exact test was applied due to small expected cell counts. A statistically significant association was observed (p = 0.018). A significant difference was found between respondents with vocational and secondary education (OR = 0.19, p = 0.01), indicating that individuals with vocational education were significantly less likely to use public transport than those with secondary education. No statistically significant differences were found between the remaining educational categories. Among respondents who had not used public transport in the past three years, the majority held a driver’s license (84.1%), whereas this proportion was somewhat lower among public transport users (70.7%) (Table 4). However, the chi-square test did not reveal a statistically significant association between holding a driver’s license and public transport use (p = 0.062). Therefore, not holding a driver’s license cannot be considered a statistically significant determinant of public transport use in this sample. This result suggests that other factors may play a more substantial role in influencing public transport use among residents of Łódź.

Respondents most frequently use public transport for commuting to schools and workplaces, with these trips being regular and occurring several times a week or daily (68.3%) (

Table 5. Public Transport Use by Gender, Education, and Driver’s License Ownership.

Public Transport Use		Gender		Education				Driver’s License		Total
		Male	Female	Primary	Vocational	Secondary	Higher	No	Yes
No	n	26	18	2	5	26	11	7	37	44
	%	59.1	40.9	4.5	11.4	59.1	25.0	15.9	84.1	100.0
Yes	n	156	206	16	10	274	62	106	256	362
	%	43.1%	56.9%	4.4	2.8	75.7	17.1	29.3	70.7	100.0
p		0.044 *		0.018 a *				0.062
V		0.10		-				-

n—number of respondents, p—significance level from the Chi-square test; ^a—significance level from the Fisher test; *—differences statistically significant (α = 0.05), V—V-Cramer coefficient, Source: own elaboration.

). Another important travel purpose was attending social gatherings, typically a few times per month. Similarly, trips to shops and supermarkets were commonly made using public transport several times a month (47.2% of respondents). Less frequent visits to public administration offices or medical facilities were reflected in the lower frequency of public transport use for these purposes. Individuals who frequently used public transport for one purpose tended to do so for other purposes as well. Spearman’s rank correlation coefficients indicated positive, moderately strong, and statistically significant associations between the frequency of trips to entertainment/cultural venues and social gatherings (rho = 0.638, p < 0.001), recreational sites and entertainment venues (rho = 0.664, p < 0.001), shops and entertainment venues (rho = 0.580, p < 0.001), and medical facilities and administrative offices (rho = 0.619, p < 0.001). Two distinct activity clusters emerged: leisure mobility, encompassing social gatherings, recreation, culture, and entertainment, and service mobility, comprising administrative offices, medical services, and shopping.

The analysis of the relationship between gender and the frequency of trips for different purposes revealed a statistically significant difference only for travel to medical facilities (Fisher’s exact test, p = 0.003). Women were more likely than men to report making no trips for this purpose, whereas men more frequently reported infrequent trips (“a few times a year”). Spearman’s rank correlation analysis indicated a statistically significant but weak association between education level and the frequency of public transport use only for trips to workplaces and educational institutions (rho = −0.110, p = 0.037). The negative coefficient suggests that individuals with higher education levels used public transport slightly less often for this purpose than those with lower education levels, although the strength of this association remained small. The analysis of differences between individuals with and without a driver’s license revealed statistically significant associations with travel frequency across all purposes analyzed. Respondents holding a driver’s license use public transport significantly less frequently than those without a license; this effect was strongest for daily trips (work/study, shopping) and weaker for leisure and cultural activities.

3.2. Reasons for Use and Intentions for Continued Use of Public Transport

The most frequently reported reasons for using public transport were economic factors related to the high cost of car ownership (38.4%) (AaV), lack of a personal vehicle (32.9%) (SE), difficulties with parking (31.8%) (BE), and the absence of a driver’s license (27.9%) (SE) (

Table 6. Purpose and Frequency of Public Transport Trips (N = 362).

Travel Purpose		Never	A Few Times a Year	A Few Times a Month	A Few Times a Week	Daily	M	Me	Gender		Driver’s License
									p	V	p	V
Commuting to school/work	n	25	39	51	102	145	3.84	4.0	0.630	-	0.003 a *	-
	%	6.9	10.8	14.1	28.2	40.1
Trips to shops/supermarkets	n	93	71	113	75	10	2.55	3.0	0.308 a	-	<0.001 a *	-
	%	25.7	19.6	31.2	20.7	2.8
Trips to social gatherings	n	34	93	171	56	8	2.75	3.0	0.653	-	0.004 a *	-
	%	9.4	25.7	47.2	15.5	2.2
Trips to entertainment/cultural venues	n	50	139	139	29	5	2.45	2.0	0.645	-	0.017 a *	-
	%	13.8	38.4	38.4	8.0	1.4
Trips to recreational/leisure sites	n	92	145	99	23	3	2.17	2.0	0.491	-	0.029 a *	-
	%	25.4	40.1	27.3	6.4	0.8
Trips to public administration offices	n	149	170	32	8	3	1.75	2.0	0.726	-	0.014 a *	-
	%	41.2	47.0	8.8	2.2	0.8
Trips to medical facilities	n	165	163	25	6	3	1.67	2.0	0.003 a*	-	0.007 a *	-
	%	45.6	45.0	6.9	1.7	0.8

n—number of respondents, M—mean, Me—median, p—significance level from the Chi-square test; ^a—significance level from the Fisher test; *—differences statistically significant (α = 0.05), V—V-Cramer coefficient, Source: own elaboration.

). These findings suggest that, for most respondents, public transport represents a practical and cost-effective travel option driven primarily by resource constraints and urban environment characteristics rather than by individual preferences. Contextual factors such as traffic congestion (22.9%), planned alcohol consumption (22.9%), or the temporary breakdown or unavailability of a personal car (14.4%) were reported less frequently, though they remain noteworthy. These motivations are situational in nature, dependent on specific circumstances, and do not constitute the basis of everyday transport decisions. Among service quality criteria, travel time (15.2%) was rated as more important than travel comfort (4.42%), suggesting that improvements in efficiency and reliability of public transport may have greater potential to encourage its wider use in Łódź. The least frequently indicated reasons included noise reduction (3.04%) and air pollution reduction (9.7%) (AaV), as well as other unspecified reasons (3.04%). Noise reduction appeared to be a marginal motivator of transport behavior, whereas the slightly greater importance of air pollution may reflect increasing awareness of its health risks. Overall, public transport use in the studied population appears to be primarily utilitarian, driven by economic, social, and infrastructural constraints. Environmental motivations and those related to perceived service quality play a relatively minor role, with environmental motives being the least influential.

The analysis of gender differences using the chi-square test revealed several statistically significant associations, although most exhibited weak effect sizes (V < 0.131) (Table 6). Women more often than men indicated the lack of a driver’s license (30.4% vs. 18.1%, p = 0.013, V = 0.131) and the lack of a personal vehicle (34.8% vs. 22.5%, p = 0.020, V = 0.122) as reasons for using public transport. In contrast, men more frequently reported the temporary unavailability of a personal car (16.1% vs. 9.8%, p = 0.022, V = 0.121) and planned alcohol consumption as reasons for using public transport (30.8% vs. 12.1%, p < 0.001, V = 0.268), the latter representing the strongest and only moderate association observed in the analysis.

Correlation analyses between reasons for using public transport and respondents’ education levels revealed only two statistically significant associations. As education level increased, the likelihood of citing the lack of a driver’s license as a reason decreased (rho = −0.187, p < 0.001), indicating a weak but statistically significant negative association. This finding was also confirmed by the chi-square test of independence. Conversely, respondents with higher education levels more frequently reported using public transport due to the temporary unavailability of a personal car (rho = 0.167, p = 0.001), reflecting a weak but statistically significant positive association, also confirmed by the chi-square test.

The analysis of differences between respondents with and without a driver’s license revealed several statistically significant associations. Individuals holding a driver’s license more frequently indicated reasons such as economic factors (43.8% vs. 25.5%, p = 0.001, V = 0.171), the temporary unavailability of their car (19.9% vs. 0.9%, p < 0.001, V = 0.246), difficulties finding a parking space (43.4% vs. 3.8%, p < 0.001, V = 0.387), high parking fees (21.1% vs. 2.8%, p < 0.001, V = 0.228), anticipated traffic restrictions in the city (7.4% vs. 0.9%, p = 0.011, V = 0.129), traffic congestion (29.7% vs. 6.6%, p < 0.001, V = 0.250), and planned alcohol consumption (28.5% vs. 9.4%, p < 0.001, V = 0.207). These associations ranged from weak to moderate in strength, with the strongest effects observed for parking-related issues.

Respondents without a driver’s license more often cited the lack of a driver’s license (91.5% vs. 1.6%, p < 0.001, V = 0.913) and the lack of a personal vehicle (61.3% vs. 21.1%, p < 0.001, V = 0.390) as obvious reasons for using public transport. Notably, the effect size for the former was very strong, indicating a clear and expected association between driver’s license ownership and reported motivations for using public transport.

Reasons related to service quality played a minor role in respondents’ decisions to use public transport. This aspect was examined in more detail through questions assessing satisfaction with public transport services in Łódź, using a Likert scale from 1—“strongly disagree” to 5—“strongly agree.” The results are summarized in

Table 7. Reasons for Using Public Transport and Measures of Association with Gender, Education, and Driver’s License Ownership (N = 362).

Determinant Group	Reason	n	%	Gender		Driver’s License		Education
				p	V	p	V	rho	p(rho)	p
AaV	Economic factors—high cost of car ownership	139	38.40	0.371	0.047	0.001 *	0.171	0.061	0.244	0.142
SE	Lack of a driver’s license	101	27.90	0.013 *	0.131	<0.001 a	0.913	−0.187	<0.001 *	<0.001 *
SE	Lack of a personal vehicle	119	32.87	0.020 *	0.122	<0.001 *	0.390	−0.053	0.314	0.029 *
C	Temporary unavailability/breakdown of a personal car	52	14.36	0.022 *	0.121	<0.00 1 a*	0.246	0.167	0.001 *	0.001 *
AaV	Desire to reduce air pollution	35	9.67	0.068	0.0959	0.143	0.0771	0.048	0.360	0.561
AaV	Desire to reduce noise pollution	11	3.04	0.124 a	0.0891	0.311 a	0.0629	−0.072	0.168	0.367
SQaA	Travel time	55	15.19	0.836	0.0109	0.100	0.0863	−0.028	0.586	0.070
SQaA	Travel comfort	16	4.42	0.196 a	0.0786	0.193	0.0684	−0.045	0.394	0.3697
BE	Difficulty finding parking for a personal car	115	31.77	0.090	0.0892	<0.001 a *	0.387	0.089	0.091	0.141
BE	High parking fees	57	15.75	0.455	0.0393	<0.001 a *	0.228	0.002	0.969	0.543
C	Expected traffic disruptions	20	5.52	0.521	0.0337	0.011 a *	0.129	0.074	0.159	0.514
C	Traffic congestion	83	22.93	0.116	0.0827	<0.001 *	0.250	0.062	0.237	0.522
C	Planned alcohol consumption	83	22.93	<0.001 *	0.268	<0.001 *	0.207	0.048	0.361	0.555
	Other	11	3.04	0.763 a	0.0241	0.737 a	0.0276	−0.035	0.502	0.452

n—number of respondent, p—significance level from the Chi-square test; ^a—significance level from the Fisher test; p(rho)—Spearman’s rank-order correlation coefficient *—differences statistically significant (α = 0.05), V—V-Cramer coefficient, Source: own elaboration.

. Mean ratings were moderate, not exceeding a value of 3.0. Respondents were least likely to agree with the statement that public transport in Łódź adequately meets residents’ needs: 40% rated this aspect negatively (1 or 2), whereas only approximately 26% provided positive ratings (4 or 5). The remaining two statements received similarly moderate evaluations, with neutral (3) and moderately positive (4) responses predominating. In both cases, only about 5% of respondents expressed strong satisfaction, while over 30% (1 or 2) reported dissatisfaction. Gender, education level, and driver’s license ownership did not significantly influence respondents’ ratings (chi-square tests showed no statistically significant associations). The only exception was the statement “Overall, I am satisfied with public transport services in Łódź,” for which women’s ratings were statistically significantly lower than men’s (ρ = −0.108, p = 0.041), although this association was very weak.

Based on the mean ratings of the three questions assessing public transport services, a satisfaction index was constructed. Descriptive statistics for the index are presented in

Table 8. Evaluation of Public Transport Services in Łódź (N = 362).

Items		1	2	3	4	5	M	Me
Overall, I am satisfied with public transport services in Łódź	n	35	80	139	90	18	2.93	3.00
	%	9.7	22.1	38.4	24.9	5.0
Public transport services in Łódź meet my expectations	n	41	75	125	101	20	2.96	3.00
	%	11.3	20.7	34.5	27.9	5.5
I believe that residents’ public transport needs in Łódź are well met	n	48	99	119	80	16	2.77	3.00
	%	13.3	27.3	32.9	22.1	4.4

M—mean, Me—median, Source: own elaboration.

. The average level of satisfaction with public transport in Łódź among the surveyed group was 2.89 (

Table 9. Public Transport Satisfaction Index (PTSI) (N = 362).

	M	SD	Min.	Max.
PTSI	2.89	0.96	1.0	5

M—mean, SD—standard deviation, Min.—minimum total score, Max.—maximum total score, Source: own elaboration.

), which can be interpreted as moderate. The index showed no significant or strong associations with education level, gender, or driver’s license ownership.

Relatively low levels of satisfaction with public transport services were reflected in a moderate intention to use them in the future (

Table 10. Respondents’ Intentions for Future Use of Public Transport (N = 362).

Items		1	2	3	4	5	M	Me
In the future, I will use public transport in the same way as I do now	n	27	38	111	94	92	3.51	4.00
	%	7.5	10.5	30.7	26	25.4
In the future, I will probably use public transport more frequently for trips in Łódź	n	79	88	104	65	26	2.64	3.00
	%	21.8	24.3	28.7	18.0	7.2
I am certain that in the future I will use public transport in Łódź more frequently	n	98	93	101	44	26	2.47	2.00
	%	27.1	25.7	27.9	12.2	7.2
Not only will I use public transport in Łódź, but I will also recommend it to friends and family	n	132	89	76	41	24	2.27	2.00
	%	36.5	24.6	21.0	11.3	6.6

M—mean, Me—median, Source: own elaboration.

). Respondents evaluated their future use of public transport on a Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The highest mean score was observed for the intention to continue using public transport at the current level (M = 3.51, Me = 4).

With regard to intentions to increase usage, 167 respondents (46.1%) indicated that they “probably will not” use public transport more frequently in the future, and 191 (52.8%) stated that they “certainly will not.” Furthermore, 221 respondents (61%) declared that they would not recommend public transport to friends or family.

Overall, respondents demonstrated a rather passive stance: they did not intend to increase their use of public transport nor to actively promote it. Gender, education level, and driver’s license ownership did not significantly differentiate these intentions, as no statistically significant associations with the control variables identified.

3.3. Factors Motivating Non-Users to Use Public Transport in the Future

Non-users of public transport evaluated 17 factors in terms of their potential to motivate future use, employing a Likert scale ranging from 1 (“definitely does not motivate”) to 5 (“definitely motivates”). The highest-rated factors were free public transport (M = 4.66), lower ticket prices (M = 4.16), higher travel comfort (M = 4.07), reliability of connections (M = 4.00), and shorter travel time (M = 3.82) (

Table 11. Factors Motivating Non-Users to Use Public Transport (N = 44).

No.	Factors	1	2	3	4	5	M	Me	Driver’s License
									rho	p
1	Direct connections	3	3	9	14	15	3.80	4.0	−0.296	0.051
2	Higher service frequency	1	5	15	8	15	3.70	4.0	−0.166	0.280
3	Walking accessibility (max. 10 min) to nearest stop	2	4	14	11	13	3.66	4.0	−0.244	0.110
4	Shorter travel time	2	4	10	12	16	3.82	4.0	−0.301	0.047 *
5	Reliability of connections	3	1	8	13	19	4.00	4.0	−0.288	0.058
6	Smooth transfers	3	3	14	11	13	3.64	4.0	−0.244	0.110
7	Higher travel comfort	2	2	9	9	22	4.07	4.5	−0.195	0.204
8	Lower ticket price	3	2	6	7	26	4.16	5.0	−0.130	0.402
9	Free public transport	0	3	1	4	36	4.66	5.0	−0.058	0.707
10	Discounts for shared vehicles (bikes, scooters, cars)	4	8	9	7	16	3.52	4.0	−0.281	0.064
11	Better travel planning and payment apps	3	6	12	11	12	3.52	4.0	−0.275	0.071
12	Access to apps for planning and paying trips via public transport	7	1	12	14	10	3.43	4.0	−0.360	0.016 *
13	Option to pay for a monthly transport package with unlimited access	6	4	9	10	15	3.55	4.0	−0.306	0.044 *
14	Lack of parking/difficulty parking	9	6	6	11	12	3.25	4.0	−0.033	0.834
15	Higher parking fees	12	3	7	5	17	3.27	3.5	0.018	0.908
16	“Park and ride” parking on city outskirts	8	3	15	14	4	3.07	3.0	−0.069	0.657
17	Car restrictions/fees in downtown Łódź	11	3	11	8	11	3.11	3.0	0.121	0.435

M—mean, Me—median, rho—Spearman’s rank correlation coefficient, p—significance level; *—differences statistically significant (α = 0.05), Source: own elaboration

). These findings indicate that economic incentives exert the strongest motivational effect, confirming that financial considerations remain a key determinant of the willingness to shift from car use. Service quality attributes were also rated highly, suggesting that for this group, the primary barrier is not public transport per se, but rather the manner in which the service operates—particularly its reliability, convenience, and travel time.

Built environment factors also played a meaningful, though moderate, role. Walkable access to stops (M = 3.66) and smooth transfers (M = 3.64) were assessed as important, underscoring the relevance of spatial accessibility and transport integration in shaping travel decisions. Technological tools supporting travel, such as advanced apps for trip planning and ticket payment (M ≈ 3.4–3.5), received slightly lower evaluations, indicating that technological facilitation is secondary to core service attributes for this group. The lowest ratings were assigned to park-and-ride facilities located on the outskirts of Łódź (M = 3.07), restrictions or charges for car entry into the city center (M = 3.11), difficulties in finding parking (M = 3.25), and higher parking fees (M = 3.27). Regulatory measures aimed at limiting car access to urban space thus demonstrated the weakest motivational potential. Overall, these results suggest that strategies based on restrictions for car users may encounter lower acceptance and prove less effective in influencing travel behavior than measures focused on enhancing the attractiveness of public transport.

Gender and education level did not significantly differentiate the perceived importance of individual motivational factors. In contrast, holding a driver’s license was statistically significantly associated with several factors: shorter travel time (rho = −0.301, p = 0.047), access to apps for planning and paying for public transport trips (rho = −0.360, p = 0.016), and the option to pay for a monthly transport package with unlimited access to public transport (rho = −0.306, p = 0.044). Respondents without a driver’s license rated these factors as significantly more motivating than those holding a license, with associations of moderate strength. This suggests that digital services and flexible payment models constitute relatively stronger incentives for individuals without a driver’s license, although they remain less influential than core determinants such as cost, comfort, and reliability.

4. Discussion

As a key component of sustainable mobility, public transport (PT) plays a central role in urban areas; therefore, understanding the factors that influence its use is essential. A bibliometric analysis of the relevant literature has enabled the identification of the following groups of determinants of PT use: The following factors were considered in the study: socio-economic factors (SE), built environment (BE), service quality and affordability (SQaA), attitudes and values (AaV), and contextual factors (trip-related) (C). The findings of our research suggest that Socio-Economic (SE) factors significantly influence the decisions of PT users in Łódź. Among the factors related to attitudes and values, perceived financial costs of car ownership clearly outweighs the ecological motivations for using PT, making this the most frequently cited reason for PT use among respondents. The built environment (BE) and contextual factors, which are trip-related, were found to be marginally less significant but nevertheless substantial. The factors identified as least important are those of a qualitative nature (SQaA) and environmental nature (AaV). A review of the scientific literature indicates that public transport (PT) use is influenced by multiple factors, with no single factor clearly dominating. The relative importance of these factors varies depending on the specific context [46].

The most frequently cited reasons for using public transport (PT) are predominantly economic and resource-related: high costs of car ownership (38.4%) (AaV), lack of access to a personal car (32.9%) (SE), and absence of a driving license (27.9%) (SE). These factors have likewise been identified in previous studies as key determinants of PT use [46,47]. These reasons are more prevalent among women and respondents without a driving license. Consequently, PT use among the study participants appears to be primarily utilitarian in nature, rather than driven by pro-environmental attitudes or service quality considerations. Men and respondents with higher levels of education more frequently report situational motivations, such as planned alcohol consumption (C) or the temporary unavailability of a car (C). Among respondents holding a driving license, the strongest motivation for using PT was parking-related difficulties (BE), which also constitute one of the most frequently cited reasons across the entire sample (31.8%), alongside planned alcohol consumption (C). Limited parking availability is identified in the literature not only as a factor encouraging PT use [47] but also as a necessary precondition for achieving a high modal share of PT trips [48]. In light of these findings, PT use in Łódź can be interpreted primarily as an adaptive strategy shaped by socio-economic constraints (lack of a car, absence of a driving license, car maintenance costs), spatial conditions (difficulty finding parking), and situational factors (temporary unavailability of a car, traffic congestion, planned alcohol consumption).

Demographic and socio-economic factors (gender, level of education, and possession of a driving license) are also associated, to some extent, with patterns of public transport (PT) use, although their overall influence appears limited. The greater propensity of women to use PT is consistent with previous studies, which attribute this, inter alia, to women’s stronger preferences for sustainable modes of mobility [49,50]. The relationship between educational attainment and PT use is complex. Individuals with the lowest level of education tend to use PT less frequently, which may be related to financial barriers limiting access to PT services. Conversely, respondents with higher education levels report slightly lower use of PT for commuting to work or educational institutions. These findings are partially supported by other studies, although no clear consensus exists in the literature. It has been noted that individuals with lower socio-economic status (often correlated with lower education) rely more heavily on PT due to the absence of a car or driving license [51,52], while simultaneously experiencing inequalities and barriers in PT use, such as lower service quality associated with overcrowding and relatively high fares [53]. Other studies indicate the opposite pattern: individuals with higher educational attainment are more likely to use PT in well-connected neighborhoods, a trend attributed to better accessibility [54] and greater environmental awareness [55]. Overall, higher educational attainment is generally associated with more frequent PT use or a greater propensity to use PT, as well as with more sustainable travel behaviors. At the same time, a range of contextual factors (income, fare structures, type of employment, urban form, family situation) substantially moderates this relationship [56,57]. Additionally, possession of a driving license is associated with lower use of PT for daily commuting (work, education, shopping), but higher use for recreational and cultural mobility purposes.

Respondents rarely indicated quality- or environmentally related factors (travel comfort, noise reduction, environmental concerns) as reasons for using public transport (PT). This aligns with findings from other studies, showing that environmental awareness, pro-ecological identity, and social norms can increase the willingness to use public or “eco-friendly” transport, but generally with only a moderate effect compared to instrumental factors such as travel time and cost [58,59,60].

The results of the satisfaction assessment confirm a moderate level of contentment among respondents with public transport services. Approximately 40% of respondents believe that their mobility needs are not well met, while only 26% rate them positively. This indicates a gap between expectations and service quality, which may limit the potential for increasing public transport (PT) share in urban travel, given the demonstrated direct impact of service quality on PT usage [61].

The moderate level of satisfaction with PT services and the lack of significant differences in ratings across socio-demographic groups suggest that perceptions of service quality are relatively uniform and not strongly rooted in individual characteristics. At the same time, the observed average service rating does not translate into intentions to increase usage or into a willingness to recommend PT, indicating limited potential for user acquisition and loyalty building.

Our findings regarding the motivations of non-users of public transport indicate that key determinants are economic and service-quality related, while regulatory measures restricting car traffic are associated with low acceptance and weak motivational effect. Overall, this suggests that without substantial improvements in functional and cost-related aspects of services, public transport will remain a substitute rather than the preferred mode of urban mobility.

5. Conclusions and Limitations

Our study enabled a comprehensive assessment of mobility behaviors among residents of the Łódź metropolitan area in the context of public transport use. The results indicate that urban public transport is widely used within the studied population; however, its use is compensatory rather than preferential. Public transport often serves as a substitute solution, utilized in situations where individuals lack access to a car or a driving license, or face high costs associated with using a private vehicle. These findings contribute to the literature by empirically distinguishing between necessity-driven and choice-driven public transport use, thereby providing a more nuanced understanding of user motivations in a metropolitan context.

A key factor differentiating transport behaviors is the possession of a driving license, which influences both the frequency of public transport use and the reported motivations for using it. Demographic factors, such as gender and education, play a secondary role, explaining only a small portion of the variation in mobility behaviors. The assessment of public transport service quality in Łódź is moderate, and respondents do not express a willingness to increase their use of these services or to recommend them. This may indicate limited potential for growth in urban public transport demand. The result highlights a structural challenge for local administrations and service operators, as maintaining current ridership may be as critical as attracting new users.

At the same time, the study revealed that non-users of public transport are willing to consider changing their travel behavior, provided that certain conditions are met—primarily a reduction in travel costs and improvements in the quality and reliability of services. Measures of a restrictive nature toward car use (e.g., fees, access bans) were found to have a low motivational effect. This suggests that policy strategies based predominantly on restrictions may generate limited behavioral change unless accompanied by tangible improvements in service attractiveness.

From a transport policy perspective, the results suggest that measures aimed at increasing the attractiveness of public transport—particularly through pricing instruments and improvements in service quality—may be more effective in attracting new PT users than strategies based on restrictions targeting car users. Maintaining the loyalty of current users, in turn, can be supported by solutions that enhance the cost-effectiveness of public transport compared to private mobility, such as stable and flexible pricing policies, service packages, or loyalty programs. These measures should also be supported through educational and informational campaigns. Maintaining existing PT users, based on our findings, also requires improvements in service quality parameters related to travel time. Future interventions should focus on increasing travel efficiency, developing transfer infrastructure, improving intermodal integration, and improving punctuality and service frequency. The justification for promoting public transport extends beyond individual mobility benefits. For local administrations, a stronger public transport system contributes to reduced congestion, lower environmental externalities, and more efficient land-use management. For service operators, increased and stabilized demand improves financial sustainability and operational planning. For citizens, enhanced public transport offers cost savings, improved accessibility, and greater travel reliability, thereby supporting overall urban quality of life.

The scientific implications point to the need for further development of transport behavior models that simultaneously account for resource-related factors, perceptions of service quality, and travel context. It is also important to distinguish between public transport use “out of necessity” and “by choice,” as these forms generate different attitudes, levels of satisfaction, and willingness to change long-term travel behavior.

Our study has certain limitations that should be considered when interpreting the results, particularly regarding its temporal and spatial scope. First, the cross-sectional design of the study prevents drawing causal inferences. The observed relationships between respondent characteristics, perceptions of public transport, and mobility behaviors are correlational and do not allow for the determination of causal direction. Second, the spatial scope of the study, which was limited to the Łódź metropolitan area, restricts the generalizability of the findings to other cities or regions, especially those with different spatial structures, transport systems, or levels of car ownership. Therefore, the results should be interpreted in the context of the local conditions of the Łódź agglomeration. Both limitations also indicate directions for future research. Longitudinal and comparative analyses would enable a better understanding of the mechanisms shaping mobility decisions in cities with diverse transport systems.